Carbon Zero Cities - Research Document by nadia-architecture

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C C

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How can we tackle the climate emergency through a deep understanding of zero carbon urban city design. The race to ZERO

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Zero Carbon Cities A document of research for understanding routes towards carbon zero cities CPU[AI] - 2021 The time for a NET ZERO future is NOW.

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Manchester City Center (Author,2021)

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Contents

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14 - 51

Policies

Introduction Carbon budget Carbon analysis Carbon budget summary Systems map Systems dynamic diagram Policy research Newham carbon budget Manchester carbon budget WLCC document The question Mathematical model Calculations Calculations and results Generated model Investigation summary Bibliography

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52 - 131

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132 - 225

Air Quality

Energy

Introduction Measuring Air Quality Issues and Factors Greenhouse Gases’ Greenhouse Gas Emissions Emissions by Sector i Emissions by Sector ii UK CO2 Emissions GHG Breakdown UK System Map Domestic Emissions Pollutants in the Air Domestic CO2 Usage Household Energy Heat Loss & Insulation Day in the Life Scenario Overall Emissions CO2 in Manchester Manchester’s PM10 Manchester’s NO2 Manchester’s Plan Systems Dynamic The Invisible Killer Health & Climate Change Urban Strategy Improving Air Quality Air Quality Plans Air Pollution Model Types Air Quality Model Experimentation Chapter Summary Bibliography

Introduction The Problem Energy Generation Fossil Fuel Energy Nuclear Energy Hydrogen Energy Solar Energy Bioenergy Geothermal Energy Hydroelectric Energy Wind Energy Comparing Embodied CO² Transmission Emission and Reduction Energy Use Precedent Summary Bibliography

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226 - 265

Social Transformation Introduction Energy Use, Low Carbon Behaviour Household Carbon Emissions HCEs Categorization Carbon Footprint & Lifestyle GHG Intensity of Time Use Time Spent of Activities Carbon Mitigating Factors Emissions Contributing Factors Real-Life Scenario Study Carbon Saving Solutions Food Systems Domestic Heating Collective Living Housing Typology Case Study: Eco Village Towards Household Decarbonization Summary Bibliography

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266 - 319

Urban Heat Island Introduction Context UHI and Zero Carbon Cities UHI in Manchester Heat Sources UK Cooling Demand Wider Systems Map Considerations & Methods System Dynamics Urban Heat Transfer Sankey Parameters Affecting UHI Metabolism - Transport Metabolism - People Green Infrastructure Green Spaces Trees Geometry Materials Case Study: Stuttgart Tool for calculating UHI Towards Zero Carbon Bibliography

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320 - 373 Urban Forest Introduction Background Define Urban Forest System Map System Dynamic Manchester Report Overall Assessment Policies Headline Figures in Manchester Northern Gateway Research Method Calculation Field Research Further Report - I-Tree Eco Species Performance Summary Tree Id Guide Tree Placement Rules Private area Public area Proper Placement for trees around the houses Suggestion for Improvement Green Corridors Green Cycling Executive Summary Bibliography

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374- 445 Accessibility Introduction Context Accessibility Systems Map Systems Dynamics Diagram Population Land use Spatial Configuration Compact City Transit Oriented Development Superblocks 15 Minute City Manchester City Plan Regional Road Communications Mobility Manchester Transport Target Low Emissions Zones Case Study: London Motorised Dominance Nuremberg Case Study Motorised Congestion Urban Network Analysis Gravity Accessibility Closest Facilities Pedestrian Flows Carbon Calculations Carbon Emissions from Collyhurst (Private Car) Carbon Emissions from Collyhurst (Bus) Approaches Conclusion Bibliography

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446 - 535 Transportation Introduction Understanding current emissions Types of vehicles Types of greenhouse gas CO2 GHG emission regulations in the EU GHG emissions standards Fuel options Fuel economy Emission based on fuel type Types of road Manchester road networks Speed limits Tax bands Fun facts Grants & Incentives Deadhailing The system System dynamics map Calculating current emissions Embodied energy & embodied carbon Calculating running carbon Carbon emissions for M1 vehicles Carbon emissions for M2 & M3 vehicles Carbon emissions for N1 Light goods vehicles & N2 & N3 heavy goods vehicles Metrics in transportation Vehicle emission analysis An electric way Charging & charger types Charge point locations Cost factors Proportion of new vehicles Ultra-low emission vehicles Road to zero Case studies Summary Bibliography

 536 - 601

Buildings

Introduction Scale of improvement Wider system map Low-Carbon Scaling Cycle & process Circular economy case study Life cycle Material type Material process Material supply Future of materials Material performance Comparison Zero-Emission construction and Context Digitised construction and Transportation Machinery Case study and Methods life cycle assessment Calculations Embodied energy calculation Embodied energy Sankey Performance factors Typology operation factors Typology operation use Context Manchester Methods to quantitative data Heating calculation approach Lighting ventilation calculation approach Calculation overview Annual energy use Sankey System dynamics map Summary Issues & Suggestions Bibliography



602-671 Carbon Water Introduction Problem Identification Sustainable Issues and Goals UK Carbon Emissions Water-Energy Nexus UK Demand and Losses Systems Diagram Manchester Supply Manchester Treatment Manchester Policy Building Typology Residential Water Usage System Dynamics Shower Usage Shower Calculation Shower Results Precedent Rain Water Harvesting Urban Drainage (Suds) Demand and CO2e Method Water Reuse Systems Calculations Demand and CO2 Results Emissions Summary Water Treatment Systems Decentralised System Wastewater Treatment Scale of Improvement Executive Summary Bibliography

 672-759

Smart Cities

Introduction Evolution of cities A future Roadmap, Green Net-Zero Smart city Industry The city as an experiment Smart City Systems Smart City Index: Comparing smart cities Smart initiatives Top-down, Bottom-up The connected city Digital infrastructure Enabling Technologies The Internet of Things (IoT) Sensing the City Sensor Node Deployment Sensor Network Application Smart Motorways Systems Dynamics Smart cities and Manchester Smart City Metrics Smart City Data Dashboards Big Data Decentral Systems Digital Twins Barriers and Summary Bibliography

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INTRODUCTION

Zero Carbon Cities 11

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Image Source: https://www.placenorthwest.co.uk

Introduction The climate emergency is at the forefront of conversations in our industries today. Architecture is particularly affected and directed by changes in the climate, and how governments all over the world choose to response to these changes. In the U.K, measures to tackle climate change have already been undertaken at a country scale, such as the gradual increase in renewable energy generation to power the grid. However, there is still a long way to go, which is where the concept of Zero Carbon Cities comes in. Manchester City Council have set themselves a goal to be a Net Zero Carbon City by 2038. This is incredibly ambitious but will ultimately have a great

impact in terms of carbon consumption and emission reduction. In order to achieve this goal, there needs to be significant changes made to both current and future developments in Manchester. We as an atelier year group were given the opportunity to collaborate with Manchester City Council and FEC (The Far East Consortium) by researching and subsequently proposing Zero Carbon City initiatives that could be viable for Manchester. This process involved conducting research in order to create a comprehensive overview of potential strategies and considerations to be aware of when aiming to achieve Zero Carbon. The research was conducted collectively, while dividing into smaller

groups to focus in on eleven specific topics that all relate to Zero Carbon Cities, such as energy consumption and green spaces. Focusing in on key topics ensured that a variety were covered, and allowed us to go into a more detailed study for each, including using mathematical calculations and extrapolations to conclude the viability of relevant Zero Carbon initiatives. Our atelier year group then had a meeting with Manchester City Council members, where each group presented their topic of focus to council members and FEC. This gave all students an opportunity for feedback on the research and to collaborate with a range of people including those specialising in

sectors such as transport and smart cities. Because of the collaborative nature of the research between student groups, the council, and FEC, the final document covers a range of helpful approaches for achieving a Zero Carbon City all while positioning these findings within the scope of the city of Manchester. It is our hope that this research will be a useful point of reference in relation to Zero Carbon development. The findings in this document have also informed the second stage of our 6th year thesis projects, which aims to aide the design of a Zero Carbon City using methods discovered during this research.

As Manchester aims to become zero carbon by 2038, specific policies and rules need to be implemented in order to achieve this goal. We look into the policies and carbon budgets which are currently in place within Manchester’s Climate Change Framework and how these compare against other council policy frameworks.

INTRODUCTION Importance of zero carbon and policies

SECTION ONE

SECTION TWO

Research methodology

Policy framework comparisons

SECTION THREE Mathematical model

CONCLUSION Summary and reflections

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POLICIES

CARBON BUDGETING AND POLICIES

Nadia Al-Shawi, Nayeem Shaik, Kareem Alsaady

Zero Carbon Cities

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Introduction Introduction to Manchester's road to Zero Carbon

What is Manchester’s goal?

Net Zero vs. Zero Carbon Net zero states that any carbon emissions created are balanced by taking the same amount of carbon out of the atmosphere. By doing this, we will reach net zero when the amount of carbon emissions we add is no more than the amount which is being taken away. (What is net zero and zero carbon?, 2021).

To limit the impacts of climate change, cities need to implement new policies and rules in order to reach certain goals which will reduce the effects of climate change by a certain year. The city of Manchester has become committed to being zero carbon by 2038 (Five Year Environment Plan, 2019) and by meeting this target, Manchester will become one of the world’s leading cities for action on climate change. This will allow for Manchester’s economy to become more resilient and dynamic where local businesses can thrive and residents will have secure jobs and a high quality of life.

Zero carbon is where there are no carbon emissions being produced from a product or service, for example from building construction or transport. (What is net zero and zero carbon?, 2021). Great Britain’s goal is to become net zero by 2050 and to do this, little steps need to be taken such as running a zero carbon grid.

Zero Carbon

Definition

Zero carbon means that no carbon emissions are being produced from a product or service

Net zero refers to reaching zero carbon dioxide emissions as close as possible

Process

Includes several steps such as commitment, counting and analysing, reduction

By balancing a particular amount of carbon released with an emission offset

Method

By balancing carbon emissions with carbon removal or using renewable energy does not produce carbon emissions

Use of technologies such as carbon capture for carbon offsetting

Source: What is net zero and zero carbon?, 2019

Source: Five Year Environment Plan, 2019

Introduction

Net Zero

Introduction

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Carbon Budget

Policies Manchester City Council plans to support the delivery of the citywide Manchester Climate Change Framework 2020- 2025 which has been produced by the Manchester Climate Change Partnership and Agency.

Manchester's Carbon Budget Goals

Manchester’s Carbon Budget Plan By using science based research, Manchester will take part in limiting the impacts of climate change in line with the Paris Agreement. Analysis conducted by the Tyndall Centre at the University of Manchester shows the current budget targets of carbon dioxide emissions. These targets were adopted by Manchester City Council in November 2018. The percentage reduction estimates represent the average emissions of each 5 year carbon budget period compared against the previous 5 years period. As each carbon budget period passes, there is a reduction in carbon dioxide emissions by approximately 40% each time.

Why are policies relevant to zero carbon cities?

Why is the carbon budget important?

- Role of governance and regulation

- For monitoring and evaluation purposes

- Provide Framework for designers and architects

- For reliability and to measure progress

- Methodology to reach net zero goals

- Understand quantitative steps in wider systems

The chart below shows these estimates and suggests that by 2038 the carbon emissions should be nearly at zero and a zero carbon system should be put in place. There will be a large carbon reduction with a 50% reduction by 2022 comparing to the 2018 emissions.

MCC Headline Objectives 2020-25 To ensure that Manchester plays its full part in helping to meet the Paris Agreement objectives by keeping our direct CO2 emissions within a limited carbon budget, taking commensurate action on aviation CO2 emissions and addressing our indirect / consumption-based carbon emissions (Zero Carbon Manchester, 2021).

Source: Draft Manchester Zero Carbon Framework 2020-2038, 2019

Carbon budget

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Carbon Budget Policies and Funding

Detailed Manchester Budget Analysis Manchester city’s carbon budget sets out a limit of carbon emissions that shouldn’t be exceeded, which is a total of 15 million tonnes of carbon dioxide (Draft Manchester Zero Carbon Framework 2020-2038, 2019).

How is the carbon budget split? UK Direct Energy Only

UK Aviation Industry

55%

37%

This budget has been based on the 2°C global average temperature rise on the basis that:

UK Shipping Industry

1) The Paris Agreement commits us to limiting warning to this level 2) Global modelling for both 1.5°C and 2°C assume planetary scale negative emissions

What was Manchester’s carbon budget based on? In June 2018, the Tyndall Centre for Climate Change Research at the University of Manchester was commissioned by the Manchester Climate Change Agency to give science- based advice on carbon reduction targets and aims for Manchester City. The Tyndall Centre calculated a carbon budget for Manchester which aliigned with the Paris Agreement. The Paris Agreement sets out a global framework which aims to avoid climate change by limiting global warming to well below 2°C and by aiming to limit the change to 1.5°C. It is a legally binding global climate change agreement which aims to make the climate net zero by 2050 (Gray, 2016).

Key Points:

Source: Draft Manchester Zero Carbon Framework 20202038, 2019) The city-wide current year emissions inventory, which is the total emissions given off in the year 2017, is a total of 2.3MtCO². The breakdown of these emissions is shown in the pie charts below. 29% of the emissions is due to the transport industry such as airplanes, cars and trains. 30% is due to domestics which includes the co2 given off by the running of homes and properties and 41% due to non-domestic emissions which can include sectors such as education, hospitality and faith.

Carbon budget

Source: Draft Manchester Zero Carbon Framework 2020-2038, 2019 MMU 1.5% = 193,500MtCO². This methodology will allow for each different sector to allocate responsabilites and will engage and empower them to act towards a zero carbon future (Draft Manchester Zero Carbon Framework 2020-2038, 2019).

Temperatures

Financing

Emission Goals

• Keep warming well below 2 degrees Celsius

• Wealthier countries must provide $100 billion from 2020

• Aim for greenhouse gas emissions to peak as soon as possible

• Amount should be updated by 2025

• Rapid reductions to achieve net zero emissions

• Limit the rise in gobal temperatures to 1.5 degrees Celsius

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Carbon Budget

Sectors where emission reductions come from

Accounting and Analysis

How was Manchester’s Carbon Budget Calculated? Local authorities use the SCATTER (Setting City Area Targets and Trajectories for Emissions Reduction) tool to build a highly detailed inventory of their area’s annual emissions which allows them to identify the largest sources of emissions and therefore come up with strategies to reduce these emissions. This tool was created by Anthesis, who are sustainability consultants and help organisations and authorities across the world by delivering sustainability performances (Blundell, 2019).

The scatter tool can be used alongside the local authority carbon budget given by the Tyndall Centre to work out the best approximations for future emissions and the rate at which local authorities need to reduce their emissions each year (Blundell, 2019). Carbon reductions. Image by (Draft Manchester Zero Carbon Framework 2020-2038, 2019)

What does the graph represent? The bar chart above (Five Year Environment Plan, 2019) shows the breakdown of carbon reductions and which sectors these reductions come from. The SCATTER models will allow us to understand the scale of the carbon reduction challenge, and by breaking down the emissions into sectors we will be able to advise each sector on which steps to take in order to reach zero carbon. From this research, it shows that in each year the majority of the carbon emission reductions comes from domestic building heat, hot water and cooking.

SCATTER tool. Image by (Blundell, 2019)

Carbon budget

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Carbon Analysis

Carbon Budget Summary

Policies and Funding

Policies and Strategies

Funding Total investment figure is £92.5m which is made up of £89.2m of capital investment and £3.3m of revenue investment. The breakdown of this by funder is below: - £23.5m is council funding - £32.9 is from the UK government - £25.7m is from greater Manchester Combined Authority projects - £4.9m is from the European Union - £1.1m secured by the Manchester Climate Change Agency for community projects.

£3.3m revenue investment

By using research from outsourced companies such as the Tyndall Centre and Anthesis, Manchester has been able to come up with a carbon budget which details the amount of carbon dioxide emissions given off each year and predicts the amount of emissions which should be given off every year until 2038, which is when Manchester aims to be zero carbon. In order to reach this goal, certain policies need to be put in place for individuals and businesses within Manchester which will align with each carbon budget period and allow the city to meet this target by the year 2038.

£1.1m £4.9m Climate change agency European Union

£23.5m Council funding

£25.7m Mcr authority

£89.2m

capital investment

£92.5m

Total investment Source: Manchester City Council, 2021

Carbon analysis

£32.9m

UK government

£89.2m breakdown

Source: Manchester City Council, 2021

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Systems Map Listing the key factors involved Below is a systems map showing the different factors which affect and are affected by new zero carbon policies and carbon budgeting. If one aspect in this system changes then the whole system will change and therefore each factor and the relationships between these factors need to be understood.

Source: Image by authors

Systems map

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Systems Dynamic Diagram Contributing factors, flows and relationships Systems dynamic diagram illustrates the various contributing factors mainly in the form of flows and relationships between certain factors. It highlights the nature of the relationship if there is firstly a direct or indirect relationship between the factors. Secondly, if the related factors have a negative or positive influence on each other. The diagram below is grouped into three main areas of interest that govern the system quantitative flows are important in providing tangible information for targets, whereas, the obtained data from this is derived from the flows of information documents. This group is then affected by the controls of policy dominated by the policymakers

£95 PER TONNE OF CARBON DIOXIDE

AECOM CARBON PRICES

CARBON OFFSETTING PRICES

BRICK

ENERGY ASSESMENT GUIDANCE REPORT

STEEL + CONCRETE

CONSTRUCTION TYPES

WHOLE LIFE CYCLE CARBON ASSESMENT

CARBON OFFSET GUIDANCE REPORT

STEEL + GLASS

TIMBER

FLOWS OF INFORMATION

KEY MEMBERS

POLICY IN RELATION TO ZERO CARBON CITIES

BENCHMARKS

CARBON EMISSIONS

ARCHITECTS DEVELOPERS INDUSTRY EXPERTS

EMBODIED ENERGY

GOVERNMENT FRAMEWORK

CARBON STORAGE

SEQUESTERED CARBON QUANTITATIVE FLOWS

LOCAL PLAN

CITY COUNCIL

INCENTIVES

THIRD PARTY CONSULTANTS CONTROLS OF POLICY

Source: Image by authors

Systems dynamic diagram

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The Government/ Policy Frameworks

Policy Research

The diagrams below show the frameworks for both Manchester and London on how the cities willl reach zero carbon. Both cities follow a similar structure however London follows a more detailed plan which outlines specific benchmarks and goals, which Manchester hasn’t outlined yet.

Research Methodology Manchester Zero Carbon - 2038

Manchester vs. London Policies

Manchester Local Plan London’s borough of Newham is one of the best performing borough in terms of being on track/close to its net zero ambitions, which is why it has been chosen for comparison against Manchester, so that we can understand their strengths and see if it can be applicable to Manchester. Newham has a population of around 352,000 over an area of 36.21km2, comparing to Manchester which has a population of around 553,000 in an area of 115.6km2.

Manchester City Council

Manchester Climate Change Framework

Paris Climate Agreement

Outsourced Carbon Accounting Planning Authority

Tyndall Centre Research

Manchester Zero Carbon Advisory Group - BREAAM, LEED possibly

Stakeholders Developers

STUDY STRATEGIES PROVIDED BY GOVERNMENT TO REACH NET ZERO

Architects Other industry experts

Analyse the framework and steps provided Source:. Image by authors

London Newham Policy

COMPARE TO

Manchester Policy

London Zero Carbon - 2050 London Plan

Manchester Local Plan

Newham Local Plan

Paris Climate Agreement

Energy Assessment Guidance Report

Tyndall Research Centre

Carbon Offset Guidance Report

Manchester Zero Carbon Advisory Group

Whole Life Cycle Carbon Assessment

London Plan

Newham Local Plan

Greater London Authority (GLA) Newham Council

Energy Assesment Guidance Report Carbon offset Fund Guidance Report

Planning Authority

Source:. Image by authors Whole life cycle carbon assessment template (Planning Apps to utilise this from Summer 2021)

Stakeholders Developers Architects Other industry experts

Source: Image by authors

Policy research

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Zero carbon London by 2050

Newham Carbon Budget

-10

Policies and Strategies

In April 2019, Newham declared a climate emergency and was committed to achieving carbon neutrality by 2030 and net zero greenhouse gas emissions by 2050.

London Plan

CHG emissions (MtCO2e)

1. Evidence and Legislation

60 70

Greater London Authority (GLA)

100 2000

Newham Council

Newham Local Plan

Reduction over 1990 levels

2005

2010

No additional action

2015

2020

2025

With additional electricity and gas grid decarbonisation

2030

2035

2040

With additional local action

2045

2050

Reported emissions - LEGI

Energy Assesment Guidance Report Source: Zero Carbon Technical Seminar, n.d.

Planning Authority

Carbon offset Fund Guidance Report

Newham Emissions and Trajectory

Whole life cycle carbon assessment template (Planning Apps to utilise this from Summer 2021)

Stakeholders

Year

Carbon Emissions

Developers Architects

2014/2015

16,847

2015/2016

14,969

2016/2017

14,164

2017/2018

12,329

Other industry experts

Source: Image by authors

2. External Influences

The Council’s total emissions for 2019/20 were 7,125 tonnes of C02, a 42% reduction within the timeframe of this administration (Since 2017/18); and some 58 per cent since data collection Commenced in 2014/15.

Climate Change Act

GLA Act

Paris Agreement

2018/2019

9,216

‘‘However, this trend alone is not sufficient enough to guarantee that we will meet our C02 targets. To achieve these goals, we need to continue being ambitious in our plans’’

min 80% reduction in carbon emission

Mayor has legal responsibility to address climate change

international urge for deep and urgent cuts in CO2

2019/2020

7,125

(Newham Climate Change report, 2020)

Source: Newham London Council, 2020

Newham carbon budget

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Newham Carbon Budget Policies and Strategies

London Plan Strengths and Weaknesses (Policy Criteria)

Building Regulation Policies

- Major non residential buildings are to meet excellent standards of BREAAM UK New Construction.

Decarbonisation of grid and effect of policy implementation

- However, residential buildings are to be in line with London Plan which states only positive trends and no specific targets. - With a majority of Newham Council being residential, it is counteractive for a strong policy to reach net zero by 2050. - However, Policy SC1 b mentions all developments incorporate water efficiency measures to achieve target of 105 litres or less per head per day, 'excellent' 01 rating. Similarly, this doesnt apply to non residential schemes and is upto discretion.

Source: Zero Carbon Technical Seminar, n.d.

Source: Newham Council, 2018

- Environmental resilience is mentioned as an important factor and certain indicators to keep on track to meet net zero ambitions.

- Building regs use outdated carbon emission factors that do not reflect the recent decarbonisation of the grid. - Governments draft carbon emission factors have been consulted on but not yet adopted at a national level (closer to reality)

- However, as highlighted in SC-OP-01 no specific targets only positive trends are attributed for policy, therefore monitoring and robustness of policy is very weak.

Mitigating flaws - London Plan responds through heating hierarchy ensuring new buildings are not locked into high carbon energy systems. - Technologies that previously performed well with high grid emission factors (eg. CHP) will not achieve the same savings in future.

Source: Newham Council, 2018

- One positive from this is the policy intention can be changed or adaptable as this is a plan for 15 years, however stakeholders and designers can utilise this loophole to use the lowest rating or marginal positive trends in carbon accounting to align with policy.

- Updated energy assesment guide encourages use of updated carbon factors until building regulations are updated.

Newham carbon budget

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Newham Carbon Budget Policies and Strategies

London Plan Strengths&Weaknesses (Policy and Criteria)

GLA Energy Assesment Guidance Document

Documents required for Planning Application:

- The use of Smart meter technology encouraged in policy allowing occupants to record and monitor their data usage is very useful for carbon accounting on a widespread level.

- Design and Access Statement - Sustainability Assessment

- Unlike water consumption where the targets and monitoring policy is vague, major developments are required to carry out post construction audits demonstrating compliance with targets and deliver data to Local Authority for min. 3 years post occupation.

- BREEAM Pre-assessment report - Environmental Impact Assessment - Whole Carbon Life Cycle Assessment

- Energy Strategy/Assesment required at planning stage illustrating compliance to GLA guidance concerning zero carbon.

- Circular Economy Assessment

Source: Energy Assessment Guidance, 2020

Source: Newham Council, 2018

- "Demonstrate how the net zero carbon target for major development will be met, with atleast 35% on site reduction beyond Part L 2013 and proposals for making up the shortfall to achieve net zero carbon."

- Water efficiency although not given a set specific target, but efficiency outputs must be provided at application stage and this is done by use of Part G or any water efficiency calculator. Source: Newham Council, 2018

Source: Energy Assessment Guidance, 2020

Newham carbon budget

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Newham Carbon Budget

Manchester Carbon Budget

Policies and Strategies

Carbon Offsetting - If the net zero-carbon target cannot be met on site and the GLA is satisfied that onsite savings have been maximised, then the annual remaining carbon emissions figure is multiplied by the assumed lifetime of the development’s services (e.g. 30 years) to give the cumulative shortfall.

1. Evidence and Legislation Manchester City has announced that it hopes to become zero carbon by 2038 by implementing specific policies and benchmarks.

- The cumulative shortfall is multiplied by the carbon dioxide offset price to determine the required cash-in-lieu contribution.

Manchester Local Plan

Manchester City Council

- Boroughs are expected to use the recommended carbon offset price of £95 per tonne of carbon dioxide. (Mayor of London, 2018)

GLA Energy Assessment Guidance Document

Manchester Climate Change Framework

Paris Climate Agreement

Outsourced Carbon Accounting Tyndall Centre Research

Manchester Zero Carbon Advisory Group - BREAAM, LEED possibly

Planning Authority

Stakeholders Developers Architects Other industry experts

Source: Image by authors

2. External Influences Climate Change Act

GLA Act

Paris Agreement

min 80% reduction in carbon emission

Mayor has legal responsibility to address climate change

international urge for deep and urgent cuts in CO2

Source: Energy Assessment Guidance, 2020

Newham carbon budget

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Manchester Carbon Budget Policies and Strategies

Manchester Plan Strengths and Weaknesses (Policy Criteria) This page looks into the strengths and weaknesses within Manchester's zero carbon policy document, specifically looking into zero carbon building development and the benchmarks which need to be set in order to reach the zero carbon goal by 2038.

Policy EN6 is the singular policy stating the use of a minimum target of energy ef ficiency as a criteria for planning application submitted as part of a design and access statement.

Source: Manchester City Council, 2012 As stated earlier, the building regulations energy targets as a measure is outdated highlighted by London Plan.

Similar to the London Plan, the Manchester plan in outlining its policy is very vague as it states the consideration and requirement but does not address any specific goals or targets that might be crucial to meet net zero targets. As the outsourced private companies handle data analysis and target setting, the data is difficult to access and with no framework in place can be difficult to follow in line with a vague policy plan of action.

Manchester carbon budget

Source: Manchester City Council, 2012

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WLCC Document Policies and Strategies

Whole Life Cycle Carbon Assesment Document WLC emissions are those carbon emissions resulting from the construction and the use of a building over its entire life, including its demolition and disposal.

Source: Mayor of London, 2020 Source: Mayor of London, 2020 They capture a building’s operational carbon emissions from both regulated and unregulated energy use, as well as its embodied carbon emissions, i.e. those associated with raw material extraction, manufacture and transport of building materials, construction and the emissions associated with maintenance, repair and replacement as well as dismantling, demolition and eventual material disposal. Required to submit WLC at these stages to Planning Authority •Pre-application • Planning application submission (i.e. RIBA Stage 2/3) • Post-construction (i.e. upon commencement of RIBA Stage 6 and prior to the building being handed over, if applicable. Generally, it would be expected that the assessment would be received three months post-construction) (Energy Assessment Guidance, 2020)

WLCC document

BS EN 15978 and the RICS PS set out four stages in the life of a typical project described as life-cycle modules: • Module A1 – A5 (Product sourcing and construction stage) • Module B1 – B7 (Use stage) • Module C1 – C4 (End of life stage) • Module D (Benefits and loads beyond the system boundary) (Energy Assessment Guidance, 2020) A further set of aspirational WLC benchmarks have been developed which are based on a 40% reduction in WLC emissions on the first set of WLC benchmarks. This is based on the World Green Building Council’s target to achieve a 40% reduction in WLC emissions by 2030. If manchester is to become zero carbon by 2038, these aspirational WLC benchmarks are to be used as the conventional standards.

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The Question?

Mathematical Model

What is our approach?

Steps taken to Investigate Question

To test whether the benchmarks/targets set out in the framework are substantial in keeping Manchester on track to becoming zero carbon by 2038.

Find the ratio of building use in Manchester (Office, Retail, Residential, etc.)

Use data as a representation of Manchester on a smaller scale eg. - 50 buildings

Calculate the carbon emissions of each different building and construction typology eg. - timber, steel, glass construction

Testing these calculations against Manchester's emissions budget eg. - 3.6 million tonnes CO2/e (2018-2023)

- Also test best case scenario carbon emissions for a sample of Manchester - Analyse if aligns on track to 2038 net zero goal

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Calculations

Steps and Process

Calculate the carbon emissions of each different building and construction typology eg. - timber, steel, glass construction

Manchester's emissions budget (Tyndall Centre target) eg. - 3.6 million tonnes CO2/e (2018-23) 4 900,000 tonnes CO2/e per year

Calculate volume of building using different sizings for a typology

Calculate WALL + FLOOR mass = (Volume) x Density of material

eg - 80x20x30 and 100x30x60 for Mid - Rise Offices

eg - Density of brick = 2000 kg/m3

TOTAL EMISSIONS = (WALL + FLOOR) MASS x EMBODIED CARBON (material) eg

- embodied carbon of brick = 0.454 kgCO2e

11 % of emissions attributed to construction and building materials

O.11 99,000 tonnes CO2/e per year

MAIN TARGET

RESULT

REPRESENTATIONAL CITY INCLUDES 50 BUILDINGS

BREAKDOWN OF TYPOLOGY PERCENTAGE IN MANCHESTER CITY CENTRE

Time taken to construct certain typology High rise Residential - 2 years Mid rise Residential - 1 year Retail - 6 months Offices - 1 year Educational - 8 months

Number of Buildings of certain typology in representational city

Residential - 46%, Retail - 32% , Offices - 14%, Educational - 6% , Green space - 2%

06 05

RESULT

Total emissions for typology

EMISSIONS CALCULATION includes 3 versions based on performance excellent, medium, poor

Best case scenario - 70,302 tonnes CO2/e per year

177,859 tonnes CO2/e per year

TOTAL EMISSIONS FOR TYPOLOGY

FINAL RESULT

Calculations

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Calculations and Results

Generated Model

Background Calculations and Final Results

Representational City

Manchester has total 285 HighRise buildings, and 41 MidRise. HighRise + MidRise Offices = 14% of buildings in Manchester Hightrise + MidRise Residential = 46% of buildings in Manchester HighRise+MidRise Total = 60% of buildings in Manchester (100/60) x 285= 475 = total number of buildings in Manchester Representational City = 50 Buildings = 10.53% of Manchester

Illustrating the model and typologies used to create the representational city, to note it does not involve analysis of urban morphology or the relationship between the buildings. A purely calculative model

Results from Representational City x 9.497 = Results for Manchester

Best scenario - 70,302 tonnes CO2/e per year

99,000 tonnes CO2/e per year

MAIN TARGET

177,859 tonnes CO2/e per year

FINAL RESULT

Going forward these construction methods and per year rate numbers are not enough to meet net zero target by 2038

Calculations and results

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Investigation Summary

Bibliography

Final thoughts and summaries Greatermanchester-ca.gov.uk. 2019. Five Year Environment Plan. [online] Available at: <https://www.greatermanchester-ca.gov. uk/media/1975/5_year_plan_exec_summ_digital.pdf> [Accessed 13 November 2021].

• From our analysis and calculations, policymakers should update their documents as to accurately record progress consistently at all scales of the system - policy, local council, boroughs and down to independent homes. •The ability to track and set smaller goals is imperative to meet any larger target, however, this seems to be missing and within the policy documents, in the occassion a target or goal is specified; the effect is dampened as they specify building regulations of older documents such as 2010 or specify targets that are not a requirement to meet for architects and designers. •There is little incentive for designers and architects to be sustainable, from awareness created by the government and campaigns. This area of focus is improving as certain budgets are being allocated for zero carbon funding as evidenced by Newham council. •Although Newham's framework needs improving, it is more robust than Manchester in two regards, one - from a policy and goal setting perspective. Secondly, the carbon data analysis and target achievement is outsourced to private companies instead of being done by the architects, designers. This creates complexity and barriers for the government as these companies are non transparent with their data and tools resulting in greater difficulties for regulation/monitoring/controlling flow of information.

Nationalgrideso.com. 2019. What is net zero and zero carbon?. [online] Available at: <https://www.nationalgrideso.com/futureenergy/net-zero-explained/net-zero-zero-carbon> [Accessed 13 November 2021]. Democracy.manchester.gov.uk. 2019. Draft Manchester Zero Carbon Framework 2020-2038. [online] Available at: <https:// democracy.manchester.gov.uk/documents/s5288/5.1%20-%20Manchester%20Zero%20Carbon%20Framework%20202038%20-%20App%201.pdf> [Accessed 13 November 2021]. Secure.manchester.gov.uk. 2021. Zero Carbon Manchester. [online] Available at: <https://secure.manchester.gov.uk/ info/500002/council_policies_and_strategies/3833/zero_carbon_manchester/2> [Accessed 13 November 2021]. Gray, A., 2016. 5 charts that explain the Paris climate agreement. [online] World Economic Forum. Available at: <https://www. weforum.org/agenda/2016/11/5-charts-that-explain-the-paris-climate-agreement/> [Accessed 13 November 2021]. Blundell, B., 2019. SCATTER Offers Local Authorities a Solution for Climate Action. [online] Anthesisgroup.com. Available at: <https://www.anthesisgroup.com/scatter-greenhouse-gas-tool-offers-a-quicker-easier-solution-for-cities-to-delivercomprehensive-climate-action/> [Accessed 13 November 2021]. Manchester City Council, 2021. Manchester City Council Climate Change Action Plan 2020-25. [online] Manchester: Manchester City Council, p.7. Available at: <https://democracy.manchester.gov.uk/documents/s22754/MCC%20Climate%20Change%20 Action%20Plan%202020-25.pdf> [Accessed 13 November 2021]. Mayor of London, 2018. Carbon Offset Funds. [online] London: Greater London Authority. Available at: <https://www.london.gov. uk/sites/default/files/carbon_offsett_funds_guidance_2018.pdf> [Accessed 13 November 2021]. Newham London Council, 2020. Newham's Climate Emergency Annual Report 2020-2021. London: Newham Council, p.6. Premalatha, M., Tauseef, S., Abbasi, T. and Abbasi, S., 2013. The promise and the performance of the world's first two zero carbon eco-cities. Renewable and Sustainable Energy Reviews, [online] 25, pp.660-669. Available at: <https://www.sciencedirect.com/ science/article/abs/pii/S1364032113003146> [Accessed 13 November 2021]. Manchester City Council, 2021. Manchester Residential Quality Guidance. Manchester: Manchester City Council.

•Through the use of data driven approaches and computational abilities in liasion with robust policies, the targets stated by the government to reach net zero by 2038 is achievable. Policy incentivisation and a thorough collaboration between policymakers and designers would contribute to a cohesive approach of making manchester net zero.

2020. Energy Assessment Guidance. 1st ed. [ebook] London: Greater London Authority. Available at: <https://www.london.gov. uk/sites/default/files/gla_energy_assessment_guidance_april_2020.pdf> [Accessed 13 November 2021]. n.d. Zero Carbon Technical Seminar. Newham Council, 2018. Newham Local Plan 2018. [online] London: Newham London Council. Available at: <https://www. newham.gov.uk/downloads/file/1111/newham-local-plan-2018-pdf-> [Accessed 13 November 2021]. Mayor of London, 2020. Whole Life-Cycle Carbon Assessments Guidance. [online] London. Available at: <https://www.london. gov.uk/sites/default/files/wlc_guidance_consultation_version_oct_2020.pdf> [Accessed 13 November 2021]. Manchester City Council, 2012. Core Strategy Development Plan Document. [online] Manchester: Manchester City Council. Available at: <https://secure.manchester.gov.uk/info/200074/planning/3301/core_strategy> [Accessed 13 November 2021].

Investigation summary

Poor Air Quality is more harmful to health than the Covid 19 Pandemic yet very little action is taken to reverse the situation. This chapter beigns to unpack air quality in the UK by first understanding it’s emissions overtime by sector. Followed by consumption patters to decode human behaviours. Finally, the city of Manchester will be discussed before exploring solutions.

INTRODUCTION This chapter explores the role of air quality in our day to day lives .

SECTION ONE

SECTION TWO

SECTION THREE

Emissions

Consumption

Manchester's Air Quality

SECTION FOUR

SECTION FIVE

CONCLUSION

Health

Solutions

Chapter Summary

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AIR QUALITY CONTRIBUTIONS CONTRIBUTIONS TOWARDS ZERO CARBON

Tazeen Raza, Jack Whitehouse, Maryam Al-Irhayim

Zero Carbon Cities

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What is Air Quality? An Introduction to Air Quality in Manchester, with Consideration to the Key Sectors Contributing to Air Quality Levels

Air quality is a measure of how polluted the air around us is. Monitoring the air quality is a key consideration, as poor air quality can lead to many concerns and problems, effecting human health and providing extensive damage to the environment around us.

Air Quality & Zero-Carbon Cities Air quality is a major factor when it comes to achieving a Zero-Carbon approach as trends and figures show that certain contributors are affecting the atmosphere producing Greenhouse Gases which consists of Carbon Dioxide, Nitrous Oxide and Methane while other major pollutants; Carbon Monoxide, Airborne Particles, Nitrogen Dioxide, Sulfur Dioxide and the ever-effecting Ozone layer. All aspects that need to be combated to achieve ZeroCarbon.

2038

The Air Quality Index

Manchester’s Aim to be Zero-Carbon

15AQI Manchester’s Air Quality Index Level

1200

Adapted from (AirNow.gov 2021)

Key Contributors Key Contributors

Deaths

Related to Air Quality Levels in Mancheseter

30%

Manchester’s CO2 Emissions come from

20%

9% - Industry Total 20% - Commercial Total 9% - Public Sector Total

Homes, Workplaces and Transport

32% - Domestic Total 9%

30% - Transport Total

32% 9% - Industry Total

Introduction

20% - Commercial Total

9% - Public Sector Total

32% - Domestic Total 30% - Transport Total Climate Change Framework, 2020) Diagram by Authors. Adapted from Manchester

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Chapter Sequence Breakdown of the Topics within the Air Quality Chapter

According to the Kyoto Protocol, the GHG inventory covers seven GHGs: Carbon Dioxide (CO2) Methane (CH4) Nitrous Oxide (N2O) Hydroflurocarbons (HFCs) Perflurocarbons (PFCs) Sulphur hexafluoride (SF6) Nitrogen Trifluoride (NF3) DIRECT CO2

Air Quality

EMISSIONS IN THE UK

IDENTIFY KEY CONTRIBUTOR

Introduction

Multiple Cell Model Fixed Box Model

IDENTIFY IMPACTS ON URBAN CITIES THROUGH POLLUTANTS

EMISSIONS IN MANCHESTER

IDENTIFY KEY SECTORS

INDIRECT CO2

Energy (Electricity, Gas) Transport (Private/Public) Waste Management Agricultre, Forestry, Land Use Residential Commercial

DOMESTIC

NONDOMESTIC

CONSIDER AIR POLLUTION AS A BY PRODUCT

CONSIDER EXISTING METHODS OF MODELLING

USE EXISTING METHODS, CREATE OWN TO OFFER SOLUTION

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Measuring Air Quality As covered in the previous chapter there is a variety of governing bodies that legislate with policy however each with their own personal aims.

Governing Bodies in the UK

What about Manchester

Air can be considered a commodity. Those who are able to afford it have access to cleaner air as determined by their geographical region or neighbourhood. With an active effort to integrate different demographics to create an inclusive society, it is the role of various monitoring bodies each with their own influence to maintain the neutrality and quality of the air we breathe. Some of these governing bodies in the UK include:

Three automatic monitoring stations at the highlighted areas which document hourly data that is independently audited.

EEA European Environment Agency UNSD UN Sustainable Development Goals DAQI Daily Air Quality Index AURN Automatic Urban and Rural Network DEFRA Department for Environment, Food, Rural Affairs NAEI National Atmospheric Emissions Inventory NAO National Audit Office

Clean Air Greater Manchester Air Quality England UK Air Picadilly Gardens

Oxford Road

The Manchester we want by 2038 While the UK aims to reach its climate targets in 2050, Manchester is aiming further. With an endeavour to become Net Zero by 2038, that is twelve years ahead of the national goal, Manchester is ready to outperform the capital. Some of the city’s goals include the following: Whythenshawe

Decarbonise the city

Improved Health

Efficient Transport

Cleaner Energy

Sustainable Homes

Renewable Energy

Introduction

Diagram adapted from AirNow.gov 2021

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Issues and Factors

Nitrogen

Carbon Monoxide Essential Gases

Exploring Relationships Between the Factors of Air Quality

This is largely due to the pollutants that have become an integral part of our lifestyle. Public electricity and heat production contributes to approximately 30% of all carbon dioxide emissions and 26% of all greenhouse gases in the European Union Countries. Longterm exposure to greenhouse gases and related pollutants such as particulate matter leads to cardiovascular diseases, lung cancer, asthma and a shorted life expectancy on a whole. Initial thoughts suggest advocating the use of public transport, walking and cycling to reverse the health impacts of poor air quality. If these were perhaps if incentivised by the local authorities they would have a greater positive impact.

Airborne Particles (PM)

Methane

Nitrogen Dioxide

Greenhouse Gases

This mind map begins to unpack the issues and factors that effect Zero Carbon Cities involving Air Quality. The first theme that comes to mind is the direct effect on health. Poor air quality can lead to harmful toxins in the air being inhaled which is detrimental to the most vulnerable members of society. Air pollution is by far the largest environmental cause of poor health in Manchester. For example, there have been upto 1200 deaths each year in Greater Manchester due to poor air quality.

Oxygen

Nitrous Oxide

Atmosphere

Major Pollutants

Carbon Dioxide

Ozone

Major Contributor to Carbon Emissions

Public Electricity & Heat Production Contributes around 30% of all C02 Emissions and 26% of all Greenhouse Gases in EU-27 Countries

Sulfur Dioxide

Public Transport, Walking &

Air Quality

How can Air Quality be Improved?

The Issues’ & Factors’ that effect Zero-Carbon Involving Air Quality Plant & Care for Trees Renewable Energy Sources (Reduce Fossil Fuel Consumption)

Manchester = Good Level (16 AQI Points)

Cardiovascular & Respiratory Air Quality Index

Records Air Quality data in relation to levels of Health Concern

Health Links to Type2 Diabetes, Obesity, Alzheimer’s & Dementia Lack of Activity = Cycling & Walking

Impacts

Lung Cancer

Asthma

Mortality

Main Pollutant = PM2.5

Industrial Processes and Vehicle Fumes

Emissions

£5.3 Billion Health & Social Care cost in England by 2035 unless action is taken.

Air Pollution is the biggest environmental cause of poor health upto 1200 deaths each year in Greater Manchester are contributed to by poor air quality.

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Greenhouse Gases’

2% - HFC, PFC,

16% - Methane

The following diagrams highlight carbon dioxide as the largest contributor to the greenhouse gas emissions with energy use causing significant damage

The atmosphere comprises of many greenhouse gases which are a by product of industrial processes and a general make up of the atmosphere. Too much of any one of them can prove to be detrimental to our surroundings. Up to 76% of the earth’s atmosphere comprises of carbon dioxide followed by methane which represents 16% of air due to green house gas emissions. This is largely due to the huge demand of energy we have as a result of our comfortable, first world lifestyle. Up to 31% of energy is consumed in electricity and heat which is understandable as the UK has a temperate climate and we require additional heat to keep our homes, schools and offices warm. Having said that, we also have a luxurious lifestyle where we opt for more complacent choices that prioritise comfort rather then environment. An example of this is driving short distances which are easily walkable. This leads to highlighting transportation as the next biggest demand at 15% as we have sufficient disposable income to travel however and how often we like. Finally, manmade greenhouse gas emissions echo the statistics of the greenhouse gas emissions pie chart with 72% of emissions being released from the Energy Sector.

Greenhouse Gas Emissions

6% - Nitrous Oxide

76% - Carbon Dioxide

6% - Industrial Processes 11% - Agriculture

Manmade

3% - Waste 6% - Land-Use

72% - Energy

31% - Electricity & Heat 12.4% - Manufacturing & Construction 8.4% - Other Fuel Combustion

Energy

2% - Bunker Fuels 5.2% - Fugitive Emissions 15% - Transportation

Diagram by authors, 2021. Data sourced from Governement Department for BEIS.

Emissions

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UK Carbon Budget 2013

254, 400 ktCO2e 2017

2018

195, 000 ktCO2e 2022

2023

172, 500 ktCO2e 2027

2028

2032

Greenhouse Gas Emissions UK Greenhouse Gas Emissions Provisional Figures 2020 (MtCO2e) showing a negative correlation between emissions and time suggesting a promising decline

900 800 700 600 500 400 Percentage from year before

2% - 2% - 8%

2019 2020

2018

2017

2015 2016

2013 2014

2012

2011

2009 2010

2008

2007

2005 2006

2003 2004

2002

2001

1999 2000

1998

1997

1995 1996

1994

1993

1992

1991

1990

- 10%

UK Territorial greenhouse gas emissions, 1990-2020. Here we see a massive fall in greenhouse gas emissions Graph from Governement Department for BEIS: Annual Statement of Emissions,2018

Table from Governement Department for BEIS: Annual Statement of Emissions,2018

Total 2017- Carbon budget 460, 989, 443 tCO2e - 278, 200, 000 tCO2e = 182,789,443 tCO2e (278, 200, 000 tCO2e / 460, 989, 443 tCO2e) x100 = 60.3%

Total CO2 2017- Carbon budget 373, 801, 849 tCO2e - 278, 200, 000 tCO2e = 95, 601, 849 tCO2e (278, 200, 000 tCO2e / 373, 801, 849 tCO2e) x100 = 7.4%

Total 2018 - Carbon budget 451 463 569 tCO2e - 254 400 000 tCO2e = 197 063 569 tCO2e (254, 400, 000 tCO2e / 451, 463, 569 tCO2e) x100 = 56%

Total CO2 2018- Carbon budget 451 463 569 tCO2e - 254 400 000 tCO2e = 197 063 569 tCO2e (254, 400, 000 tCO2e / 451, 463, 569 tCO2e) x100 = 56%

The figures above show the carbon budget targets the UK has set which contradict the figures in the table below. Net UK GHG Emissions by gas, base year, 2017, 2018 (tCO2e) shows carbon dioxide as the largest contributer to UK Emissions

Do we need a global financial crisis or a pandemic to reduce our emissions? 64

Emissions

Government Data highlights the UK consistently exceeds it own carbon budget targets without much accountability. 65

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Emissions by Sector i Greenhouse Gas Emissions in KTonnes CO2e showing a breakdown of usage by sector in the UK1990 - 2018

Water supply dwelling services

Misc goods and services

Restaurants and hotels

Purchase of vehicles

Furniture, furnishings, carpets

Other Recreational Equipment

Clothing

Recreation and Audio, cultural services visual, photos

Maintenance of dwelling

Acoholic Non-Aco- Medicine Beverages holic Supplies Beverages

Glassware

House- Appli- Tools ances hold Utensils APL ToMerbacco DRI chan-

Textiles

MRC TES SHO

dise Diagram by Authors, 2021. Data sourced from Governement Department for BEIS: Annual Statement of Emissions,2018

Electricity, gas and other fuels

Other Recreational Equipment

Operation of personal transport

Purchase of vehicles

Food

Clothing

Transport Services

Furniture, furnishings, carpets

Water Supply and misc dwelling

Recreational and cultural services

Misc goods and services

Audio, visual, photography

Restaurants and hotels

Maintenance and repair of dwellings

Misc goods and services

Glassware, tableware and utensils

Emissions

Main contributors to UK GHG Emissions:

The table above highlights that the energy sector demands the greatest use of emissions followed by the transport

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Emissions by Sector ii CO2 Emissions in KTonnes CO2e showing a breakdown of usage by sector in the UK by sector from1990 - 2018 Misc goods and services

Purchase of vehicles

Other recreational equipment

Water supply dwelling services

Restaurants and hotels

Furniture, furnishings, carpets

Other Recreational Equipment

Recreation and cultural services

Audio, visual, photos

Clothing

TES

Acoholic MainteBeverages nance of dwelling

Medicine Supplies

APL

Glassware

Textiles

Non-Acoholic Beverages

HouseAppli- Merances chan- hold U dise MRCSHO DRI Tools Tobacco

Diagram by Authors, 2021. Data sourced from Governement Department for BEIS: Annual Statement of Emissions,2018

Main contributors to UK GHG Emissions:

Electricity, gas and other fuels

Clothing

Operation of personal transport

Purchase of vehicles

Transport Services

Clothing

Food

Furniture, furnishings, carpets

Restaurant and Hotels

Recreational and cultural services

Misc goods and services

Audio, visual, photography

Purchase of Vehicles

Maintenance and repair of dwellings

Other recreational Equipment

Glassware, tableware and utensils

Emissions

The table above highlights that the energy sector demands the greatest use of carbon dioxide emissions followed

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UK CO2 Emissions

Graphs showing trend lines for GHG Emissions in the UK from 1990-2020, the UK CO2 Emissions and UK Energy oil equivalence.

CO2 Emissions in the UK (KTonnes)

CO2 Emissions in the UK (KTonnes) 600,000 500,000 400,000 300,000 200,000

Emissionsin in the the UK CO2e) GHGGHG Emissions UK(KTonnes (KTonnes CO2e) 700,000

100,000

600,000

-00 1985

500,000

1990

1995

2000

2005

2010

2015

2020

This shows a negative correlation suggesting the CO2 emissions overtime are decreasing in the UK

400,000 300,000

Energy NRG Oil Equivalence (KTonnes)

200,000 100,000

145,000

-00

140,000

1985

1990

1995

2000

2005

2010

2015

2020

This shows a negative correlation over the thiry year period suggesting the greenhouse gas Diagram by Authors, 2021. Data sourced from UK’s Carbon Footprint, Gov.uk, 2020

135,000 130,000 125,000 120,000 115,000 1985

1990

1995

2000

2005

2010

2015

2020

This graph shows a series of dispersed data points highlighting the fluctuating demand and supply thus suggesting a volatile market in the UK Diagram by Authors, 2021. Data sourced from UK’s Carbon Footprint, Gov.uk, 2020

Emissions

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GHG breakdown UK GHG Emissions Breakdown in the UK

450000

400000

350000

250000

300000

150000

100000

50000

Changes in inventories Valuables Gross fixed… Local… Central… Non-profit… Miscellaneous goods and services Restaurants and hotels Education Newspapers, books and stationery Recreational and cultural services Other recreational equipment etc Other major durables for recreation and culture Audio-visual, photo and info processing equipment Telephone and telefax services

2018 2010 2000

Telephone and telefax equipment Postal services Transport services Operation of personal transport equipment Purchase of vehicles Hospital services Medical products, appliances and equipment Goods and services for household maintenance Tools and equipment for house and garden Glassware, tableware and household utensils Household appliances Household textiles Furniture, furnishings, carpets etc Electricity, gas and other fuels Water supply and miscellaneous dwelling services Maintenance and repair of the dwelling Imputed rentals for households Actual rentals for households Footwear Clothing Tobacco Alcoholic beverages Non-alcoholic beverages Food

Valuables

Local…

Gross fixed…

Central… Non-profit…

Restaurants and hotels

Miscellaneous goods and services

Education Newspapers, books and stationery

Other recreational equipment etc

Recreational and cultural services

Other major durables for recreation and culture Audio-visual, photo and info processing equipment Telephone and telefax services Telephone and telefax equipment

Transport services

Postal services

Operation of personal transport equipment

Hospital services

Purchase of vehicles

Medical products, appliances and equipment Goods and services for household maintenance Tools and equipment for house and garden Glassware, tableware and household utensils

Household textiles

Household appliances

Furniture, furnishings, carpets etc

Water supply and miscellaneous dwelling services

Electricity, gas and other fuels

Maintenance and repair of the dwelling

Actual rentals for households

Imputed rentals for households

Footwear

Tobacco

Clothing

Non-alcoholic beverages

Alcoholic beverages

Food

The trend has not changed in 30 years however each existing spike has increased significantly in its value. From the graphs we can observe that the greatest contributors to GHG are firstly the energy sector closely followed by the transport sector and finally the Gross Fixed Capital Formation (commercial) Sector thus these are the three areas we will be focusing on.

Changes in inventories

100000

Emissions 72

300000

350000

1990

2018 2010 2000 1990

GHG Emissions Breakdown in the UK 1990 - 2018 (KTonnes) GHG Emissions Breakdown in the UK 1990-2018 (KTonnes) GHG Emissions Breakdown in the UK 1990 - 2018 (KTonnes)

CO2 Emissions Breakdown UK 1990-2018

250000

200000

Diagram by Authors, 2021. Data sourced from UK’s Carbon Footprint, Gov.uk, 2020

Main contributors to UK GHG and CO2 Emissions: Electricity, gas and other fuels Operation of Personal Transport Gross Fixed Capital Formation (Commercial Sector)

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Systems Map

Sector responsible for 40% Greenhouse Gases in UK

Exploring causes and effects of Air Quality using a systems map tool to brainstorm key recurring themes.

Global Warming

Construction Dust

UN Development Goals

Concrete Timber Genetic

The systems map begins with four key themes: Emissions, health, Waste and Pollutants. From here we find that the transport sector in particular the ownership of private cars contributes to their excessive use which increases the demand for fuel. By extension this leads to a demand in the energy industry due to the lifestyle choices made in the UK. As a result, a rise in pollutants may be noted which include sulphur dioxide, nitrous oxides, methane and most importantly carbon dioxide. Long term exposure to these pollutants exacerbates human health leading to respiratory illnesses, asthma and genetically transferred illnesses which creates a cycle of poor health and thus a shortened life expectancy. Further, it may be noted that the construction sector contributes to 40% of greenhouse gases in the UK due to by-products from building materials the use of which highlight the vast amounts of human activity that participate in greenhouse gas emissions which in turn play an integral role in Global Warming. These are a few relationships that have been recorded so far. Later on in this chapter, more direct relationships and feedback loops will be discussed.

Material Embodied Energy

Deforestation Early Death

Asthma

Manufacturing

Health

Fossil Fuel Production

Construction Sector

Cancer

Increase in Greenhouse Gases due to Human Activity

Trees

Respiratory Illnesses Cement Production Long Term Exposure to Human Health

Pollutants Carbon Dioxide

Health

Globalisation

Sulfur Dioxide

Transport of Goods Commerical

Transport Sector

Emissions Electric

Waste Private

Air Quality

Tram Uber

Waste Particulate Matter

Fuel

Train

Greenhouse Gases

Nitrogen Dioxide

Cars

Public Bus

Pollutants

Circular Economy

Landfill Sites

Methane

Amount of people living in a household

Emissions

Fossil Fuel Combustion Domestic Sector (Household Use) Weather Conditions Type of Residence

Industrial Processes

National Grid

Energy Production

Nitrous Oxide Electricity

Heating Homes

Renewable Energy

Wind

Natural Gas Fossil Fuels

Consumption

Agriculture

Solar Human Behaviour/Choices

Fertillizer Application

Coal

Geothermal

electricity from renewables and nuclear generators. Given the information above about changes to heating technologies in homes, it comes as no surprise to see a big expansion in gas use in homes, with a parallel contraction in solid fuel use (see graph below). All fuels are measured in terawatt hours in the graph, TWh. (As a reminder, 12 this is a million million Watt hours, 10 Wh – equivalent to leaving on a small hairdryer in every home in Britain, continually, for 1.6 days.)

Domestic Emissions Almost half of all UK emissions are sourced from the typical household primarily for heating as discussed on this spread. Can the British home be designed in a way to reduce dependency on heating?

Today, gas provides two-thirds of household energy (excluding the gas used to generate electricity in power stations). In 1970, gas provided only a quarter of household energy.

Energy use in housing type by fuel

TWh

700

Gas

600

Solid

40% of ALL UK emissions come from households which is categorised as domestic. This includes Carbon Dioxide, Nitrous Oxide and Methane also known as Greehouse Gases.

electricity, and it is usually more difficult to move around, but renewable 300 heat is still a useful contribution to the UK’s energy mix.

OF ALL UK EMISSIONS

Diagram from The Committee for Climate Change, 2021

The UK’s use of renewable heat has quadrupled since 1990, and more than doubled since 2003 (see graph below). The largest share comes from 100 ‘bioenergy’: all renewable sources except aquifers, heat pumps and solar 0 heating. Wood combustion is the largest contributor to bioenergy, and wood burnt heating accounted for 1997 more2000 than2003 half 2006 of all 2009 2012 1970 1973 1976for 1979 1982 homes 1985 1988 1991 1994 renewable heat used in housing in 2012. Graph 8a: Energy use in housing by fuel type

Today, gas provides two-thirds of household energy excluding the gas used However, wood combustion has grown much more slowly than other to generate electricity in power In heating) 1970, gas provided onlystark: a quarter household energy. The demise of solidstations. fuels (for was even more they of provided sources of renewable heat. It grew 160% from 1970 to 2012, while active nearly half of the energy Graph usedsourced in homes in 1970, from (Palmer, 2013) but are down to just 2% solar heating (mainly solar water heating) grew by a factor of 24, and plant biomass nearly quadrupled. Solar water heating is now more than an eighth Renewable heatingeneration of renewable heat used housing. by fuel (not only for housing) 73

14000

Heat pumps Deep geo-thermal

12000

-36.72%

-44.44%

2014 8.1 Tonnes of CO2

18%

18% - Cold Appliances 15% - Cooking Appliances 15% - Wet Appliances 19% - Lighting

19%

15%

19% - Consumer Electronics

8000

Plant biomass

2030

6000

Animal biomass

4.5 Tonnes of CO2

4000

The CO2 emission factor used is of 0.277 kge / kWh. (2019) The average electricity consumption is 4,800 kWh per household. A smaller than average household is taken arbitrarily to be 3,000 kWh and a larger than average household to be 7,000 kWh

9% - Domestic ICT 5% - Other 19%

15%

Diagram adapted from The Committee for Climate Change, 2021

Consumption

Energy from waste combustion Anaerobic digestion

10000

Diagram from The Committee for Climate Change, 2021

Renewables

200

GWh

Average Domestic Electricity Use (Excluding Heating)

Oil

400

-64.84%

12.8 Tonnes of CO2

Electric

500 UK Housing Energy Fact File

The below diagram highlights the domestric emissions used by households since 1990 to reduce emissions by 64.84% in 40 year period.From the graphics it is clear to see the emissions for heating will rise while the aim for a lower CO2 in electricity production, transport use and waste disposal is in place. This may be achieved by the shift of using fossil fuels and the increase demand for renewable energy.

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A value of 2000 kWh per person per year is used for student accommodation in a hall of residence.

2000

Wood combustion domestic Sewage sludge digestion Landfill gas

Active solar heating

1990 1993 1996 1999 2002 2005 2008 2011 Graph 9b: Renewable heat generation by fuel (not only for housing)

Today, gas provides two-thirds of household energy excluding the gas used to generate electricity power In heat 1970,from gaslandfill provided a quarter of household energy. It appearsinthat the stations. decline in gasonly stems from competition Graph sourced from (Palmer, 2013) between electricity generation and heat production. Many times more landfill gas is now burnt to generate electricity than heat, which is beneficial for cost reasons and carbon emissions.

Microgeneration in housing Feed-in Tariffs, introduced in 2010, changed the landscape for generating renewable power in the home. FITs made it much more attractive for householders to add renewable electricity systems – and particularly ‘photovoltaics’ (solar electric arrays) to their homes.

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Pollutants in the Air Sankey Diagram

Commercial

Energy Carbon Dioxide

Transport

Nitrogen Dioxide Domestic

PM10

Agriculture

Methane

Diagram by Authors, 2021. Data sourced from UK’s Carbon Footprint, Gov.uk, 2020

Main Pollutants towards Air Quality

Consumption

2021 CPU[AI] UK Housing Energy Fact File

Part of the savings came from electricity itself having a lower carbon footprint, again due to the famous ‘dash for gas’ in the 1990s, when newly privatised electricity companies developed gas-fired power stations using North Sea gas to replace (more expensive) coal-fired power stations. However, the downward 20 yearsover before, and continued after Observing a promising decline oftrend CO2started per houshold a fourty year period (below) however2004. the population has increased significantly with 10 million more homes using more

Domestic CO2 Usage

energy between 1970 and 2012 (right) suggesting there are non-linear connections influencing Part of the savings also came from better insulation in homes and more the data. efficient space and water heating systems, reported above.

1970

2012

429

502

TWh

£20

£34

Billion/year

Tonnes TonnesCO2/ CO2/ household household 12

Tonnes CO2 per household

10 8 6 4

182

0 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009

The trendGraph between5i: theCO CO2 emissions perper household over time is a ‘lumpy’ one with troughs corresponding household 2 emissions to mild winters and peaks corresponding to severe ones and this lumpiness is likely to continue as households consume different amounts of energy depending on the season thus it sometimes supports and acts against Again, the trend is On ‘lumpy’, with troughsin corresponding and carbon savings per home. average, the reduction CO2 per householdto wasmild 2% awinters year

Graph sourced from (Palmer, 2013)this lumpiness is likely to continue peaks corresponding to severe ones, and – sometimes supporting and sometimes acting against carbon savings per home. On average, the reduction in CO 2 per household was 2% a year.

Reductions in CO2 per household a year

137

Million

Diagram by Authors, 2021. Data sourced from Palmer, 2013

Consumption

CO2

UK Housing Energy Fact File The UK’s use of energy to provide hot water in homes has fallen dramatically since 1970. This is athequiet success story. suggests Modelling suggested However, good news is that modelling a significant reduction in heating energy used since the cold year of 2010, and a gradual downward there was a cut of one third in energy used for hot water, in spite of the trend since 2004. The gradual trend does not appear to be the result of 27 increase of more than two-fifths in and thesome number of households graph milder winters, commentators (for example see(see reference ) have suggested that this is largely due to the increase in energy costs since 2004. below).

UK Housing Energy Fact File

(This section and the four sections that follow are based on modelling using Space heating However, the good news Model is that modelling suggests a significant reduction in BREHOMES Housing (CHM). Graphs drawn from Energy use for heating has and the Cambridge Heating by far thethe biggest slice of of 2010, UK household energy use. To heatingenergy energyisused since cold year and a gradual downward increased bymodelled a third in the past 40 data are highlighted with a coloured A brief summary of make serious inroads cuttingtrend CO2border. from reducing heating trend since 2004. Theingradual does housing, not appear to be the result energy of years. 27 has toare bewinters, part of any milder and solution. some reference ) have the modelling procedures included ascommentators Appendix(for 3, example and asee discussion of suggested that this is largely due to the increase in energy costs since 2004. uncertainty in modelling provided Appendix (Thisissection and thein four sections that4. follow are based on modelling using

The UK has cut energy use for heating by a fifth since 2004.

Hot water

Unsurprisingly, this led toThe a UK’s shrinkage in the proportion of household energy use of energy to provide hot water in homes has fallen sincenearly 1970. This30% is a quiet story. Modelling suggested used for water heating – dramatically down from tosuccess just 18%*.

BREHOMES and the Cambridge Housing Model (CHM). Graphs drawn from Hot water modelled data are highlighted with a coloured border. A brief summary of The modelling movedthe from using to CHM in 2009, so there The UK’s useprocedures of BREHOMES energy toare provide hot the water in homes modelling included as Appendix 3, has andfallen a discussion of dramatically since 1970. is asee quiet success story. Modelling suggested uncertainty modelling isThis provided inAppendix Appendix 4. 3.) is a discontinuity in time seriesindata in 2009,

* Evidence from EST Field Trials

suggested that less energy is used for hot water than we thought in the past. This improvement is Figures reported here have been water (through better lagging of tanks and pipes, and eliminating hot water 28 adjusted to the old Unsurprisingly, this led to a shrinkage in the proportion of household energy * Evidence from EST compared Field Trials used for water heating – down heating from nearly systems. 30% to just 18%*. tanks with combi boilers), and more efficient Greater use suggested that less energy is used for Domestic Energy Fact Files to reflect Household energy use has changed overtime with data showing less water consumption, hot water than we thought in the past. of electric showers and dishwashers – which heat water separately using with energy used for hot This improvement is consistent with the reduced heat loss from stored hot reported hereless have been reduced energy for space heating andenergy cooking with energy use forEnergy appliances onFigures anthis, (through lagging of as tanks and and eliminating hotFile water UKpipes, Housing Fact electricity – also reduces water usebetter recorded ‘water heating’. However, adjusted compared to the old water and more for heating. tanks with combi boilers), and more efficient heating systems. Greater use

Household Energy

there was a cut of one third in energy used for hot water, in spite of the increase of more than two-fifths in the number of households (see graph consistent below). with the reduced heat loss from stored hot

exponential rise.

even allowing for this there haveshowers still been significant total of electric and dishwashers – whichsavings heat waterfrom separately using electricity – alsoan reduces energyin useelectricity recorded as ‘water However, energy userecommend for hot water. UK, and we readers with interest referheating’. to that even allowing for this there have still been significant savings from total report. energy use for hot water.

80 60

Appliances

UK Housing Energy Fact File 15%

Water Heating’s UK, and we recommend readers with an interest in electricity refer to20% that 40 10% UK, and we recommend readers with an interest in electricity refer to that report. share 20 report.

Across all homes, the direction of travel needed to meetthis climate change objectives. Unsurprisingly, to a shrinkage the proportion of Modelling household energy Across all homes, theled four-decade storyinabout heating energy is not the used for water heating – down from nearly 30% to just 18%*. suggests heating energy increased just over a tenth (see graph below). This UK Housing Energy Fact File direction of travel needed to meet climate change objectives. Modelling suggests heating energy increased just over a tenth (see graph below). This is much less than the increase in theisnumber of households (upfrom from 18.8 This improvement consistent with the reduced heat loss stored hot to is much less than the increase in the number of households (up from 18.8 water (through better lagging of tanks and pipes, and eliminating hot waterto 27.1 million an increase of 44%). This means that improvements Third, much –greater use27.1 of cold appliances to44%). store food –heating freezers andinlarge million an increase This means that improvements in use tanks with –combi boilers),ofand more efficient systems. Greater insulation and heating system efficiency offset thewater effect of household fridges areand nowheating commonplace, and likely tooffset increase energy use even insulation system efficiency the effect of household of electric showers and dishwashers – which heat separately using growth, and–the demand warmer homes, see Chapter 6. electricity also reducesfor energy use recorded as ‘water heating’. However, though the efficiency of new cold appliances has improved. Further, growth, and the demandeven forallowing warmer homes, see Chapter 6. for this there have still been significant savings from total

5% 15%

survey provides a rich seameven of information aboutit electricity use. On The growth in appliances*0 The energy use has been sharper: has tripled 0%

* Evidence from EST Field Trials

suggested that less energy is used f hot water than we thought in the p Figures reported here have been adjusted compared to the old Domestic Energy Fact Files to reflec this, with less energy used for hot water and more for heating.

microwaves are oftenEnergy used toforuse thaw out frozen food. This energy service did energy for hot water. used Space heating's share of all spaceenergy heating (TWh) use for Space Heating household energy use Household not exist in 1970. 450 80%

Energy used for Space heating's share of all Energy used for water Water heating's share 400 space heating (TWh) 70% household energy use heating (TWh) 30 35% 140 Space Water survey mentioned above found that, on average, 450 The Powering the Nation 80% 350 60% heating

heating's share Energy used for The survey provides a rich seam ofwater information about electricityWater use.Water On heating's share heating (TWh) heating (TWh) 35% 140 140 average, it found that 15% 35% Water Water or more of the electricity used in homes surveyed heating heating 30% 120 % household was used for lighting. It found that homes in the study had an average of 34 120 30% energy % household 100incandescent bulbs, 24% compact fluorescents, 25% lights: 40% old-fashioned energy 80 fluorescent strip lights. 20% 100 31% halogen lights and 6% 25% UK Housing Energy Fact File 60

there was a cut of one third in energy used for hot water, in spite of the

increase of more thanfrom two-fifths the number households (see graph The modelling moved using in BREHOMES toofthe CHM in 2009, so there four-decade story about energy is abelow). discontinuity in time series dataheating in 2009, see Appendixis3.)not the

Domestic Energy Fact Files to reflect this, with less energy used for hot water and more for heating.

Household energy use for Water Energy used for water

Energy used for water heating (TWh)

2021 CPU[AI]

The UK has cut energy use fo heating by a fifth since 2004

heating

120 %household household 50% or more of the300 electricity consumption in homes surveyed was used 30% for % 50% 70% energy energy 250100 appliances. The work suggested that 16% of household electricity powers25% Space 40% 200 60% heating cold appliances (fridges 80 and freezers), 14% is used for wet appliances 20% 30% 150 UK UK Housing Housing Energy Energy Fact Fact File File % household (washing machines100 and 6% 60 dishwashers), 14% for consumer electronics, and 15% 20% 50% energy Space Heating’s for information and 50communication technology. readers 10% UK, and and we we recommend recommend readers with with an an interest interest in in electricity electricity refer refer to to that that10% 40UK,

400 350

Energy used for space heating (TWh)

300 250

40%

share of all household energy The The survey survey provides provides aa rich rich seam seam of of information information about about electricity electricity use. use. On On30% report. report.

200

0 20 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009

*Appliances are defined in the 0 0% 150 Cooking average, it found that 15% or of electricity used in homes surveyed average, found that 15% or more more of the the electricity used in 2006 homes surveyed 1970 1973it1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2009 Cambridge Housing Model as 20% was lighting. found in study had average The UK now uses two-fifths less was used used for lighting. It Itenergy found that that homes in the the study (TWh) had an average of of 34 34 Graph 5b:for Household use homes for space heating 100 A more positive outcome from changes inincandescent lifestyles, perhaps, is an energy was used lighting. It found that homes in the study had an average of 34 lights: 40%for old-fashioned incandescent bulbs, 24% compact fluorescents, lights: 40% old-fashioned bulbs, 24% fluorescents, energy was nearly 3% a year, although the annual rise appears to be lights: 40% old-fashioned incandescent bulbs, heating 24% compact compact fluorescents, everything except spacefor and water – partly Graph 5c: Household energy use for water heating (TWh) Graph 5c: Household energy use for water (TWh) energy cooking lights:halogen 40% old-fashioned bulbs, 24% compact fluorescents, 31% lights and 6%incandescent fluorescent strip lights. 20 5% 31% lights and fluorescent strip use for cooking is getting on(both for average half oftemperature what10% it and 31% halogen halogen lights and 6% 6% in fluorescent strip lights. lights. 50 saving from cooking. Energy Given the improvements thermal comfort slowing. heating, lighting, the oven main 31% halogen lights and 6% fluorescent strip lights. because ofand more efficient the number of rooms routinely heated), the growth in heating’s share of below). (Note, though, that part of this saving has 0% 0 was in 1970 (see graph Appliances Appliances hob. This meansappliances that the energy used ‘ready 0 0% and more total energy use in homes has been modest – from 58% to 62% – although Appliances really been to appliances energy, as past small portable devicesreflects Appliances 1970 1973just 1976 1979transferred 1982 1985 1988 1991 1994volatile 1997in2000 2003 Appliances’ share total1985 energy in 1994 homes hasuse followed a sharper: similar path, this proportion has been the been few2006 years. 2009 The volatility 1970 1973 1976 1979of1982 1988use 1991 1997 2000 2003even 2006 2009 The growth in appliances* energy has been it has tripled in microwaves, sandwich toasters and The *Appliances are defined inmeals’. the **Appliances The growth growth in in appliances* appliances* energy energy use use has has been even even sharper: sharper: it it has has tripled tripled Appliances are are defined defined in in the the like sandwich toasters and bread machines – which are included as the cold weather in 2010, by mildgrowth weather in 2011, see The inused appliances* energy hasof been even sharper: it has in 40growth years (see graphless below). Theuse average annual growth in appliances in years (see graph The average in *AppliancesHousing are defined in the Cambridge Model as Cambridge and whereas household appliances than 5% total energy in tripled in 40 40very years (see graph below). below). Thefollowed average annual annual growth in appliances appliances Cambridge Housing Housing Model Model as as toasters, for example, is counted here in 40 years graph The average annual rise growth in appliances energy was(see nearly 3% abelow). year, although the annual appears to be previous section. energy was nearly 3% a year, although the annual rise appears to be Cambridge except Housing Model aswater everything space and everything except space ‘Appliances’ above rather than – have replaced traditional ovens energy was ‘Cooking’ nearly 3% a year, although the annual rise appears to be everything except space and and water water Household energy use for space heating (TWh). According to this graph, heating energy increased just over a tenth which 1970, they now use nearly 14%. energy was nearly 3% a year, although the annual rise appears to be slowing. Graph 5c: Household energy use for water heating (TWh) andsince not inthe ‘Cooking’ below. slowing. everything except space and water heating, lighting, oven and main heating, Household energy use for water (TWh). Despite an increase of more than two fifths in the number of households slowing. use for space heating (TWh) heating, lighting, lighting, the the oven oven and and main main Graph 5b: Household energy The survey provides rich seam of information aboutused electricity use.surveyed On average, it found thata 15% or more of the electricity in homes

1970 1973 1976 1979 1982 1985 1988 1991 1994 1997in 2000 2003 2006 2009 10% 40 in 40 years (see graph below). The average annual growth appliances average, itfor found that It15% or more of the electricity used surveyed was used lighting. found that homes in the study hadinanhomes average of 34

slowing.

heating, the oven and main hob. Thislighting, means that the energy used 1970s there has been a reduction of one third in Appliances’ energy for hot water. Asuseaindirect result, theahas led to a shrinkage in thethat share of total energy homes has followed similar path, hob. This meanssandwich the energy in microwaves, toastersused and There are three factors at play in increased appliances energy use – none of Appliances’ share of totalappliances energy use in homes has followed a energy similar and whereas household used less than 5% of total in microwaves, sandwich toastershere and proportion of household energy used for water heating - down from nearly 30% to inpath, just 18% toasters, for example, is counted and whereas household appliances less thangadgets 5% of totalin energy in 1970, they now usemany nearly 14%. toasters, example, is counted here them unexpected. First, there are now moreused electric homes and not infor ‘Cooking’ below. 1970,sourced they now nearly2013) 14%. and not in ‘Cooking’ below. Graph fromuse (Palmer, – washing machines, tumble consoles and There are threehairdryers, factors at play incomputers, increased appliances energy use – none of 36dryers, There are three factors playare in increased energy use –innone of them unexpected. First,at there now manyappliances more electric gadgets homes chargers.

unexpected. First, theredryers, are now many more electric gadgets homes –them washing machines, tumble hairdryers, computers, consolesinand – washing machines, tumble dryers, hairdryers, computers, consoles and chargers. chargers. Appliances share

Household Energy use for Appliances

Appliances energy use (TWh) 70

60 50 40

Appliances energy 30 use (TWh) 20

Appliances share of Appliances energy all household energy allAppliances householdshare energy use (TWh) of Appliances energy 16% 16% 70 all household energy use (TWh) 16% 70 14% 60 14% 14% 60 12% 50 12% 12% 50 10% 40 10% 8% 40 10% 30 8% 6% 30 20 8%6% 4% 20 4% 10 2% 6%2% 10 0 0% 01970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009 4%0% 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009

Appliances Appliances

Appliances

% household energy % household

Appliances share of all household energy

Graph 5e: Household energy use for appliances (TWh) 2% Graph 5e: Household energy use for appliances (TWh) Second, the use of these appliances has increased (ownership alone does 0 0% Second, use of these appliances increased (ownership doesand not raisethe energy use). These changeshas point to higher disposablealone incomes not1988 raise lifestyle energy These changes point to higher disposable incomes complex changes –1997 automation of2003 jobs previously done by hand, and 1970 1973 1976 1979 1982 1985 1991use). 1994 2000 2006 2009 complex lifestyleenergy-using changes – automation jobs previouslyand done by hand, and substituting appliancesoflike computers consoles where and substituting energy-using likepen computers andorconsoles where in the past people would have appliances worked using and paper entertained Household Energy useGraph for appliances. The growth appliances has tripled inusing 40pen years withoran average annual growth of inof the pastfor people would have worked and paper entertained themselves with board games or books. 5e: Household energy use appliances (TWh) themselves gamesraise or books. 3% a year. Despite the ownership having increased it doeswith notboard alone energy use. It is the result of higher disposable

incomes and complex the automation of jobs that has alone causeddoes the exponential rise. Second,lifestyle the usechanges of theseincluding appliances has increased (ownership Graph sourced from (Palmer, 2013) not raise energy use). These changes point to higher disposable incomes and Consumption complex lifestyle changes – 38 automation of jobs previously done by hand, 38 and substituting energy-using appliances like computers and consoles where

Cooking energy use (TWh)

70 70

16% 16% 7%

60 60

14% 14%

Appliances Cooking Appliances

Part of the long-term increase in energy use for space heating comes6%from %% household household % household 12% 12% energy energy 50 the way homes have50 been extended over the years, increasing the heated energy 10% 10% 40 5% 40 volume, and especially how conservatories have been added and heated – 20 8% 8% 25,26 30 30 which significantly raises heating energy use . 6% 4% 6% 20 Cooking’s share 20 15 4% 4% 3% of all household 10 10 2% 2% 10 energy 0 0% 0 0% 2% 1970 1970 1973 1973 1976 1976 1979 1979 1982 1982 1985 1985 1988 1988 1991 1991 1994 1994 1997 1997 2000 2000 2003 2003 2006 2006 2009 2009 35 25

% household energy energy

andincrease hobs.) in the number is significantly less than the households (up from 18.8use tofor 27.1 million, increase of 44%. Thisthat the Part of of the long-term increase in energy space heating an comes from hob. hob. This This means means that the energy energy used used Appliances’ share of energy use homes has followed aa similar path, Appliances’ share of total total energy use in in homes has followed similarthe path, the way homes have been extended over the years, increasing heated and in sandwich toasters suggests that improvements in insulation and heating system efficiency offset the effect of household growth demand for in microwaves, microwaves, sandwich toasters and and and whereas household appliances used less than 5% of total energy in and whereas appliances used lessaverage than 5% of total energy toasters, volume, and household especially how conservatories have been added andinheated and – toasters, for for example, example, is is counted counted here here As a proportion of all energy use in the home, cooking has more than Given the improvements in thermal comfort (both temperature warmer homes. 25,26 1970, they they now use use raises nearly 14%. 14%. 1970, now nearly and which significantly heating energy use . and not not in in ‘Cooking’ ‘Cooking’ below. below. halved: fromof6% to lessroutinely thanGraph 3%.sourced The decline levelling share off, and the number rooms heated), theappears growthtoinbeheating’s of from (Palmer, 2013) There three factors at play in increased appliances energy use –– none of 36 are There are three factors at play in increased appliances energy use none of the rate of change more rapid in the 1980snow 90s58% thantoit 62% has been total energy use inwas homes has been modest –and from –inalthough them homes them unexpected. unexpected. First, First, there there are are now many many more more electric electric gadgets gadgets in homes since 2000. –– washing machines, tumble dryers, hairdryers, computers, consoles washing machines, tumble dryers, hairdryers, computers, consoles and andreflects 35 this proportion has been volatile in the past few years. The volatility chargers. chargers. Household Energy use for Cooking the very cold weather in 2010, followed by mild weatherCooking's in 2011,share seeof all Cooking energy Appliances share of Appliances Appliances share of Appliances energy energy household energy use (%) previous section. use (TWh) all use all household household energy energy use (TWh) (TWh)

Graph Graph 5e: 5e: Household Household energy energy use use for for appliances appliances (TWh) (TWh)

Second, 0 0% Second, the the use use of of these these appliances appliances has has increased increased (ownership (ownership alone alone does does raise energy use). higher disposable incomes not raise1988 energy1991 use). These These changes point to2003 higher 2006 disposable incomes and and 1970 1973 1976 1979 1982 not 1985 1994changes 1997 point 2000to 2009

complex complex lifestyle lifestyle changes changes –– automation automation of of jobs jobs previously previously done done by by hand, hand, and substituting substituting energy-using and energy-using appliances appliances like like computers computers and and consoles consoles where where Graph 5f: Household energy use for cooking (TWh) in the the past past people people would would have have worked worked using using pen pen and and paper paper or or entertained entertained in for cooking. Overtime more and more energy has been conserved from cooking themselves themselves with with board board games games or or books. books.

Household Energy use as the proportion of all energy use in a household tocome have halved: to less than 3%. Thecooking decline seems to be levelling Where cooking have theseems savings from? Infrom part6% from more efficient off and the devices: rate of change was more rapid in the 1980s and 90s than it has been microwaves and fan-assisted ovens have surely helped, and since 2000. 31

Graph sourced from (Palmer, 2013) microwaves were found to save 10% of cooking energy. But the huge expansion in ‘ready meals’ 38 38 and takeaways is probably a bigger factor in the decline in cooking energy, and it is questionable whether these lifestyle

Household electricity-using habits revealed and Early Findings: Demand 34 side management ).

2021 CPU[AI]

Heat loss parameter UK Housing Energy Fact File and SAP have a direct effect on insulation and The Building Regulations

airtightness for new homes. These shape the ‘Heat Loss Parameter’ of a dwelling: a measure of how well a home retains heat. Thetheir Heat seals Loss fail, the Double-glazed units have a limited life-span. Eventually Parameter is internally based on heat through fabricenergy of a building (e.g.Units units mist up and transfer their capacity forthe saving declines. walls and windows), as years. heat loss due to air movement, can perform well for as upwell to 35 However, they often failfrom longboth before 54,55 , although it this. Failed units cannot beuncontrolled repaired and have to be replaced deliberate ventilation and infiltration. is now possible to replace just the glass. loss coefficient (measured in W/K) is divided by the total floor The averageDwellings, heat The losstotal byheat dwelling has been steadily decreasing 2with the arrival of double millions area of a home to give a measure of heat loss per unit area (W/m K). This glazing in 198330 resulting incomparison 83% of homes being betterdwellings insulated now size. than thirty years ago. allows a fair of the heat loss between of different

Heat Loss & Insulation

UK Housing Energy Fact File

Cavity wall insulation

Whole Dwelling The graph below shows how the average heat loss parameter in 2011 varies80-99% of 25 between homes built in different periods, including the effect of retrofit Dwelling 50-80% of upgrades (like insulation and more efficient boilers) added after the home Dwelling 20 was built. >50% of Dwelling 15 Potential for W/m2 K Double Glazing 4.5

There has been a stark increase in cavity wall insulation in Britain’s housing stock, see graph below. (This graph shows figures for households in Great UK Housing Energy Fact File Britain, rather than the UK like the rest of the Fact File, to match DECC’s wall insulation data.) Cavity Wall Insulation in households

Heat Loss Parameter by dwelling age (2011)

Households, As the graph shows, the two initiatives have mainly been successful at millions installing cavity wall and loft insulation. EECs resulted primarily in installing 25 Households

4.0

3.5 5

Thermal Value

3.0 0 2.5

2008

2009

2.0

2010

Households (Millions)

2011

1.5 Graph 6m: Double-glazing 2008-2011 (UK) 1.0

Glazing units are available now to a significantly higher standard than previously. And a window rating system, similar to that for boilers, is in place 0.0 so that consumers can identify the performance of different products 56.

0.5

Before 1900

19001929

19301949

19501966

19671975

19761982

19831990

19911995

19962002

20032006

Graph 5h: Heat Loss Parameter by dwelling age (2011)

and external

Heat Loss Parameter by dwelling age (2011). This graph shows a measure of well a home retains heat based on heat The rate at which homes in the UK lose heat during the heating season has ed the ‘temperature transfer through the fabric of a building and heat loss due to air movement from ventilation and uncontrolled infiltration. The fallen significantly in the last four decades. (This reflects the improvements measure of heat loss says graph thus shows the changes in heat loss between homes built in different periods including retrofit upgrades. described in the three previous sections.) 42 Graph sourced from (Palmer, 2013)

ge home, if it is 1qC cooler

de, you need 376 watts of

fected by insulation and

typical cold winter’s day

temperature of 0qC and an

ture of 20qC, an average

300

d six kilowatts of heat to

250

temperature. This is

Efficiency small electric Thermal fan heaters.

Double Glazing 1970- 2007

2002 because of difficulty in classifying homes in the old Home Audit survey Dwellings, – a forerunner of the English Housing Survey.) millions

Roofs Floors Doors

150

50 0 1970 1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003 2006 2009

6n: Average loss per dwelling Average heat loss perGraph dwelling. In 1970, heat the overall rate of heat(UK) loss from a home was approximately 376W/C. Since then, fourty years later is has fallen to 290W/C which is a fall by 25% highlighting an efficiency in building materials and insulation overtime.

Consumption

Dwellings (Millions)

There is a consensus of opinion that insulating the existing stock of solid wall homes is one of the strategic opportunities for improving energy 20 efficiency.49 This is one of the priorities for the Green Deal, see page 6, which is expected to have a major impact on the solid wall insulation 15 market. In 2008, annual installations of solid wall insulation were estimated in the 50 range from 25,000 to 35,000. Of these, an estimated 60% were external wall insulation, 30-40% were internal wall insulation, and 10-20% of these 5 used ‘insulated wallpaper’. Around a third of all projects applying solid wall insulation were reckoned to be new homes built with solid walls. However, 0 there is considerable uncertainty over these figures, and they should be 1983 1989 1992 1995 1998 2001 2004 2007 treated1986 with caution.

100

Solid wall insulation

Windows

Graph sourced from (Palmer, 2013)

*Changing from the Englis

Condition Survey to the En Housing Survey in 2008 m double-glazing data was c Household energy use for space heating (TWh). According to this graph, heating energy increased just over a tenth which differently. This means the In 1974, two-thirds of the housing stock was capable of having cavity wall is significantly less than the increase the time number of households (up frompenetration 18.8 to 27.1became million, an increase of 44%. This Since 1983 (theinfirst figures for double-glazing to be split in 2008. insulation but it had been installed in less than 2% of these homes. By 2011, suggests that improvements in insulation and heating system efficiency offset the effect of household growth and demand for available), the proportion of homes with 80% or more of their rooms the proportion of the stock capable of having this form of insulation had double-glazed has increased nine-fold, from 9% to 83% in 2011. warmer homes. grown a little to 71% and nearly two-thirds (64%) had it. This was more than Graph sourced from (Palmer, 2013) a 40-fold increase.

Ventilation

200

Glazing The last four decades have seen significant increases in the number of

Walls

350

Not known if cavity insulated

0 homes with double-glazing. Since 1970, the proportion of homes with some 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 2010

W/°C 400

re for 2010, 287W/qC,

However, both initiatives have led to much smaller numbers of solid walls Households being insulated. Just 2% of the measures shown in the graph as implemented under the initiatives have involved solid wall insulation. Thiswith is cavity insulation in line with policy aims, which were to promote the most cost-effective measures first.

Some form of whole-house double-glazing is close to becoming a near universal standard. (There were a large number of homes with unknown status from 1985 to

In 1970, the overall rate of heat loss from a home was, on average, 376W/qC*. Forty years later, it had fallen by almost a quarter to 290W/qC, see graph below.Average heal loss per dwelling

ain a stable temperature.

for cavity wall insulation

level of double-glazing has grown 12-fold, from just under 8% to 93% in Graph 6i: Cavity wall insulation (GB) 2011, see graphs below*.

Heat loss

ed to the difference

cavity wall insulation, with the CERT tilting the balance towards significantly with potential greater uptake of cavity wall and loft insulation.

Not stated 80% or more of rooms 60% - 79% of rooms 40% - 59% of rooms 20% - 39% of rooms Less than 20% of rooms Potential for Double Glazing

Graph 6l: Double-glazing 1970-2007 (UK)

Double Glazing 1970-2007. The year was thewall first insulation time was 51the first time glazing penetration became suggest thatdouble there were Current estimates of 1983 installed solid In this section, ‘double-glazing’ refers to sealed units rather than windows 211,000 homes with this energy efficiency measure by April 2013, see graph available. Since then, the proportion of homes with 80% or more of their rooms double-glazed has increased nine fold from with secondary glazing. nowin must to meet below. These more recentHomes estimates the installation rate has 9%built to imply 83% 201 1.have double-glazing increased – toRegulations. around 75,000 a year. the Building Since 2002, most homes where windows Graph sourced fromexisting (Palmer, 2013) are replaced also need to be double-glazed.

The graphs show that upgrades were very common from 1983-2007, but 54

2021 CPU[AI]

Day in the Life Scenario Exploring human behaviour and calculating embodied carbon energy released by a family of four in one day.

The following time line highlights the day-to-day life scenario of a household consisting of 2no. adults and 2no. Children. Bring to light the carbon emissions emitted into the air daily, highlighting several key contributors in a daily routine; being at home, travelling and attending work or school. The diagram illustrates the key moves within the routine and their emissions stats measured in KgCO2. Approximately 220.336 KgCO2 is emitted daily by a family of 4, with both parent attending a workplace, traveling via car and train, while dropping off and collecting children from school in the meaning time alongside household activities; showers, heating and cooking.

Daily KgCO2 output of an average family of 4

Diagram by Authors, 2021. Data sourced from UK’s Carbon Footprint, Gov.uk, 2020

Consumption

Typical Daily Routine

2021 CPU[AI]

Day in the Life Scenario Improving the previous time line thus exploring optimised human behaviour and calculating embodied carbon energy released by a family of four in one day.

The following time line highlights an improved version of the day-to-day life scenario of a household consisting of 2no. adults and 2no. children. Bring to light the carbon emissions emitted into the air daily, highlighting several key contributors in a daily routine; being at home, travelling and attending work or school. The diagram illustrates the key moves within the routine and their emissions stats measured in KgCO2. Approximately 129.90 KgCO2 is emitted daily by a family of 4 after improvement such as reduction in transport and less car use in the morning with one parent attending a workplace alongside household activities; showers, heating and cooking.

Key

Daily KgCO2 output of an average family of 4

KgCO2 output of an average family of 4 if the daily life was improved

Improved Daily Routine

Consumption

Diagram by Authors, 2021. Data sourced from UK’s Carbon Footprint, Gov.uk, 2020

Improved Daily Routine

2021 CPU[AI]

Day in the Life Scenario Exploring human behaviour and calculating embodied carbon energy released by a couple in one day.

The following time line highlights the day-to-day life scenario of a household consisting of 2no. adults. Bring to light the carbon emissions emitted into the air daily, highlighting several key contributors in a daily routine; being at home, travelling and attending work. The diagram illustrates the key moves within the routine and their emissions stats measured in KgCO2. Approximately 174.56 KgCO2 is emitted daily by a couple as they engage in household activities shown below.

Daily KgCO2 output of an average household of 2 adults

Typical Daily Routine

Consumption

Diagram by Authors, 2021. Data sourced from UK’s Carbon Footprint, Gov.uk, 2020

Typical Daily Routine

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Day in the Life Scenario Improving the previous time line thus exploring optimised human behaviour and calculating embodied carbon energy released by a couple in one day.

The following time line Shows An improved version of the day-to-day life scenario of a household consisting of two adults. The carbon emissions emitted into the air daily by the household activities include using appliances at home, travelling and attending work. The diagram illustrates the key moves within the routine and their emissions stats measured in KgCO2. Approximately 100.51 KgCO2 is emitted daily by a couple as they engage in reducing their emissions.

Key

Daily KgCO2 output of an average family of 4

KgCO2 output of an average 2 adults, if the daily life was improved

Daily KgCO2 output of an average family of 4

Improved Daily Routine

Consumption

Diagram by Authors, 2021. Data sourced from UK’s Carbon Footprint, Gov.uk, 2020

Improved Daily Routine

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Overall Emissions It may be observed that CO2 in the residential, transport and commercial sectors is the biggest contributor to the UK Emissions which changes both seasonally and daily depending on time of day which gives an insight into human behaviour.

Residential 20.8%

Transport 19.5%

Commercial13%

CO2 65%

Industry 5.85

24 Hour Energy Usage of energy in UK

Public 5.85% Waste 1.1%

CH4 25%

Land Use Change 3.1% Energy 3.2% Energy Energy

Y axis

NO2 8%

Agriculture Manure 2.5% Other

other 2%

Agriculture 13.7%

Road Transport 2.6% Industry 2.1% Power Station 1.7% Non Road Transport 0.8% Other

This graph shows energy used in a whole day, compared and overlayed in relation to each other. There is a correlation between behaviour and time useage in the day. The heating is the highest energy useage followed by lighting. When showcasing the energy correlation together it is easier to understand how energy is used in the house and the different activities that take place in a day. It may also be noted when energy peaks two fold in the evening as compared with the morning which is a pattern that assists how we can create energy saving solutions that will work with human behaviour. Ref: (graph was created by the author from UK data set) Graph adapted from (Palmer, 2013)

Manchester's Air Quality

The Sankey Diagram above highlights the atmospheric gases in the UK and the main contributor being Carbon Dioxide at 65% followed by Methane at 25% then Nitrogen dioxide at 8% afterwards F-gases at 2%. (UK local authority and regional carbon dioxide emissions national statistics: 2005 to 2019, 2021) Graph adapted from (Buchs and Schnepf, 2013)

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CO2 in Manchester

The sankey diagram below highlights the CO2 use in Manchester showing domestic is the mose prominent followed by the transport sector.

Domestic Gas

Electricity

32.3% Domestic

Domestic other fuel

Transport Minor Road

Transport Major Road

30% Transport

Transport Other

Commercial Electricity

Commercial Gas Industry Agriculture Industry Gas

20%

Commercial

Industry

9% Public

Industry other fuel Public Sector Gas Public Sector Electricity

Manchester's Air Quality

Diagram by Authors, 2021. Data sourced from Government Department for BEIS, 2020

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Manchesters PM10

Manchesters NO2

A Key Pollutant

PM10 Particulate Matter (Measured Hourly)

Nitrogen Dioxide NO2 (Measured Hourly)

Amount of PM10

Amount of NO2

Time Particulate matter levels in Manchester, in hourly chart measurment showcases an increase at 1am. Diagram by Authors, 2021. Data sourced from Manchester Oxford Road Air Quality Index, Air Visual, 2021.

30%

Time This graph observes fluctuating levels of PM10 concentration throughout one whole day. The highest levels appear to be in the early morning with a trough at 8am which then gradually increases to peak at 5pm in a day perhaps due to workers and school children returning home from vehicles. Thus, we are able to note key behaviours of pollutants and lifestyle in the UK. Diagram by Authors, 2021. Data sourced from Manchester Oxford Road Air Quality Index, Air Visual, 2021.

32.3% Transport

Industrial Processes

28%

26.8% Industry

Domestic Combustion

12% Road Transport

12% Construction

18%

21.5% Power Station

10.7% Non-road Transport Machinery

5.4%

Domestic Use

Other Diagram by Authors, 2021. Data sourced from Emissions of Air Pollutants in the UK, 2021)

Industrial process and use of solvents is 30%, while domestic combustion is 28%, followed by road transport 12% then construction at 12% while 18% other.

Manchester's Air Quality

Diagram by Authors, 2021. Data sourced from Manchester Oxford Road Air Quality Index, Air Visual, 2021.

Nitrogen dioxide levels come from transport 32.3% then Industry 26.8% , followed by Power stations 21.5%, then 10.7% Non road transport machinery then finally 5.4% from Domestic use.

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Manchester’s Plan Criticism of Manchesters Air Quality Plan

Manchesters Air Quality Plan does not consider other pollutants in its Air Quality plan. Focus solely on Carbon Dioxide and Nitrogen Dioxide. Ignoring other pollutants such Sulfur Dioxide, PM10 and PM2.5

As Manchester is aiming to become Net Zero by 2038, that is tweleve years ahead of the national target, the city is taking drastic steps to achieve that goal. The first is the Bee Network which includes 108 cycling and walking schemes with 55 Miles of Routes completed in 2021 and 17 Active neighbourboohds thus far in an attempt to make the city more active. The second is to introduce a congestion charging zone in the city centre to reduce the poor Air Quality and thus improve the air we breathe. (council,2021) Some criticisms include a lack of consideration to wards pollutants other than Carbon Dioxide and Nitrogen Dioxide. This means other harmful toxins like Sulfur Dioxide, PM10 and PM2.5 are able to reign free in the atmosphere.

“In 2020, 16 of the above sites measured NO2 concentrations exceeding the legal Annual Average standard of 40 μg/m3. Exceedances were recorded in Manchester, Tameside, Stockport, Bolton and Rochdale. This compares to 129 locations that were measuring concentrations above 40 μg/m3 in 2019”

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Manchester's Air Quality

The Bee Network 108 Cycling and Walking Schemes 55 Miles of Routes Completed 2021 and 17 Active Neighbourhoods (Council,2021)

Manchester is Set to Influence a Congestion Charge

The plan also only focuses on Cars and Road Transportation and does not consider other transport sectors like Airports and Trains. It also doesn’t consider the Construction Industry or Industrial Manufacturing

Diagrams by Authors, 2021. Data sourced from Clean Air Greater Manchester,

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Systems Dynamic A systems dynamic map exploring cause and effect relationships with feedback loops indicating cycles within the framework of Air Quality in relation to Emissions, Health, Pollutants and Waste -

Initially having brainstormed themes relating to Air Quality we have come up with a systems dynamic map which discusses cause and effects between each nodes. Where a plus sign is seen, a positive influence is hinted. With a minus sign, a negative influence may be anticipated. A double slash suggests a delayed response for example a long-term exposure to pollutants will have an adverse effect on health.

Key

Positive Influence A

Inequality in resource

Illnesses

Global Warming & Climate Change

Longterm exposure to pollutants

Emissions

Delays

Pollutants

Globalisation

+ B

+ +

Construction

Variable Indicator

Negative Influence A

Population

Increase in Energy Production

Increasing demand for high rise buildings

Poor Health

Fossil Fuels

Population

+ Increase in Housing demand

Increase in vehicle ownership

Results

Addition of Trees

- - +

+ Increased demand in electricity

Reinforced Loop

+ + Material Embodied Energy Dynamics between nodes

Core Nodes

Diagram by Authors, 2021.

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Loop

Health

Greenhouse Gases

Waste

Landfills

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The Invisible Killer Many mega cities like Manchester suffer from poor air quality. To put this in perspective, inhaling Manchester's air is equivalent to smoking seventeen cigarettes in a month. Manchester’s Air Quality is Equal

Air quality is the biggest Public Health crisis responsible for more deaths than AIDS and Malaria combined. If Air Pollution in Manchester was cut by 1/5:

8.8 million

- 284 fewer children suffering with low lung function - 5 fewer babies being born underweight

Smoking

1 Cigarette Daily

- A decrease in lung cancer cases by around 5.6% leading to 20 fewer cases every year Children are 4.4% is more likely to be hospitalised for asthma on days with high Nitrogen Dioxide.

7.2 million 1 Cigarette per day = Rough Equivalent of PM2.5 Level of 22 ug/m3

64,000 Excess deaths

Air Pollution

4 Cigarettes Weekly

1.5 years Life ExpectancyReduction

Diagram by Authors, Data sourced from Guradian News, Taylor 2020

17 Cigarettes Monthly

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Health

Diagram by Authors, Data sourced from Guradian News, Taylor 2020 Diagram by Authors, 2021. 2021.

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Health & Climate Change The growing climate emergency is having a negative on our health for example environmental degradation for capitalist gain is resulting in displacement of communities, civil conflict and mental health impacts. Climate change is having a large impact of human health, which is caused by the ever worsing climate emergency. For instance; air pollution is being seen as a cause for asthma and cardiovascular diesase while environment degradation is a stimulate behind mental health likewise is serve weather which can also lead to injuries and fatalities. All aspects which are relevant to Manchester.

• • •

• •

Injuries Fatalities Mental Health Impacts

Asthma Cardiovascular Disease

Changes in Vector Ecology Extreme Heat • • •

Heart-related illness Death Cardiovascular Failure

• • • • •

Malaria Hantavirus Rift Valley Fever Lyme Disease West Nile Virus

Environment Degradation

Water Quality Impact

• • •

• • • •

Forced Migration Civil Conflict Mental Health Impacts

Increasing Allergens

• •

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Solutions

Rising Sea Levels

Cholera Cryptosporidiosis Campylobacter Harmful Algal Blooms

Water & Food Supply Impact Malnutrition Diarrheal Disease

Rising Temperatures Increase CO2 Levels

Air Pollution

Extreme Weather

Serve Weather

Respiratory Allergies Asthma

Diagram by Authors, Adapted from Centre of Disease Control and Prevention, 2021.

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Urban Strategy As Manchester is a growing city it will inevitably experience greater amounts of density which must be controlled to give the city dwellers a high quality of life. With greater density, Manchester is aiming to reduce it's dependency on car use and encourage cycling as one example.

The increase in population is increase the Sulfur Dioxide levels in the air

Compact City Given to proximate developments it’s expected to produce lower emissions of transport to produce lower emissions of transport related pollutants compared to fragmented city.

Dense City Limited need for roads and translate more efficient infrastructure better public transport leading to a decrease in overall emissions, require less land and so less adverse affect on biodiversity.

= Urban Fragmentation The increase in the urban fragmentation results in an increase in Carbon Dioxide and Nitrogen Dioxide levels which is influenced in need the car transportation

A large proportion of green areas in cities reduces the concentration of SO2 and CO2 Pollution and addition air emissions can be more easily trapped by dense urban construction and thereby lead to higher pollution concentration

Diagram by Authors, Adapted from Rodriguez, Dupont-Courtade and Oueslati, 2016.

Neo-Urban Fragmentation Diagram by Authors, Adapted from Rodriguez, Dupont-Courtade and Oueslati, 2016.

The increase of neo-urban framentation is encourage less of cars wtih the promotion of environmental friendly ways of transport. Such as cycling, which leads to a positive impact of the environment

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Solutions

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Improving Air Quality Air Quality can be improved through design and spatial changes for example relocating or introducing new amenities in a neaighbourhood close to residential areas to reduce short car journeys.

Promixity of Areas to Reduce Private Vehicle Flow Design and Spatial Changes Sugesstion for

To improve Air Quality it is important to reduce vehicle emissions, industrial emissions and agricultural emissions. In order to achieve a Zero Carbon Status some of the actions required include considering the proximity of areas to reduce private vehicle flows, investing in renewable energy plans for domestic homes and commercial buildings too. Green Spaces should be maximised through strategic planning which leads to careful urban planning as factories should be placed away from residential and densely populated areas.

Displace Pollutant Emissions Outside Hot Spots & Populated Areas

Ir order for these spatial changes to come into action, the government and local authority must play it’s part in legislation to ensure businesses and individuals do not exceed their consumption levels and should be reprimanded if they do and commended if they dont.

Electrification of Rail Network

Promote Low Emission Vehicles

Air Quality

Improving

Renewable Energy Plan for Domestic Homes and Commercial

Air Quality Levels

Vehicle Emissions

Lower Marine Fuels & Operational Interventions at Ports

Green Spaces with Trees and Plants through Strategic Planting

Policy Interventions

Displace Pollutant Emissions Outside Hot Spots & Populated Areas

Achieving Zero Carbon

It is through collective effort that we will be able to improve our cities and our air quality. Improving

Industrial Emissions

Encourage Cycling and Walking

Technology Replacements Reduce Demand for More Polluting Forms of Transport

Change in Government Policy

Low Emissions in Application To Land Change in Livestock Diet

Improving

Agriculture Emissions Strategic Tree Planting

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Solutions

Change Land Use/Consumption/ Productivity/Genetic Selection

Diagrams by Authors, Adapted from Review of interventions to improve air quality, 2019

Public Transport within Walking Distance

Change Land Use/Consumption/ Productivity/Genetic Selection

Technology Replacements

Diagrams by Authors, Adapted from Review of interventions to improve air quality, 2019

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Air Quality Plans

West Yorkshire Air Pollution Plan

Precedents

The following page highlights example of Air Quality plans which have been implemented in other UK cities. Outlining key points of the plans and the importance of them being an essential part of managing the air quality.

Classification of Development

Stage 1

Minor or Medium or Major Based on the criteria that would trigger transport Assessment and those that meet the additional criteria

London Air Quality Plan

“Air Quality Neutral” in London. This is achieved by establishing benchmarks for both building and transport emissions which all new developments must comply with.

Where compliance cannot be achieved, developers are required to prepare strategies to demonstrate how the excess will be mitigated, on or off-site. Or must pay compensation through schemes.

Air Quality Impact Assessment

Stage 2

Minor + Medium development proposals further screened to identify if they will introduce new exposure ( then needs further mitigation) Major Developments are required to carry out a Detailed Air Quality Assessment

Key Characteristics of Air Quality Plans

Air Quality Officer

Mitigation and Compensation

Submission of an Air Quality Assessment for Contruction. Mitiagation or low emission strategy as Section 106 of the Town and Country Planning Act 1990 Diagrams by Authors, Adapted from Land Use Planning & Development COntrol:Planning for Air Quality, 2017.

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Solutions

Stage 3

Outcome of Stage 2 used to determine the level of appropriate mitigation. Then the remainder left for developments is the calculation of pollution damage costs

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Diagrams by Authors, Adapted from Land Use Planning & Development COntrol:Planning for Air Quality, 2017.

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Air Pollution Model Types Multiple Cell Model is the Preffered Starting Point

Multiple Cell Model

The Gaussian Plume Model

The Air space over a city is divided into multiple cells, each cell seperate from the rest. This modelling type is used for Ozone.

A single point from a factory smokestack (approximated as a point) then from this point source computing the schematic representation and nomenclature of the contaminated gas stream called a plume. Which rises from the smokestack and then levels off to travel. In the direction x and spreads through y and z direction as it travels. The plumes rise above the smokestack as the temperature are higher than the atmospheric levels.

The UAM model the division in the x and y is a uniform grid of normally 2 to 5 km across the city. In the z axis there is 4 to 6 layers between the mixing height and half below. For this image there is 5x4x4 = 80 cells. To create this model requires: Wind velocity and direction at each cell, emission esitimate for ground level cells, subprogram to compute chemical transformation in time. Also using historical records of wind speed, directions, solar inputs and estimated emissions for the day. (De Nevers, 2000)

Multiple Cell Model Diagram from De Nevers, 2000

Fixed-Box Model

The city is split into a rectangle with dimensions E and L with one side parallel to the wind direction. This model assumes that the turbulence is strong enough that the wind concentration is uniform in the whole volume of air over the city and not higher or lower than the box. This assumption is contrary to nature but allows for simplification of mathematics. The wind blows in direction x and with velocity u. The velocity is contant and independent of time location or elevation. This is also a false assumption. The model also assumes there is no pollutant that enters this space or leaves it. (De Nevers, 2000)

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Solutions

Guassian plume model Fixed-Box Model

Diagram from De Nevers, 2000

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Air Quality Model

Photochemical Reactions

Sink Processes

Aerosol Processes

Thermalchemical Reactions

Exploring air quality models to record, analyse, generate and optimise air quality around us.

RECEPTOR-ORIENTED AND SOURCE ORIENTED AIR POLLUTION MODELS

POLLUTANT CREATION AND DECAY IN THE ATMOSPHERE

Source-oriented models. Uses best estimates of emission rates and various metereology reports as well as wind reports, Chemical composition of the pollutant is relevent and ues a atomic absorption spectroscopy. to identify the difference between PM2.5 or PM10. However if the chemical is CO or SO2 then these is no way to distringuish between sources

No pollutants remain in the atmosphere forever. All pollutants have natural removal mechanisms. “However, for pollutants like suspended mineral particles or carbon monoxide, it is a satisfactory approximation, because their removal rates are slow enough to ignore in most urban areas.”(De Nevers, 2000) In contrast, sulfur dioxide, hydrocarbons, nitrogen oxides, and oxidants all undergo reactions in the atmosphere, and their reaction times may be comparable to travel times across a city. “For these pollutants the simple box and Gaussian plume methods, as presented so far, predict values much higher than the observed values.” (De Nevers, 2000)

Anthropogenic Emissions Advected Pollutants

Transformation

Natural Emissions

Sources

Mathematic Model

Predicted Concentration

Figure x below showing decision making diagram (De Nevers, 2000)

Transport

Meteorology

Cloud

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Diagram from De Nevers, 2000

Solutions

Temperature

Wind

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Air Quality Model Exploring air quality models to record, analyse, generate and optimise air quality around us. `

Air quality and pollution is a major factor when it comes to achieving a Zero-Carbon approach as trends and figures show that certain contributors are affecting the atmosphere producing Greenhouse Gases which consists of Carbon Dioxide, Nitrous Oxide and Methane while other major pollutants; Carbon Monoxide, Airborne Particles, Nitrogen Dioxide, Sulfur Dioxide and the ever-effecting Ozone layer. All aspects that need to be combatted to achieve Zero-Carbon. Air quality and pollution is a major factor when it comes to achieving a Zero-Carbon approach as trends and figures show that certain contributors are affecting the atmosphere producing Greenhouse Gases which consists of Carbon Dioxide, Nitrous Oxide and Methane while other major pollutants; Carbon Monoxide, Airborne Particles, Nitrogen Dioxide, Sulfur Dioxide and the ever-effecting Ozone layer. All aspects that need to be combatted to achieve Zero-Carbon.

Decision Making Diagram

Increase in Housholds

Start Input Air Quality CO2 Emission

Does it meet WHO quality?

Compute: How much emissions is needed to reduce

Yes

Calculate future Air Quality growth

Is it acceptable?

Yes

Lower Standard of Housing

No More Construction

Upgrading Existing Stock

Future: Good Insulation & Less Heat-Use

Lower Standard of Housing

No More Construction

Upgrading Existing Stock

Future: Good Insulation & Less Heat-Use

Stop

Control Emission Reduction

Compute potential reductions needed Diagram by Authors, 2021.

Diagram by Authors, 2021.

Control Emission Reduction

Test Alternative Lower Emissions

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Solutions

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Experiment - Models Testing models using grasshopper to identify links between carbon emissions from domestic life, workplace and from transportation.

1km Home

1km

220kgCO2 1km 1km

1km

The grid containing a house, car or commercial building attached with the carbon level

1km

The diagram above showcases the method of creating an experimental model scenerio in Rhino Grasshopper that can be parameterically inputted to showcase different configurations. First using the Multiple Cell model as a starting point we created a grid that would split the city into 1x1 km grid.

Carbon Energy Used Per Day

kgCO2 Workplace 7087kgCO2

220

kgCO2

Transport (Car)

7087

The following diagram highlights suggested improvement which can be put in place which will result in air quality improvement. This may be; renewable energy plans, encouragement of cycling and walking as well as the movement high pollution contributors to be outside hot spots and populated areas.

kgCO2

1x The following icons showcase a key of the energy useage in a domestic house, commercial office and car. Which are the main contributors to Carbon Dioxide.

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Solutions

0.17 1x

kgCO2 Diagram by Authors, 2021.

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Residential Scenario

Commercial Scenario

Creating a Scenerio Model and Finding Out How Much Energy is Used

9738.176 kgCO

Visual Representation of the Model Scenerio

2 Total Carbon Levels of House Scenerio

Small House Example 174.56kgCO2 per house

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Solutions

213,874 kgCO

2 Total Carbon Levels of Commercial Scenerio

Different House Types:

16x

Visual Representation of the Model Scenerio

Different Commercial Types:

26x

Medium House Example 220.336kgCO2 per house

Large House Example 304.12kgCO2 per house

Diagram by Authors, 2021.

3x Mirco Commercial Example 7087gCO2 per unit

Small Commercial Example 17717kgCO2 per unit

3x Medium Commercial Example 31891kgCO2 per unit

1x Large House Commercial 50876kgCO2 per unit

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Car Scenario

Tree Model Scenario

Creating a Scenerio Model and Finding Out How Much Energy is Used

Most Common Tree Types in Manchester and Their Importance to CO2 Sequestration

The following model showcases a render of trees on a hypothetical site, this is a figurative visual to showcase the scenerio. The numbers below showcase the type of trees in Manchester with the creation of a scenerio with 86 trees.

23x

Small Car (Red) 0.14208 kgCO2 per car

Medium Car (Blue) 0.17061 kgCO2 per car

11x

26x

Large Car (Green) 0.20947 kgCO2 per car

Standard Car (White) 0.17336 kgCO2 per car

Luxury Car (Black) 0.21286 kgCO2 per car

15x

Sports Car (Yellow) 0.17332 kgCO2 per car

Scenario Calculation:

Distance Travelled

Vehicle Emission Factor

Answer KgCO2/km2

Figure x: (by author)

Carbon Storage x Number of Trees E.g 2km

Changeable Variable

Figure x: (by author)

18x Visual Representation of the Model Scenerio

30.3857 kgCO /km 124

Solutions

2 2 Total Carbon Levels of Car Scenerio (x88 Cars) Diagram by Authors, 2021.

Willow Tree Example 1.59kgCO2seqestration per tree

39x

32x

2.76 Diagram by Authors, 2021.

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Chapter Summary Consumption levels: We have learnt that the UK consistently exceed its own carbon budget this problem is further explored by identifying the key sources of pollution. Electricity and other fuels are major greenhouse gas emitters followed by personal transport then food and other transport services for the UK. Almost half of all UK emissions are sourced from household primarily from heating. Manchester’s CO2 mainly comes from domestic gas for heating homes, then followed by transport from minor roads. Then from electric use in commercial buildings. NO2 levels are predominantly from transport use and the levels of NO2 on the road are related to the working day lifestyle and car use of city inhabitants. PM10 levels is predominantly from Industrial resources followed by domestic contribution. From this research we are able to identify which sectors to explore in detail, such as Domestic use, we then examined the behaviour scenarios in a household examining the CO2 emissions from different activities in the day. We found that certain behaviour change can decrease a households CO2 emissions by half. This helps our research as it has allowed us to understand different scales of pollution and potential intervention spots from Macro to micro scale systems and how they are linked. By understanding the most producing sectors domestic, transport and commercial we are able to simulate models using grasshopper that help us understand how and how much energy is being used or wasted. By reducing cars for example on a road we can understand the air pollution level impact as we are able with the information we gathered to simulate a scenario. This helps our research to simulate real world scenarios and have quantifiable results. Furthermore the information helps us understand the energy flows in a city from macro to micro scale.

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Conclusion

Manchester’s plan:

Air Pollution Model:

We have learnt that Manchester’s Council plan includes the introduction of congestion charges along roads in the city, the implementation of an infrastructure upgrade called the bee network hoping to improve cycling and walking infrastructure. The issue will the Manchester Air quality plan is it does not consider other pollutants other than NO2 such as CO2, SO2 and PM.

We have learnt that after examining air pollution models and found the multiple cell model to be the best starting point dividing the city into 1km2 cells to measure air quality. To develop a air quality model decisions tree was created to represent the different data needed to be included.

Air pollution is the invisible killer and is responsible for 8.8 million deaths worldwide. In Manchester air quality is equal to smoking 17 cigarettes a month. We can use the information to suggest different resolutions that take into account the Urban structure of Manchester. As we learnt that Mass Urbanisation links to poor air quality, as an increase of population in a city leads to an increase in Sulphur dioxide levels which is harmful to the residents. The Urban layout of a city impacts the residents choice of transport. For example Urban fragmentation in cities leads to higher CO2 and NO2 levels due to car reliance, therefore we must consider the Urban layout and connectivity of a city as factor that impacts air quality levels. There is several ways to reduce air bad air quality such as through achieving zero carbon, Proximity of areas to reduce vehicle integrating renewable energy use, increasing green space, encourage active transport, introduce policy changes, using technology replacements, increase public transport and well connected infrastructure. Change land use consumption.

We created several experimental models that measured several factors into consideration from household energy use to car usage and commercial work activity. We created several scenarios by populating a 2km grid then measure the total energy and carbon used in the area as well as carbon offset by trees. We examined air quality plans by other places in the UK from London and West Yorkshire to understand how councils are implementing strategies to reduce bad air quality. This information allows us to consider and test several scenarios to better understand how air pollution is caused in a city. As well as understanding how decisions about air quality are made that can help mitigate future emissions. Therefore it’s important in our research that we consider a variety of air pollutants to better understand the impact on health. We also may need to examine developing a policy strategy for Manchester that is correlated to quantifiable evidence to reduce air pollution on citizens, from our understanding behaviour as well as total energy of the residents needs to be considered in modelling scenarios as domestic use is the highest air pollution emitter. This indicates that a need for awareness of the citizens on their behaviour and how their consumption levels impact air quality is better needed. All this can help us to better accurately understand ways to mitigate air pollution.

Therefore it’s important for us to consider the urban layout of Manchester, how connected the urban layout is, as well as the use of renewable energy sources as they are less polluting to the air, all these things can influence air quality levels in the city.

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Bibliography (Environment, 2020) Environment, U. N. (2020) Causes of air pollution. Cleanairblueskies.org. [Online] [Accessed on 21 November 2021] https://www.cleanairblueskies.org/did-you-know/causes-air-pollution. (February, n.d.) (Improving air quality improves people’s health and productivity, 2020) (N.d.) Gov.uk. [Online] [Accessed on 22 November 2021] https://assets.publishing.service. gov.uk/government/uploads/system/uploads/attachment_data/file/880498/annual-statement-of-emissions-for-2018.pdf. (N.d.) Gov.uk. [Online] [Accessed on 22 November 2021c] https://assets.publishing.service.gov. uk/government/uploads/system/uploads/attachment_data/file/938623/Review_of_interventions_to_improve_air_quality_March-2019-2018572.pdf. (n.d.),(n.d.) (N.d.) Org.uk. [Online] [Accessed on 21 November 2021] https://www.theccc.org.uk/wp-content/uploads/2016/07/5CB-Infographic-FINAL-.pdf. (Sizing Up Humanity’s Impacts on Earth’s Changing Atmosphere : A Five-Part Series By Alan Buis, NASA’s Jet Propulsion Laboratory, 2019) 2004. Nitrogen Dioxide in the United Kingdom Summary. Department for Environment, Food and Rural Affairs; Scottish Executive; Welsh Assembly Government; and Department of the Environment in Northern Ireland. 2021. Shoot!Smoke. Shoot smoke. 21 October 2021]. and_regional_CO2_emissions.xlsx> [Accessed 21 October 2021]. Air Quality Strategy (n.d.) Gov.uk. [Online] [Accessed on 22 November 2021] https://www.cityoflondon.gov.uk/services/environmental-health/air-quality/air-quality-strategy. Apis.ac.uk. 2021. Methane | Air Pollution Information System. [online] Available at: <http://www. apis.ac.uk/overview/pollutants/overview_ch4.htm> [Accessed 14 November 2021]. AQI Basics (n.d.) Airnow.gov. [Online] [Accessed on 22 November 2021] https://www.airnow. gov/aqi/aqi-basics/. AQI Basics (n.d.) Airnow.gov. [Online] [Accessed on 22 November 2021] https://www.airnow. gov/aqi/aqi-basics/. Assets.publishing.service.gov.uk. 2021. [online] Available at: <https://assets.publishing.service.gov. uk/government/uploads/system/uploads/attachment_data/file/633270/air-quality-plan-detail. pdf> [Accessed 14 November 2021].

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Conclusion

Buchs, M. and Schnepf, S., 2013. UK Households’ Carbon Footprint: A Comparison of the Association between Household Characteristics and Emissions from Home Energy, Transport and Other Goods and Services. [ebook] Available at: https://ftp.iza.org/dp7204.pdf?fbclid=IwAR3S6YPjaIEeYClqAfCxiceCmYQjqhrczGxBVjuEnh6Fmq8R-aG3dOUKbVc> [Accessed 14 November 2021]. Clean Air GM (n.d.) Cleanairgm.com. [Online] [Accessed on 22 November 2021] https://cleanairgm. com/. Cleanairfund.org. 2021. [online] Available at: <https://www.cleanairfund.org/wp-content/uploads/2020/08/policy-brief-Manchester.pdf> [Accessed Climate change: Atmospheric carbon dioxide (n.d.) Climate.gov. [Online] [Accessed on 21 November 2021] https://www.climate.gov/news-features/understanding-climate/climate-change-atmospheric-carbon-dioxide. Climate effects on health (2021) Cdc.gov. [Online] [Accessed on 22 November 2021] https://www.cdc. gov/climateandhealth/effects/?fbclid=IwAR0TJmxFN-aHp2aNKUqIIhcccdGplhWwFNjbz5NUkR7PybbiO6h9722rm7w. De Nevers, N., 2000. Air Pollution Control Engineering. McGraw-Hill Education. February, 2. (n.d.) 2019 UK greenhouse gas emissions, final figures. Gov.uk. [Online] [Accessed on 21 November 2021] https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_ data/file/957887/2019_Final_greenhouse_gas_emissions_statistical_release.pdf. Ftp.iza.org. 2021. [online] Available at: <https://ftp.iza.org/dp7204.pdf fbclid=IwAR3S6YPjaIEeYClqAfCxiceCmYQjqhrczGxBVjuEnh6Fmq8R-aG3dOUKbVc> [Accessed 14 November 2021]. gov, U., 2021. [online] Uk-air.defra.gov.uk. Available at: <https://uk-air.defra.gov.uk/library/assets/documents/reports/aqeg/nitrogen_dioxide_in_the_UK-summary.pdf> [Accessed 14 November 2021]. GOV.UK. 2021. Emissions of air pollutants in the UK – Particulate matter (PM10 and PM2.5). [online] Available at: <https://www.gov.uk/government/statistics/emissions-of-air-pollutants/emissions-of-air-pollutants-inthe-uk-particulate-matter-pm10-and-pm25> [Accessed 14 November 2021]. GOV.UK. 2021. UK local authority and regional carbon dioxide emissions national statistics: 2005 to 2019. [online] Available at: <https://www.gov.uk/government/statistics/uk-local-authority-and-regional-carbon-dioxide-emissions-national-statistics-2005-to-2019> [Accessed 14 November 2021]. gov.uk/government/uploads/system/uploads/attachment_data/file/996057/2005-19_UK_local_ Hart Water Softeners. 2021. Average Water Usage Statistics With Tips On Saving Water. [online] Available at: <https://www.hartwater.co.uk/blog/water-usage-statistics/> [Accessed 14 November 2021].

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Has.concord.org. 2021. Factors that Affect Air Quality - High-Adventure Science Interactive. [online] Available at: <https://has.concord.org/air-pollution.html> [Accessed 14 November 2021].

Statista. 2021. UK: methane (CH4) emissions 1990-2019 | Statista. [online] Available at: <https://www.statista.com/statistics/486621/methane-emission-uk/> [Accessed 14 November 2021].

Improving air quality improves people’s health and productivity (2020) Europa.eu. [Online] [Accessed on 21 November 2021] https://www.eea.europa.eu/signals/signals-2020/articles/improving-air-quality-improves-people2019s. Iqair.com. 2021. Manchester Oxford Road Air Quality Index (AQI) and Manchester Air Pollution | AirVisual. [online] Available at: <https://www.iqair.com/us/uk/england/manchester/manchester-oxford-road> [Accessed 14 November 2021].

Taylor, M. (2020) ‘“Invisible killer”: UK government urged to tackle air pollution.’ The guardian. [Online] 4th February. [Accessed on 22 November 2021] http://www.theguardian.com/environment/2020/feb/04/ invisible-killer-uk-government-urged-to-tackle-air-pollution.

Lancaster uni, L., 2011. The Total Carbon Footprint of Greater Manchester Estimates of the Greenhouse Gas Emissions from Consumption by Greater Manchester Residents and Industries. [ebook] A report by Small World Consulting Ltd. Available at: <http://media.ontheplatform.org.uk/sites/ default/files/gm_footprint_final_110817.pdf> [Accessed 14 November 2021]. Manchester Climate Change Framework 2020-25 (n.d.) Manchesterclimate.com. [Online] [Accessed on 22 November 2021] https://www.manchesterclimate.com/framework-2020-25. Media.ontheplatform.org.uk. 2021. [online] Available at: <http://media.ontheplatform.org.uk/sites/ default/files/gm_footprint_final_110817.pdf> [Accessed 14 November 2021]. Palmer et al. (2013) Further Analysis of the Household Electricity Use Survey - Early Findings: Demand side management. London: Palmer, J., Terry, N. and kane, t., 2013. Further Analysis of the Household Electricity Survey Early Findings: Demand side management. [ebook] Reference 475/09/2012. Available at: <https://assets. publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/275483/ early_findings_revised.pdf> [Accessed 14 November 2021].

UK Air Pollution: How clean is the air you breathe? (2020) Clientearth.org. [Online] [Accessed on 21 November 2021] https://www.clientearth.org/latest/latest-updates/news/uk-air-pollution-how-clean-is-the-airyou-breathe/. UK’s carbon footprint (n.d.) Gov.uk. [Online] [Accessed on 22 November 2021] https://www.gov.uk/government/statistics/uks-carbon-footprint. uni, L., 2011. The Total Carbon Footprint of Greater Manchester Estimates of the Greenhouse Gas Emissions from Consumption by Greater Manchester Residents and Industries. [ebook] A report by Small World Consulting Ltd. Available at: <http://media.ontheplatform.org.uk/sites/default/files/gm_footprint_final_110817.pdf> [Accessed 14 November 2021]. US EPA. 2021. Nitrogen Dioxide (NO2 Primary) Air Quality Standards - Documents from Review Completed in 2010 | US EPA. [online] Available at: <https://www.epa.gov/naaqs/nitrogen-dioxide-no2-primary-air-quality-standards-documents-review-completed-2010> [Accessed 14 November 2021]. Where does air pollution come from? (2017) Org.uk. [Online] [Accessed on 21 November 2021] https:// www.blf.org.uk/support-for-you/air-pollution/where-does-it-come-from.

Palmer, J., Terry, N. and kane, t., 2013. Further Analysis of the Household Electricity Survey Early Findings: Demand side management. [ebook] Reference 475/09/2012. Available at: <https://assets. publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/275483/ early_findings_revised.pdf> [Accessed 14 November 2021]. Publishing, C., 2019. [online] Assets.publishing.service.gov.uk. Available at: <https://assets.publishing.service. Scied.ucar.edu. 2021. How Weather Affects Air Quality | UCAR Center for Science Education. [online] Available at: <https://scied.ucar.edu/learning-zone/air-quality/how-weather-affects-air-quality> [Accessed 14 November 2021]. Sizing Up Humanity’s Impacts on Earth’s Changing Atmosphere : A Five-Part Series By Alan Buis, NASA’s Jet Propulsion Laboratory (2019) The atmosphere: Getting a handle on carbon dioxide. Climate Change: Vital Signs of the Planet. [Online] [Accessed on 21 November 2021] https://climate. nasa.gov/news/2915/the-atmosphere-getting-a-handle-on-carbon-dioxide/.

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The energy sector is one of the main contributing sectors to the production of greenhouse gases. This chapter explores the different producing systems and calculates agencies the ability to watch events as they unfold, understand how demand patterns are changing, and respond with faster and lower-cost solutions. INTRODUCTION Energy in Context: Manchester

SECTION ONE

SECTION TWO

SECTION THREE

The Problem

Energy Generation and calculations

SECTION FOUR

SECTION FIVE

SECTION SIX

Emissions and Reductions

Precedent

Executive summary and bibliography

Transmission

CONCLUSION 132

Application within Victoria North

ENERGY

INVESTIGATING RENEWABLE AND NON-RENEWABLE ENERGY SYSTEMS

Abdullah Jawdatt, Bella Kimathi, Bethany Stewart Zero Carbon Cities

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Introduction Energy in Greater Manchester

Manchester is one of the fastest growing cities in the UK due to its rapid development of its city centre and environs. As a result, consideration of the city’s carbon emissions has become a cause for concern with regards to the contribution of its energy consumption and emission rates. The city’s growing population has had a large influence on the rapid development of dwellings and the growing amounts of energy supplied for consumption. The greater Mavnchester Combined Authority has pledged to lower the amount of carbon emissions by 80% as well as a maximum production of 2 tonnes of CO2 per capita by 2050. They aim to achieve this by shifting away from types of energy and highlight the use of others such as gas and electricity respectfully. According to the Greater Manchester Spatial Energy Plan, Greater Manchester is responsible for 3% (51.6TWh/year) of the UK’s total energy consumption with Manchester being the highest consumer and Oldham being the lowest consumer in Greater Manchester. (Energy Systems Catapult, 2016) With 95% of the buildings in the county consuming gas as the primary energy type for heating, the systematic prioritisation of electricity should aid in lowering the CO2 emissions associated with the type of energy.

Where 28% the annual energy consumption is transport fuel, other fuel makes up the remaining 7% of energy consumption in Greater Manchester. Accounting for the rise in development, the overall energy demand in Manchester is set to increase by 3% by the year 2035. The Greater Manchester Combined Authority endeavours to explore more renewable means of generating at least 9% of the electricity used in the city. However, they acknowledge that by using the National grid, Manchester’s electricity will source the remainder of its electrical power load while reducing the use of coal and gas.

Percentage of EPC ratings or better within Manchester (Source: Author)

To attain the goals set for Manchester and attain Carbon Zero, the shift towards more renewable sources of energy, and the incorporation of more sustainable energy types to older buildings in Manchester will also be required. The following document will be an exploration into the various ways in which energy is generated, accounted for, consumed and can be reduced to help reduce CO2 emissions and hit the targets set by the government.

“Heating accounts for 42% of energy consumption” Energy Consumption Density (Source: Author)

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Introduction

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The Problem

Issues with current major non-renewable energy systems

Energy Generation and CO2 Emissions

NONRENEWABLE

There are two types of energies being used to provide electricity to houses and businesses in Manchester and beyond: Renewable Energy and non-renewable energy. The usage and production using non-renewable energy sources poses the most problems and are one of the major causes of carbon emissions as well as contributors to the global warming. Coal, petroleum, and natural gas are the most common non-renewable energy sources. In fossil fuels, carbon is the most abundant element and as such the largest contributors of CO2 emissions. Whilst non-renewable energy sources are relatively easy to extract and are inexpensive to produce and distribute; the process

of buring them and creating energy and electricity out of them are extremely harmful for the environment. That is because Burning fossil fuels disrupts the Earth’s “carbon budget,” which maintains a balance of carbon in the ocean, on land, and in the atmosphere. When fossil fuels are burned, carbon dioxide is released into the atmosphere causing the “greenhouse effect” in which carbon dioxide traps heat in the Earth’s atmosphere causing an imbalance in the Carbon budget. This problem can be mitigated by the usage of renewable energy sources that does not produce harmful emissions into the atmosphere.

“Heating accounts for 42% of energy consumption” 136

Energy Generation

HIGH PERECENNAGE OF GHG EMISSIONS DESTRUCTION OF HABITAT

VERY EXPENSIVE TO SETUP AND OPERATE

EXTRACTION OF MATERIALS (Source: Author)

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Energy Generation Types of Energy Generation

Energy, in its most simple definition, is the capacity to do work (McFadden et al., 2021). Energy exists in potential, kinetic, thermal, electrical, chemical, nuclear, or other various forms. Fossil fuels, alongside conventional energy generation has dominated the energy supply. Crude oil, coal, and natural gas represented over 80% of primary energy supply globally in 2018 (Rabaia et al., 2021). Since the declared climate emergency, it is imperative to look to alternative, renewable energy generation systems. In this chapter, an insight into ten different types of energy generation systems is given: wind, solar, nuclear, hydrogen, biomass, oil, gas, hydroelectric, coal and geothermal power. Although other technologies exist, these are the most common and relevant to the UK. The chapter considers the life-cycle and entire system of each energy type to understand the full impacts of its carbon emissions, to then suggest applications to the Victoria North development.

Emerging Renewable:

“Crude oil, Coal, and natural gas

• Marine Energy (wave, tidal, salinity gradient, ocean thermal energy conversion)

represented over 80% of primary energy

• Concentrated solar photovoltaics (CSP) (parobolic troughs, linear Fresnel reflectors, parabolic dishes, solar towers)

supply globally in 2018”

• Enhanced Geothermal Energy (EGE) • Cellulosic Ethanol

(Rabaia et al., 2021).

• Artificial Photosynthesis

(Rabaia et al., 2021

OIL & GAS 40.8 %

Types of Energy Generation: Non-renewable: • Fossil: coal, oil, natural gas • Nuclear: fission

Renewable:

WIND 20.8% NUCLEAR

• Hydroelectric: water • Solar • Geothermal • Wind • Bioenergy

138

Energy Generation

SOLAR 4.1%

16 %

BIOMASS 6%

HYDROELECTRIC 4.2%

(Source: Author)

COAL 2.8%

GEOTHERMAL

5.3%

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Energy Generation Types of Energy Generation

“The Energy sector is one of the largest sectors in the UK. That means that it plays a fundamental part in the function of other sectors. These sectors and the energy sector provide each other a two-way system of interaction.” (UKgov Department of BEI, 2021).

A system's map showing the contribution of sectors to the Energy Sector (Source: Author)

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Energy Generation

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Energy Generation Types of Energy Generation

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Energy Generation

A dynamics map showing the The direct relationships between energy systems (Source: Author)

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Energy Generation UK Facts and Figures

36%

increase in fossil fuel generation in 2021

27%

decrease in total energy production in 2nd quarter of 2021- a record low quarterly level this century.

Energy generation in the UK is significantly dominated by oil and gas extraction. It’s use has fallen significantly since 1986 until 2014, before falling below the electricity sector. In 2020 the demand of the Covid-19 pandemic contributed to the fall of production and prices, ‘however the oil and gas sector remained the second largest contributor’ (Department for Business, Energy & Industrial Strategy, 2021). ‘Electricity (including renewables) accounted for 56%, oil and gas extraction accounted for 27%, and gas accounted for 11% ‘ of the energy total in 2020 (Department for Business, Energy & Industrial Strategy, 2021).

The UK currently imports more crude oil energy than it produces. North Sea production peaked in the 1990s but now levels are in tandem with the reliance on imports in the 1970s (Office for National Statistics, 2021). Generally there is an increase in renewable energy production, however, renewable generation fell due to less favourable conditions in 2021. Wind generation fell the most with a 14 percent decrease. As a result, fossil fuel generation increased by 36 per cent as gas was used alternatively (Department for Business, Energy & Industrial Strategy, 2021).

21.5%

primary energy in UK obtained from low carbon sources (Department for Business, Energy & Industrial Strategy, 2021)` UK Prodution (Department for Business, Energy & Industrial Strategy, 2021).

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Energy Generation

Proportion of UK energy supplied from low carbon sources 2000 to 2020

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Energy Generation Breakdowen of energy allocation Energy type

Hydro

Equipment

Primary Process Processing Storage Extraction

Wind Generator Bioenergy Transmission Gas

Oil

Foundation Wind Farm Transformers Power Lines Solar panel DC/DC Converter DC/DC Inverter MPPT Controller Transformer Inverter Dam Powerhouse Mining Boiler Stack Water purification Condenser Extraction (Uranium) Milling Conversion Enrichment Deconversion Fuel fabrication Reprocessing Harvesting Processing & drying Furnace/boiler

Sector Serviced Secondary Process

Waste Imports Other domestic biomass Buildings biomass Transport biofuels Industry biomass Buildings natural gas Industry natural gas

Use

Buildings oil Transport oil Industry oil Agriculture Industry coal Buildings coal

Separation Process (boiler distillation) Compressor Station Solar (PV)

Generator Gas Processing Plant Generation

Coal

Steam Turbine Substation

Transmission Electricity generation

Maintenance Turbine

Nuclear

Powerplant Conversion factor

Generator

Breaking down the energy systems is a vital part to understanding the output emissions as well as the embodied energy and carbon that it has. This is because it will allow for a more accurate cacluations of the system's sub-parts and their processes. (Source: Author)

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Energy Generation

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Fossil Fuel Energy Technologies, Cost and Efficiencies

35%

average efficiency for the generation of coal

45%

average efficiency for the generation of natural gas

38%

average efficiency for oil-fired power generation

There are multiple oil refineries and companies across the UK. The closest to Manchester is in Warrington. (Source: Data from Thory (2021).)

Advantages:

Fossil fuels are energy sources that were formed under intense pressure from plants and organisms approx. 286-360 million years ago (Fossil Fuel Energy, 2021).

Map of Oil Generation Plants in the UK • Readily available moment)

Fossil Fuel Types

(at

the

• Relatively easy to produce energy from

• Coal: formed from plant material hardened under pressure and heat from the earth (Fossil Fuel Energy, 2021).

• Potential to decarbonised

• Oil: formed from smaller organisms including, zooplankton and algae, which decompose under intense pressure, into oil (Fossil Fuel Energy, 2021).

become Natural Gas power stations are more common in the UK than oil refineries. The closest power station to the Northern gateway site is in Stretford, with others located outside of Greater Manchester. (Source: Data from Thory (2021).)

Disadvantages:

• Natural Gas: undergoes the same process as oil; however the process is longer and subject to higher amounts of heat and pressure, causing further decomposition (Fossil Fuel Energy, 2021).

• Non-renewable source

Map of Gas Generation Plants in the UK

• Increasing fuel costs • Releases carbon dioxide when burnt

Energy Types Energy Types Renewable and non-renewable systems Renewable and non-renewable systems

(Ziess, 2021)

only 4

active coal-fired power plants in the UK (GovUK, 2021)

148

The n o n - r e n e w a b l e e n e r g y s y s t e m s ha v e been a consistent factor in the increase of GHG emissions, prompting quick action to reduce their uses. (UK Energy Statistics,

2019)

Decarbonising Fossil Fuels:

OIL & GAS

40.8 %

The UK plans to decarbonise existing non-renewable power sources by 2050. One method is using natural gas with Carbon Capture, Utilisation and Storage (CCUS) WIND can beWIND which very low carbon, depending on the 20.8% efficiency of the20.8% CCUS (Bodel et al., 2021). NUCLEAR

SOLAR

16 % SOLAR

4.1%

Non-renewable Energy Generation

NUCLEAR BIOMASS 16 % 6%

BIOMASS 6%

HYDROELECTRIC 4.2%

Coal Generation has declined significantly and this is reflected in the number of plants in the UK; only 4 plants are currently active. There are no immediate plants in Manchester. However, plants can be found near Long Eaton, Gainsborough and Snaith (Source: Data from Thory (2021).) COAL 2.8% HYDROELECTRIC 4.2%

GEOTHERMAL COAL

2.8% 5.3%

GEOTHERMAL

5.3%

Map of Coal Generation Plants in the UK

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Fossil Fuel Energy System Process & Calculations

Energy Types Overview: This next section of the chapter explores different energy systems and their processes to understand areas that contribute to embodied carbon emissions. Calculations are made to compare costs, and carbon emissions.

Oil and Gas System Process: After the oil is extracted, through mechanical or chemical manipulation techniques, it is separated, vented and flared. Natural gas is processed at the plant by separating the various hydrocarbons and fluids, leaving pure natural gas (NaturalGas.org, 2021). Non-hydrocarbon products are released as waste. At the compressor station, the oil and natural gas can either be used and distributed as is, stored, or converted to electrical energy. Electrical energy is generated and distributed via the national grid for use in homes and other infrastructure.

Calculations: This set of calculations shows the cost of usage per hour for a residential building , for each fuel type. For oil, it is assumed that all oil is imported from Norway (the UK’s main international oil supplier). Data Source: Local Government Association (2021) and (UK Power, 2021) Calculations

Average electricity consumption per UK household:

Oil:

Electricity = 350KWh p/m

Cost of Usage per hour, residential:

Cost of usage per hour:

Assuming the UK imports most of it’s oil from Norway,

If 1 boe = £41.99 and 1 boe = 5.658 GJ

Average rates 2021: 487.6337 Oil/NOK

5.658 : 41.99 ÷ 4.49

Currency conversion: 1 NOK = 0.086 GBP boe : toe ÷ 7.4

Coal System Process:

7.4 : 1

÷ 7.4

Conversion: month

÷ 7.4

Cost of Usage per hour, residential = £0.0128 p/h ÷ 7.4

£0.0128 p/h

0.1351 : 5.658 Therefore the price is £41.99/boe

To power a residential building directly from oil, if costs for production and business profits etc. were not included

= 5.658 GJ/boe Mainline sales

Oil and Gas well Separation

Oil

Gas Processing Plant

Vented and flared

Compressor station

Gas well

Water

Raw Material Extraction

Waste Heat

Coal Mining

150

boiler

Non-renewable Energy Generation

stack

water purification

Odarant

natural gas company

Underground storage reservoir

Liquified nitrogen gas storage

Products Non-hydrocarben gases

Steam Turbine

Condenser

hours:

9.35 ÷ (30.436875 x 24) = £0.0128 p/h

toe : GJ 1 : 41.868

÷ 4.49

Therefore, to power a house on oil, the cost would be £9.35 p/m

1 : 0.1351

Coal is mined and milled into a fine powder to be burned. This process is called Pulverised Coal Combustion. Heat energy and gases produced from burning produce steam in the boiler, generating turbines. Generators convert the energy into electrical energy which is then transformed and distributed via grid power lines for user consumption (World Coal Association, 2021).

1.26 : 9.35

Distribution and Use

Generator

Substation

Grid

Fossil Fuel System 151

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Fossil Fuel Energy Amount of fuel required to power a household

Calculations: This set of calculations shows the cost of usage per hour for a residential building , for each fuel type. For coal, it is assumed that all coal is mined in the UK. Data was sourced from DUKES (GovUK, 2021) and (Statista, 2021). Coal:

Calculations:

Cost of Usage per hour, residential:

Amount of coal required to power domestic household:

This set of calculations continues to show the amount of oil required to power a residential building , for each fuel type. For oil, it is assumed that all oil is imported from Norway (the UK’s main international oil supplier).

Assuming the cost of coal per ton is £69.46

If Average consumption for house = 3.846 kWh/m2

Oil:

Conversion: 1 Ton of coal e = 29,307,600,000 J

And 1 ton of coal = 8,141 kWh

Price per KW, residential:

Amount of oil required to power domestic household:

If £41.99 = 5.658 GJ,

If 1 toe = 11630 kWh

5,658,000,000 1000(60 x 60)

3.864 : 3.3e -4

x 3.3e -4

KWh = 8,141 KWh

x 3.3e -4

x 0.0429

8,141 : 69.46 350 : 2.99

= 0.336 kg/day ÷ 1,571.667

0.027 : 1

÷ 1,571.667

Amount of oil required, domestic = 0.336kg/day

Conversion month

hours: 2.99

Price per kW, residential = £0.027 /kW

= £0.004 p/h

(30.436975 x 24)

Amount of oil required to power non-domestic building:

x 0.36

If Average consumption for house = 350 kWh p/month per hour =

4151 : 0.356

Cost of Usage per hour, residential = £0.004 p/h x 0.36

= 362.649 kg/day 350

= 11.499 kWh/d

If each household has a useable floor area of 91m2 0.479 91

= 0.0052 kW/m

= 3.846 kWh/m

Energy consumed, domestic = 3.846 kWh/m2

Non-renewable Energy Generation

362.65 kg/day To power a residential building directly from oil.

Amount of coal required, domestic = 0.48 kg/day

Amount of coal required to power non-domestic building:

And 1 ton of coal = 8,141 kWh 8,141 : 1

Price per KW, residential:

= 0.479 kW Amount of oil required, non-domestic = 362.649 kg/ day

4.72e -4 x 1016.04691 = 0.48 kg/day

x 0.51

4.1451 : 0.51

÷ 8.141

x 0.51 = 518.07 kg/day

Conversion/day =

If £69.46 = 8,141kWh

(30.436875 x 24)

152

11630 : 1

Conversion/day =

If Average consumption for non-domestic = 3.846 kWh/ m2

If 1 toe = 11630 kWh Energy consumed, domestic:

x 4.72e -4

3.846 : 4.72e -4

x 0.0429

Therefore the 350 kWh of coal costs £2.99 p/m

41.99 : 1,571.667

8,141 : 1

x 4.72e -4

Assuming average electricity consumption per UK household = 350 kWh p/m

11630 : 1

= 1,571.667 kW

8,141 : 69.46 1: 0.0085

÷ 8.141

4.72e -4 x 1016.04691

Amount of coal required, domestic = 518.07 kg/day Price per KW, residential = £0.0085 /kW

£0.0085 p/h

To power a residential building directly from coal, if costs for production and business profits etc. were not included.

518.07 kg/day

To power a residential building directly from coal. 153

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Fossil Fuel Energy Amount of fuel required to power a household

Calculations: This set of calculations shows the cost of usage per hour for a residential building , for natural gas. For coal, it is assumed that all coal is mined in the UK. Data was sourced from Department for Business Energy & Industrial Strategy (2021) and (Statista, 2021). Natural Gas:

Amount of natural gas required to power domestic household:

Price per KW, residential:

If 1 m3 = an average of 10 kWh

Price per kW = £0.02

Conversion m3 to kg = 1m3 = 128.2kg

Energy consumed, domestic:

128.2 kg = 10 kWh

If Average consumption for house = 350 kWh p/month

1 kWh = 128,2/10

per day = 350

= 12.82 kg/kWh = 0.479 kW

(30.436875 x 24)

For domestic household: 1 : 12.82

= 11.499 kWh/d

350 : 4487 kWh per month

If each household has a usable floor area of 91m2 0.479 91

= 0.0052 kW/m2 = 3.846 kWh/m2

Energy consumed, domestic = 3.846 kWh/m2

154

Non-renewable Energy Generation

Conversion/day = 4487/24)

Fossil Fuel Power Plant Cooling Towers: (Source [adapted from] Edie Newsroom (2021) https://e2k9ube.cloudimg.io/s/cdn/

= 186.96 Amount of oil required, domestic = 0.336kg/day

186.96 kg/day To power a residential building directly from natural gas.

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Nuclear Energy Technologies, Cost and Efficiencies

Nuclear energy ‘is the

Nuclear energy is generated through the fission process. Using uranium ore, atoms are split in a reactor to heat water into steam, which turns a turbine thus generating electricity (The Nuclear Energy Institute 2021).

Technologies:

Advantages:

Disadvantages:

• Fission • Nuclear Hydrogen Production

only

proven, dispatchable,

low-carbon energy source’ (Bodel et al., 2021)

• Can produce large amounts of energy from small quantities of fuel therefore transportation is relatively cheap and effects on environment are reduced. • .Uranium is less expensive to procure and transport. • Nuclear power plants do not pollute the atmosphere. Lifecycle emissions are on par with renewable energy sources. • Less space is required compared to other power plants.

HTGR and

hydrogen generation using nuclear heat

is the future!

• Mining uranium ore can release harmful radiation

Energy Types

• Cost of building nuclear plants and decommissioning are very expensive. • Site selection makes building a power plant difficult, as waste products can harm the environment. • Difficult to react quickly to changes in electricity demand. • Nuclear plants have a limited life

Decarbonising Nuclear Energy: Bodel et al. (2021) states that in order to reach the UK’s 2050 target, new reactor technology should be developed, licensed and built by 2040. The demonstration reactor should feature high-temperature gas reactor (HTGR) technology and hydrogen generation using nuclear heat. It is important for the UK to understand closed fuel cycles to find a place for these systems in the energy market. Methods: Direct Air Capture (DAC): uses an engineered, mechanical system to capture carbon dioxide directly from the air. CO2 is extracted in a compressed form and stored underground or reused (Carbon Engineering, 2021).

Renewable and non-renewable systems The n o n - r e n e w a b l e

Map of the closest Nuclear Generation Plants in the UK to Manchester e n e r g y s y s t e m(Source: s ha v e Data from Thory (2021).)

There are currently eight operational power stations (Department for Business, Energy & Industrial Strategy, 2018). The closest station to Manchester is Heysham 1 power station located on England’s north west coast, near Lancaster. This site operates two power stations, supplying 1155MW to the national grid (EDF, 2021).

Carbon Capture Utilisation and Storage (CCUS): prevent CO2 from being released into the atmosphere by placing a chemical in the source stream to extract CO2 . The carbon dioxide is then compressed and transferred via pipeline (Congressional Research Service (CRS), 2020). Both technologies are still under development and face various challenges as the processes are both capital and energy-intensive. Additionally, there is a low demand for CO2 , presenting difficulties in commercialisation of these technologies (CRS, 2020).

been a consistent factor in the increase of GHG emissions, prompting quick action to reduce The their UK uses. has (UK invested in a Energy Statistics,

new generation of power plants; two2019) of which are currently under construction. Nearly half of current nuclear plants are to be retired by 2025 (World Nuclear Association, 2021).

WIND 20.8%

90%

of annual time is spent SOLAR in generating electricity a nuclear plant. 4.1%

NUCLEAR

BIOM

16 %

(Koval and Chala, 2018) Of total UK energy generation

156

Non-renewable Energy Generation

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Nuclear Energy System Process & Calculations

Calculations

1,100,000kW x $8,100 = $8,910,000,000

Cost of Nuclear Energy per kW = Between ($5,500/kW or £4000/kW) and ($8100/kW or £6000/kW)

1/3

of worldwide nuclear capacity is generated using pressurised water reactors (PWRs) (World Nuclear

~ = $9 Billion Converted to GBP currency based on 2018 rate at $1=£ 0.73 = £6,493,830,750 ~ = £6.5 Billion

Typical maximum output per power plant per annual Nuclear System Process: The nuclear process involves the extraction and mining of uranium ore to fuel nuclear fission. At the power plant, the fission process in controlled. Uranium ore is milled and then undergoes de conversion to other forms of uranium, and is stored. In the fuel fabrication process, uranium is turned into nuclear fuel rods; the physical structures that hold the fuel rods are engineered with extremely tight tolerances (World Nuclear Association, 2021). Pressurised water reactors (PWRs) are the most common type of nuclear reactor. PWR cores use water as a coolant and moderator. Nuclear fission occurs in reactors which heats the cooling agent, produces steam which turns a turbine hence, generating energy for transmission via the national grid. The embodied carbon of a nuclear system is predominantly in the construction and maintenance of nuclear power plants. The electrical conversion itself produces little to no C02 emissions - clean energy. Excess steam powering turbines is cooled in a cooling tower; some of which is recycled as clean water vapour back into the atmosphere. The main concern of nuclear energy is the radioactive waste which have to be safely stored.

Association, 2021)

= 1, 100MW

To reach a 1,100MW converted to kW Power Plant energy output (Note: (1kW = 0.001MW) = (1MW = 1000kW) : 1000kW x 1100MW = 1,100,000kW

Cost of the power plant to be functional:

One Nuclear plant operating at 1,100MW requires around 600,000m2 of plot land To find £/m2 = Total Cost of Plant (Maximum Plant Cost)/ Plot Size = £6,493,830,750 / 600,000m2 = Each m2 of Nuclear Plant Plot has an estimated cost of £10,823.10/m2

1,100,000kW x $5,500 = $6,050,000,000 ~ = $6 Billion

Converted to GBP currency based on 2018 rate at $1=£ 0.73 = £4,409,391,251

£10,823.10 2 p/m

To power a nuclear power plant

~ = £4.4 Billion

158

Non-renewable Energy Generation

Nuclear Energy System

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Nuclear Energy System Process & Calculations

As of 2020, the UK has 15

active nuclear reactors that

are used to provide electricity nationwide (Satatista, 2020)

160

Nuclear System within the UK: As of 2020, the nuclear energy system’s usage have shown to gain interest due to its long term sustainable positives. This lead to nuclear energy in the UK to make up 16% of the UK’s electricity whilst lower than 2019 in which nuclear energy supplied 17%, the reduction was mainly due to the pandemic and the decrease of overall industrial electricity output. Whilst there is a major interest in employing the usage of nuclear energy once again, there was a clear decline in the past with the peak usage of nuclear energy being in the 1990s producing over 25% of the UK electricity. This decline was mainly caused by the heavy short term costs, constant maintenances and rapid increase of efficiency technology rendering older nuclear power plants unnecessary and costly. (Lords Library Parliament, 2020) This energy is generated by 13 major nuclear reactors at six sites, albeit some of these reactors are not operational at any given moment due to planned or unplanned maintenance. The usage of nuclear power once a again, according to the government, is a key aspect of reaching the country’s carbon reduction goals. The third of ten points in the Government’s Ten Point Plan for a Green Industrial Revolution, published in November 2020 and confirmed by the government in its energy white paper strategy document in December 2020. This shows nuclear energy despite its heavy initial costs have a prominent future amongst the UK energy production systems. (The Ten Point Plan for a Green Industrial Revolution HM Government, 2020)

Non-renewable Energy Generation

Table showing figure of Nuclear Generation Plants in the UK and their capacity (Source: Energy-charts, 2021.) Calculations: Total minimum energy produced / number of power plants in the UK (15)

Total maximum energy produced / number of power plants in the UK (15)

(minimum energy produced by plants) 6,491.95MW / (of power plants) 15 = 432.80MW Minimum Energy Produced

( maximum energy produced by plants) 8,289.12MW / ( of power plants) 15 = 552.60MW Maximum Energy Produced

Nuclear Energy System

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Hydrogen Energy Technologies, Cost and Efficiencies

1st The UK is on track to be the first country in the world to use hydrogen power to provide electricity to common households. (UK Hydrogen Strategy

Hydrogen is one of a few innovative low-carbon technologies that will be crucial in the UK’s net-zero transformation and reaching its zero-carbon goal. Low carbon hydrogen is one of few other highly versatile replacement for high-carbon fuels used today as part of a thoroughly decarbonised, deeply renewable energy systems, helping to reduce emissions in important UK industrial sectors and providing flexible energy for power, heat, and transportation. With almost no low-carbon hydrogen production in the UK or internationally today, attaining the 2030 net-zero goal and delivering decarbonisation and economic advantages from hydrogen would necessitate rapid and massive scale-up.

The UK Hydrogen Strategy takes a comprehensive approach to building a successful hydrogen industry in the United Kingdom. It lays out the steps that must be taken to enable the production, delivery, storage, and use of hydrogen, as well as to ensure economic prospects at an industrial level. The Strategy laid out by the government’s Business, Energy & Industrial department combines near-term pace and action with long-term direction to unlock the innovation and investment critical to meeting the zero-carbon ambitions. (UK Hydrogen Strategy UK Gov, 2021)

Map of Hydrogen Generation Plants in the UK

UK Gov, 2021)

Advantages:

Disadvantages:

• Can produce large amounts of energy from small quantities of fuel therefore transportation is relatively cheap and effects on environment are reduced.

• Mining uranium ore can release harmful radiation

• .Uranium is less expensive to procure and transport. • Nuclear power plants do not pollute the atmosphere. Lifecycle emissions are on par with renewable energy sources. • Less space is required compared to other power plants.

Calculations: Hydrogen plant uses a P2G technology (Power-to-Gas) to produce hydrogen gases that is then used to output electric power.

A typical P2G system has: •

A Nominal power of 1MW

• A Net production rate of up to 300 Nm3H2/h (Normal Metre Cubed Hydrogen per hour) • A Power consumption at stack 3.8–4.4 kWh/ Nm3 of H2

Data from https://www.thehydrogenmap.

The specific density of the hydrogen used in a P2G system = 0.08988 kg/Nm3 Lower heating value (LHV) of the hydrogen used in P2G system: 119.96 MJ/kg

The ratio between the internal energy of the produced hydrogen and the energy invested in the production of hydrogen: (P2G) = Hydrogen energy production energy (kWh/kg).

(kWh/kg)/Hydrogen

Considering the LHV of the generated hydrogen and the highest consumption of the electrolyser (48.95 kWh/kg), the efficiency of the P2G system is: η(P2G, LHV) = 33.32 kWh/kg/48.95 kWh/kg = 0.681 = 68.1% Efficiency

162

Renewable Energy Generation

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Hydrogen Energy System Process & Calculations

Calculations:

The production cost (PC) of hydrogen consists of two parts:

Maximum electric power consumption of a P2G system needed for full hydrogen production capacity (300 Nm3 /h) is:

• PC1 – Costs of P2G system equipments and maintenance

P(EL_MAX) = 300 Nm3 /h × 4.4 kWh/Nm3 = 1320 kW = 1.32 MW

Emission of hydrogen fueled vehicle are

30%

lower than

traditionally powered vehicles

Hydrogen System Process: Traditional hydrogen production formerly used to be based on fossil feedstocks, such as steam reforming of natural gas, and this has become distinguished from the new renewable hydrogen production method which is based on renewable feedstocks, such as biogenous processes (biomass gasification or biogas reforming) or electrolysis of water (H2O) with wind, hydro energy, or solar energy. Hydrogen is now produced mostly by steam reforming fossil fuels like natural gas. As a by-product of several industrial operations, excess hydrogen is also recovered. Despite the fact that hydrogen produced from fossil feedstocks has no tailpipe emissions, the manufacturing process nonetheless has a carbon footprint that in comparision with other non-renewable energy systems is considerably lower. (British Oxygen Company, 2021)

PC2 – Cost of electric energy for operation

PC1 is calculated as: PC1 = (Capital + Operations)/m (Total hydrogen production assuming the system operates 80% of the time for the plant’s lifespan of 15 years) =

The costs of components in P2G systems to build a single hydrogen plant as of 2020:

m(Total) = 647 kg/day × 365 days/year × 15 years × 0.8 = = 2,833,860 kg

•

Project documentation £84,459.41

•

Electrolyser £1,351,350.62

PC1 = (£1,858,107.10 + 15 × £92,905.35)/2,833,860 kg = £1.15/kg

•

High pressure storage £168,918.83

•

BoP components £101,351.30

•

Electric connection to HPP £84,459.41

Electricity Costs/MWh and output for PC1, PC2 and PC total:

•

Construction and assembly works £67,567.53

£29.56/MWh - £1.14/kg + £1.48/kg = £2.62/kg

•

Total costs £1,858,107.10 or

£42.23/MWh - £1.14/kg + £2.11/kg = £3.25/kg

PC2 is calculated as: PC2 (£/kg) = electric energy price (€/kWh) × hydrogen production power consumption (kWh/kg)

£2 Million rounded to the nearest million as the maximum estimate

(British Oxygen

•

101.35/MWh - £1.14/kg + £5.07/kg = £6.21/kg

Company, 2021) Sun Electricity Grid AC

Sun Natural Gas Grid

Power Generation

Blancing the energy output

Water AC Volatge

Transformer

Rectifier

Spotting Process

Electrolysis

CO2 Spotting Process

Methanation

Use

Spotting Process

Hydrogen System 164

Renewable Energy Generation

Decommissioning

Recycling

CO2

Sun Natural Gas Storage

Gas mixing

Biomass

Salt Cavern

Gas and pipe storage facility

H2 Seperator

Sun Hydrogen Storage

O2 Seperator

SunWater Storage

165

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Solar Energy Technologies, Cost and Efficiencies

60%

world’s renewable overall capacity growth 2019 (Rabaia et al., 2021)

Solar power is energy from the sun that has been converted into electrical or thermal energy through various solar technologies such as photovolaltaic (PV) panels. Energy generated can be used or stored in batteries or thermal storage (How Does Solar Work?, 2021). Solar energy accounted for 60% of the world’s of renewable’s overall capacity growth in 2019 (Rabaia et al., 2021).

energy • Solar cells power space vehicles such as satellites and Hubble (Sakthivadivel et al., 2021) Advantages: • Solar power is very cheap compared to other sources of energy generation (Rabaia et al., 2021)

Solar Cell Applications

• Low maintenance costs.

• Distinct solar photovoltaic (SPV) cells are used to operate torches, flashlights, electronic watches and others.

Disadvantages:

• Polymer solar cell exhibit high transparency and are used as in windows, stretchable electronics and so on. • The use of SPV systems in Solar power generations can be used for residential, commercial, industrial, agricultural and traction applications. • Electrical vehicles driven by solar

• Solar efficiency is affected by seasons, weather and installation site (Lakatos et al., 2011) • Most of the materials used in thin film photovoltaic cells (TFPV) and PV manufacturing, in general, are potentially toxic, highly valuable, and often rare, and might possibly be released to the environment through air and water then cause some serious problems (Rabaia et al., 2021)

Energy Types Renewable and non-renewable systems Map of Solar Generation Plants in the UK (Source Author)

Solar Farms and companies are prominent across the UK, but particularly in the south of England, as the solar conditions are better. There are currently 50 operational solar farms alongside many companies providing solar

The n o n - r e n e w a b l e Thory e n e r g y s y s t eData m s ha from ve been a consistent factor in the increase of GHG emissions, prompting quick action to reduce (Department Business, Energy & (UK Energy Statistics, theirfor uses.

(2021).

installations 2019) Industrial Strategy, 2021b). Greater Manchester has multiple particularly in Denton, Ashton and warrington

WIND 20.8%

NUCL

16 %

SOLAR 4.1%

Of total UK energy generation

166

Renewable Energy Generation

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Solar Energy Technologies, Cost and Efficiencies

Cost UK (PV):

Technologies

40 - 50 years

Solar Cooling Technologies:

Photovoltaic Technologies: The PV system converts solar energy (photons) into electricity through the photoelectric effwect. It is referred to as solar electric energy to distinguish it from thermal energy (Sakthivadivel et al., 2021). There are four generations of PV technologies that range in conversion efficiency. (Sakthivadivel et al., 2021).

life span of photovoltaic panels

Solar cooling is the process through which heat from the sun is converted into a useful cooling system. Solar powered cooling systems have zero-emission when used with eco-friendly working fluids (Sakthivadivel et al., 2021).

• Silicon • p-n junction flat module

(The Renewable Energy

Solar Thermal Collectors: Solar thermal collectors (STC) differ from PV cells as they convert solar energy into thermal energy that can be stored. STCs have become known for their easy construction and ability to deliver heat for domestic and industrial purposes. Heat energy generated can be used for cooking, refrigeration, cooling, desalination, drying and melting metals (Sakthivadivel et al., 2021).

168

• Silicon is the most widely used material in PV cells: conversion efficiency of 27.6%

The mean cost receded over the year, after the peak at £1,763 per kW installed in April. The mean cost then reduced to reach a minimum mean cost for the year in October of 2020. £1,545 per kW installed and then stayed around the average until March 2021 (Gov UK, 2021)

• p-n junction flat module: The highest efficiency reported from Spectro lab for a 5-junction nonconcentrator cell: 38.8%

Hub, 2020)

System

Conversion Efficiency materials:

• Thin- film technology: conversion efficiency of 20.3%

• perovskite solar cells (PSCs)

Solar Energy

Average cost of solar installations in 2020/21 was slightly higher than in 2019/2020. For the smallest (0-4kW) installations, the mean cost increased to £1,628 per kW installed.

Material Processing

Panel Manufacturing

SOLAR ENERGY Usage of Solar Energy heavily reduces the amount of emissions produced and directly reduces the pressure on the grid

Energy Output

65%

Energy Output

Energy Efﬁciency

82%

Energy Efﬁciency

23%

Energy Emissions

72%

Energy Process

£1,628 p/kwh

Energy Emissions Energy

Process Average cost for small solar installations

Solar Energy Efficiency Rating. (Source: Author)

The highest efficiency reported for concentrating cells from Fraunhofer, Institute for Solar Energy: 46.0% • Perovskite solar cells (PSCs) Alternative renewable: Conversion efficiency of 22-28% (hybrid organic)

Photovoltaic Array

DC/DC Converter

DC/DC Inverter

Step up transformer

Transportation

Site Selection and Installation

Controller

Sun Use

Battery

GHG

Renewable Energy Generation

GHG

Grid

(Sakthivadivel et al., 2021) MPPT

Raw Material Acquisition

WIND ENERGY Wind energy has a very low cost compared to the electricity it is capable of generating making its efﬁciency high.

Decommissioning

Treatment Disposal

Recycling

GHG Solar Thermal Collector

Storage

Boiler

Heat Engine

Generator

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Solar Energy

Solar

Technologies, Cost and Efficiencies

40 - 50 years life span of photovoltaic panels

Solar energy accounts for part of 26.5% of the cumulative energies required to power the UK. The 26.5% consists of solar, wind and hydro energies. The annual amount of electricity generated and sent into the grid exclusively by solar energy is approximately 4% which is estimated to be 13158TWh from an installed capacity of 13462GW of Photovoltaic Cells. Monthly, this would equate to 1096.5Twh.

Solar Energy System Process: Carbon emissions within the solar energy system comes from the manufacturing of the photovoltaic (PV) panels themselves. Silicon tetrachloride and other materials in PV panels are toxic and need to be recycled correctly. After the material acquisition and manufacturing of PV panels, they are transported to site and installed. The panels convert photons from the sun into electrical energy using a converter, inverter and transformer to allow distribution to consumers, via the national grid (Sakthivadivel et. al, 2021). Solar panels have a life span of 40-50 years. Recycling and correct disposal is necessary after use.

If 12 Panels account for 3KW produced, then we can calculate the number of panels used to generate 1096.5TWh as follows: 12 x 1096.5e9 = 13158 / 3

Understanding that 24 panels cover 38.4m2 of space, the required area for 4.386e12 panels would be: 4.386e12 x 38.4 = 1.684e14 / 24 = 7.0176e12m2 = 7.017e6km2 WIND ENERGY

SOLAR ENERGY

GEOTHERMAL EN

Wind energy has a very low cost compared to the electricity it is capable of generating making its efﬁciency high.

Usage of Solar Energy heavily reduces the amount of emissions produced and directly reduces the pressure on the grid

Geothermal energy fuel and it is on environmentally sus

Assuming a PV system covering a 65% 10,000m2 office has a carbon emission of 2920TCO2, then we can assume for 82% the energy generated per month, the carbon emission can be calculated 23% as follows: Energy Output

Energy Output

Energy Efﬁciency

Energy Emissions

Energy Process

72%

7.0176e12 x 2920 = 2.049e16TCO2 / 10000

= 4.386e12 panels.

Solar Energy Efficiency Rating. (Source: Author)

= 2.049e12TCO2 emissions

(The Renewable Energy Hub, 2020)

Photovoltaic Array

Solar Energy

System 170

DC/DC Converter

MPPT Raw Material Acquisition

Material Processing

Panel Manufacturing

Transportation

Site Selection and Installation

DC/DC Inverter

Step up transformer

Controller

Sun Use

Battery

GHG

Renewable Energy Generation

GHG

Grid

Decommissioning

Treatment Disposal

Recycling

GHG Solar Thermal Collector

Storage

Boiler

Heat Engine

Generator

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Bioenergy Technologies, Cost and Efficiencies

Lignocellulosic biomass is considered to be a renewable feedstock,

most abundant and the

carbohydrate on Earth (Fan et al., 2021)

The increasing industrialization and motorization of the world has led to a steep rise for the demand of petroleum-based fuels warranting the need for alternative energy substitutions (Fan et al., 2021). Biomass is good substitution as it is carbon neutral with positive environmental properties. Biomass can be converted into liquid fuels or gas substitutes made from plant matter and residues, such as municipal wastes, agricultural crops and forestry by-products. Several energy products can be obtained by various biomass feedstocks (Fan et al., 2021). Ethanol and butanol are the typical bioalcohols, which can be used as transportation fuel. Ethanol could be combined and blended with petrol within unmodified spark-ignition engines or burned in its pure form within modified spark-ignition engines. Biomass resources: • Organic food waste • Municipal sewage wastewater • Sewage • Industrial organic effluents • Energy crops • Agriculture residues (crop straw, livestock and poultry manures, horticultural residues, etc.). Biogas Applications: • ○ Motor fuel • ○ Electricity

Biogas: Biogas is a mixture of gas predominantly consisting of methane (CH4) and CO2, is produced using modern bioenergy technologies for anaerobic digestion. Biogas can also be converted to electricity and heat in cogeneration units (combined heat and power), or the biogas is burnt to produce heat. Microorganisms: Ethanol fermentation: process in which the cells use its own enzyme system to convert monosaccharide or disaccharide into ethanol and carbon dioxide through anaerobic respiration. Feedstocks: 1st Generation: feedstock-starch such as maize, wheat, rice, corn, and cassava which could be utilized directly. (bioalcohols production by fermentation is less widely used.) 2nd Generation: technologies that use energy dense lignocellulosic biomass are under development Lignocellulosic biomass is considered to be a renewable feedstock, and it is the most abundant carbohydrate on Earth (e.g. forestry waste) 3rd Generation: microalgae Mainly used as the feedstock for the biodiesel. Microalgae after the production of biodiesel was still rich in carbohydrate such as starch and cellulose and have the possibility to be used as the fermentation substrate for bioalcohols.

Energy Types Renewable and non-renewable systems Data from Thory (2021).

n oUK n - r e(Source n e w a b l eAuthor) Map of Bioenergy Generation Plants Tinh ethe e n e r g y s y s t e m s ha v e been a consistent factor in the increase of GHG emissions, prompting are currently 12 biomass plants in thequick UK action alongside to reduce (UK Energy Statistics, bioenergy companies (Departmenttheirforuses.Business,

There other 2019) Energy & Industrial Strategy, 2021b). Great Manchester has the potential to increase the role of bio-fuels (The Energy Technologies Institute and Energy Systems Catapult, 2021).

OIL & G 40.8

WIND 20.8% NUCLEAR SOLAR

16 %

BIOMASS 6%

4.1%

• ○ Heat Technologies

172

Renewable Energy Generation

Of total UK energy generation

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2021 CPU[AI]

Bioenergy

Nutrient/ Water

System Process & Calculations Algal culture productions

Microalgae

the combustion of bioenergy

does not add to the total co2 emission

Bioenergy System Process:

Algal culture Harvesting Recycling of water

There are a number of ways to convert biomass to electricity, dependant on the type of fuel source. Each go through a conversion process to create the desired end product. For the production of electricity, the fuel source undergoes a combustion and boiling process which produces steam that spins a turbine. The turbine is connected to a generator which produces electricity to be distributed to the grid. As a whole there are various processes that contribute to the embodied carbon emissions of the plant. The construction of power plants, harvesting of plant fuel and transportation of fuel add to the carbon footprint. However, the combustion of bioenergy does not add to the total emission of carbon dioxide as long as the burned biomass doesn’t exceed the renewed production (within a reasonable time), or it is not transformed in processes requiring CO2-forming energy (Department for Business, Energy & Industrial Strategy, 2021).

Discharged water

Biomass

Feedstock

Energy Dense Lignocellulosic Biomass

Receiving & storage

Thermo-chemical conversion

Algal culture dewatering

Extraction of fatty acids

Simultaneous saccharification and fermentation

Processing & drying

Furnace/ Boiler

Combustion

Heat & Power

Gasification

Hydrogen, Alchohol, Olefins Gasoline, Diesel

Transesterification

Biodiesel Glycerol

Transportation

Distribution

Turbine

Generator

Grid

Use

Distribution

Transportation

Hydrothermal processing

(Department for Business, Energy & Industrial Strategy, 2021)

Calculations: Typical maximum output per power plant per annual = 4.5MWe

Total running costs - £3.02Million for a net output of 4MWe

The gross output of circa 4.5 MWe will cost in the region of £12-13Million over a period of 15 years with an additional initial £4-5Million for installation.

The fuel needed for 30% wet waste wood paper and card will be 5-6 tonnes per hour or 45,000 tones per year.

Annual cost = £12-13Million/15 = £800,000-£860,000 1000kw x 4.5MW = 4500kw Cost of the power plant to be functional: staffing to operate the plant = 6+ people at £200,000 maximum required for spare parts and consumables the plant need = £500,000

174

Renewable Energy Generation

Power output for a 2MW produced by Waste wood, reclaimed contaminated wood, and card fuel = £4000/MW with an efficiency rate of 20% Power output for a 20MW (2 Bioenergy plants) produced by Waste wood, reclaimed contaminated wood, and card fuel = £3500/ MW with an efficiency rate of 21% Power output for a 2MW produced by Forest Wood Fuel = £3500/MW with an efficiency rate of 23%

Biochemical conversion

Liquification

Hydrogen Methane Oils

Pyrolysis

Hydrogen Olefins Oil Bioethanol, Biodeisel, Biobutoanol Methane, Speciality chemicals

Bioenergy System

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Geothermal Energy Technologies, Cost and Efficiencies

Geothermal power plants can potentially produce up to

2 TW

£1.4 -4M

to install a 1MW Capacity geothermal plant

Currently, there are no deep geothermal power plants in the UK. However is one geothermal heat-generating station in Southampton that utilises heat from an aquifer under Wessex. Geothermal power is created from accessing the heat beneath the earth’s surface. Geothermal resources are classified by compositional and thermal features such as geothermal fluid temperature/enthalpy (Dincer and Ezzat, 2018). Geothermal is a great source of power as geothermal heat is always available.

Technologies/Resources:

Electricity production requires temperatures over

150 C o

(Dincer and Ezatt, 2018)

• Geothermal energy has a massive potential: 0.035 - 2 TW. • Geothermal reservoirs are natural and can easily be replenished • Geothermal plants produce significantly less emissions than fossil fuels. • Stable source as the power output can be predicted with great accuracy.

Energy Types

• Can be used for heating and cooling. Renewable and non-renewable systems

• Magma bodies. • Conductive sedimentary. • Hydrothermal convective. • Geopressured.

(Hyder, 2020)

Advantages:

• Radiogenic resources • Enhanced geothermal systems (EGSs): Aritficial geothermal rervoirs for energy generation (Dincer and Ezzat, 2018). • Organic Rankine Cycle (ORC): A suitable technology for geopower systems that converts low-median grade waste heat into electricity (Liu et.al, 2021).

Disadvantages:

The n o n - r e n e w a b l e e n e r g y s y s t e m s ha v e been a consistent factor in the increase of GHG prompting plants emissions, may release quick action to reduce the theirgreenhouse uses. (UK Energy Statistics,

Map of Geothermal Generation Plants in the World (Source Author) Calculations

• Geothermal some of gases below 2019) the earth’s surface. However, pollution from geothermal power is considerably lower than from fossil fuels.

• District Heating

(Hyder, 2020)

OIL & GAS

Surface Costs = $762/kW - $1192/kW (US Currency) = £567.70/kW - £888.06/kW (UK Currency conversion 2021)

• It is location specific and is difficult to access.

• Geothermal Heat Pumps (GHP)

(US Currency)

The costs of a geothermal power plant that has £835.91/kW – £1484.07/kW produces an output power ranging between (UK Currency conversion) 40.8 % 20-60MW annually are:

• It is expensive to WIND build as total installation costs 1.8 - 4 million 20.8% pounds for a 1MW capacity.

• Construction can affect the stability of the land and earthquakes can be triggered.

SOLAR 4.1%

NUCLEAR Total cost in a known field = BIOMASS $1062/kW –$1692/kW 16 % (US Currency) 6% £791.21/kW –£ 1260.57/kW (UK Currency conversion)

Renewable Energy Generation

The average yield of a typical 1500m well is 1.5×(3.4±1.4)=(5.1±2.1) MW, and the cost per MW is 1.5/(5.1±2.1)=$0.29 (+0.21/−0.09) million or £0.22 Million The likely cost per MW produced by the power COAL plant is £220,000

2.8% HYDROThis falls within the average estimated maximum ELECTRIC and minimum yield costs of producing 1MW 4.2%and £370,000 between £150,000

GEOTHERMAL

5.3%

Total cost in an unknown field = $1122/kW –$1992/kW

176

Data from Thory (2021).

Of total UK energy generation

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Geothermal Energy System Process & Calculations

Geothermal System Process: The site must be determined based on the amount of fluid (reservoirs), heat, and permeability of the land. Once determined, drilling occurs ta few miles deep to pump steam or hot water to the surface. The steam turns a turbine, connected to a generator which produces electricity. Some GHG are released during this process. CO2 is also emitted from the manufacturing of drilling equipment and construction of geothermal power plants (Save on Energy, 2020). Dry-steam power plants use pressurised dry or superheated steam from reservoirs. The steam from those reservoirs contain a small amount of CO2. The steam turns a turbine which powers the generator and produces electricity.

WIND ENERGY

SOLAR ENERGY

GEOTHERMAL ENERGY

Wind energy has a very low cost compared to the electricity it is capable of generating making its efﬁciency high.

Usage of Solar Energy heavily reduces the amount of emissions produced and directly reduces the pressure on the grid

Geothermal energy does not require fuel and it is one of the most environmentally sustainable methods

Flash-steam plants have a supplementary flashing process which produces additional steam to operate another turbine, hence generating additional Energy power. Energy 65% Output

Energy Output

Output

Binary Cycle plants utilise most resources in medium and high temperature Energy Energy classifications as low as 73o C.82% These plants Efﬁciency utilise ORC technology and Efﬁciency recover heat from geothermal water using heat exchangers to evaporate Energy Energy organic fluid. 23% Emissions

(Dincer Energy and Ezzat, 2018). Process

72%

H e s

Energy Efﬁciency

Emissions

Energy Emissions

Energy Process

Geothermal Energy Efficiency Rating. (Source: Author) Ground Water heating Pump

Heating Pump Conventional Geothermal Systems

LowTemperature

Naturally Naturally Occuring Occuring Fluid, Fluid,Heat Heatand and permeability permeability

Earth/ Ground

Engineered Fluid, Heat and/or permeability

Water

Dry Steam Power Plant

Hydrothermal fluids (primarily steam)

Flash Steam Power Plant

Fluid > 182°C pumped

Flash Tank

Fluid < 204°C geothermal fluid

Heat Exchanger

Binary Cycle Power Plant

Turbine

Water vapour

Use

Generator

HighTemperature

Excess Liquid

closed-loop system Water Vapour Enhanced Geothermal Systems

178

Ground-coupled heat exchange

Renewable Energy Generation

Deep acquifer

Cooling System

Geothermal System

Electricity Network

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Hydroelectric Energy Technologies, Cost and Efficiencies

The UK has a total hydropower installed capacity of over

4,700 MW

(hydropower.org, 2019)

UK is the global leader in marine ebnergy

The

(Scottish Renewables, 2019)

The UK currently generates 4.2% of electricity from hydroelectric schemes. Hydroelectricity is generated by the flow of water turning a turbine. Water sources can be natural or man-made installations. Opportunities for large-scale use of hydropower is limited due to most economically attractive sites being already in use (Government, 2021).

Two reservoirs are used. During low demand, electricity is used to pump water to the upper basin. The water is alter released when demand is higher. This scheme is not renewable because of its reliance on electricity, however, it is useful to improve overall energy efficiency (UK Government, 2021). (UK Government, 2021)

Applications: Large-scale capacity: producing over 5 MW.

Pumped Storage:

Hydro

plant

Small-scale capacity: Hydro producing less than 5 MW.

plant

Micro-scale capacity: Hydro plant producing less than 50 kW. (UK Government, 2021)

Technologies:

• Low emissions as it is a clean power source. • Reservoirs created can be used or recreation purposes.

Electricity is generated from a dam which impounds water in a reservoir. Turbines and generators are usually located within the dam itself.

• Potential for drought. • Can impact water quality and flow which is harmful to riparian habitats. • Fish populations impacted.

The n o n - r e n e w a b l e Generation Sources in the UK (Source e n eMap r g y s of y s t eHydroelectric m s ha v e been a consistent factor in the increase of GHG emissions, prompting quick action to reduce Many of the UK’sStatistics, hydropower is generated in Scotland (UK Energy their uses.

Author)

and2019)Wales in hydroelectric power plants. These often are located within reservoirs and dams in the highlands and countrysides. The UK also generated hydropower in the sea (marine energy). The UK is a global leader in marine energy (Scottish Renewables, 2019).

Disadvantages: • Expensive to build.

Electricity is generated using the natural flow of the river. This scheme alongside storage schemes can be diversion schemes that channel water to a remote powerhouse which contains the turbine and generator.

Renewable and non-renewable systems

• Renewable.

Storage Schemes:

Run-of-river Schemes:

Energy Types

Advantages:

can

(U.S. Department of Energy, 2021)

Data from Thory (2021).

OIL & GAS 40.8 %

WIND 20.8% NUCLEAR SOLAR 4.1%

16 %

BIOMASS 6%

COA 2.8

HYDROELECTRIC 4.2%

Of total UK energy generation

180

Renewable Energy Generation

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Hydroelectric Energy

Where

amount per day as follows:

P = Mechnical `power in kW Q = flow rate in the pipe (m3/s)

System Process & Calculations

22000/365 = 60.3kWh per day

ρ = density of water (kg/m3) g = Acceleration of gravity (m/s²)

The cost of electricity per annum averages to £38000 thus one can conclude that the amount per day:

H = waterfall height (m) Hydroelectric System Process:

η = global efficiency ratio (usually between 0,7 and 0,9

Materials are required to harvest energy from water. For example, a dam, turbine and generator will need to be manufactured, built and installed on-site before electricity can be generated. These materials and components will be transported to site which adds to the carbon footprint of this technology. Independent of the type of hydroelectric scheme used, the principles to generate energy remain the same. The kinetic energy of flowing water pushes a turbine which generates electricity. A transformer increases the voltage to be transmitted via the national grid and to the consumer. Calculations: The hydroelectric power generation process varies as it s output relies on the scale of the setup and intended final yield.

Thus:

0.125m and area 0.0123m2, and a fall height of 2m can produce power using an equation as follows: P=QxρxgxHxη

P = 0.34 x 1000 x 9.81 x 2 x 0.9

Assuming 60.3kWh is worth £104.10, then a single kWh of hydroelectric power could be worth:

P= 6003.7W / 1000 = 6.04kW

104.10/60.3 = £1.72

With larger hydroelectric power schemes, such as one with a 100kWh turbine, a flow rate of 0.136m3/s a pipe with diameter 0.56m and area 0.2463m2, and a fall height of 100m can produce power as follows:

Granted the amount of hydroelectricity produced within the UK accounts for approximately 2%-12% of the current electricity demand (Wave and tidal energy: part of the UK’s energy mix - GOV.UK, n.d.), this ranges between 2530GWh. The cost in return can be estimated as follows:

P = 0.136 x 1000 x 9.81 x 100 x 0.9

(Hydropower Head and Flow - Renewables First, n.d.) (hydroelectricity power and energy calculator - free online, n.d.)Using a 5kWh turbine, a river with a flow rate of 0.34m3/s and a pipe with diameter

38000/365 = £104.10 per day of kWh produced

£1.72 x 25000000 = £43,000,000

P= 120,074.4W / 1000 = 120.07kW If the amount of electricity produced by a 5kWh hydroelectric system throughout the year can be approximated as 22000kwh/year, then one can calculate the produced

£1.72 x 30000000 = £51,600,000

Dams

Water Flow

Turbine

Sun Water Tidal Bridges

Water Wave Power

182

Renewable Energy Generation

Generator

WIND ENERGY

SOLAR ENERGY

GEOTHERMAL ENERGY

HYDRO POWER ENERGY

Wind energy has a very low cost compared to the electricity it is capable of generating making its efﬁciency high.

Usage of Solar Energy heavily reduces the amount of emissions produced and directly reduces the pressure on the grid

Geothermal energy does not require fuel and it is one of the most environmentally sustainable methods

Hydropower provides more than just energy. It can control ﬂoods, irrigation support and clean drinking water

Energy Output

Transformer

Power House

Use

Grid

65%

Energy Output

79%

Energy Efﬁciency

82%

Energy Efﬁciency

43%

Energy Emissions

23%

Energy Emissions

35%

Energy Process

72%

Energy Process

50%

Hydroelectric System

Hydropower Energy Efficiency Rating. (Source: Author)

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Wind Energy Technologies, Cost and Efficiencies

Wind power is one of the fastest-growing renewable energy technologies.

The use of wind energy is continually increasing across the world due to the fall in costs. In the UK, wind makes up 20.8% of electricity generation - an increase of 715% since 2009 (Office for National Statistics, 2021). Applications

Advantages: • Renewable and clean energy source

(International Renewable Energy Agency, 2021)

Onshore Wind: Turbines are based on land. They range in size from 100kW to multiple megawatts. Groups of larger turbines make up wind plants taht power the electrical grid.

• Low operating costs

• Uses small amounts of water

The UK has the

Offshore Wind: Turbines are much larger than onshore wind turbines. These turbines capture ocean winds which generated large amounts of energy.

largest offshore wind farm in the world

Distributed Wind: Turbines installed directly for consumers or near the place of energy consumption are called distributed wind. (Office of Energy Efficiency Renewable Energy, 2021)

and

• Creates jobs • ‘Fuel’ is free

• Can function in dry areas • Requires less land than other energy types

Disadvantages: • Noise Pollution • Visual Pollution

(Terra, 2021) Technologies:

• Affected by weather conditions

Turbine: convert energy from the wind into electrical energy. The aerodynamic force propels rotor blades, connected to a generator which, in turn, generates electricity (Office of Energy Efficiency and Renewable Energy, 2021).

• Initial costs are expensive (LetsBuild, 2021)

Map of Wind Generation Plants in the UK (Source Author)

Data from Thory (2021).

There are over 41 operational offshore plants and 176 onshore wind plants in the UK. Manchester has multiple wind farms in close proximity, for example Scout Moor Wind Farm in Rochdale (Department for Business, Energy & Industrial Strategy, 2021b). Greater Manchester plans reveal that 9% of electricity demand could be met from its own renewable sources (The Energy Technologies Institute and Energy Systems Catapult, 2021).

WIND 20.8%

Of total UK energy generation.

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Renewable Energy Generation

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Wind Energy System Process & Calculations

UK is the windiest place in Europe

The

(Gov. UK, 2019)

Calculations:

hourly usable electricity supply:

Wind Generation Data:

10.96

Rotor Diameter: 11.5m

Rotor Area : 103.87m2

=0.4567kWh per hour

Air Density: 1.23kg/m3

Cost per Hour Usage:

Wind System Process:

Wind Speed: 12.5m/s

Raw materials, such as steel, are collected for the manufacturing of turbines, which includes the rotor blades, generator and tower. The parts are prefabricated before being transported to site. Site selection is an important part of the process as the area needs to have relatively consistent wind speeds (over 25 km/h). The site itself also requires preparation, as the land is graded (onshore wind farms) and the pad area is levelled to allow for the laying of foundations and installation of the turbine itself . The turbine’s parts are prefabricated but assembled on site using a crane to position it. Once erected, electrical energy is generated and transmitted through the national grid. Each of these processes in the system contribute to the embodied carbon emissions.

Total losses: 50% Area of Single turbine site: 3.8m2

Assuming £0.055 is charged per 1kwh, then: 0.055 x 0.4567 / 1

Energy Hour Usage:

= £0.025 for 1 hour of usable electricity (0.4567kWh)

Assuming a 2-3MWh generates 6.0E+6 kWh for 1500

Therefore:

homes,

A single 2-3MW turbine provides a house with 0.4567kWh per hour usage at a cost of £0.025 per hour usage.

6000000 1500

However, a total of 9.3 kW is lost from generation to final

= 4000kWh per home p.a.

usage.

daily usable electric supply: 4000 365 =10.96 kWh

Raw Material Acquisition

Material Processing

Turbine Manufacturing

Transportation

Water CO2

186

CO2

Renewable Energy Generation

CO2

Site Selection and Installation

Sun Wind

Converter

Generator

Wind Energy System

Transformer

Grid

Use

CO2

187

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200

Wind Energy

System Process & Calculations

Maximum Power Output

Estimated Project Cost

£/kW Installed

25 kW

£169k

£6.8k

Wind Generation Data:

hourly usable electricity supply:

Rotor Diameter: 11.5m

10.96

50 kW

£300k

£6.0k

Rotor Area : 103.87m2

100 kW

£529k

£5.3k

250 kW

£963k

£3.8k

500 kW

£1.6M

£3.2k

Air Density: 1.23kg/m3 Wind Speed: 12.5m/s

=0.4567kWh per hour

Total losses: 50% Area of Single turbine site: 3.8m2

Cost per Hour Usage:

Energy Hour Usage:

Assuming £0.055 is charged per 1kwh, then:

Assuming a 2-3MWh generates 6.0E+6 kWh for 1500 homes, 6000000

0.055 x 0.4567 / 1

(0.4567kWh)

Therefore: A single 2-3MW turbine provides a house

daily usable electric supply: 4000

£ / kW i

800

Estimat

= £0.025 for 1 hour of usable electricity

1500 = 4000kWh per home p.a.

1000

Maximu

600 400 200

with 0.4567kWh per hour usage at a cost of £0.025 per hour usage.

0 1000

365 =10.96 kWh

£ / kW installed

800

However, a total of 9.3 kW is lost from generation to final usage.

Estimated Project Cost k £ Maximum Power Output kW

600

Wind Energy System Maximum Power Output

400 200

Estimated Project Cost

£/kW Installed

£169k

£6.8k

25 kW

50 kW

188

Renewable Energy Generation

100 kW 250 kW

Maximum Power Output

25 kW 50 kW

100 kW 250 kW 500 kW

Estimated Project Cost

£/kW Installed

£169k

£6.8k

£300k

£6.0k

£529k

£5.3k

£963k

£3.8k

£1.6M

£3.2k

£300k £529k £963k

£6.0k £5.3k £3.8k

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Wind Energy System Process & Calculations

Wind power is one of the fastest-growing renewable energy technologies. (International Renewable Energy Agency, 2021)

Calculations:

hourly usable electricity supply:

Wind Generation Data:

10.96

Rotor Diameter: 11.5m Rotor Area : 103.87m2

=0.4567kWh per hour

Air Density: 1.23kg/m3

Cost per Hour Usage:

Electricity Generation Equations

Wind Speed: 12.5m/s

Power Plant Emissions Calculations

Total losses: 50% Area of Single turbine site: 3.8m2 Energy Hour Usage:

Baseline Electricity Emissions Calculations

largest offshore wind farm in the world

1500 homes,

1500 = 4000kWh per home p.a. daily usable electric supply: 4000 Emissions Reduction

365 =10.96 kWh

(Terra, 2021)

Assuming £0.055 is charged per 1kwh, then: 0.055 x 0.4567 / 1 = £0.025 for 1 hour of usable electricity

Assuming a 2-3MWh generates 6.0E+6 kWh for (0.4567kWh)

6000000

The UK has the

Therefore: A single 2-3MW turbine provides a house with 0.4567kWh per hour usage at a cost of £0.025 per hour usage.

However, a total of 9.3 kW is lost from generation to final usage.

Assuming every square metre of the Northern Gateway is occupied by households and taking the above the calculation into account, one can then assume the Northern Gateway’s projected Carbon Emissions from households would be: 85500gC or 85.5kgC from the energy used and produced.

A 2-3MW turbine provides a house with:

0.4567 KWh Trends Electricity Production from DIfferent Energy Sources

190

Renewable Energy Generation

Territorial Trends Electricity Production from DIfferent Energy Sources UK

at £0.025 191

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Comparing Embodied CO2 Emissions Our Embodied Carbon Calculator

We created a

Creating the Embodied Carbon Calculator:

carbon emission calculator

Using the grasshopper software, we created a carbon emission calculator that considers the various sections within the life-cycle of each energy system (coal, oil, natural gas, nuclear, wind, solar, and biomass). This allows for a comparison of each energy type throughout its entire life-cycle. The data inputs were for the year 2019 as the data was more readily available and the 2020 pandemic created a few energy anomalies. However, the calculator does allow for other data to be used. The emissions were calculated in kilotonnes of CO2 per year for an average power plant.

that considers the various sections within the

life-cycle

of each

energy system to calculate

embodied carbon emissions

For each section within the life-cycle of the energy system, the calculation methods varies slightly based on the available data.

Extraction relates to raw the materials used for fuel. For Oil and Gas, figures for drill rig machinery were used to calculate the emissions. Based on the diesel usage and hours used per year, assuming the entirety of oil and gas is imported from Norway, the emissions were calculated per average UK power plant. For nuclear and coal calculations, a similar process was followed using values from mining machinery. For Biomass, machinery for harvesting were used to

192

Manufacture: Manufacture looks at the processing and assembling of materials to create the technologies to produce energy. For solar and wind this would require the materials and components required to produce solar panels and wind towers. For hydro, the production of dams or other water diversion techniques. For fossil fuels, this would include (in a detailed calculation) the emissions associated with the construction of the power plant. For renewables, a large

The process:

Extraction:

“The most important time to calculate embodied carbon is in the early design stages.”

calculate these values. Renewables do not have values for extraction as the fuel sources are natural.

Embodied Emissions Calculations

Embodied CO Earth/ Ground2 Emissions

Extraction of raw material Emissions

Machinery emissions

Manufacture Emissions

Machinery emissions

Individual elements production

Transportation Emissions

Imports: Vehicle Emissions

Local: Vehicle Emissions

Installation Emissions

Machinery emissions

Production Emissions (Used on works)

Machinery emissions

Generation Emissions (Conversion to electricity)

Combustion/ conversion emissions

Transmission Emissions (Transportation of electricity via grid)

Grid Line Emissions

Consumption Emissions (Residential Use)

Household appliance use emissions

End of Life Emissions (Deconstruction and Recycling)

Transport emissions

Installation (Kilotons CO2/year) Installation calculations pertain to the emissions emitted from installing energy technologies such as solar panels and wind farms. The process accounts for the preparation of site and installation of technologies.

Energy Life Cycle: (Source: [adapted from] Schroeder, E. (2017) Lifecycle Energy. [image] [Accessed on 17 November 2021] https://slipstreaminc.

Transport (Kilotons CO2/year) Transport includes the journeys from raw material extraction to manufacturing to production. The calculations are based on the amount of diesel used per journey, per year for each transport type. This includes various truck and ships for imported energy.

Machinery emissions

Material emissions

Waste proccessing & disposal

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Comparing Embodied CO2 Emissions Our Embodied Carbon Calculator

Nuclear, Solar and Wind release

kilotons/ CO2 per year, per power plant when converting to electricity Coal releases an average of

1598.5

kilotons/ CO2 per year, per power plant during combustion

Natural Gas releases an average of

884.8

kilotons/ CO2 per year, per power plant during combustion

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Production Emissions (Energy Used on works): To calculate production emissions, the energy used on works from one power plant in a year, for each energy type, was multiplied by the conversion efficiency of CO2 for electricity to convert it into carbon emissions in kgCO2/year. The value was then converted into Kilotonnes of CO2 per year, as the figures were quite large. Generation Calculations: The value of the amount of each fuel type needed to produce fuel for the year 2019 was used to calculate the emissions from the combustion or conversion from fuel to electricity process. The amount of fuel used was multiplied by the specific CO2 emission for its energy type to find the kilotonnes of CO2 per year for one power-plant. For the fossil fuels: coal, oil and natural gas, large emissions were produced through combustion as a large volume of fuel is required to convert into electricity. The conversion efficiency is relatively low and therefore larger amounts of these fuels are required to produce the same amount of energy than other fuels such as nuclear energy which can produce large amounts of electricity from small quantities of fuel. Nuclear energy does not produce CO2 emissions at the energy generation process as carbon is not a by-product of the fission process. This makes nuclear energy a useful generation source. If other elements of the nuclear system were decarbonised, nuclear energy would be

Embodied Emissions Calculations

a great substitute for coal, oil and gas. Hydropower releases carbon trapped in the water as it converts to energy, however this value is much lower than the emissions for coal, natural gas, and oil. For other renewables such as solar and wind energy, no carbon emissions are produced at this stage. Bioenergy, however, produces a considerable amount of carbon emissions through its combustion process (more than coal and natural gas). Despite this, these figures are not added to the total embodied energy calculations ‘as long as the burned biomass doesn’t exceed the renewed production (within a reasonable time), or it is not transformed in processes requiring CO2-forming energy’ (Department for Business, Energy & Industrial Strategy, 2021). Consumption: This considers how much emissions are produced from the use of electricity by the user. The calculator can be expanded to allow for calculations based on specific typologies and sector types to find average emissions. End of Life Calculations: End of life calculations include the emissions from de-construction and demolition, transport and disposal or recycling of materials.

Embodied CO Earth/ Ground2 Emissions

Extraction of raw material Emissions

Machinery emissions

Manufacture Emissions

Machinery emissions

Individual elements production

Transportation Emissions

Imports: Vehicle Emissions

Local: Vehicle Emissions

Installation Emissions

Machinery emissions

Production Emissions (Used on works)

Machinery emissions

Generation Emissions (Conversion to electricity)

Combustion/ conversion emissions

Transmission Emissions (Transportation of electricity via grid)

Grid Line Emissions

Consumption Emissions (Residential Use)

Household appliance use emissions

End of Life Emissions (Deconstruction and Recycling)

Transport emissions

Machinery emissions

Material emissions

Waste proccessing & disposal

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Transmission Energy in Greater Manchester

The National Grid network is made of highvoltage power lines, gas pipelines, inter-connectors and storage facilities that together enable the distribution of electricity. The UK largely relies on the National Power grid as its primary conduit for the different forms of energy. Using Distribution network operators, electricity is fed into individual homes. The grid’s span all across Britain is made up of high voltage electricity wires that extend across Britain and nearby offshore waters. Transmission is carried out at a number of voltages; 400kV, 275kV and 132kV. The grid is run by a single system operator who oversees the distribution network operators that feed the electricity into individual homes. Where heating is still largely dependant on gas, demand in homes is affected by the materiality, age of the building and the density of the population occupying the home. In the process of electricity generation, energy is lost from stage to stage via heat, sound and leakages. The need to compensate for these losses has increased as the city has grown resulting in

energy being produced in surplus. It is estimated that the demand for electricity will double within the next 30 years causing one to conclude that the emissions associated will increase as a result. Considering the main parts of a typical transmission and distribution network, Average power loss can be viewed as follows: 1-2% – Step-up transformer from generator to Transmission line 2-4% – Transmission line 1-2% – Step-down transformer Transmission line to Distribution network cables

from

4-6% – Distribution network transformers and

The overall losses between the power plant and consumers is then in the range between 8 and 15%

The chart shows the transmission of energy in GWh within Greater Manchester. Source:

“Demand for electricity is set to double within the next 30 years in Manchester” The table shows the transmission of energy in different sectors within Greater Manchester. Source:

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Transmission

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Transmission

The criteria in which the statement can be fully fleshed out and calculations determined are as follows:

Energy in Greater Manchester - Calculating Transmission Losses The National Grid network is made of high-voltage power lines, gas pipelines, inter-connectors and storage facilities that together enable the distribution of electricity. The UK largely relies on the National Power grid as its primary conduit for the different forms of energy. The network’s breakup through various points allows for the storage and transformation of energy to the appropriate forms. However, due to indirect transmission through various points, there is a loss of energy from point to point before it arrives at the final point of consumption.

The calculation of this energy loss in transmission can be calculated in two ways: 1) GROSS ELECTRICITY GENERATED GROSS ELECTRICITY CONSUMED = TRANSMISSION LOSS This allows one to understand the larger amounts of energy in between the two points on a larger scale and calculate the approximate amount needed to supplement the present amount or the amount that can be diverted elsewhere. Conversely, the following equation allows us to understand the individual losses to a more accurate extent.

2) GROSS ELECTRICITY GENERATED GROSS ELECTRICITY CONSUMED = TRANSMISSION LOSS where energy present at point A energy present at point B

• Population Density • Building age (materiality, energy type used) • Type of energy used (renewable, non renewable sources) • Area serviced (large, small, densely populated, sparsely populated, many pylons/few etc.) These parameters act as a starting point for understanding the individual factors that may increase or decrease the energy supply to the various areas of the city. This therefore aids in calculating and forming a more complete picture of the electrical energy requirements of development necessary at the Northern Gateway. Indirect

interval transmission loss

The map shows the electrical distribution of substations. As the grid’s density increases in areas towards the city centre one can conclude that the losses in the dense areas materialise as increased temperature in these areas thus affecting energy supply to compensate via cooling (therefore increased Carbon footprint). Source: GMCA Spatial energy Plan

Emissions

Non-renewable

Direct

GROSS ELECTRICITY GENERATED

Emissions

Dense

Indirect

GROSS ELECTRICITY GENERATED

Emissions

TRANSMISSION LOSS

Renewable

Population

Direct Emissions

Non-renewable Indirect Emissions

Sparse

Direct Emissions

GROSS ELECTRICITY CONSUMED

Renewable Indirect Emissions

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Transmission

GROSS ELECTRICITY CONSUMED

Direct Emissions

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Emission and Reduction Overview

This section provides a detailed overview and examinations of the distribution of total direct and indirect as well as embodied emissions by households in the United Kingdom, as well as the factors including the technologies that influence them. Whilst previous research has looked at how households distribute direct emissions, such as those from domestic fuel and electricity, this goes on further to look at how indirect emissions are embodied in food, consumer goods, and services, including imports and how that may affect the total emissions produced in the UK and more locally within Manchester.

In terms of emissions, Net zero is identified as that the UK’s total greenhouse gas (GHG) emissions would be equal to or less than the emissions the UK removed from the environment during the same time.’

The UK government has been consistently analysing the trends of emissions produced within the UK. As such they have provided records of the latest estimates of 1990-2019 UK territorial greenhouse gas emissions, meaning emissions that occur within the UK’s borders, as well as predictions to 2050 and beyond. The emissions cover the Kyoto “basket” of seven greenhouse gases: carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFC), perfluorocarbons (PFC), sulphur hexafluoride (SF6) and nitrogen trifluoride (NF3).

In making the amendment to the Act, the UK became the first government to set a net zero GHG emissions target. Several other countries and subnational bodies soon followed. Net zero is a now a centre-stage idea in climate action by governments, corporations, and citizens

Cons of Emission

Pros of Reduction

•Negative impact on the climate

• Air Quality

Setting off more emissions will speed up the pace of the climate change endangering habitats and people.

Air quality will improve and result in an across-the-board increase in the health of the people and the environment

• Health problems

• Economic Growth

According to the NHS, the majority of all respiratory issues can be traced back to air pollution from GHG emissions.

Clean, green energy is more appealing from an economic standpoint than ever before, with a 19-44% difference in price between new natural gas generation as opposed to new coal generation in the UK.

• Changes in Food Supply Carbon emissions contribute to increasing temperatures and decreasing precipitation, changing the growing conditions for food crops in many areas.

• Slowed Climate Change The overall slowed climate change and environmentally beneficial practices that will be implemented.

Worsening Environment Residential Fail to reach 2038 goal

High Industrial

More Waste

Emissions

“Private Transport in 2019 produced the largest GH emissions at 27%” 200

Emission and Reduction

Better Environment

Reach 2038 goal

Low

Less Waste

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Emission and Reduction

Household emissions by emissions type and sector (2019)

Household emissions

In 2019, 27% of net greenhouse gas emissions in the UK were estimated to be from the transport sector, 21% from energy supply, 17% from business, 15% from the residential sector and 10% from agriculture. The other 10% was attributable to the remaining sectors: waste management, industrial processes, the public sector and the land use, land use change and forestry (LULUCF) sector. The LULUCF sector includes both sinks and sources of emissions.They aim to achieve this by shifting away from types of energy and highlight the use of others such as gas and electricity respectfully. According to the Greater Manchester Spatial Energy Plan, Greater Manchester is responsible for 3% (51.6TWh/year) of the UK’s total energy consumption with Manchester being the highest consumer and Oldham being the lowest consumer in Greater Mancheter. (Energy Systems Catapult, 2016) With 95% of the buildings in the county consuming gasas the primary energy type for heating, the systematic prioritisation of electricity should aid in lowering the CO2 emissions associated with the type of energy.

202

The highest emitting sector - the transport sector consists of emissions from road transport, railways, domestic aviation, shipping, fishing and aircraft support vehicles. It is estimated to have been responsible for around 27% of greenhouse gas emissions in the UK in 2019, almost entirely through carbon dioxide emissions. The main source of emissions from this sector is the use of petrol and diesel in road transport. Transport emissions fell by 2% between 2018 and 2019, despite an increase in road traffic. The transport sector had historically been the second most emitting sector; however, reductions over time in what was the largest sector (energy supply) mean that since 2016 transport has been the sector with the highest emissions.

“Between 2018 and 2019, CO2 emissions decreased in 360 out of the 379 local authorities (95%)” in the UK” Emission and Reduction

Indirect emissions in the UK was the biggest type of GHG emissions by contributing to almost %80 of total emissions. Most of which stemmed from Domestic Energy and Housing sector as well as the biggest contributor, the Transport Sector. (Source: )

End-user carbon dioxide emissions and carbon dioxide emissions per km2 by region, 2005 and 2019

The South East had the largest total emissions per year in 2019 standing at 41 MtCO2 with the North West being a close second at 39MtCO2. This was mainly attributed to the large population density, transportation amd major construction works. (Source: )

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Emission and Reduction

Greenhouse Gas Emissions

GHG emissions and consumptions of energy

UK is on track to meet its 2050 carbon neutral goals

Between 1990 and 2019, there has been relatively little overall change in the level of greenhouse gas emissions from the transport sector. Between 1990 and 2007 (when emissions peaked) there was a general increasing trend, with some fluctuations year to year. After this peak, emissions declined each year until 2013, at which point this trend reversed to show small increases most years. The overall effect of these fluctuations over time means emissions are estimated to have been around 5% lower in 2019 than in 1990. Emissions from transport fell by 1.8% (2.2 MtCO2e) in 2019, their second year of falls having previously risen since 2013. Despite this transport remains the largest emitting sector, responsible for 27% of all greenhouse gas emissions in the UK. Transport emissions are only 4.6% lower than in 1990, as increased road traffic has largely offset improvements in vehicle fuel efficiency.

The decrease in greenhouse gas emissions from 2018 was mainly caused by reductions in emissions in the energy supply sector, down 8.1% (8.4 MtCO2e). This was driven by the continued decrease in power station emissions due to the change in the fuel mix for electricity generation, in particular a reduction in the use of coal. Emissions from energy supply are now 65.5% lower than they were in 1990. There was an 8% fall in emissions from the energy supply sector between 2018 and 2019, meaning that between 1990 and 2019 they have reduced by 66%. This decrease has resulted mainly from changes in the mix of fuels being used for electricity generation, including the growth of renewables; together with greater efficiency resulting from improvements in technology. The energy supply sector had historically been the sector with the largest emissions. However, these reductions mean that since 2016 it has been the second largest sector (the largest being transport).

“Demand for electricity is set to double within the next 30 years in Manchester” 204

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A trend of the total greenhouse gas emissions produced since 2015 with estimation till 2050 (Source: McKay Carbon Calculator Department of BEIS, 2021)

Primary Energy Consumption

A trend of the primary energy consumption since 2015 with estimation till 2050 (Source: McKay Carbon Calculator Department of BEIS, 2021)

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Energy use precedent Hammarby Sjöstad, Stockholm, Sweden

Hammarby Sjöstad is one of Stockholm’s inner residential districts and one of the world’s most successful urban renewal districts. The district’s urban renewal is known as the Hammarby urban redevelopment strategy or The Hammarby Model” and it is a project aiming to provide housing for 25,000 people. One of the main aims of the project is to become twice as sustainable than the Swedish Best Practice in 1995, and the city authorities heavily invested in green public spaces and public transportation systems. The district’s land policy encourages people to cycle and walk rather than use vehicle transportation, and it has done so by heavily subsidising public transport, cycling as well as it has heavily invested in pedestrianizing routes within the district, hence the significant reduction in GHG. By 2016, when the second and final phase of the building activities was completed, it became home to 25,000 people and offer work to another 10,000 people. The attractive mix of apartments, shops, offices and small traders with a focus on culture and entertainment gave Hammarby Sjöstad an inner-city atmosphere, ridding itself of its past stigma of having been a heavily industrialised and polluted inner-city district.

District heating is the primary source of heat in Hammarby Sjöstad. Purified wastewater, combustible household garbage, and biofuel account for 34%, 47%, and 16% respectively, of the heating produced by the district (2002 figures). The residual cold water can be used for district cooling once the heat has been taken from the warm, purified wastewater. This is utilised in cold storage in grocery stores, as well as in office buildings to replace energy-intensive air conditioning systems. This system of recycling cooling heating using the buildings within the district contribute heavily to the self-sustaining mechanism that the district follows, making it one of the most energy conserving and sustainable districts in the world. (urbangreenbluegrids, 2016) The town’s current environmental and energy goals refer to the annual sum of all energy purchased to heat and operate its public buildings. These include: - District heating connection with exhaust air systems: 100, of which 20 kWh electricity/m2 UFA. [Hammarby Sjöstad, 2012] - District heating connection with heat extraction systems: 80, of which 25 kWh electricity/m2 UFA. [Hammarby Sjöstad, 2012]

“The entire heating supply of Hammarby is derived from waste energy or renewable energy sources” 206

Executive Summary

The district is the result of a successful collaboration between municipal officials, urban planners, developers, architects, landscape architects, eco-tech engineers, energy companies, and the Stockholm Water Company. (Source: Stockholm City Planning Administration, 2016)

Within the district, GlashusEtt, an environmental centre, has been established to provide locals with information and education on all elements of sustainable urban design, as well as to urge residents to live a more sustainable lifestyle. (Sources: GlashusEtt, 2007, City of Stockholm, 2012)

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Energy use precedent Hammarby Model of Hammarby, Sjöstad, Stockholm, Sweden

The Hammarby Closed Loop System Model. The model overviews all the connections between the several energy systems and renewable mechanisms used within the Hammarby district, ultimately allowing it to be a self-susustaining district and a closed loop system. The Hammarby model is particularly innovative as it loops and cascades resource flows. This is a closed cyclical urban metabolism system where wastes are recycled if possible. The model aims at optimizing the use of resources through multi-functionality, renewable energy, recycling and reducing waste. The goal is to increase the self-sufficiency of the area using innovative eco-technologies. (Source: digitalcommons.calpoly.edu)

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Executive Summary Energy and Victoria North This chapter aims at identifying the major ways energy is produced both globally and within the UK. These identifications comes in the form of a thorough research of the energy systems, their sub-systems, processes of energy production and the emissions produced. In order to reach the conclusions of each energy systems, a comprehensive quantitative tool is developed to calculate all the elements that can contribute to the energy systems for both energy output and energy costings; beginning with the extraction of raw materials to the commissioning and usage by the end user. Then all of that is used to determine the most efficient and best energy system that could be integrated into Victoria North.

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Proposing the usage of renewable energy systems in Victoria North will allow the production of large amounts of electricity with far less emissions. Examples of Energy systems include Wind energy for its low cost and high efficiency, solar energy for its drastically reduced emissions and less reliance on the grid and geothermal energy for its low emission output due to its independence from fuel.

One of the ways to improve the methods of obtaining sustainable energy is by investing into having energy systems dedicated to Victoria North such Solar Panels and Biomass energy generators. This will help Victoria North to become a closed loop system similar to that as the Hammarby model, allowing it to ultimately optimise and reuse its own localised resources, and become a selfsustaining system.

As Victoria North is mostly undergoing development to accommodate sustainable approaches to obtaining and utilising energy. This will not only reduce local emissions but will improve many other local aspects such the air quality, the habitats and the population’s health.

This will have the advantages of costing the local council less in the long term as well as create sustainable and green energy precedent within Manchester and the UK. A very important move towards the Manchester’s 2038 Zero Carbon initiative goals.

1 There are two types of energy sources; renewable and non-renewable. Non-renwable energy cause the most harm and the most emisssons globally.

2 This is proven using trends, statistcs and quantitative methods to present in detail each energy systems' generation, costs, emissions, transmission and reduction.

3 The energy systems are explored locally in Manchester and Victoria North and the most efficient application of the energy systems are strengthened by the Hammarby precedent.

The locations of and links of the energy systems in Manchester. (Source: Author)

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Understanding the complexity of human behaviour to reduce household carbon footprint and investigating strategies to promote the collective pursuit of low carbon living.

INTRODUCTION What is '0' carbon living?

SECTION ONE

SECTION TWO

SECTION THREE

Context

Data research, analysis and calculation

Carbon saving solutions

CONCLUSION Summary

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SOCIAL TRANSFORMATION INTO LOW CARBON LIVING

King Yi Wong, Hsuan-Fang Chen, Wendell Lu

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Zero Carbon Cities

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cc t essibili

ers

e Hous

rgy Sharin

nectivi

“How To Live A Greener Life?”

Low Carbon

unal Sp

Image Top: WHITE GUM VALLEY LOW CARBON COMMUNITY Source: DevelopmentWA

In many emerging and matured cities, significant improvement in living standards and lifestyles had resulted in disproportionate increase in household energy consumption. To achieve global carbon reduction targets, household carbon emissions (HCEs) have to be reduced. On an aggregate level, compliance with the 1.5oC goal of Paris Agreement will require reduction in HCEs to a per capita lifestyle carbon footprint of around 2 to 2.5 tons of CO2e by 2030. The European Long-term Strategic Vision for climate-neutral economy emphasizes that “the transformation towards a net-zero greenhouse gas economy happen is not just about

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technologies and jobs but about people and their daily lives, about the way Europeans work, transport themselves and live together,” and “personal lifestyle choices can make a real difference, while improving quality of life.” (Koide et al., 2019) Due to the diverse nature of consumer lifestyles and underlying social factors varied across different countries, the carbon footprint of households can be examined from the perspective of lifestyles. From wider topic of designing for sustainable and low carbon living, the One Planet Living framework has been used by cities around the globe including Oxfordshire (UK), Saanich (Canada), Durban (South Africa), Tarusa (Russia), Elsinore (Denmark) and

Vila Mariana (Sao Paulo) to drive low carbon living. The White Gum Valley is the first development project in Western Australia designed using One Planet Living principles. The development priorities accessibility and is located within walking and cycling distance of local parks, art galleries, cafés, golf courses and the nearby Fremantle city centre. Green pedestrian walkways run through the centre of the village opening private streets and laneways to the surrounding area. The diversified housing typologies provide flexible space on the ground floor with additional living space or to support a home business.

ONE PLANET LIVING One Planet Living is a global movement to meet the challenges of resource competition and climate change. It is based on the idea to live sustainably within the limit of one planet’s natural resources. The principles of OPL include health and happiness, culture and community, local and sustainable food, zero waste and zero carbon energy.

10 PRINCIPLES OF ONE PLANET LIVING Health and happiness

Local and sustainable food

Equity and local economy

Travel and transport

Culture and community

Materials and products

Land and nature

Zero waste

Sustainable water

Zero carbon energy

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‘0’ Carbon Living Energy use, Low carbon behaviour

SOCIAL FACTORS INFLUENCING HCEs Many of the energy efficient policies in place usually target the improvement of building shell thermal performance, the installation of energy efficient appliances and the adoption of renewable energy. However, these measures do not provide a holistic approach as unpredictability of occupancy constitutes an important factor.

From the social physiology aspects, people’s web of actions are linked with meanings and the Why-How dimension will influence the likelihood of successful behaviour change. For example, convincing someone to turn their thermostat at a lower setting in winter will likely not be effective if the connected Why of creating a comfortable home is left unsatisfied.

From the social system perspective, household carbon emissions can be defined as “the emissions of an individual or their families in order to meet the demands of their existence and development under certain socio-economic conditions, which includes both direct and indirect emissions”. (Zhang et al., 2015)

The social system consisting of the building occupants are often ignored and not well understood. Previous study has shown that identical buildings can consume different levels of resources due to their occupants, which may not only own different appliances, but also likely to follow different routines and distinct behaviour patterns. New building technologies such as smart meters failed to reduce energy consumption as occupants are forced to shift their customary behaviours.

The second theory involves The IntrapersonalInterpersonal or ‘Who’ Dimension. People have strong inclination to take their cues about how to behave from others. The interpersonal factor shapes people’s thoughts, feelings and behaviours through social influence and changing old behaviours, especially from whom they feel connected (Masson & Fritsche 2014). A 2017 survey of the Australian population found that if people had higher household regulation, they tended to have greater participation in low carbon routines where members remind each other to engage in low carbon behaviour. Thus, collective pursuit of low carbon living can amplify the tendency for low carbon behaviour that requires changes in social norms.

Direct emissions are related to direct household fuel use, such as electricity, heating, gas and other liquids whereas indirect emissions are those occurred in the production and distribution processes of goods and services for households, such as during the manufacture of food, clothes, furniture and services.

Understanding the complexity of human behaviour through theoretical ideas from Behavioural Practices Theory (BPT) To understand social behavioural patterns of home energy consumption, we look at the concept of Home System of Practice emerged from the practice theory to focus on people’s everyday practices as opposed to behaviour, knowledge and attitudes.

As designers, we need to have a holistic understanding of the social system by focusing on human everyday practices as opposed to assumptions of occupants’ behaviours, knowledge and attitudes to enable a positive change in how people live.

Practice theory suggests that individuals do not use energy resources directly, but rather as instruments to achieve specific outcomes:

Diagram 1a: The home system complex: social, metabolic and physical systems Source: Eon et al. (2019)

Diagram 1b: Examples of behaviours connected along the Why-How Dimen sions Source: O’Brien et al. (2019)

The main factors influencing HCEs are household income, household size, age, education level, location, gender and rebound effects. Of these, the most factor contributing to a significant increase in carbon emission is household income as it has a considerable effect on spending on household-related activities such as food, transportation, recreation, education comfort, health and hygiene.

For example, it has been shown that shorter showers are associated with meanings such as cleanliness or refreshment thus less energy and water consumption, whereas longer showers are associated with meanings such as warmth and relaxation.

For example, in Ireland, direct emissions per person fall gradually as household income increases, whereas indirect emissions increase sharply with income (Lyons et al., 2012). In terms of UK household

Household heating expenditure in the UK also increases with household size and number of children in a household due to a rise in the number of rooms occupied. Studies in Ireland and China show that larger households have less indirect emissions than a one-person household, indicating per capita emissions to be generally lower for larger households. Although the use of new technology can improve household energy efficiency, human behavioural responses can offset the beneficial effects of the actual potential energy saving. For households, these are divided into direct and indirect rebound effects. Direct rebound effects are generated by the rising consumption of the, now cheaper, energy services such as heating or lighting, whereas indirect rebound effects stem from increased expenditure on other goods and services (e.g. food and clothing). In the UK, it is estimated the rebound effects for the combined three carbon reduction behaviours to be around 34%. The adverse effects may lead to increased overall energy consumption in the long term.

HOUSEHOLD CONSUMPTION EMISSIONS account for

GLOBAL GHG greenhouse gas emissions

Source: Emissions Gap Report 2020

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heating expenditure, there is an increase in the average age of household members as older people are more sensitive to indoor temperature. However, there is a downward trend when the average age of households reaches around 80 years.

30%

of UK's total carbon emissions

HOUSEHOLD SECTOR (residential, excluding transport)

T10

M40

mainly due to high household energy consumption Source: Palmer (2006)

Diagram 1c: Relationship between household income and carbon emissions Source: Palmer (2006)

Context

B50

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DEFINITION

STUDY OBJECTIVE

What are the differences between ‘Consumption-based Carbon Footprint’ and ‘Total Carbon Footprint’? There are two basic components of carbon footprint: direct and indirect (or ‘embedded’) emissions.

In this chapter, our study objective is to identify the carbon emission calculation associated with END-PURPOSE/ENDACTIVITIES, that is for which energy services are used.

‘Carbon emissions’ refers to a basket of six GHGs: carbon dioxide, methane, nitrous oxide, hydro-fluorocarbons, perfluorocarbons and sulphur hexafluoride. Embedded emissions that occur in the supply of products purchased by the UK households are attributed to UK households carbon emissions regardless whether they arise in the UK or overseas. The carbon footprint of food produced in Greater Manchester but exported beyond Greater Manchester’s boundaries are not included in this analysis.

DIRECT EMISSIONS

CONSUMPTION-BASED CARBON FOOTPRINT Emissions from Exported Goods and Services

2.1 MtCO2e

Emissions from Imported Goods and Services

The main focus of the study is on the consumption problem and human lifestyle: 1. Minimizing the impacts of climate change requires rapid transitions in people’s lifestyles and how we organize our societies, institutions and infrastructure.

2.1 MtCO2e Production-based Emissions

0.9 MtCO2e

1.2 MtCO2e Emissions from Household Use of Fuel and Electricity, Consumption of Goods and Services produced in the city

2. The importance of low carbon living in mitigating climate change as Ivanova et al. (2016) estimated Lifestyle and Consumption Emissions at 65 % of the global total; Hertwich and Peters (2009) suggested the proportion to be around 72 % of total emissions.

Estimated consumption-based carbon footprint for Manchester Source: Wendler et al. (2021) based on 2017 BEIS data and the consumptionbased footprint of the C40 cities

3. Understanding the distribution of lifestyle emissions among populations and by activities is important for equitable targeting of mitigation measures, in order to encourage reductions from households with high consumption emissions.

Est. 3.3 MtCO2e Consumption-based Emissions

Direct Fuel Use: Such as gas for space and hot water heating, electricity for powering lights, appliances and gadgets, fossil fuel for personal transportation

CARBON FOOTPRINT

INDIRECT EMISSIONS (EMBEDDED CARBON)

Supply Chain: Arose in the production and distribution of products and services purchased by households, such as GHG emissions embedded in food, clothing and vehicles

232

Context

“Consumption-based emissions reflect the consumption and lifestyle choices of a country’s citizens.”

Carbon footprint related to daily lifestyle is estimated using both the consumption amounts of human activities (measured in average expenditure data) and the carbon intensities of mobility, housing, food, goods and leisure based on consumer’s choices and time-use. The role of consumption is crucial in the context of carbon accounting (Wendler et al., 2021). Productionbased emissions (‘scope 1’) or emissions from energy generation (‘scope 2’)

are addressed in Manchester’s zero carbon budget. However, consumption in cities can affect the production of emissions outside of them as cities do not exist in a vacuum. Production and consumption-related emissions need to be considered in parallel as emissions are often ‘outsourced’. Therefore, Manchester has committed to the reduction of consumption-based carbon footprint alongside its productionrelated emissions and energy use in the Manchester Climate Change Framework 2020-25.

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Purpose-based HCEs Mapping consumption-based carbon footprint to purpose of activities Using the framework of Surrey Environmental Lifestyle Mapping (SELMA), RESOLVE calculated the carbon footprint for an average UK household according to purpose of activities. This was to explore a basis for untangling the complex interplay between the material, economic, psychological, sociological and cultural forces that drive the emissions that arise from UK household consumption.

While other footprint studies tend to analyse emissions according to COICOP (Classification of Individual Consumption According to Purpose), which gives no indication of the endpurpose for which these energy services are used, RESOLVE allocated emissions into high level functional use categories to shed more light on the drivers of carbon footprint as a whole without direct/embedded carbon emissions separated.

Study from RESOLVE showed that the carbon footprint by an average UK household is 26.1 tCO2e, with ‘Recreation & Leisure’, ‘Food & Catering’, and ‘Space Heating’ contributing the most. At simple level, it was concluded that approximately two thirds (66%; 17.2 tCO2e) of emissions are embedded emissions, with the remaining 34% being direct emissions.

SPACE HEATING 10%

HOUSEHOLD 11%

LEISURE & RECREATION (HOLIDAY) 10%

CLOTHING & FOOTWEAR 8%

FOOD & CATERING 24%

EDUCATION 2%

COICOP Category 1

Food & non-alcoholic beverages

Alcoholic beverages, tobacco, narcotics

Clothing & footwear

4.4.1

Electricity

4.4.2

Gas

4.4.3

Other fuels

4.1 - 4.3

Housing

Furnishings, household equipment &

CONVERSION FACTOR GHG INTENSITY PER UNIT POUND Existing Data 1

routine household maintenance

Health

7.2.2.1-2

Personal transport fuels

7 (Remainder) Other transport 8

Communication

Recreation & culture

Education

Restaurants & hotels

Miscellaneous goods & services

HOUSEHOLD FINAL CONSUMPTION EXPENDITURE ACCORDING TO COICOP Existing Data 2

LEISURE & RECREATION (NON-HOLIDAY) 17%

COMMUTING 5%

COMMUNICATION

The carbon footprint of an average UK household (2004): classified according to HIGH LEVEL FUNCTIONAL NEEDS CATEGORIES 1. RECREATION AND LEISURE Holidays Non- holiday recreation and leisure

CARBON FOOTPRINT ACCORDING TO COICOP SOCIAL & PSYCHOLOGICAL NEEDS SELMA Model CARBON FOOTPRINT ACCORDING TO HIGH LEVEL FUNCTIONAL NEEDS CATEGORIES

HEALTH & HYGIENE 9%

BASIC FUNCTIONAL NEEDS

SOCIAL NEEDS

2. FOOD AND CATERING Eating in Eating out 3. CLOTHING AND FOOTWEAR Embedded emissions in supply chain Care of clothing Travel to shops for clothes shopping 4. HOUSEHOLD Fabric of household and furnishings Household services Lighting 5. SPACE HEATING 6. COMMUTING 7. HEALTH AND HYGIENE 8. EDUCATION

234

Data research, analysis and calculation

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Carbon Footprint & Lifestyle Understand the correlation between human behavior and other CO2 emission aspects Point of Point of Intervention Intervention

TY ARBON CITY

SUSTAINABLE ZERO CARBON CITY

ZERO CARBON ZEROINFRASTRUCTURE CARBON INFRASTRUCTURE

The study in previous page of mapping carbon footprint with high level AIR functional needs helps to address the ONPOLLUTION FOREST URBAN & FOREST & + + + relationship betweenURBAN human activities, GREEN SPACE GREEN SPACE psychological needs and direct/ indirect carbon emission. The system map here visualizes such relationship,LOW-CARBON LOW-CARBON and further illustrate the linkage with any LIFESTYLELIFESTYLE + correlated board aspects. CARBON DIRECT CARBON

sport)(transport) +

To summarize, the social / psychological need behind human behavior influences the amount + + + + of direct carbon (transport) and UNCTIONAL BASIC FUNCTIONAL SOCIAL & SOCIAL & NEED NEED embedded carbon PSYCHOLOGICAL emission, mainly PSYCHOLOGICAL ++ + in three categories of NEED daily NEED life + ++ Leisure + activities: Food & Catering, CONSUMPTIONCONSUMPTIONBASED BASED & Recreation (holiday), and Leisure LEISURE & LEISURE & CARBON FOOTPRINT CARBON FOOTPRINT RECREATION RECREATION & Recreation (non-holiday). Worth (NON-HOLIDAY) (NON-HOLIDAY) noted that Leisure & Recreation THES & FOOD & influence FOOD + & + the TWEAR (non-holiday) highly CATERINGCATERING + and+ thus household carbon emission, directNEED carbon SOCIAL SOCIAL NEED emission (household + fuel). ++ +

ZERO CARBON INFRASTRUCTURE

AIR POLLUTION

TRANSPORTATION

EMBEDDEDEMBEDDED CARBON CARBON (supply chain) (supply chain)

LOW-CARBON LIFESTYLE

ACCESSIBILITY

BIG DATA / SMART CITIES

DIRECT CARBON (transport)

LEISURE & RECREATION (HOLIDAY)

COMMUTING

URBAN HEAT ISLAND

BASIC FUNCTIONAL NEED

+ -

GREENER ENERGY GENERATION

SOCIAL & PSYCHOLOGICAL NEED

HOUSEHOLD

EDUCATION EDUCATION

URBAN FOREST & GREEN SPACE

LEISURE & LEISURE & RECREATION RECREATION (HOLIDAY)(HOLIDAY)

UNICATION COMMUNICATION

Point of Intervention

CONSUMPTION- BASED CARBON FOOTPRINT

+ + +

CLOTHES & FOOTWEAR

LEISURE & RECREATION (NON-HOLIDAY) FOOD & CATERING

CARBON POLICIES

DIRECT CARBON (household fuel)

+ +

SOCIAL NEED

COMMUNICATION

Legend Legend CATEGORYCATEGORY OF PURPOSE OFOF PURPOSE ACTIVITY OF ACTIVITY CATEGORYCATEGORY OF MAJOROF ACTIVITY MAJOR ACTIVITY TYPE OF CARBON TYPE OFEMISSION CARBON EMISSION

OTHER ASPECTS OTHER RELATED ASPECTS TORELATED CARBON TOCONSUMPTION CARBON CONSUMPTION KEY FACTOR KEY FACTOR -VE INFLUENCE INSIDE BOUNDARY -VE INFLUENCE INSIDE BOUNDARY +VE INFLUENCE INSIDE BOUNDARY +VE INFLUENCE INSIDE BOUNDARY -VE INFLUENCE OUTSIDE BOUNDARY -VE INFLUENCE OUTSIDE BOUNDARY

EDUCATION

WATER CONSUMPTION & WASTEWATER TREATMENT

BUILDING EMBODIED CARBON

EMBEDDED CARBON (supply chain)

+VE INFLUENCE OUTSIDE BOUNDARY +VE INFLUENCE OUTSIDE BOUNDARY

236

237

Data research, analysis and calculation Legend

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GHG Intensity (kgCO2e/hr)

GHG Intensity of Time Use To identify carbon-intensive behavior

Work & other categories excluded from study 3.3

Other, 1.0 Commuting, 0.3

The total annual direct and embedded GHG emissions of an average UK household, G can be estimated using SELMA.

4.0 3.5 3.0 2.5 2.0

It is also important to note that the travel component of emissions is shown separately in the graph. The travel component includes both direct fuels used for transportation, such as petrol and diesel, as well as embedded emissions attributed to travel, such as those from the production and distribution of cars, and those attributed to public transportation.

1.5 Daily Average Intensity 1.2

1.0 0.5 0.0

Food & Drink

Household

Sleep & Rest

Commuting

Other

Source: Druckman, A. et al. (2012)

where, p = average number of adults per household among n activities the average adult takes part in, each k-th activity gives rise to GHG emissions gk

where, tk = time allocated to each activity k gk = intensity of expenditure x household expenditure

Leisure & Recreation 5.7

6.0

Leisure & Recreation (Non-holiday)

Food & Drink

Personal Care

Figure 1a: Time use of an average British adult Source: ONS (2006b)

“All we can do is to transfer the time to another activity” (Druckman, A. et al., 2012)

Data research, analysis and calculation

Commute

5.0 4.0 3.0 2.0

6.0

Leisure & Recreation (Non-holiday)

Food & Drink

Personal Care Commute

5.0 4.0 3.0 2.0

1.0

0.0

e s e e g g g c re ut) re) ing ing tin om hom adin usi Gam ultu tivitie ppin ca rden g o ash th mu C tin lth Re Ac Sho &M & sa the om h-w ea ea Ga s io bies ent & oor C nd side i h d e & & i a l d &D irs /fr s out g& , R Hob tainm Out ho ily Ds hin Repa lco ation d & ter as r la DV fam ien En port s/ sw ith ly/fr Inc repa ( o e S w h e t g P i e id lo kin ood im fam &V s, c rin F gt th he TV wi din &D lot en time lc ng i c t Sp g (in Ea din re en Ca Sp al on s r Pe

Household 2.7

Embedded Emissions Direct Transportation Fuel Direct Household Fuel

Travel Component EXCLUDING Travel Component

Figure 1c: Detail categories showing total travel disaggregated

Figure 1d: Detail categories showing direct and embedded emissions

‘Leisure & Recreation (Non-holiday)’ Data Analysis: - relatively low emissions per unit time, i.e. lower than the daily average intensity.

‘Food and Drink’ Data Analysis: - relatively low travel emissions - high GHG emission per unit time

Summary: Possible strategy for reducing GHG is to shift leisure activities towards those taking place in and around the home, e.g. reading, playing games, from those involving travel.

Summary: High GHG emission per unit time implies its carbon emissions mainly associate with food supply chain. Low-carbon food diet (reduce red meat consumption) have to be the strategy

TOTAL TIME: 24 HOURS

238

Leisure & Recreation (Non-Holiday)

Figure 1b: GHG intensity of time use of an average adult (in board categories)

Food & Drink 2.1 Sleep & Rest 8.9

Based on Figure 1b, the graph shows the GHG intensity of different time-use activities. We can see that the most GHG intensive time use categories are Commuting and Food & Drink, and Food & Drink is nearly 4 times as intensive as Leisure & Recreation. The GHG Intensity of Leisure & Recreation is even lower than the daily average intensity.

GHG Intensity (kgCO2e/hr)

Despite the common approach of investigating how people spend money on goods and services (and the associated carbon emissions), this study brings our attention on behaviour change by time allocation. We can (and must) cut our carbon emission per capita, by we cannot cut our 24 hour per day time allotment. All we can do is to transfer the time use among activities.

The GHG intensity of each activity category is defined as the GHG emissions that arise (direct and indirect) per unit time while carrying out the activity.

EXCLUDING Travel Component

4.5

GHG Intensity (kgCO2e/hr)

This study from Druckman, A. et al. investigated the GHG emissions per unit time for different types of activities to explore the possibility to achieve GHG reduction through changing the way people use their time. By limiting the focus on ‘nonwork’ time and routine daily life (holiday is excluded), this study mainly focused on the time use pattern of an average British adult and how time use varies within household.

Travel Component

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Time Spent of Activities

TIME USE SURVEY (Mapping Activities) Total time spent in each activity per person per day (in mins)

To identify carbon-intensive behavior Looking into Time-Use Survey (2015) helped to understand the average time-spent for an adult in specific categories, and identify the list of activities with relatively high time-use among a population. The United Kingdom Time Use Survey (UKTUS) provided a rich information in recording people’s daily activities in detailed activity-breakdown and among a large population. Time diaries record events sequences for prescribed periods, usually a single day. They are an effective means of capturing rich data on how people spend their time, their location throughout the day, and who they spend their time with. The sample was based on households, and household members eight years and over completed time-diaries for one weekday and one weekend day.

ACTIVITY TIME-SPENT CALCULATION METHODOLOGY 1. Eliminate the data for respondents aged outside 18-65, so the data-set would be focused on British adult. 2. Re-arrange the time-diary according to weekday and weekend. 3. Grouping and mapping the activity code with the selected activity category. 4. Count the frequency of activity code. 10 minutes for each count. 5. Calculate the total time-use (in minute) for each activity as well as overall, and divide by number of respondent / sample size: Sample Size for adult Weekday 5589 Weekend 5584

Leisure & Recreation (Outdoor)

Weekday

Weekend

0.41 0.64 0.00

0.61 0.90 0.00

Shopping and services as help to other households

0.03 0.00 0.37 0.00

0.01 0.00 0.37 0.00

Unspecified entertainment and culture Cinema Unspecified theatre or concerts Plays muscials or pantmimes Opera operetta or light opera Concerts or other performances of classical music Live music other than classical concerts, opera, and musicals Dance performances Other specified theatre or concerts Art exhibitions and museums Unspecified library Borrowing books records audiotypes videotypes CDs VDs etc. from lirary Reference to books and other library materials within a library Using internet in the library Using computers in the library other than internet use Reading newspapers in a library Other specified library activities Sports events Other specified entertainment and culture Visiting a historical site Visiting a wildlife site Visiting a botanical site Visiting a leisure park Visiting an urban park playground designated play area Other or unspecified entertainment or culture

0.42 1.40 0.53 0.08 0.03 0.12 0.72 0.21 0.20 0.38 0.26 0.02 0.01 0.08 0.01 0.00 0.04 1.63 0.16 0.48 0.39 0.14 0.50 1.43 1.28 0.00

0.44 1.46 0.39 0.51 0.06 0.16 0.97 0.00 0.14 0.40 0.31 0.02 0.01 0.07 0.00 0.00 0.00 1.48 0.40 0.77 0.29 0.05 0.85 1.41 1.31 0.00

Unspecified sports and outdoor activities

0.07 0.00 0.32 4.12 2.26 0.06 0.86 0.40 0.74 0.14 0.04 0.38 0.13 1.53 1.22 0.20 0.62 3.53 0.01 0.84 0.19 1.43 0.00

0.07 0.00 0.13 4.07 2.67 0.09 0.95 0.72 0.37 0.06 0.01 0.24 0.06 1.32 1.10 0.32 0.63 3.62 0.01 0.93 0.24 1.14 0.00

0.02 0.28 0.00 11.81 0.00 8.73 7.20 3.10 1.02 2.94 0.22 2.40 68.78 1.15

0.00 0.30 0.00 12.07 0.00 9.10 7.21 3.74 0.78 2.94 0.22 2.65 71.14 1.19

Leisure and Recreation (outdoor) Window shopping or other shopping as leisure Other specified shopping Shopping for and ordering entertainment via the internet

Unspecified physcial exercise Walking and hiking Taking a walk or hike that lasts at least miles or 1 hour Other walk or hike Jogging and running Biking skiing and skating Biking Skiing or skating Unspecified ball games Indoor pairs or doubles game Indoor team games Outdoor pairs or doubles games Outdoor team games Other specified ball games Gymnastics Fitness Unspecified water sports Swimming Other specified water sports Other specified physcial exercise

** The calculation is done using UKTUS 2015 diary-wide format.

In our study, we extracted the data for respondents aged between 18-65) to maintain the data focused on daily activities for an average adult. From the result, we found that, although the GHG intensity is not high for indoor leisure activities, due to the high timespent this category of activities can highly contribute to carbon emission. In addition, outdoor leisure is an important category as the accumulated travel component can be a major reason to carbon-intensive behaviour.

Unspecified sports related activities Activities related to sports Travel related to shopping Travel to visit friends/relatives in their homes not respondents household Travel related to other social activities Travel related to entertainment and culture Travel related to other leisure Travel related to physcial exercise Travel related to hobbies other than gambling Travel for day trip/just walk Total (in minute) Total (in hour)

240

AVERAGE TIME SPENT FOR AN ADULT Weekday Weekend

Data research, analysis and calculation

**There is no particular activity with significantly high time-spent, but the total time spent in this category is not negligible.

241

Construction and repairs as help to other households Physical care and supervision of an adult as help to another household Travel related to services Total (in minute) Total (in hour)

ACTIVITY CATEGORIES TIME USE SURVEY (Mapping Activities) Total time spent in each activity per person per day (in mins)

Leisure & Recreation (Indoor) Leisure and Recreation (Indoor) Unspecified social life and entertainment Unspecified social life Socializing with family Visiting and receiving visitors Celebrations Telephone conversation Other specified social life

Weekend

0.06 0.08 6.82 21.05 3.04 6.23 13.14 0.00

0.05 0.04 6.37 23.29 3.52 6.17 13.06 0.00

Unspecified arts Unspecified visual arts Painting drawing or other graphic arts Making videos taking photographs or related photographic activities Other specified visual arts Unspecified performing arts Singing or other musical activities Other specified performing arts Literary arts Other specified arts Unspecified hobbies Collecting Correspondencve Other specified or unspecified arts and hobbies

0.06 0.00 0.14 0.00 0.67 0.52 0.06 0.07 1.08 0.12 0.15 0.00 0.09 0.01 0.47 0.50 0.00

0.08 0.00 0.04 0.01 0.45 0.47 0.05 0.05 1.40 0.14 0.30 0.01 0.05 0.01 0.32 0.53 0.00

Unspecified games Solo games and play Unspecified games and play with others Billiards pool snooker or petanque Chess and bridge Other specified parlour games and play Computer game Gambling Other specified games

0.70 0.99 0.16 0.23 0.04 1.42 8.30 0.47 0.22 0.00

0.69 0.66 0.30 0.29 0.02 1.29 7.42 0.50 0.30 0.00

Unspecified mass media

0.25 0.00 5.10 4.14 5.43 0.23 0.00

0.33 0.00 5.88 4.00 4.88 0.20 0.00

Unspecified TV video or DVD watching Watching a film on TV Watching sport on TV other specified TV watching Unspecified video watching Watching a film on video Watching sport on video Other specified video watching

118.29 5.95 5.90 5.06 1.00 2.30 0.02 0.87 0.00

119.39 5.75 5.11 3.52 0.94 1.91 0.02 0.70 0.00

Unspecified listening to radio and music Unspecified radio listening Listening to music on the radio Listening to sport on the radio Other specified radio listening Listening to recordings

1.51 1.79 0.03 0.07 0.15 0.28 225.23 3.75

1.21 1.87 0.03 0.11 0.24 0.36 224.35 3.74

Unspecified hobbies games and computing

Unspecified reading Reading periodicals Reading books Other specified reading

Total (in minute) Total (in hour)

AVERAGE TIME SPENT FOR AN ADULT Weekday Weekend

Weekday

**Activities with relatively high timespent include visiting and receiving visitors, TV video or DVD watching

ACTIVITY CATEGORIES TIME USE SURVEY (Mapping Activities) Total time spent in each activity per person per day (in mins)

Food & Drink

83.14

84.24

Unspecified food management Food preparation and baking Dish washing Preserving Other specified food management

0.02 37.75 11.40 0.06 0.01

0.03 36.77 10.33 0.07 0.01

7.33 0.00 0.15 0.00

6.77 0.00 0.07 0.00

0.64 140.50 2.34

0.61 138.89 2.31

Total (in minute) Total (in hour)

Total time spent in each activity per person per day (in mins)

Primary Activity

Personal Care and Household Personal Care, Repair & Gardening Unspecified personal care

0.15

0.47 54.64 1.38

0.43 53.97 1.45

Unspecified household and family care Laundry Ironing

5.95 6.39 4.86

6.07 6.09 4.10

Gardening Other specified gardening and pet care

6.14 0.15

5.85 0.16

Unspecified construction and repairs House construction and renovation Repairs of dwelling Making repairing and maintaining equipment Woodcraft metalcraft sculpture and pottery Other specified making repairing and maintaining equipment Vehicle maintenance Other specified construction and repairs

0.46 0.49 3.81 0.38 0.12 0.53 1.87 0.14

0.52 0.35 3.83 0.25 0.20 0.57 1.73 0.01

Shopping mainly for clothes Personal services

0.61 2.75

0.59 3.19

Shopping for and ordering clothing via the internet Shopping for and ordering unspecified goods and services via the internet

0.08 0.58

0.01 0.59

Gardening and pet care as help to other households Construction and repairs as help to other households Physical care and supervision of an adult as help to another household

0.60 0.71 0.15

0.43 0.86 0.13

1.83 95.25 1.59

2.07 93.62 1.56

Eating

83.14

84.24

Unspecified food management Food preparation and baking Dish washing Preserving Other specified food management

0.02 37.75 11.40 0.06 0.01

0.03 36.77 10.33 0.07 0.01

7.33 0.00 0.15 0.00

6.77 0.00 0.07 0.00

0.64 140.50 2.34

0.61 138.89 2.31

Total (in minute) Total (in hour)

**Activity with relatively high time-spent Food and Catering includes wash and dress

Shopping for and ordering food via the internet Food management as help to other households

Data research, analysis and calculation

Total Time Spent per person per day (Min) (WeWeekday ekday) (WeWeekend ekend) 0.17

Unspecified other personal care Wash and dress Other specified personal care

Shopping mainly for food

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**Activities with relatively high time-spent include eating, food preparation and baking

Travel related to services

AVERAGE TIME SPENT FOR AN ADULT Weekday Weekend

2.07 93.62 1.56

Weekend

Food management as help to other households

TIME USE SURVEY (Mapping Activities)

1.83 95.25 1.59

Weekday

Shopping for and ordering food via the internet

ACTIVITY CATEGORIES

0.86 0.13

Food and Catering Eating

Shopping mainly for food

AVERAGE TIME SPENT FOR AN ADULT Weekday Weekend

0.71 0.15

Total (in minute) Total (in hour)

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FOOD PRODUCED FOOD PRODUCED

COLLECTIVE COLLECTIVE MIXED- MIXEDUSE USE HOUSING HOUSING

COMMUNAL COMMUNAL KITCHENKITCHEN

LLECTIVE + FOOD ON SUMPTION

Factors to Carbon Mitigation +

COMMUNAL COMMUNAL HEAT PUMP HEAT PUMP

USEHOLD D AL RATIONAL + + YNCY EFFICIENCY

PUBLIC AWARENESS PUBLIC AWARENESS

LOCAL LOCAL NEIGHBOURHOOD NEIGHBOURHOOD CONNECTION CONNECTION

INCENTIVE INCENTIVE TO TO LOWCARBON LOWCARBON DIETDIET

+ +

Visualizing the complex system between carbon contributing factors and human behaviours +

PROXIMITY PROXIMITY TO TO AMENITY AMENITY

FOOD PRODUCED FOOD PRODUCED

LOW-CARBON CARBON LOWPURCHASING CHOICE PURCHASING CHOICE

IC TATION

LOWCARBON LOW- CARBON MEAL MEAL

PATTERN STREET PATTERN in Following theSTREETresearch + previous page, the mitigation factors work towards the + main + three+ categories + VISIBILITYVISIBILITY ALTERNATIVE CAR- ALTERNATIVE of CARactivities: Food & Drink, Leisure TRANSPORT TRANSPORT (Indoor) and (Outdoor), + Leisure + + + in which CHOICECHOICE the carbon reduction to be achieved by reducing GHG intensity of each activity low-carbon food diet, CYCLING CYCLING /through CAR- SHARING / CAR- SHARING INFRASTRUCTURE INFRASTRUCTURE low-carbon household and low-carbon mobility.

COLLECTIVE COLLECTIVE + FOODFOOD CONSUMPTION CONSUMPTION

LOCAL FOOD LOCAL FOOD

FOOD WASTE FOOD WASTE

LOWCARBON LOWCARBON FOOD DIET FOOD DIET

EMBEDDEDCARBON CARBON EMBEDDED (supplychain) chain) (supply

KEY STRATEGY KEY STRATEGY CONSIDERATION CONSIDERATION CLOSELYCLOSELY CORRELATED CORRELATED -VE INFLUENCE -VE INFLUENCE

+VE INFLUENCE +VE INFLUENCE +VE RELATED +VE RELATED

FOOD&& FOOD DRINK DRINK

GHG INTENSITY GHG INTENSITY PER TIME USE PER TIME USE

- -

ROUTING ROUTIN

WALKABILITY WALKABILITY DIRECT CARBON DIRECT CARBON (transport) (transport)

PROXIMIT PROXIMITY TO DAILY LIFE DAILY L NECESSITY NECES

LESS INCENTIVE LESS INCENTIVE TO LONG-TO LONGDISTANCE DISTANCE TRAVEL TRAVEL

TRAVELLING TRAVELLING TIME TIME

LEISURE LEISURE (INDOOR) (INDOOR)

LESS LESS CARBONINTENSIVE CARBONINTENSIVE BEHAVIOR BEHAVIOR

HOUSEHOLD HOUSEHOLD DIRECT CARBON DIRECT CARBON (household (household fuel)fuel) -

LEISURE LEISURE (OUTDOOR) (OUTDOOR)

- -

LOWCARBON LOWCARBON MOBILITY MOBILITY

LOW- CARBON LOW- CARBON TRANSPORT TRANSPORT +

PUBLIC PUBLIC TRANSPORTATION TRANSPORTATION

+ + + LOW-CARBON + LOW-CARBON

PROXIMIT PROXIMITY TO AMENITY AMEN

CO2 EMISSION CO2 EMISSION ASSOCIATED ASSOCIATED - CATEGORY - CATEGORY OF ACTIVITY OF ACTIVITY

LOW-CARBON LOW-CARBON LIFESTYLE LIFESTYLE

SHARING USE SHARING USE OF SPACE OF SPACE

LegendLegend Legend

LOCAL LOCAL NEIGHBOURHOOD NEIGHBOURHOOD CONNECTION CONNECTION

COMMUNAL COMMUNAL HEAT PUMP HEAT PUMP

HOUSEHOLD HOUSEHOLD OPERATIONAL OPERATIONAL + ENERGY EFFICIENCY ENERGY EFFICIENCY

TYPE OFTYPE CARBON OF CARBON EMISSION EMISSION

COLLECTIVE COLLECTIVE MIXED- USE MIXED- USE HOUSINGHOUSING

COMMUNAL COMMUNAL KITCHEN KITCHEN

SUPPLY SUPPLY

LOW- CARBON LOW- CARBON TRANSPORT TRANSPORT +

HOUSEHOLD HOUSEHOLD FOOD GARDEN FOOD GARDEN +

By listing out PROXIMITY the PROXIMITY possible TO TO carbon mitigating factors, DAILY LIFE DAILY LIFE this + + diagram + NECESSITY NECESSITYthe system dynamics shows ARBON LESS INCENTIVE LESS INCENTIVE EHOLD interconnected relationship between TO LONGTO LONGcontributing factos with low-carbon DISTANCE DISTANCE TRAVEL TRAVEL behavior. With the quantitative effect - between TRAVELLING TRAVELLING TIME TIME factors being shown, this helps to formulate design + + the complex ROUTING ROUTING WALKABILITY WALKABILITY system to low-carbon lifestyle. SHARING SHARING USE USE OF SPACE OF SPACE

AREAAREA / SIZE/ SIZE

STREET PATT STREET PATTERN

+ +

CAR- ALTERNATIVE CAR- ALTERNATIVE TRANSPORT TRANSPORT

VISIBILITY VISIBILITY

CHOICE CHOICE

/ CAR- SHARING CYCLINGCYCLING / CAR- SHARING INFRASTRUCTURE INFRASTRUCTURE

244

Data research, analysis and calculation

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Sankey Diagram

The diagram shows the summary of pathways to emission contribution from three aspects of human needs in daily lives, including ‘social and psychological’, ‘basic functional’, and ‘social’ needs. The first flow from the left side is separated into 9 categories to understand how each percentage of overall CO2e in UK households, and then is linked

The summary of pathways to emission contribution

to a detailed activity classification, how many hours or minutes people spend in a day. Next, in order to understand the conversion of greenhouse gas emissions, we reintegrate back to a larger category and utilize greenhouse gas intensity to obtain the relative greenhouse gas emissions results of indirect or direct emissions activities respectively.

GHG EMISSIONS (kgCO2e)

COMPONENTS OF CARBON FOOTPRINT

246

CATEGORIES (HR)

89.2

Household and family care

63.8

Social life and entertainment Hobbies, games, and computing

3.85 GHG Intensity (excluding travel)

Food & Drink

4.2

Leisure & Recreation (Holiday)

Leisure & Recreation (Indoor)

Leisure & Recreation (Non-holiday)

Data research, analysis and calculation

Commuting

Volunteer work and meeting Travel and unspecified time use

Personal Care

0.25 GHG Intensity (excluding travel)

DIRE C T

Other

7.61 kgCO2e 1.97 kgCO2e

1.64

37.1 2.4 20.4

Sports and outdoor activities

0.95 GHG Intensity (travel) 2.36 kgCO2e

Communication

Personal care, repair & Gardening

0.3 GHG Intensity (travel)

Mass Media

0.62

Education

Leisure

Leisure & Recreation (Outdoor)

58.5

Commuting

1.61

Household

7.61

0.7 GHG Intensity (excluding travel)

172.5

Clothes & Footwear

20%

2.32

87.9

Personal care (Eating)

26.7

2.36

Food & Catering

1.17

17%

10%

24%

Per person per day

1% 2%

SO CIAL & PSYCHOLOGICAL BASIC FUNC TION AL SOC IAL

C ATEGO RIES O F HUMAN N EE DS IN DAILY LIVES

NEEDS

MIN /

INDIREC T / EMBEDDED

HR /

Per person per day

8.93 kgCO2e

of overall CO2e in UK household

3.8 GHG Intensity (travel)

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Real-Life Scenarios

Carbon Saving Solutions

Pragmatic experimentation in reducing daily carbon footprint

The introduction of potential carbon saving methods in terms of three main categories of functional needs

TRAVEL FROM HOME

Male 56 years old

EATING/FOOD PREP

8:10 a.m.

Food and Drink.

Female 44 years old

7:20 a.m. Wash/Dress Eating

Wash/Dress

Laundry

Sleep Sleep

From our statistics and calculation which was extracted from the ‘United Kingdom Time Use Survey’ (2015), each person spent about 2.32 hours per day. However, the category generates the most greenhouse gas emissions in people’s daily lives due to the highest GHG intensity, at 3.85 kgCO2e / Hr. We take the reduction of food waste and food travel as the starting point and propose a ‘sustainable food system’ to maintain people’s basic needs and enjoy fresh food while reducing carbon emissions.

12:00 a.m.

Hom

Work TV

e Leisure Tim e

9:50 a.m

FOOD PREP/BAKING

TRAVEL RELATED TO SHOPPING 2:20 p.m. Wash/Dress Lunch

3:00 p.m.

VISITING/ RECEIVING VISITORS

3:20 p.m.

TRAVEL BACK HOME e Leisure T ime Hom

EATING/FOOD PREP

Leisure and recreation. 4:00 p.m.

As we mentioned earlier, among the nine types of advanced functional uses based on the family level, it revealed that people spend the most time on ‘leisure and recreation’ a day, at exactly 27%. While from the calculation of the time we spend, it contributes 7.61 hours per person per day, including outdoor and indoor activities, which demonstrates its importance to our daily lives. The change of ‘housing typologies’ will provide people with new ways to feel relaxed and entertained under a low-carbon life.

HOUSEHOLD UPKEEP

5:30 p.m. Gardening/Household Care

5:00 p.m. Dish Washing

EATING/FOOD PREP

PET CARE 10:00 p.m. 5:30 p.m.

TV/DVD WATCHING

Wash/Dress Wash/Dress

TV/DVD Watching Shopping for Goods/Services via Internet

Sleep Sleep

12:00 a.m.

10:30 p.m.

TV/DVD WATCHING

HOUSEHOLD OPERATIONAL ENERGY LOW CARBON COMMUNITY

SUGGESTIONS TO PROMOTE BEHAVIOURAL CHANGE

• Examples of projects include White Gum Valley, Fremantle with housing typologies designed for Gen Y lifestyles. • Onsite communal spaces include courtyard, food garden, bicycle repair station are designed to encourage conversation between neighbours to foster relationship

248

Carbon savings solutions

FOOD CONSUMPTION

Household Energy (Space Heating). In the UK, more than half of household energy comes from heating. As architects and designers are committed to improving materials and building performance for many years, how heating system transformation can make energy renewable and more efficient. The carbon saving solution we put forward is the ‘communal heating system’ on a building scale and creating a district heating network to reduce household energy consumption effectively. The detailed elaboration of ‘house heat source’ is as follows.

TRAVEL FOR ACTIVITIES/GOODS/SERVICES

LOW CARBON DIET • Encouraging low carbon diet at multi-level approaches through promotion of individual health and environmental benefits • The intent of urban farming to

LOW CARBON MOBILITY • Non-essential travel should be discouraged by proper planning of activities and purpose of a particular trip. • Proper spatial planning can help

increase local food resources, lower the amount of food and material waste, and reduce embedded carbon in the supply chain

to reduce long-distance travel. • Provision of public transport and less carbon intensive modes of transport such as electric vehicles, bikes, scooters

Functional Needs

Potential Carbon Savings

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RENEWABILITY

EMBODIMENT

EFFICIENCY

SUFFICIENCY

Food Systems

British Columbia kgCO2e/t

Agricultural activities generate roughly one third of human GHG emissions, but the majority of this is caused by meat and dairy production compared to fruits and vegetables (Figure 1e). Are there real social or environmental benefits to growing food within city limits?

Various studies about vertical farming in European cities suggested different environmental benefits and impacts. Based on study in Sweden, Martin and Molin (2019) suggested vertical farms are capable of growing produce at a carbon footprint of 0.27 to 0.74 kg CO2e per kg of edible plant material. Another study by Romeo et al. (2018) suggest that vertical farms have a carbon footprint of approximately 0.39 kg CO2e per kg of lettuce grown, assuming they are powered by French energy mix, which is 70% nuclear. A case study of vertical farming in Stockholm by Hallikainen (2018) using life-cycle assessment, however, suggested a minimum carbon footprint of approximately 4.0 kg CO2e per kg of lettuce grown based on the life cycle assessment of urban farming. (see Diagram 1d)

kgCO2e 45 40

Meat Intake

Non-meat Intake

39.2

GHG emissions of food

Post-production Emissions (includes processing, transport, retail, cooking and waste disposal) Production Emissions (includes emissions before product leaves the farm plus avoidable and unavoidable waste)

35 30

27.0

Low carbonintensive food

(Red meat, diary products)

(Plane-based/ vegan products)

hydroponic farming of fodder products

20 13.5

15 10

12.1 11.9

6.1 4.8 2.9 2.7 2.5 2.3 2.2 2.0

m La

450

Hydroponic barley (distributed) Hydroponic barley (centralized) Conventional barle

425

400

375

350

325

300

275

250 200 220 240 260 280 300 320 340 360 380 400 420

Carbon mitigation potential

Energy consumption (kWh/day)

Figure 1f: Changes in hydroponic energy consumption for British Columbia and Alberta scenarios Source: Newell et al. (2021)

Another study by Newell et al. (2021) explores the potential hydroponic systems have for contributing to climate mitigation in fodder agriculture. In the case of fodder production, using hydroponic systems have the potential to offset GHG emissions produced through the transportation of fodder products. However, as demonstrated in the case study of British Columbia and Alberta, it is important to note that localization of production does not necessarily lead to emissions reductions because certain crops can be produced more efficiently elsewhere. Thus, this leads to difficulty in balancing trade-offs between production and transportation related emissions.

From the analysis, it is revealed that more significant changes in seed-to-fodder and energy consumption levels need to occur before crossing thresholds in situations that involve longer supply chains and product transportation. The energy consumption threshold was not reached in the BC scenario, but these thresholds were crossed in both Alberta scenarios. The findings concluded that for hydroponic systems to effectively serve as carbon mitigation strategy, the energy resources used to power a particular context is important (low carbon grid), with further strategy implemented to reduce supply chain (transportation of seeds).

System boundary of carbon footprint study

hydroponic farming

Urban farming

10.9 6.9

250

High carbonintensive food

GHG emissions per fodder production

kgCO2e/t Hydroponic barley Conventional barley

450

Impact of urban gardening activities on food consumption and carbon footprint Making our urban food systems more sustainable can yield major benefits in terms of carbon intensity and resource efficiency. It involves notably the use of local and seasonal products (short supply chains), improving diets (reducing the share of animal protein and processed foods), using products that meet environmental and sustainability criteria (certification), promoting selfproduction (fruit and vegetable gardens, use of derelict lands), and preventing waste (food and its packaging).

Alberta

2.0 2.0 1.9

1.1 1.1

) es ils s es e er li fu ns y n n a ts rt ef se rk Be hee Po almo Turke hicke d Tun Egg tato Ric Butt Nu Yogu occo To Bea k (2% ato Lent r t l om o C S i y e C u B P r n n T M n D a ed Pe rm Ca Fa

Low carbon diet per kg of consumed food

Sustainable Urban Food Systems

Figure 1e: GHG emissions of food produced in the agriculture sector

Diagram 1d: Urban hydroponic vertical farming system from cradle-to-gate perspective

Source: EWG

Source: Martin and Molin (2019)

Carbon savings solutions

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RENEWABILITY

EMBODIMENT

EFFICIENCY

SUFFICIENCY

Domestic Heating Food miles reduction can lead to reduction of carbon footprint one truck = 26 pallets x 635

Using low carbon heat to reduce household heating energy

Assume distance travelled = 2989 miles,

Carbon footprint calculation:

2989 miles travelled

4105.8kg of CO2e

What is Low Carbon Heat?

= 16,510kg of leaf lettuce

635kg

of leaf lettuce

26x

7.28 miles per gallon of diesel used

10kg of CO2e combusted per gallon of diesel used

4105.8kg

80% of 16,510kg of leaf lettuce

of CO2e

(20% of total weight discounted due to weight of pallets, packaging and transport wastage)

0.31kg of CO2e for each kg of leaf lettuce transported

Carbon footprint of food transport (traditional field farming)

A leading containerized system uses approximately 130 kWh of power per day

At a yield rate of 50kg per week, 130 kWh x 7 x 0.233 kgCO2e 50kg of leaf lettuce

Based on UK carbon emissions for average home energy use:

0.233kg of CO2e per kWh of electricty Container farm system (Vertical farming)

4.24kg

District Heating

of CO2e for each kg of leaf lettuce grown

Energy consumption and carbon footprint for vertical farming

Although the carbon footprint and energy consumption of vertical farming is relatively higher than traditional field farming due to power-intensive dehumidification systems required, less water is used in the process, with water savings up to 99% compared to outdoor field farming. Vertical farming provides benefits in regards to overall sustainability

as the input nutrients used in the growing process are not wasted as they can be recirculated within the hydroponic systems. In contrast, traditional method of production using fertilizer remains a problem for field production, as outdoor farming fields tend to be over-saturated with excess nutrients that run into local waterways or tailwater collection pond.

Urban Farming Direct & Indirect Emissions

Energy Use (Lighting), Transport, Water (Hydroponic System)

Carbon Offsetting

Packaging and Supply Chain (Substrate, Product Distribution)

252

Carbon savings solutions

_ Energy Use

Transport

Water

As domestic heating and hot water accounted for around 75% of household energy demand, replacing high carbon fossil fuels used in current heating system with low carbon heating technologies such as heat pump is required to achieve the necessary energy savings. Low carbon heating systems include heat pumps (air source, ground source, water source), electric combi boilers, biomass boilers, micro-CHP systems and solar water heating. These heating systems can provide energyefficient and sustainable domestic heating while offering the same level of warmth as more carbon-intensive heating systems like gas-fuelled boilers.

= Packaging

Supply Chain

kgCO2e

District heating, or also known as heat network, is a distribution system of insulated pipes that takes heat from a central source and delivers it to a number of domestic or non-domestic buildings. Using heat network is more energy efficient, due to simultaneous production of heat and electricity in combined heat and power generation plants. The Manchester Octagon Project Energy Network (OPEN) undertaken by MEPL was granted planning approval by Manchester City Council in March 2021. The project area will cover 5 sq. km and plans to distribute locally generated, low carbon electricity, heat and cooling to a range of buildings including Manchester University NHS Foundation Trust, major University buildings, a mix of over 1000 social housing units, student accommodation blocks, and commercial organisations. Phase 1 of the network will satisfy a heat demand of 75 GWh and an electricity demand of 84 GWh, with the estimated Phase 2 expansion brining heat demand to 96 GWh and electricity to 126 GWh.

Heat Energy Generation Municipal Solid Waste (MSW) Coal Light & Heavy Oil LPG Biomass Solar Urban Excess Heat (UEH) Geothermal Industrial EH Previous chapter

Electricity

Heating Systems CHP DH

HOB solar collector large scale HP large electric boiler small HP small electric boiler

Building Heating building heating demand in Zone A

buildings performance

building heating demand in Zone B

buildings performance

Following chapters

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2021 CPU[AI] Towards low carbon heat

Building Type

Implications of heat pump deployment in common development types in London

The heat pump systems perform better against Part L than the alternatives across all building types considered. This is due to a combination of the efficiency heat pumps can achieve, decarbonization of grid electricity and reduction of distribution losses.

-35%

76%

41%

Emissions over Part L 2020 Baseline Part L 2020 Emissions

Part L 2013 Baseline Emissions

CO2 emissions

Several case studies of common development types in London (10 storeys, 150 units) were investigated and the Figure 1g indicates the modelled heat pump system performance against Part L using a grid electricity carbon emission factor of 302 gCO2/kWh.

Target Emissions: 35% Improvement over Part L 2013

Communal boiler

GSHP

Communal Hybrid ASHP

Connection to DH

Heat pump provides up to 30% carbon reduction per kWh compared to gas CHP

CCommunal o mmunalheating heat ing with w it h gas gas boilers boilers

CoCommunal mmunal hheating eat ing ggas as CCHP-led HP-l ed

(gCO2/kWh)

Heat pumps in London

HHeat eat pump pump ssystem y stem

DiDirect rect eelectric lectric Reresistance sistanc e

(gCO2/kWh)

Space Heating

Hot Water

1. Residenti al Block: 70 units

264

274

101

178

302

2. Residenti al Block: 100 units

264

274

106

302

3. Pri mary Sc hool (6,500m2)

264

274

181

302

4. 100-bed Hotel

264

274

101

180

302

5. Office Buil ding (7,000m2)

264

274

101

302

6. Office Buil ding (50,000m2)

264

274

302

7. District (Resi dential)

330

342

148

8. District (Mi xed-use)

330

342

141

120

Towards low carbon heat

Heat pumps in London

TTable able 61a: .02 –Modelled Modelled heat heat source sourc e ccarbon arbo n eemission missio n fafactors c tors – based based oon n 3carbon 02 gCOfactor fo r e l ectrici ty 2/kWh for electricity

Figure 1g: The Impact of four heat pump technologies for a typical London development on GHG emissions

302 gCO2/kWh

Source: Greater London Authority (2018)

Notes concerning values in Table 6.02

Source: Greater London Authority (2018)

•

The ‘CHP’ case assumes an 80% thermal load from CHP and 20% from gas boilers. This Communal heating Communal heating Heat pump Direct electric represents a very high and was Cowith mm unaboilers lproportion heat ing Co mm unCHP-led aused l heatto ingclearly show H easystem t pthe umpimpact of the Direresistance cCHP t elecrather tri c gas gas than ‘blending’witithwith effect of a gas boiler. gas the boile rs gas C HP-l edCHP total efficiency Syst em of 80% withReheat-tosistanc e power ratio of 1.5(kgCO are assumed. (kgCO2/yr) (kgCO2/yr) (kgCO2/yr) 2/yr)

Building Type gCO2 350

Determining the carbon content of heat based on grid emission factor

1. •70-unit For ‘Gas Boiler’ and ‘CHP’ cases 1 to 6, internal pipework heat distribution losses of 10% are residential 164,000 168,000 137,000 178,000 assumed. Cases 7 and 8 factor in an additional 20% losses through the underground district block

Communal Gas Boiler

heat network pipes.

250

Heat Carbon Factor

As shown in figure 1h, individual heat pumps provide substantially lower carbon heat than gas-fired CHP and individual gas boilers when used for either space heating or domestic hot water. The model with highest heat carbon factor is the baseline district heating system with assumed distribution losses of 20%, where 80% of the heat is provided by a gas-fired CHP unit (a very high contribution from CHP), with the remaining heat provided by a large gas boiler.

300

6.1.5

200

2. 100-unit high rise residential Part L assessments block

235,000

240,000

190,000

254,000

3. 6,500 sqm The above carbon contents212,000 of heat have been applied 219,000to the Part L results 200,000to assess which238,000 primary school combination of case studies/heating systems were likely to be able to achieve a 35% improvement 4. Part 100-bedroom over L 2013, taking into293,000 account the reduced emissions factor for251,000 grid electricity. 300,000 320,000

150 100

hotel

50 0

Gas CHP 80%/ Heat pump 70%/ Individual Individual heat Boiler 20% + DH Boiler 30% + DH heat pump for pump for space network network at 55oC domestic hot heating at 60oC water at 60oC

Electrical heating

Figure 1h: Carbon factor of heat based on grid emission factor of 302gCO2/kWh Source: Greater London Authority (2018)

5. table 7,000and sqmbar chart on the following page (Table 6.03 and Figure 6.01) indicate that the modelled The 369,000 375,000 364,000 393,000 office systems were generally lower carbon than the alternatives and provided a larger heat pump 6. 50,000 reduction sqm percentage over the Part L baseline, in line with the requirements of the draft London Plan 4,007,000 3,913,000 3,958,000 office (2018) requirements. Please note that none of the case studies above include PVs, which would enable some scenarios to achieve additional carbon savings and potentially comply with the 35% 7. District 4,274,000 4,373,000 3,619,000 (Residential) carbon reduction improvement over Part L 2013. 8. District 3,724,000 3,388,000 3,648,000 (Mixed-use) * For the purposes of this calculation the future Part L TER (Target Emission Rate) has been adjusted proportionately to difference in BER calculated using Part L 2013 emission factors for grid electricity and the figure TTable a302 ble 6gCO .05 – Resulassumed t s of prcarbon edin ic tthis ed emissions astudy. ct ual carbbased o n savion ng predicted assessmencarbon t - Total saving annual cassessment arbo n emissio ns 1b: Total of 2/kWhannual

Source: Greater London Authority (2018) 25.0%

254

Carbon savings solutions

20.0% 15.0%

20180167 | Sep 2018 | Rev L

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RENEWABILITY

EMBODIMENT

EFFICIENCY

SUFFICIENCY

Leisure and Recreation

Scale of Improvement

The suggestion to think about 'house typologies' differently

How to enable low carbon living at scale? The challenge to facilitate a shift towards low carbon lifestyles requires intervention ranging from community to municipalities to national level. Low carbon practices at household level (communityinitiatives) focus on collective creation of shared visions and decisions by fostering low carbon practices and discourage carbonintensive ones. Low carbon municipalities mainly focus on introducing technologies and offering additional infrastructure such as car charging station, bike sharing to promote low carbon practices without restricting particular daily practice with high carbon intensity.

MIXED USES MIXED SIZES MIXED TENURE

Collective Living

As we mentioned earlier, leisure and recreation time account for one-third of daily life, including indoor and outdoor activities. How can we improve the ways people travel and move around the city, the neighbourhood, and even inside the buildings? ‘Collective Living’ is a potential new lifestyle to reduce quantities of programmes and time use by ‘sharing’.

256

From the scale of buildings, extracting the spaces in the home which residents are willing to share with the neighbourhood is a good starting point to design. For example, ‘a communal lounge’ to enjoy social life and shared entertainment facilities among three to five units is a possibility to intervene in design. Without the stress from using lounges open to hundred residents in apartment buildings, smaller sizes and close distance of share leisure spaces will encourage residents

Carbon savings solutions

to visit them and have social lives. ‘New Housing Typology’ in terms of leisure and recreation we proposed means mixing and diversification, injecting the possibilities of activities in surroundings, rather than specific functional spaces. Promoting people shared communal spaces and amenities will contribute to reducing GHG emissions to achieve greater embodiment and sufficiency.

Land use, Policy, Energy generation Mobility practices, Low carbon infrastructure Food, Daily housing practices

URBAN

DISTRICT

HOUSEHOLD

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Case Study_ Eco Village The UK's first zero energy development project_ BedZED

Residentia l Home s Residential

Burning off-cuts from tree surgery waste

57%

Less tha n average

Workspaces

Renewable Energy

(Hot-water consumption)

Combined heat & power

Local produce market

Mixed sizes, mixed tenure, & mixed use

Social & Psychological Needs

Solar energy

A children’s nursery An exhibition centre Commercial use

South facing ( maximise heat gain )

777

Precinct Bioregional

Square metre s solar panels

Miles radius Local materials coming from nearby

(11% generation of total electrical power used)

Greener Construction BedZED- Zero Energy Housing: Image from author YeQianyi

The BedZED project was the UK’s first major zero-carbon community completed in 2002 and environmentally friendly housing development in the London Borough of Sutton. All aspects the architects considered were based on the needs in people daily lives to decrease the distances and develop mixed-use building types on a precinct scale. This high-density residential development accommodates mixedincome groups and combines workspaces and homes. It includes 82 residential homes, with 34 for outright sale, 23 for shared ownership, 10 for key workers, and 15 at affordable rent for social housing. The BedZED aims to create a prosperous community where everyone can enjoy a high-quality life in a fair share of the earth’s resources.

258

At the same time, it reduced householdlevel greenhouse gas emissions and encouraged people to live a lowcarbon lifestyle. Linking back to the three aspects of carbon saving solutions we focus on, ‘food and drink’, ‘leisure and recreation’, and ‘heating’, BedZED outlined a clear framework and has practised addressing the sustainable lifestyle issues. Food and drink: to achieve the ‘sustainable food system’, one of the strategies was to reduce package and food waste, which was a starting point. In BedZED, the performance of exactly recycling or composting from residents gradually increased due to segregated bins in homes. In addition, it then promoted a local produce market in the neighbourhood which served healthy,

Carbon savings solutions

low-meat meals for locals to influence people’s choices. Leisure and recreation: : As people spend much more time relaxing and entertaining, the importance of interaction between residents and accessibility to leisure places also increases. Mixed-sizes, mixed-tenure, mixed-use planning in BedZED provided more possibilities for residents living a healthier and happier life. Heating: Energy-efficient design includes two parts in BedZED. Firstly, to decrease the energy demand for heating, cooling, and ventilation by 90% compared with an average UK household. Secondly, the bio-fuelled combined heat and power were proposed to generate all energy on-site to reduce energy travel.

Great Neighbourliness

Basic Functional Needs

Social Needs

Reclaimed products

insulation jacket

300

Healthier & Happier Living

MM thinkness Well-ventilated houses

Roof garden

Triple glazed windows

50%

Less tha n average (Main-wate r consumption)

Water saving appliances

Reduce Energy Consumption

Low energy lighting

Green transport plan

kw at t per person & day

(The electrical power uses)

Pedestrian Pathway

Energy appliances

88%

Less than average

(Spac e- heating requirements)

Bicycle Lane Electrical cars sharing

65%

Public transportation ( Underground / Bus )

Less tha n average (Car mileage )

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Conclusion

Executive Summary

Achieving lifestyle emissions reduction

Towards household decarbonization

TheAvoid-Shift-Improve (A-S-I) framework is an approach originated from transportation studies that seeks to increase efficiency by modifying consumer behaviour. It has also been applied to various consumers sectors such as analysing of the consumption of food and energy systems.

What are the opportunities to improve human practices that could possibly lead to behavioural changes? The A-S-S-I instruments encourage designers to rethink strategies that enables behavioural changes through spatial design such as accessibility, mobility, urban fabric (density) and housing typologies.

CHANGE IN SOCIO-CULTURAL VALUES Provision of infrastructure to accommodate low carbon behaviour without changing the meaning of practices, eg. improving modes/reducing numbers of travel instead of travel limitation

LOW CARBON MODE OF CONSUMPTION New housing typologies to encourage pursuit of collective living requires integration of urban planning: land use, transport system, green spaces and water

IFT SH

toward s

S O IMPR VE

260

Conclusion

For example, the approach addresses the human practices of purchasing goods by investigating at: Avoid: How far do I need to travel? Shift: Which mode of travel is available and most convenient to me? Share: Do I need to possess this good? Improve: Which type of goods do I need to purchase for what purpose?

Designing for behavioural change It is a major design challenge to change consumption patterns and stop the massive overconsumption of non-essential goods or services. Changing human behaviour means challenging their existing practices and individual values thus contribution to a low carbon society should never be solely an individual responsibility but through a collective effort. • Lifestyle related carbon footprint can be reduced through the practice of low carbon behaviour. Change in daily food practices can reduce reliance on high carbon-intensive diet. Integrated energy resources such as communal heat pump can increase the overall efficiency of household heating system.

OID requires AV

• Participation in urban farming activities can change human food practices. They can have much deeper appreciation of the food system and be much conscientious about food waste. From the study, it seems possible that vertical farms

could reach a comparable carbon footprint as field growing if renewable energy sources are used and LED efficiency continues to improve. Urban gardening can also provide less obvious environmental benefits such as water saving and reducing urban heat. Various studies found that community gardens and rooftop farming can help filter out local air pollution, cool down cities and reduce storm water runoff into nearby waterways. • Low carbon living is associated with the planning of district/neighbourhood infrastructure to transform high desirable lifestyle options into low carbon means. The interlinked aspects of energy, water, waste, transport and buildings are fundamental in reducing carbon footprint of urban systems. Practical ways to lifestyle carbon footprint reduction include an improved planning of low carbon infrastructure development (such as communal car charging station, bike sharing station) aimed at reducing carbon footprint to zero in the longer term without compromising the quality of human life.

S TECHNOLOGY, FOOD, AND BUILDING SYSTEMS

AMENITIES AND RESOURCES Sharing of facilities such as communal electriccharging stations for cars or scooters, Shared mobility such as carpooling instead of car ownership provides people with alternative ways of travel

ENERGY

Improving the use of energy-efficient systems such as heating and emphasize the presence of renewables through community engagement. Improve sustainability of food system through urban household vegetable gardens (5)

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pilot results’ Dixit, M. K. (2013) Embodied energy calculation: method and guidelines for a building and its constituent materials. Ph.D. Texas A&M University. [Accessed on 23rd September 2021] Environmental Working Group Meat Eaters Guide: Methodology 2011 (N.d.) [Online] [Accessed on 17 November 2021b] https://static.ewg.org/reports/2011/meateaters/pdf/methodology_ewg_meat_eaters_guide_to_health_ and_climate_2011.pdf. Gerhards, J. (2019) One Planet Living® for new communities - Guidance on outcomes and indicators [Online] [Accessed on 20th October 2021] https://storage.googleapis.com/www.bioregional.com/downloads/OPL_ indicators-for-new-communities.pdf Greater London Authority (2018) Low Carbon Heat: Heat Pumps in London [Online] [Accessed on 17 November 2021d] https://www.london.gov.uk/sites/default/files/low_carbon_heat_-_heat_pumps_in_london_.pdf. Greenroofs (2021) BEDZED (BEDDINGTON ZERO ENERGY DEVELOPMENT) [Online] [Accessed on 20th October 2021] https://www.greenroofs.com/projects/bedzed-beddington-zero-energy-development/ Greig, R. (2020) Apples to apples: Are vertical farms better for the environment? Medium. [Online] [Accessed on 16 November 2021] https://robinsongreig.medium.com/apples-to-apples-are-vertical-farms-better-for-theenvironment-b80304ffa8cc. Gerhards, J. (2019) One Planet Living® for new communities - Guidance on outcomes and indicators [Online] [Accessed on 20th October 2021] https://storage.googleapis.com/www.bioregional.com/downloads/OPL_ indicators-for-new-communities.pdf Hallikainen, E. (2019) Life cycle assessment on vertical farming. How do CO2 emissions compare when we adjust for trade? (n.d.) Ourworldindata.org. [Online] [Accessed on 11th November 2021] https://ourworldindata.org/consumption-based-co2. Innovation (n.d.) Com.au. [Online] [Accessed on 11th November 2021] https://developmentwa.com.au/projects/ residential/east-village-at-knutsford/innovation. International Energy Agency (2016) Evaluation of Embodied Energy and CO2eq for Building Construction (Annex 57). EBC. [Accessed on 23th September 2021]

Department of Economic and Social Affairs. (2018) Classification of Individual Con-sumption According to Purpose (COICOP) 2018. [Online] [Accessed on 25th Sep] https://unstats.un.org/unsd/classifications/unsdclassifications/ COICOP_2018_-_pre-edited_white_cover_version_-_2018-12-26.pdf

Jones, C. and Kammen, D. (2011) ‘Quantifying Carbon Footprint Reduction Opportunities for U.S. Households and Communities.’ Environmental Science & Technology, pp. 4088-4095 [Accessed on 26th September 2021]

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Koide, R., Lettenmeier, M., Kojima, S., Toivio, V., Amellina, A. and Akenji, L. (2019) ‘Carbon footprints and consumer lifestyles: An analysis of lifestyle factors and gap analysis by consumer segment in japan.’ Sustainability, 11(21) p. 5983.

Druckman, A., Buck, I., Hayward, B., and Jackson, T. (2012) ‘Time, gender and carbon: A study of the carbon implications of British adults’ use of time.’ Ecological Economics 84. [Online] [Accessed on 7th October]https://www. sciencedirect.com/science/article/abs/pii/S0921800912003709

Kibwami, N and Tutesigensi, A (2014) Mathematical modelling of embodied carbon emissions of building projects. In: Raiden, A B and Aboagye-Nimo, E (Eds) Procs 30th Annual ARCOM Conference.

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The Urban Heat Island in all of its manifestaton is to an outcome of urbanazition. The simliest definition of the Urban Heat Island(UHI) is that it represents a dufference in the equivalent temperatures of the city (and its parts) and the surrounding natural area (Iain D. Stewart, Gerald Mills ,2021).

INTRODUCTION Issue

SECTION ONE

SECTION TWO

Context

A Wider System Map Related Factors

SECTION FOUR

SECTION FIVE

Approaches & Calculations

Towards Zero Carbon

SECTION THREE Considerations & Methods

SECTION SIX -References

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URBAN HEAT ISLAND CONTRIBUTIONS CONTRIBU TIONS TOWARDS ZERO CARBON

Holly Millburn, Effimia Athanasakopoulou, Giorgos Porakos

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Image Top: The Safeguard Group, Inc

Introduction

Regional Wind

Urban Plume

Urban Boundary Layer

temperature by 6.4 ± 2.3 °C. The magnitude of the temperature difference (UHI intensity) correlates positively with the size of cities.

Right Bottom: The vertical structure of the urban environment. The upper diagram shows the layering of the urban boundary layer into mixed and surface layers above an urban surface. The lower diagram represents part of the urban canopy that consists of facets that create a street. Within the street, micro climatic variations affect the near-surface air. Above the street, there are exchanges with the overlying air transfer, passing through the urban canopy layer into the boundary layer.

Mixed Layer

Rural Boundary Layer

Surface Layer

Outdoor Energy Exchanges between surface and mixed layers Indoor

Roof Facet

Wall Facet

Urban climates are the result of the interaction between meteorological conditions, urban structures and human

activities. The meteorological variables (e.g. temperature, humidity, radiation, wind patterns) are modified by the physical characteristics of the urban landscape (e.g. density and height of buildings, amount and distribution of open spaces, vegetation cover, construction materials), and by human activities that produce heat and atmospheric pollution, For example motorised transport, air conditioning, emissions from industries (Parlow 201), (Nastran et al. 2019). One of the key characteristics of the urban climate is that city temperatures are higher than temperatures in surrounding rural areas, referred to as urban heat islands (UHI). According to Venter et al. (2020), the effect of UHI is to increase average

Building Height (H)

UK cities and the surrounding rural areas will increase at 0.45oC to 0.81oC per decade by 2080 under a high emissions scenario, depending on the time of day and location. These warming rates are up to about four times higher than the global warming rate since 1981. Urban Heat Island (UHI), is often the result of a combination of factors that are found in urban areas: buildings, narrow roads, reduced vegetation, air pollution, traffic, domestic energy use and industrial processes (E. Lo, D. Mitchell, 2020).

Road Facet Street Width (W)

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Issue

Image adapted by author from: Lehmann, S. (ed.) (2015) Low carbon cities: transforming urban systems. London ; New York: Routledge

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Context Why look into UHI?

UHI effect acts as an indicator to wider climate issues. Addressing the causes of UHI effect allows us to target zero carbon initiatives that work at an urban scale (Stewart and Mills, 2021) which also alleviate the negative effects that UHI can have on health and wellbeing. Heat waves killed almost 900 people in England 2019 (Delivering a ‘Net Zero’ National Health Service, 2020) and this numbe is likely to iuncrease as temperatures steadily increase with climate change. For example the introduction of green spaces (a key factor used in the reduction of UHI) which have been proven to improve the mental and physical wellbeing of those who interact with those spaces.

Regional Wind

Surface Layer

Rural Boundary Layer

Rural

Urban

When taking action on certain parameters to tackle carbon emissions, the result can often be high density urban living, which may be highly energy efficient, but cause cause ‘heat stress’, either increased electrical demand for cooling, or increased health problems associated with heat (Stewart and Mills, 2021). Studies such as ‘Land surface temperature and energy expenditures of households in the Netherlands: Winners and losers, 2020’ highlight the fact that mitigating UHI has the benefit of reducing dramatic changes in climate at an urban scale, and can reduce the likelihood of fuel poverty occuring. Research so far indicates the metabolic processes of cities are more efficient (i.e., less resource used per capita) if cities are more physically compact both in building and population density, as infrastructure costs are reduced. Pursuing this goal using conventional urban development policies will result in taller, closely spaced buildings with less vegetative cover, which will enhance the UHI and increase the population exposed to its effects. This means that, although the energy demand per capita is reduced (positive), local environmental quality may be diminished through excessive shading, loss of ventilation, and enhanced UHI (negative).

Slowed Turbulent Winds

Reduced Outgoing Longwave Rdiation

Low Sky View Factor

A/C Thermal Mass

Trapped Warm Air

A/C Anthropogenic Heat

Anthropogenic Heat Thermal Mass

Thermal Mass

Canopy Layer Surface Layer

Dark, Hard and High Thermal Capacity Surfaces

Light, Permiable, and Low Thermal Capacity Surfaces

Image created by author from information at: Kershaw, T. (2017) Climate resilience in urban environments.

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UHI & Zero Carbon Cities The impact UHI can have on reducing carbon emissions Increased Urban Heat Surface Layer Island effect

Regional Wind

Because the focus on energy use in the context of Zero Carbon initiatives (in the U.K) is often based on the heating demand, we felt that by investigating the cooling demands through the study of the urban heat island effect, we could offer the most robust analysis of the Zero Carbon initiatives available to Manchester City Council at this time. The urban heat island is a phenomenon which occurs in urbanised environments such as Manchester, and although is not an entirely new occurrence, will likely increase in frequency as the temperature on earth gradually increases over the next few decades. The primary benefit in addressing heat stressors in designs at this point in time is that we can prevent lot of the negative effects of the urban heat island before they become extreme. In the case of Manchester, the urban heat island is already present and significant, and yet there are minimal measures in place currently to prevent it worsening. In London, where the UHI intensity (UHII) is worse, there are only now some mitigation strategies being considered. In Chicago, just one deadly heat wave which killed 525 people in 1995 was enough to spark a citywide effort to tackle overheating and the urban heat island (Changnon et al, 1996). As a result, they have not since had a repeat of the mortalities reached during that heatwave, despite temperatures actually increasing since, as has been the case world wide.

The cost of cooling is already costing the city a lot of carbon during the summer months. While the push for increasingly energy efficient and well insulated buildings is good for heat retention in the winter, in the summer this increases the electrical cooling load. By taking measures that mitigate the urban heat island, we can prevent excessive cooling loads in the summer, even as temperatures continue to increase outside of our control.

Rural

Urban

Slowed Turbulent Winds

Thermal discomfort

Reduced Outgoing Longwave Rdiation

Low Sky View Factor

A/C Thermal Mass

Trapped Warm Air

A/C Anthropogenic Heat

Anthropogenic Heat Thermal Mass

Rural Boundary Layer

Thermal Mass

Canopy Layer Surface Layer

Dark, Hard and High Thermal Capacity Surfaces

Light, Permiable, and Low Thermal Capacity Surfaces

Cooling demand

Increased energy demand

82531.56 Tonnes of CO2 per annum in Manchester

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Context

Image by author

CO2

Increased CO2 emissions

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UHI in Manchester The extent of the urban heat island effect on our site

Manchester Cooling Degree Days 2020-2021 July - September

Using population density to calculate UHII Because calculating the Urban Heat Island Intensity can be difficult due to so many complex factors involved, there are some variations in the exact method of calculation, however the generally accepted method is to compare the urban with nearby rural environment. The distribution of population gradually reduces from urban to rural region, which is almost consistent with the process of urbanization. Where UHII is the urban heat island intensity, TU is the annual/seasonal mean temperature of the respective urban station, and TR is the annual/seasonal mean temperature of the respective rural station (Arifwidodo and Chandrasiri, 2015).

UHII = TU − TR For Northern Gateway during hottest month:

20+12 = 32/2 = 16 19+11= 30/2 = 15 16 - 15 = 1 UHII for Victoria North

Date

image created by author using data from: Degreedays.net.

Average temperatures in City of Manchester

Average temperatures in town of Oldham

image source: WorldWeatherOnline.com. 2021

kWh per capita in U.K (2014) : 5,130 Population of Manchester: 2,750,120 in 2021 City of Manchester:

1076.4766276378664 % increase in Joules per annum between Oldham and Manchester

The UHI is likely to get worse over time

Month: July -September

Time: Night

Temperatures, cities and populations will increase steadily over the next few decades Thermal discomfort to rise 60% in Manchester by 2050 (Levermore et al, 2015)

Lower heating load, higher cooling load, and lower wind speeds for reduced air flow

UHI levels can reach highs of 8 in Manchester at night

1961-1990

Therefore can assume that a 1076% increase in Joules contributes to the UHII increasing by 1.

5130 x 2,750,120 = 14108115600 kWh = 5.078921616e+16 Joules

Manchester temperatures forecast to continue to rise up by 3oC by 2080 (www. resin-cities.eu)

Oldham: 5130 x 233,759 = 1199183670 kWh = 4.317061212e+15 Joules

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Context

1971-2000

image source: www.resin-cities.eu

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Heat Sources

Heat sources that are the primary factors in urban heat island intensity in the canopy level

Various sources of heat in Manchester

Annual heat expenditure of Manchester population: 9.1263246e+15 Joules per annum

We can summarise this through examining the key causes of the UHI and its solutions. By preparing for an increased UHII, this means that the physical well- (2535.0901666667 GWh) being of the inhabitants will be less affected by a more extreme UHII situation, reducing the need for later Building cooling and ventilation systems: building works and behavioural changes to take place. The future increases in temperature could decrease the Annual heat expenditure: demand for energy used on space heating, which is currently at around 42% of energy use but will likely 6.46416E+15 Joules per annum increase the energy used for cooling. It is likely that 1 in 4 UK homes will have an air conditioning unit by (1795.6 GWh) 2030 (Collins et al, 2010). Transport: (road vehicles are largest form of transport Although the majority of buildings in Manchester do co2 emissions) not have air conditioning units, the use of electricity increases when temperature increases to above Annual heat expenditure: comfort levels. The use of electric cooling systems causes more CO2 than the gas used for the majority 5.0726376e+16 Joules per annum of heating systems, so although the amount of energy used for cooling is currently lower than the energy (14090.66 GWh) used for heating, the impact on climate change is more pronounced (Collins et al, 2010). Peak urban electric demand has been found to rise by 2% – 4% for each 1oC rise in daily maximum temperature above a threshold of 15oC to 20oC (Akbari and Taha 1992). In order to calculate the estimation for electricity used for cooling. Building heating is still currently the biggest energy expenditure for greater Manchester. This is energy in the form of heat directly released into the atmosphere. However, because this is mostly used during winter when the cooling demand is negligible, we have omitted this from our findings as we are only looking at peak cooling degree days during the year, and the heating demand is ususally negligent during these times.

20000

Human body heat: GWh per annum

Because the canopy level is where most of the ill effects on people are felt with UHI, this is where we should concentrate efforts to reduce UHI.

15000 10000 5000 0 Building cooling

Body heat

Transport

BUHI

CUHI SUHI GUHI

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image created by author using data complied to the left

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UK Cooling Demand

over the temperature in these types of buildings and therefore it could be difficult to argue a significant change in the reduction of cooling demand for these particular building types. therefore greater focus is placed on domestic temperature control.

Context

However due to the amounts of excess waste produced by tertiary and industrial buildings such as data centres, there is an opportunity to recover heat to be reused either in the same building or elsewhere.

40 35

Tertiary buildings e.g Offices, schools, supermarkets, logistics centres and hospitals. All require some kind of air cooling or air conditioning.

30 TWh/year

There is opportunity for Victoria North to connectto the city centre located data centres, as well as have a waste water treatment point within 100-300m of the dwelling sites. Greater Manchester has 10 NHS hospitals (mft.nhs.uk) which could provide significant waste heat to be recovered. The Civic quarter heat network that is currently under construction would be an opportunity for waste heat to be process and redistributed in close proximity to our site and therefore reducing transmission loss.

25 20 15 10 Process Cooling

Hospitals are present in most cities, and all require a considerable amount of cooling, therefore they could be a good source of heat recovery. The NHS has outlined their plans to become net zero carbon by 2040. (Delivering a ‘Net Zero’ National Health Service, 2020) .

Space Cooling Belgium

Netherlands

Poland

Malta

Bulgaria

Romania

United Kingdom

Germany

Cyprus

Portugal

France

Greece

Spain

Italy

Electricity consumption for cooling by country Image adapted by author from: Heatroadmap.eu

The image above highlights that the U.K comes in 8th place in the consumption of electricity for cooling. Process cooling makes up the majority of this, however, it is interesting to note that although the average temperature of the U.K is 14 oC. Whereas Malta has an average yearly temperature of 23 oC. Why are we spending more electricity per year on cooling than a country thats 9 oC hotter than ours? Reason 1: Data centres A mid size data centre with 1 MW IT load releases 3,700 MWh thermal energy per year into the atmosphere (equivalent to around 0.46 MWhth of waste energy/MWh of electricity consumed by the data centre). The energy requirement of the cooling system in a data centre usually takes up 40% of the overall energy consumption.

The energy consumption of data centres is expected to have increased to 104 TWh/year in 2020. This is mainly due to an increase in digital services and products. There are currently 20 colocation data centres in the Greater Manchester area. (colocation meaning data centres privately rented) The second highest concentration of colocation data centres in the U.K, second only to London.

Heat exchanger

The potential waste heat that could be recovered by data centres in the future amounts to 48 TWh/year 17 centres are within 7 miles of our site. Reason 2: Tertiary Buildings Building such as schools and hospitals are always going to require a high cooling demand due to the strict requirements around the safety of the occupants. There will always need to be a good level of control

CO2 heat pump

water to air heat exchanger

Opportunity to collect excess process cooling heat through heat exchanger image created by author using information from www.reuseheat.eu

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Wider Systems Map This systems map diagram helped us at an initial stage to gather all the components we found in relation to the urban heat island effect and start creating connections about how one thing influences the other. We have identified there are three main causal factors that influence UHI: anthropogenic heat, impervious surfaces, and three-dimensional urban geometry. On the other hand, in order to mitigate UHI effects green infrastructure such as urban forest and green roofs come in to play. This is because green infrastructure provides one of the most promising opportunities to significantly reduce urban temperatures. Extensive green infrastructure in cities increases the summer precipitation which in turn adds to cooling effects. Overall, we have identified that green infrastructure can include permeable high albedo pavements, green streets, urban tree canopy, land conservation, green walls, and green and cool rooftops. As Green infrastructure is helpful to mitigate UHI we will also examine it and its effect.

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Wider Systems Map

image created by author

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Metrics for UHI Key ‘Ingredients’ That Cause UHI Effect

Considerations & Methods The urban heat island (UHI) has been a subject of study for a very long time. Opportunities to mitigate (or enhance) the UHI are best examined by managing the form (geometry, layout), the surface cover (materials composition, green infrastructure) and the function (metabolism) of the city in response to its background climate (G. Mills, 2014). In terms of geometry, by altering the layout of a city by decreasing built density and reducing H/W ratio, and increasing sky view factorm this can reduce UHI effects. This impacts the urban canopy layer and enhances long-wave radiation loss, which is one of the main reason for the night-time canopy UHI (G. Mills, 2014). Changing material composition of urban fabric can also impact surface temperatures (G. Mills, 2014). Cities have been built of hard and impermeable materials that were selected for the durability and strength. A problem that occurs with that, is the precipitation on such surfaces is quickly removed and very little water is stored. As a consequence, these materials have little capacity to cool by evaporation. However, the easiest and most effective intervention is to alter the surface albedo. Many urban spaces have a low albedo so that they absorb the majority of solar radiation which is the driver for increased daytime surface temperatures. Increasing the green infrastructure in urban areas is one of the main strategies to mitigate the urban heat island effect. Planting vegetation improves the urban climate by moderating the effects of sun, wind and rain (Santamouris, Kolokotsa, 2014). Strategically located green spaces may also reduce the cooling energy consumption between 25% to 80% (Shashua et al, 2000).

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Considerations & Methods

Regulating the anthropogenic heat flux will moderate the UHI but it will not offset it. For example, note that the canopy-level UHI is strongest at night in densely built area of cities where there are often few occupants and little traffic. On the other hand, managing the UHI during warm periods will reduce the need for anthropogenic heat flux from airconditioning systems.

Low Wind Speed During Summer

Anthropogenic Heat

Urban Canyons

Solar Radiation Natural geography

High Heat Capacity Materials

Lack of Green Spaces

Dense population

How to Measure

Air Temperature

How to Gauge Extent

Cooling Load

Heating Load

Thermal Comfort

Human Repercussions Heat Related Mortality

Increased Spending on Energy

Carbon Repercussions Increased Co2 Emissions

image created by author

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System Dynamics Considerations & Methods

The system dynamics diagram helped us to understand the non-linear behaviour of Urban Heat Island and its components over time. Through the diagram we were able to identify how certain aspects of Urban Heat Island contribute to it and how they are interrelated. For example we have identified that the anthropogenic heat leads to a closed loop of air pollutants, heating and cooling that result in increased C02 emissions. This will help us to make better decisions in our zero carbon city in order to mitigate Urban Heat Island

image created by author

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Urban Heat Transfer Sankey Considerations & Methods

This diagram attempts to unpack the ‘chain reaction’ of events and factors that lead to the expulsion of heat into the atmosphere. From heat sources ‘inputs’ to comfort and waste ‘outputs’ there are many factors at play but in this image we focus on the physical rather than societal factors that contribute to the effects of UHII as a means to explain the process as concisely as possible. Because the majority of UHII is causes by anthropogenic heat, the processes surrounding them are complex. For the purposes of this diagram the elements are put into a form of chronological order or sequence of events, but in reality these elements all feed into each other and sometimes unexpectedly effect other factors.

image created by author

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Parameters affecting UHI

The four categories below (geometry, materials, green infrastructure, metabolism) will be the key drivers to examine in the next section that will help us to explore ways on how to mitigate UHI.

Building Geometry

Green Infrastructure

Improve

Adjust

Air Circulation

Evapotranspiration

Albedo

High Albedo (Reflects)

Shading

Metabolism

Materials

Outgoing Longwave Radiation

Adjust

Traffic

Low Albedo (Absorbs)

Emmisivity

Lighting

Thermal Conductivity

Anthropogenic Heat

Thermal Energy

Wind Flow

Overshadow

Thermal Energy +°C

Thermal Conductivity

+°C -°C

-°C

images created by author

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Considerations & Methods

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Replace HPS to LED Street Lamps

<7000 People per Sq.km 2021 CPU[AI]

Replace HPS to LED Street Lamps

Metabolism - Transport

<1% Heat Waste from LED Street Lights

Approaches & Calculations

15% of Heat Waste from HPS Street Lights

Switch from HPS to LED street lamps Fuel efficiency in cars is approximately 20 - 30%, therefore 70 - 80% of this is being released into the atmosphere primarily through the exhaust system and radiator. Vehicles are a major factor that contributes to UHII. Vehicular use in Manchester has had a steady increase from 2010 to 2020, the pandemic had a dramatic effect on traffic but this could be misleading, and we must take into account that this will probably increase sharply once the effects of Covid19 are less severe (roadtraffic.dft.gov.uk)

then completely replacing all vehicles travelling through Manchester throughout the year with EV’s would result in: a 1.004805648e+15 Joule decrease in heat each year produced by vehicles.

Replace HPS to LED Street Lamps

<1% Heat Waste from LED 15% of Heat Waste from Street Lights Street Lights <7000 People perHPS Sq.km

The annual heat produced by vehicles based on the number of vehicles, estimated fuel consumption and efficiency, taking into account the 0.77% of UK vehicles being EV’s, in Manchester is: 5.0726376e+16 joules

A 2012 Beijing study (Li et al, 2015) concluded that the replacement of all conventional vehicles with electric vehicles would reduce the temperature of the city by 0.94oC due to the EV’s being 19.8% more efficient in their fuel consumption.

Public transport over car

Change to Electric Vehicles

Change to Electric Vehicles <1% Heat Waste from LED Street Lights

15% of Heat Waste from HPS Street Lights

If we assume the electric cars in the U.K would perform similarly to those in the Beijing study (19.8% of CV’s)

85% Fuel Efficiency 15% Fuel Loss

Change to Electric Vehicles

12.97kWh p 4 People C

30% Fuel Efficiency 70% Fuel Loss

30% Fuel Efficiency Switch from 70% Fuel Conventional to Loss Electrical vehicles

380.75kWh 60 People C

Public transport over cars 85% Fuel Efficiency 15% Fuel Loss

30% Fuel Efficiency 70% Fuel Loss

85% Fuel Efficiency Switch from low 15% Fuel Loss Annual traffic by vehicle type in Manchester

to high passenger capacity vehicles

12.97kWh per 100km 4 People Capacity

380.75kWh per 100km 60 People Capacity

image source: roadtraffic.dft.gov.uk

290

Approaches & Calculations

images created by author

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Metabolism - People Approaches & Calculations

The human body is constantly adjusting using thermoregulation. When functioning properly, the body maintains a deep body temperature (Tb) of 37± 2oC (G. Mills, 2021) The albedo of human skin is 0.15 (this can be raised or lowered with light of dark clothing) however this is not sufficient against all levels of radiation (G. Mills, 2021). Radiation load leads to discomfort, discomfort leads to energy usage. Peak urban electric demand has been found to rise by 2% – 4% for each 1oC rise in daily maximum temperature above a threshold of 15oC to 20oC (Akbari and Taha 1992) indicating that excess heat leads to the use of mechanical cooling systems for relief.

Because of how much of our thermal comfort equates to health and mood, we put a lot of effort into ensuring our environment is an ideal temperature, and therefore use energy for this. This ability to adjust indoor temperatures is often not available to all of society, and therefore in order to accurately calculate the extent that this behaviour affects energy consumption, there must be an in depth analysis of the demographic of the people on our site and their access to temperature control systems.

Replace HPS to LED Street Lamps

source of short wave radiation

long wave radiation loss

short wave radiation loss

<7000 People per Sq.km

The increase in population density, i.e people per square kilometre, increases the temperature by about 0.22 Co for every 1500 additional people above 1000 (image created by author with information from Spencer, 2010)

15% of Heat Waste from HPS Street Lights

Change to Electric Vehicles

Approaches & Calculations

image adapted by author from: ‘The Urban Heat Island, A Guidebook, G.Mills 2021’

‘increased ambient temperatures to correspond to greater negative social <1% Heat Waste from LED behaviors’ (Lynott, et al, 2017) Street Lights

292

L source of long wave radiation

On average people in the UK consume 2173 calories per day (statista.com). This has gradually decreased over the last decade. 2173 calories per day = 9091832 joules x 2,750,120 (Manchester population) 2.5003629e+13 Joules

Radiation load = L + K

Public transport over cars

Approaches & Calculations 293

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Green Infrastructure

Types of Green Infrastructure

Approaches & Calculations Green Spaces

Green infrastructure is defined as “the strategically planned network of natural and seminatural areas with other environmental features designed and managed to deliver a wide range of ecosystem services” (European Commission 2013). Increasing the green infrastructure in urban areas is one of the main strategies employed to mitigate the urban heat island effect. Planting vegetation improves the urban climate by moderating the effects of sun, wind and rain (Santamouris, Kolokotsa, 2014:286). Strategically located green spaces may reduce the cooling energy consumption between 25% to 80% (Shashua et al, 2000). Usually, green spaces are found in open public areas (parks) but they can be also in the form of trees (tree cover and canopy), roof-top greenery and vertical greenery (green façades). These typologies are useful for urban planning as they allow for identifying and ensuring the diversity of components at different scales while recognizing their distinct contributions (M. Palme, A. Salvati, 2021). Although, roof-top greenery and vertical greenery, despite having a significant impact on the performance of the thermal comfort in the interior of the buildings, their contribution to the mitigation of UHI is not significant. Consequently, they will be not considered as possible solutions for tackling the UHI effect at an urban scale (Lobaccaro and Acero 2015).

Approaches & Calculations

Roof-top Greenery

Vertical Greenery

Research has provided rich evidence of the capacity of green infrastructure to decrease high urban temperatures and mitigate the UHI effect. The mechanisms that help green infrastructure mitigate extreme city temperatures is through evapotranspiration, shading and wind flow. Other positive impacts of green spaces includes improving air quality and reducing greenhouse gas emissions by reducing energy consumption, enhancing storm water management and water quality, and improving the aesthetic of an area (Santamouris, Kolokotsa, 2014:286). There has been a growing number of publications in recent years that deal with the multi functionality of green infrastructure, ranging from site-specific studies that analyse the multiple benefits and functions of green areas to landscape ecology approaches that propose concepts like multifunctional networks and landscapes (Wang and Banzhaf 2018).

“Strategically located green spaces may reduce the cooling energy consumption between 25% to 80%” (Shashua et al, 2000). 294

Trees

Significant Impact on UHI

Negligible Impact on UHI

image by author

Green Infrastructure Cooling Mechanisms Evapotranspiration

Shading

Wind Flow

image by author

The shade provided by plants keeps the air cooler by simply intercepting solar radiation and preventing energy absorption by urban surfaces and reradiation of heat to the canopy layer atmosphere (Gunawardena et al. 2017; Oke 1989). The effectiveness of shade is determined by leaf size, crown area and leaf area index (LAI) of plant canopies. The percentage of tree (and shrub)

cover is directly related to the reduction of air temperature by interacting with the reduction of solar radiation and evapotranspiration, as Chang et al. (2007) reported based on measurements of unshaded areas of urban parks.

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Green Areas

Studies Investigating the Cooling Effect in Different Scale Urban Green Spaces

Large Scale Green Spaces Large> Scale 20ha Green Spaces Large Scale > 20ha Green Spaces > 20ha

Size: 147ha CED ≈ 200-300m Size: 147ha CEImax ≈ 1.9°C CED ≈ 200-300m Size: 147ha CEImax ≈ 1.9°C Size: CED ≈111ha 200-300m CED ≈ 20-440m CEImax ≈ 1.9°C Size: 11ha - 4°C CEI ≈11.1°C CED ≈ 20-440m Size: 11ha - 4°C CEI ≈11.1°C Size: CED ≈102ha 20-440m CED NM - 4°C CEI ≈≈1.1°C Size: CEI ≈102ha 2°C CED ≈ NM Size: CEI ≈102ha 2°C CED ≈ NM CEI ≈ 2°C

Size: 21.42ha CED ≈ NM Size: CEI ≈21.42ha 1-2°C CED ≈ NM Size: CEI ≈21.42ha 1-2°C Size: CED ≈26.01ha NM CED NM CEI ≈≈1-2°C Size: CEI ≈26.01ha 1°C CED ≈ NM Size: CEI ≈26.01ha 1°C Size: CED ≈1507ha NM CED NM CEI ≈≈1°C Size: CEI ≈1507ha NM CED ≈ NM Size: CEI ≈1507ha NM CED ≈ NM CEI ≈ NM

Medium Scale Green Spaces Medium 0.1ha -Scale 12ha Green Spaces Medium Scale 0.1haSpaces - 12ha Green 0.1ha - 12ha

Size: 0.2ha CED ≈ 1m Size: CEI ≈0.2ha 0.34°C CED ≈ 1m Size: CEI ≈0.2ha 0.34°C Size: CED ≈0.3ha 1m CED 1m CEI ≈≈0.34°C Size: CEI ≈0.3ha 0.32°C CED ≈ 1m Size: CEI ≈0.3ha 0.32°C Size: CED ≈0.8ha 1m CED 22-44m CEI ≈≈0.32°C Size: CEI ≈0.8ha 0.57°C CED ≈ 22-44m Size: CEI ≈0.8ha 0.57°C Size: CED ≈2.5ha 22-44m CED 46-218m CEI ≈≈0.57°C Size: CEI ≈2.5ha 0.42°C CED ≈ 46-218m Size: CEI ≈2.5ha 0.42°C CED ≈ 46-218m CEI ≈ 0.42°C

Size: 2.9ha CED ≈ 45-149m Size: CEI ≈2.9ha 1.9°C CED ≈ 45-149m Size: CEI ≈2.9ha 1.9°C Size: CED ≈3.8ha 45-149m CED 10-85m CEI ≈≈1.9°C Size: CEI ≈3.8ha 0.77°C CED ≈ 10-85m Size: CEI ≈3.8ha 0.77°C Size: CED ≈10.1ha 10-85m CED 173-179m CEI ≈≈0.77°C Size: CEI ≈10.1ha 0.56°C CED ≈ 173-179m Size: CEI ≈10.1ha 0.56°C Size: CED ≈12.1ha 173-179m CED 329-328m CEI ≈≈0.56°C Size: CEI ≈12.1ha 0.98°C CED ≈ 329-328m Size: CEI ≈12.1ha 0.98°C CED ≈ 329-328m CEI ≈ 0.98°C

Approaches & Calculations

In 1989 T.R. Oke proposed the concept of Park Cool Island (PCI), which in mid-latitude cities should be 1–2°C cooler than surrounding areas, and rarely more than 3°C cooler, although under ideal conditions it could be as much as 5°C, as Spronken-Smith and Oke (1998) found in Sacramento (5–7 °C), while Barradas (1991) recorded differences of up to 5.6 °C. They also found that size strongly influences the cooling effect of parks. The above studies, in addition to others that were examined, report that the magnitude of temperature difference varies because of external variables like the macro scale climate or the use of surrounding land (e.g. homes with green yards or paved surfaces). They also describe the importance of internal characteristics of urban parks, such as morphology, irrigation and tree density, to maximize the adjective influence beyond its borders. For that reason and by considering the wider use of this document, the employment of a simple calculation model is necessary. In 1991, Jauregui established that park cooling may be measured up to one park’s width away from its boundaries, which is consistent with several other studies (M. Zinzi, M. Santamouris, 2019). This ratio proved to be an effective way that could be used as a rule of thumb for future low complexity experiments on this matter.

296

Approaches & Calculations

As K.R. Gunawardena, M.J.Wells and T. Kershawa (2017) mention, geometry is significant here, with square or round-shapes said to provide higher cooling efficiency and distribution. This is explained with reference to the greater opportunity for increased temperature and humidity gradients and fetch between the body and its surrounding landscape (Shi et al., 2011; Sun and Chen, 2012). The range of distribution experienced is also dependent on the vegetation profile (trees, shrubs or grass) and its heterogeneity (Gill et al., 2013). A minimum effective size of green space areas to consider, with Doick and Hutchings (2013) highlighting green space smaller than 0.05 km2 as offering negligible cooling contribution. This gives weight to the hypothesis that a certain fetch is required to create a park-breeze system and that larger parks are able to create larger parkbreezes allowing for greater cooling transport into the surrounding urban fabric, even for a minimal temperature gradient. Additionally, the shape and orientation of the park (with respect to wind speed) have been investigated and they both exerted a very limited influence compared to park size. Consequently, green spaces have a great capacity to alleviate heat waves, but they have to be located strategically within the urban fabric.

Size: 0.07ha CEI ≈ 1.7°C Size: 0.07ha CEI ≈ 1.7°C Small Scale Size: 0.01ha 0.07ha Size: Green Spaces CEI ≈≈ 0.5°C 1.7°C CEI Small Scale < 0.1ha Size: 0.01ha Green CEI ≈ 0.5°C SmallSpaces Scale Size: < 0.1ha Size: 0.01ha 0.3ha Green Spaces CEI CEI ≈≈ 0.5°C 4.5°C < 0.1ha Size: 0.3ha CEI ≈ 4.5°C Size: 0.3ha Image created by author from information at: Aram, F., Higueras García, E., Solgi, E. and Mansournia, S. CEI ≈ 4.5°C (2019) ‘Urban green space cooling effect in cities.’ Heliyon, 5(4) p. e01339.

Size: 0.06ha CEI ≈ 1.5°C Size: 0.06ha CEI ≈ 1.5°C Size: 0.2ha 0.06ha Size: CEI ≈≈ 4.1°C 1.5°C CEI Size: 0.2ha CEI ≈ 4.1°C Size: Size: 0.2ha 0.093ha CEI CEI ≈≈ 4.1°C 2°C Size: 0.093ha CEI ≈Effect 2°C CED : Cooling Intensity Size:Effect 0.093ha CEI : Cooling Distance CEI ≈ 2°C CED : Cooling Effect Intensity CEI : Cooling Effect Distance CED : Cooling Effect Intensity

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Green Areas Distribution

Computational Tool for Calculating Green Areas Green Spaces Location Through Circle Packing

Boundaries through Random Points

Offset Half their Size for Green Spaces

Relate with Closer Parcels

Final Green Spaces Distribution

Continuous Air Flow

image by author

298

Approaches & Calculations

image by author

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Trees

Trees Coverage & Arrangement Tree Coverage

Approaches & Calculations

Placement

N N

Trees Block 70% - 90% of Solar Radiation. (M. Palme, A. Salvati, 2021)

Trees are more effective in mitigating high temperatures than other types of plants (M. Palme, A. Salvati, 2021). Trees and vegetation shade surfaces from solar heat by 70% - 90%, keeping them cooler and reducing the energy they store. Increasing tree cover create differences of up to 9–10 °C between planted and paved surfaces, as has been registered previously in cities like Oslo and New York. Large well-watered tree can process up 400L of water and remove 960MJ (910kBTU) of heat a day during summer. In order for trees to mitigate UHI, it is estimated that in cities with abundant water, tree coverage should be around 40% while drier cities should be at 25%. Trees should be placed at eastern and westerns windows and should be at least 1.5 – 3m high to not cover views and block any breezes between 1.5m-3m and 10m-15m away from the building. At the street level, 0.5m - 2m high trees should be placed on both sides of the road at regular intervals of 6m - 12m. It is more preferable to use deciduous trees of an average height of 13 m, C3type, with an average albedo value of 0.2, average crown width of 9 m, and a LAD (Leaf Area Density) ranging from 0.5 to 2. More specifically, C3-type plants are referred to as the temperate or cool-season plants that are most efficient at photosynthesis in cool, wet climates. Also, deciduous trees provide significantly less shade in the colder months due to the loss of leaves, allowing solar access to horizontal and vertical surfaces (mainly pavements, roads, and building walls), thus maximizing the absorption of heat from solar radiation. This in turn may have important positive consequences for building heating demands.

300

Approaches & Calculations

Planting urban trees can be argued to be a relatively low-cost, easy-toimplement, and climatically efficient measure against urban overheating. The application of a vegetation layer to building envelopes, more specifically to roof surfaces, may be more financially intensive and, in practice, more difficult to implement due to the issues of private property ownership. Thus, the implementation of urban trees might be the strategy that local authorities would more readily adapt (M. Zinzi, M. Santamouris, 2019).

<40% Tree Coverage <40% Tree Coverage

Distance from Buildings

Street Layout 6m <9m

<9m

6m 0.5m - 2m

<13m <13m

1.5m - 15m

0.5m - 2m

1.5m - 15m

image by author

Tree Species

Deciduous Trees (C3 Type)

Summer Time Summer Time

Winter Time

Winter Time -

+ +

Albedo Value = 0.2 LAI = 0.5 - 2 Average size tree remove 35lb(16kg) of CO2. Smaller slower-growing species remove 800lb(360kg) of CO2. image by author

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Geometry

Urban Geometry Parameters Affecting the UHI

Approaches & Calculations H/W Ratio Uniform Buildings

Urbanization has a substantial impact on the micro climate of cities. Building form governs or heavily influences many relationships between buildings and key urban environmental parameters such as shortwave radiation, long-wave radiation and airflow. The urban form is composed of urban canyons that are defined by the building’s height to street’s width ration (H/W ratio) and the orientation of their long-axis. These two descriptors are controlling the absorption and reflection of the solar and emission of the thermal radiation that influence the ambient air temperature to be significantly higher than the rural surroundings (Urban Heat Island effect). Furthermore, the urban geometry factor is subdivided into three sub factors: additional heat stored in vertical walls, radiation trapping, and wind speed reduction. In micro scale climate studies, the geometry of open spaces can be the most important parameter responsible for the variation of the micro climate (AliToudert and Mayer, 2006, Bourbia and Boucheriba, 2010, Oke, 1988, Stewart and Oke, 2012). In this context, urban geometry is usually associated to the formation of urban heat island factors. The geometry variation in urban environments may influence: the increase or decrease in air temperature values when compared to measured data in the outskirts of a city; the speed and direction of winds; and long and shortwave radiation exchanges.

According to Rajagopalan, Lim, and Jamei (2014), the factors affecting the occurrence and intensity of heat islands can be broadly classified into two categories. The first category is the meteorological factors including wind speed and direction, humidity and cloud cover. The second category is basically the product of city design, such as density of built up areas, aspect ratio, sky view factor (SVF) and construction materials. Theoretically, the larger the H/W ratio, the smaller the area of visible sky and dissipation of longwave radiation. Thus, large H/W reduces the cooling rate in urban areas, by reducing the turbulent transport due to the wind and the amount of anthropogenic heat release (Oke, 1987). In addition to the possible interference on UHI, which the H/W ratio can cause, one of the most significant changes produced by buildings is the air flow changes.

Non-Uniform Buildings

Uniform Buildings Building Height

Building Desired: >0.2 Height

Desired: >0.2

Street Width

Sky View Factor

Non-Uniform Buildings H1 = H2 ; W1 = W2, B1 = B2 SVF1 = SVF2

Building Height

H1 = H2 ; W1 = W2, B1 = B2 SVF1 = SVF2

Building Height

H1 ≠ H2 ; W1 ≠ W2, B1 = B2 SVF1 = SVF2 Street Width

H1 ≠ H2 ; W1 ≠ W2, B1 = B2 SVF1 = SVF2

Street Width

Air Flow Permeability

SVFmid-canyon = cos(atan(2 H/W)) Desired: 0.2 - 0.4 SVFmid-canyon = cos(atan(2 H/W)) Desired: 0.2 - 0.4

image by author

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Approaches & Calculations

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Materials

Relevant Properties of Ordinary Materials

Approaches & Calculations

Building Materials With

Urban materials contribute to the urban heat island effect by altering radiation exchanges, water retention and thermal storage within urban environments. Urban areas tend to exhibit net increases in rates of absorption of radiation and net decreases in long-wave emission rates when compared to rural areas (Oke 1992).

High

Materials are discussed in the heat island issue with their albedo. The application of building materials with high albedo to building envelopes leads to reduce the heat absorption (Aleksandrowicz, Vuckovic, Kiesel, & Mahdavi, 2017). Materials with high albedo in buildings have been especially evaluated in roofs. In addition, cool materials in paving are also evaluated in many cases. Materials Materials

Albedo Value Materials

Reduce Heat

Absorption

reflective materials are lower than those of conventional ones. Increased pollution in urban areas lowers the amount of direct shortwave radiation that reaches cities, mostly cancelling out the differences in albedo to result in roughly equal amounts of radiation absorbed by urban and rural areas (Oke 1982). Objects with higher emissivity and surface temperatures release absorbed energy at quicker rates than objects with lower emissivity and surface temperatures. Decreased emissivity of urban surfaces is overcome by increased surface temperatures, making the net long-wave exchange rates in urban areas similar to those in rural areas (Oke 1982).

At the global scale, implementation of reflective roofs and pavements over urban areas would induce a negative radiative forcing, which is equivalent to offsetting tens of billions tons of CO2 emissions (Akbari et al). Economic analyses show that manufacturing and life cycle costs of

Concrete

Albedo: 0.70

Albedo

Emmissivity Coefficient

Thermal Conductivity W/m·K

Embodied Energy MJ/Kg

Embodied Carbon KgC02e/Kg

Aluminium

0.85

0.09

205

170

6.67

Fiberglass

0.35

0.75

0.04

12.7

8.1

Plastic

0.30

0.90

0.02

28.8

2.7

Steel

0.35

0.23

60.5

24.4

2.7

Copper

0.74

0.03

401

105.0

2.7

Cement

0.40

0.54

1.01

18.3

1.0

Glass

0.30

0.92

1.0

1.4

Ceramic

0.01-0.35

0.91

3.8

18.9

0.7

Plasterboard

0.45

0.98

0.27

15.1

0.4

Timber

0.15-0.18

0.95

0.17

8.5

0.3

Brick

0.20-0.40

0.93

0.7

3.0

0.4

Concrete

0.10-0.70

0.85

0.93

1.39

0.1

Stone

0.20-0.40

0.90

1.26

0.85

0.1

Asphalt

0.05-0.2

0.95

0.90

5.00

14.2

Materials with a Good Combination of the Above Properties

The thermal behaviour of pavements is largely dependent on the different but interactive thermal properties of pavement materials such as thermal conductivity, specific heat capacity, density, albedo, thermal emissivity, and not on one single property alone. During the past decades, several strategies have been proposed, developed and implemented to mitigate UHI, including reflective materials materials with high optical and thermal performances, green roofs (also known as eco-roofs) , urban vegetation and shading , heat sinks to name a few.

Materials

Concrete

Albedo: 0.70

Concrete

Plasterboard

Albedo: 0.70

Albedo: 0.45

Emmisivity Coefficient: 0.85

Emmisivity Coefficient: 0.98

Thermal Conductivity: 0.93 W/m·k

Thermal Conductivity: 0.27W/m·k

Embodied Energy: 1,39 MJ/Kg

Embodied Energy: 15.1MJ/Kg

Embodied Carbon: 0.1 KgC02e/Kg

Embodied Carbon: 0.4 KgC02e/Kg

Plaster Concrete

Albedo:Albedo: 0.70 0.45

Plaster

Albedo: 0.45

Brick

Albedo: 0.40

PlasterBrick

Emmisivity Coefficient: 0.93

Thermal Conductivity: 0.7 W/m·k Embodied Energy: 3.0 MJ/Kg

Albedo:Albedo: 0.45 0.40

Embodied Carbon: 0.4 KgC02e/Kg

Albed

High Coefficient: Albedo (Reflects) Albedo (Absorbs) Emmisivity 0.98Emmisivity Coefficient:Low 0.98 Emmisivity Coefficient: 0.98 0.93Emmisivity C Emmisivity Coefficient: 0.85Emmisivity Coefficient: 0.85 Emmisivity Emmisivity Coefficient: Coefficient: 0.85 image by author

304

Approaches & Calculations

Conductivity: 0.27W/m·k Thermal Conductivity: 0.27W/m·k ThermalThermal Conductivity: 0.27W/m·k Thermal Conductivity: 0.93 W/m·k Conductivity: 0.7 W/m·k Thermal Conductivity: 0.93 W/m·k ThermalThermal Conductivity: 0.93 W/m·k Thermal 305Condu

Embodied 15.1MJ/Kg Embodied Energy: 15.1MJ/Kg Embodied Energy:Energy: 15.1MJ/Kg Embodied Energy: 1,39 MJ/Kg Embodied 3.0 MJ/Kg Embodied Energy: 1,39 MJ/Kg Embodied Energy:Energy: 1,39 MJ/Kg Embodied Ene

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Strategies for Mitigating UHI in Stuttgart

Case Study: Stuttgart Approaches & Calculations

Stuttgart in Germany demonstrates how some of the suggestions that we have investigated before can be applied successfully in order to mitigate UHI. We chose to study Stuttgart as it has some very similar characteristics with Manchester in terms of climate and population as well as providing us with some practical solutions to mitigate urban heat island effect.

Stuttgart

The City of Stuttgart in Germany used green corridors to bring cooler, cleaner air from the surrounding mountain region to the city that lies in a valley. Using existing tramways, the result is a mitigated UHI effect in the centre of the town.

Manchester

Stuttgart implemented their green tramways during construction, at a significantly higher cost to that of a standard tramway. Therefore implementing this in The Northern Gateway would only be an option for any new tramways built in the future on the right, we can see a similar topography between Stuttgart and Manchester, suggesting that the success Stuttgart has had with their green corridors could be replicated (Ketterer, Christine & Matzarakis, Andreas, 2014). The UHI effect extends through the lower atmosphere to a depth of 1–2 km during the daytime and will result in a thermally driven circulation. This circulation is initiated by the formation of a weak lowpressure system above the urban canopy layer that draws air from the surrounding landscape. This air rises slowly over the city centre, expands outwards at height and descends some distance outside the city, closing the circulation. Some cities have incorporated the near-surface circulation (known as a country breeze) into the city by encouraging wind corridors. However, cities will see more benefits from utilising existing natural spaces and adapting land use.

Preserve Local Winds & Streams

Ban Projects That Might Obscure Natural Ventilation Of Nocturnal Flows

39% Of Surface Has Been Listed As Protected Green Belt Land Or Nature Conservation Area

Greenery Covers Up 60% Of The City (12,000 Acres)

150 Acres Of Open Greenfield Land, Have Been Removed From Development Plan

3 Million sq.f Rooftops Greened

Population: 590.000 Metropolitan Population: 2.7m Density: 7,900/sq mi Average Temperature: 10 °C UHII: 1-2 °C

Population: 553.230 Metropolitan Population: 2.7m Density: 12,210/sq mi Average Temperature: 9.4 °C UHII: 1 °C

>1m

80cm

Image Source: LiliGraphie, City view. urban landscape. germany, stuttgart, Stock image

306

Approaches & Calculations

Trees Up To 1m High & With 80cm Trunk Are Protected with Preservation Order

image by author

150mil oF Tram Tracks Greened

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Tool for Calculating UHI Approaches & Calculations

By having identified all the parameters that contribute to Urban Heat Island and by gaining an understanding of this effect in the area of Manchester, we have developed a tool that could calculate the UHI effect in an urban environment. In our case, this was Victoria North in Manchester. The tool is based on an algorithm that was created with computational tools. This algorithm could take as inputs a variety of urban characteristics and values. Some of them could be building height to street width ratio, building geometry and layout, building function, green spaces, tree coverage, materials properties and coverage, anthropogenic heat activities, heat waste from air cooling and local weather characteristics of the focused area.

Tool Analysis Building Building Building Building Building Geometry Building Geometry Geometry Building Geometry Building Geometry Building Geometry Geometry Geometry Geometry Building Building Building Building Building Construction Building Construction Construction Building Construction Building Construction Building Construction Type Construction Construction Type Type Construction Type Type Type Type Type Type Building Building Building Building Building Materials Building Materials Materials Building Materials Building Materials Building Materials Materials Materials Materials Building Building Building Building Building Parameters Building Parameters Parameters Building Parameters Building Parameters Building Parameters Parameters Parameters Parameters Building Building Building Building Building Orientation Building Orientation Orientation Building Orientation Building Orientation Building Orientation Orientation Orientation Orientation Building Building Building Building Building Usage Building Usage Usage Building Usage Building Usage Building Usage Usage Usage Usage Output Output Output Output Output Output Output Output Output

Urban Urban Urban Urban Parameters Urban Parameters Parameters Urban Parameters Urban Parameters Urban Urban Parameters Parameters Parameters Parameters Urban Urban Urban Urban Materiality Urban Materiality Materiality Urban Materiality Urban Materiality Urban Urban Materiality Materiality Materiality Materiality

35.00°C 35.00°C 35.00°C 35.00°C 35.00°C 35.00°C 35.00°C 35.00°C 35.00°C 29.17°C 29.17°C 29.17°C 29.17°C 29.17°C 29.17°C 29.17°C 29.17°C 29.17°C

After all the inputs are fed into the algorithm, the tool will calculate the weather temperature for the chosen urban development. Then will compare this temperature with a related temperature in a rural area close to the urban development. The output will be a bar chart that allows someone to see the differences in temperature between the two areas and therefore conclude if the urban heat island effect could occur in the new urban development. The user also could go back and change some of Tool Diagram the inputs such as building geometry and materials in order to mitigate the UHI.

Building Building Building Building Building Height/ Building Height/ Height/ Building Height/ Building Height/ Street Building Street Height/ Street Street Height/ Width Height/ Street Width Width Height/ Street Width Ratio Street Width Ratio Street Ratio Width Street Ratio Width Ratio Width Ratio Width Ratio Ratio Ratio

23.33°C 23.33°C 23.33°C 23.33°C 23.33°C 23.33°C 23.33°C 23.33°C 23.33°C

Green Green Green Green Infrustructure Green Infrustructure Infrustructure Green Infrustructure Green Infrustructure Green Green Infrustructure Parameters Infrustructure Infrustructure Parameters Parameters Infrustructure Parameters Parameters Parameters Parameters Parameters Parameters

Urban Urban Urban Urban Weather Urban Weather Weather Urban Weather Urban Weather Urban Urban Weather Weather Weather Weather Generator Generator Generator Generator Generator Generator Generator Generator Generator

Green Green Green Green Spaces Green Spaces Spaces Green Spaces Green Spaces Green Green Spaces Spaces Spaces Spaces

17.50°C 17.50°C 17.50°C 17.50°C 17.50°C 17.50°C 17.50°C 17.50°C 17.50°C 11.67°C 111.67°C 1.67°C 11.67°C 11.67°C 11.67°C 11.67°C 11.67°C 11.67°C 5.83°C 5.83°C 5.83°C 5.83°C 5.83°C 5.83°C 5.83°C 5.83°C 5.83°C 0°C0°C 0°C0°C 0°C 0°C 0°C 0°C0°C

Trees Trees Trees Trees Trees Trees Trees Trees Trees

JulyJuly JulyJuly July July July JulyJuly

Antropogenic Antropogenic Antropogenic Antropogenic Antropogenic Antropogenic Antropogenic Heat Antropogenic Heat Heat Antropogenic Heat Parameters Parameters Heat Parameters Parameters Heat Parameters Heat Heat Parameters Heat Parameters Parameters Parameters

Urban Urban Urban Temp. Urban Temp. Temp. Urban Temp. Urban Temp. Urban Temp. Urban Temp. Urban Temp. UTCIUTCI Comfort UTCIComfort UTCI Comfort Comfort UTCI Comfort UTCI Comfort UTCI UTCI Comfort UTCI Comfort Comfort Rural Rural Temp. Rural Temp. Temp. Rural Temp. Rural Temp. RuralTemp. Temp. Rural Rural Temp. Rural Temp.Temp.

Human Human Human Human Human Metabolism Metabolism Metabolism Human Metabolism Human Human Metabolism Human Metabolism Metabolism Metabolism Metabolism Traffic Traffic Traffic Traffic Traffic Traffic Traffic Traffic Traffic Weather Weather Weather Weather Weather Parameter Weather Parameter Parameter Weather Parameter Weather Parameter Weather Parameter Parameter Parameter Parameter Lighting Lighting Lighting Lighting Lighting Lighting Lighting Lighting Lighting Local Local Local Local Weather Local Weather Weather Local Weather Local Weather Data Local Weather Data Local Data Weather Data Weather Data Weather Data Data Data Data Analysis Analysis Analysis Analysis Analysis Period Period Analysis Period Period Analysis Analysis Period Analysis Period Period Period Period

Input Input Input Input Parameters Parameters Input Parameters Parameters Input Parameters Input Input Parameters Input Parameters Parameters Parameters Designers Designers Designers Designers Designers Designers Designers Designers Designers

Process Process Process Process Process Process Process Process Process

Tool Tool Tool Outputs Tool Outputs Outputs Tool Outputs Tool Outputs Tool Tool Outputs Tool Outputs Outputs Outputs

Designers Designers Designers Designers Designers Designers Designers Designers Designe

image by author

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Approaches & Calculations

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Towards Zero Carbon Based on the average temperature of the amount of cooling degree days in Manchester per annum, the amount of increased energy used per temperature above the baseline for that area (in this case we arrived at an estimate of 18%) and the amount of CO emissions associated with that increase taking into account the energy consumption for the city, we are able to make an estimation of the amount of energy that could be saved if the UHII (urban heat island intensity) was reduced from the current average of 1 to an average of 0 (over the whole year).

The exact calculation is as follows for the findings on the right:

As with all calculations and assumptions,made throughout this research. We must emphasise that because we were not collecting the data ourselves there has been some level of estimation and assumption made in order to make logical calculations to provide helpful estimates. Therefore as the data is not raw and we have used calculations from reliable but second hand sources we cannot guarantee 100% accuracy in the CO2 figure supplied here, but we believe it to be a feasible and more than reliable estimate.

Average energy consumption for year, therefore portion of this used for cooling can be obtained when calculating the amount of energy use increased for every 1 degree increase in temperature over the baseline. this went from 12.6 GWh per day to 14.68 GWh per day.

If UHI reduced to: 0

Current UHI Level: 1

CDD 2 oC

CDD 4.5 oC

103 GWh

354 GWh

average degrees above baseline for cooling degree days for the last year in Manchester: 134 average degrees above baseline for cooling degree days for the last year in Manchester if UHI was at 0 (i.e the average temperature for the whole year was dropped by 1 degree C) : 95 (39 days now no longer above the baseline which is 15.5 degrees C)

However if UHII reduced to 0, then this becomes 13.6 GWh per day at the heights of cooling demand as the average CDD is only 2 degrees above baseline versus the current estimate which is 4.5 degrees.

24013 tonnes C02e

58518 tonnes C02e

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Portion of Electricity Used for Cooling

82531.56 tonnes C02e

Estimation of CO2 tonnes saved per annum if UHI reduced to 0

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Image Top: The Safeguard Group, Inc

Executive Summary • Based on our findings we can conclude that the urban heat Island is a significant issue in the city of Manchester and its surroundings including the Victoria North site

• The effective use and alteration of building materials, building geometry, green spaces and metabolism in a city can help to mitigate the negative effects of the urban heat island

• The current climate emergency suggests that overheating and cooling use will increase steadily, and the urban heat island will excacerbate the negative effects of these changes

• UHI mitigation will assist Manchester City Council in their goal to achieve Zero Carbon by 2038 through reducing the CO2 emissions associated with the cooling demand

• The implementations suggested in this chapter have also been deemed suitable suggestions to use in the Victoria North site

• The implementation of UHI mitigation will have many co benefits related to the well-being and general liveability of the city

• Addressing the urban heat island benefits current occupants of the Manchester area, but will also benefit future residents, who will have to contend with more extreme temperature changes over the next few decades

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Urban forests create natural habitats, help buildings save energy from wind pressure, improve air quality, and reduce erosion caused by falling rain. It also has significant effects on carbon storage and carbon sequestration. We will figure out the carbon storage and sequestration value of the individual tree and grass.

INTRODUCTION Intro to Urban Forest

SECTION ONE Manchester Report

SECTION TWO SECTION THREE SECTION FOUR Northern Gateway Report

Species Performance & Placement Rules

Suggestion for Improvement

CONCLUSION --

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URBAN FOREST

CONTRIBUTIONS CONTRIBUTIONS TOWARDS ZERO CARBON

Xinzi Deng, Yao Wei

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Introduction Background 70% of the global CO2 is emitted by cities

Forests are an important carbon sink, because trees capture carbon dioxide from the air through photosynthesis. However, living trees, as well as wood products, serve as carbon storages. The role of forests as carbon storage is a crucial service to cities (Palahí et al., 2020) Within city region boundaries urban forests – including individual trees and smaller urban woods – are fundamental components of the urban fabric. They provide a multitude of climate-related ecosystem services.

UK forests store around 1

billion tonnes

of carbon, the equivalent of around 4

billion

Contibution

IMPROVE WATER QUALITY

Urban forest soils provide important ‘soak away’ areas for surface water and the resulting soil moisture allows trees to provide evaporative cooling. and as such contribute to mitigating the urban heat island effect (Livesley et al., 2016). The capacity of trees and forests to provide cooling through evaporation is however negatively impacted by dry periods, which have increased in Europe (Haase 2019). - Improve air quality & climate - Reduce energy consumption - Ameliorate groundwater management - Advocate cycling & footpaths - Biodiversity

STORING CARBON

- Economic regeneration

tonnes of CO2 Carbon stock in UK forests is estimated to have increased, from around 3.2 billion tonnes of carbon dioxide equivalent in 1990 to 4 billion tonnes of carbon dioxide equivalent in 2020, stated by Forest Research. UNITS: •Carbon storage: metric ton; kg (individual trees) •Carbon sequestration: metric ton/yr; kg/yr (individual trees)

IMPROVE AIR QUALITY

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CANOPY COVER

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Define Urban Forest Understanding our current urban forests:

Forest Research The urban forest comprises all the trees in the urban realm – in public and private spaces, along linear routes and waterways and in amenity areas. It contributes to green infrastructure and the wider urban ecosystem. It provides diverse benefits to human society and it does so in vast quantities. Maintaining a healthy and diverse urban forest is critical to sustaining resilient delivery of these benefits, and requires understanding on the urban forest resource, including: species and age composition, distribution, and health status.

Theoretical basis The theoretical framework of urban forest is based on the Urban Forest Research Group of Urban Forest. Moreover, a Green and Blue Infrastructure Strategy for Manchester from Manchester City Council is as this study guideline. UNITS: •Carbon storage: metric ton; kg (individual trees) •Carbon sequestration: metric ton/yr; kg/yr (individual trees)

Knowledge on the extent and composition of the UK’s urban forests is required to inform strategic management and to build resilience to the impacts of climate change. The Group has expertise in urban canopy cover assessment and collecting detailed information on urban forests.

Mapping urban tree canopy cover in Northern Gateway: Knowledge of existing tree canopy cover forms the baseline for urban woodland creation. Mapping canopy cover of Northern Gateway did explore a canopy cover assessment using i-Tree Canopy.

Understanding our future urban forest: Investigating how our urban forests grow and perform can inform understanding of their likely contribution to urban society in the future. The Group is studying trees in-situ and woodland renew to understand the likely impects on urban forest performance by using its expertise in Carbon Dioxide Reduction Through Urban Forestry: Guidelines for Professional and Volunteer Tree Planters to recommend canopy cover targets for towns and cities in the UK.

Valuing urban trees (i-Tree Eco, Treezilla): The Group is using i-Tree Eco to calculate the valuation urban trees and non-woodland trees. Treezilla is an auxiliary measuring tool.

Assessment of ecosystem services: Ecosystem services are the benefits that society receives from the environment; these can be broadly categorised as: provisioning, regulating, cultural and supporting services. Our expertise spans the quantification and valuation of many regulatory ecosystem services, including mitigating urban heat, and air-borne pollution and storm-water abatement. The mapping of areas of expertise is shown in figure 1, left.

Figure 1. Areas of expertise in urban forest (Source: Urban Forest Research Group, online)

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System Map

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System Dynamic

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“Woodland area is increasing in the UK and now represents

Manchester Report

New planting, 13,300 hectares of new woodland were created in the UK in 2020-21. Restocking, 14,100 hectares of publicly funded restocking were reported in the UK in 2020-21. However, the urban forest is the most important part of sustainable development in the city. comprises all the trees in the urban realm - in public and private spaces, along linear routes and waterways and in amenity areas. It contributes to green infrastructure and the wider urban ecosystem. The urban forest needs self reliant, long lived trees. Younger trees should become our mature trees of the future. According to Urban Forest Research Group of Forest Research, yet there were fewer younger trees in the urban forest in 2008 compared to 1992. Larger trees, bringing particularly strong benefits are being cut down faster than they are being replaced. Trees

of total area”

Overall Assessment The carbon stored in UK forest soils accounts for almost 70% of the carbon stock. 51% of the UK public experienced an increase in their level of happiness when in woodlands and 43% an increased connection to woodlands in the 12 months since March 2020. Carbon stock in UK forests is estimated to have increased, from around 3.2 billion tonnes of carbon dioxide equivalent in 1990 to 4.0 billion tonnes of carbon dioxide equivalent in 2020.

13.3%

19%

15%

in urban areas can be badly affected by pests and disease, and a pathway for spreading these to the wider environment. It is critical we keep alert.

10%

We must plant a range of species to improve resilience to diseases and climate change. The Forestry Commission is working to slow, and where possible prevent, the spread of pests and diseases in close partnership with public and private sector organisations. NOTE: • FE/FLS/NRW/FS = Forestry England/ Forestry and Land Scotland/Natural Resources Wales/Forest Service. Private sector = all other woodland, including some other publicly-owned woodland. = Conifers

= Broadleaves

• Figures in the tables are individually rounded, so the constituent items may not sum to the total given. • One green tonne is equivalent to approximately 0.98 m³ underbark softwood or 0.88 m³ underbark hardwood, and to approximately 1.22 m³ overbark standing softwood or 1.11 m³ overbark standing hardwood.

74% 26%

1.3 million ha

51% 49%

26% 74%

Conifers account for around one half of the woodland area in the UK overall, but the proportion varies in each country.

Certified Woodland

46% 54%

Wales

0.3 million ha

Scotland

1.5 million ha

Northern Ireland

0.1 million ha

Woodland Visits Frequency of visitors to UK woodland

44%

UK woodland area certified to FSC/PEFC schemes

Summer

Winter

10%

19%

15%

16%

12% 17%

“3,229,000 hectares of UK woodland”

England

17%

69% of the UK population visited woodland in 2019 77% of 16-34 years olds 71% of 35-54 years olds 62% of 55+ year olds Several times per week

100%

Public sector

23%

Private sector

38%

47%

Several times per month About once a month Less often Never

Source: UK Public Opinion of Forestry surveys. Average visit frequencies from last three surveys. Woodland visits are in the last few years.

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Canopy cover (%) > 20 - 25 > 15 - 20 > 10 - 15 > 5 - 10 >0-5 0 Figure 2.Percentage of canopy cover (Source: [adapted from]the UK ward Canopy Cover map, 2021: online]

Policies Trees are important part of the city’s green assets and it has significant positive effects on constructing a health, attractive, resilient city. Trees play a key role in Manchester in recent years which refer to severl approved key policy documents: The Manchester Strategy, The Manchester City Council Climate Change Action Plan and Manchester’s Great Outdoors is a Green and Blue Infrastructure (G&BI) Strategy.

from transport, help to prevent flooding, increase biodiversity and store carbon to encourage the low carbon culture and more. This also accord with the Manchester’s Local Development Framework and Core Strategy Development Plan Document, which aim to develop Manchester as a successful sustainable and accessible city.

What do trees do for us Naturae provides for us - free of charge, 24/7

These strategies indicate trees are a crucial part of our life support system: they reduce pollution

332 manchester report

Figure 3. Ecosystem Services ( Source: Manchester Tree Action Plan, 2017:online]

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Headline Figures in Manchester The top ten performing tree species for carbon sequestration

ec Cy h pr es s d

Le yla n

The top ten performing tree species for stormwater attenuation

The top ten performing tree species for pollution removed

The ten tree species estimated to have the highest replacement cost in Manchester

Replacement Cost (£)

£67,500,000 £45,000,000 £22,500,000

334 manchester report

Ch er ry nL im e Ha wt ho rn

Carbon sequestration is the removal of carbon dioxide from the air by plants. Trees store carbon in all woody tree tissue – root stem and branches. Trees therefore have a significant influence on the balance of carbon in the atmosphere, absorbing and then storing carbon, sometimes for centuries. One tree can absorb several tonnes of atmospheric carbon dioxide during its lifetime.

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£100,000

distribute resources to other systems and collaborate with other systems . The data shows these trees contribute brilliant values in carbon storage, carbon sequestration, pollution removed, stormwater attenuation and replacement cost. (Source: Manchester City of Trees, 2018)

An estimated 1,573,013 tonnes (approximately 12.3t/ha) of carbon is stored in Greater Manchester’s trees with an estimated value of £374,935,529. This is the equivalent to the carbon emitted across Greater Manchester in 238 days. The statistics show that the top ten performing tree species on environment. This can help designers fairly

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am or

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£400,000

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£15,000

Pollution Removal (£) Pollution Removal (Tonnes)

£22,500

Pollution Removal (Tonnes)

Sw e

£30,000

Value (£)

Avoided runoff Value (£) Avoided runoff (Tonnes)

Value (£)

Pollution Removed

Carbon Sotred (tonnes)

Stormwater Attenuation 50,000 45,000 40,000 35,000 30,000 25,000 20,000 15,000 10,000 5,000

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Value (£)

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The top ten performing tree species for carbon storage

Carbon Sequestration (tonnes)

Carbon Sequestration

Carbon Sotred (tonnes)

Carbon Storage

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Data of Measurement 04 Oct. 2021& 01 Oct.2021

Based on I-Tree Eco & i-Tree Canopy

Northern Gateway Research Method Circumference

1 Preparation Parameters

DHB Height

Age

To undertand the capacity of carbon storage of trees, we need to measure the diameter at breast height, the crown health status and the age of the trees. However, the capacity of trees relate to the tree growth rate. To obtain the accurate of growth rate, the health

condition of trees have to be record. For the excellent tree, base growth rates are multipied by 1. Poor condition growth rates are multuplied by 0.62, critical trees by 0.37, dying trees by 0.13 and dead trees by 0.

Crown

2 Calculation Formula

storage:

Typically, half of the dry weight of the tree is carbon

carbon stored = circumference converted into dry weight ÷ 2.

rate, the carbon emission of decomposition of dead trees have to be considered: Net carbon sequestration rate = carbon sequestered by tree growth - carbon lost by tree mortality and decay.

Nevertheless, to estimate the net carbon sequestration

3 Sample Selection

4 Field Research

The Queens Park is choosen as a sample plot. The species of trees, number of trees, crown health condition and heights will be recorded. Then estimate the carbon storage and sequestration of this area.

aspects:

Field investigations are mainly conducted on three

- Common plant species in the site.

Circumference (cm) Dry weight (kg) 40

106

310

100

668

125

1208

150

1964

175

3253

200

4221

Once the research in sample plot has been finished. The result will be used to simulate other main greenspaces, such as tree species composition.

According to the privious research, using i-Tree Eco to establish a probabilistic model of the tree coverage and function of the whole study area.

height, total height, crown top/base height, width(N/S, E/W). - Confirmation of land use properties in the site

Funtional Analyses:

- Relevant data of the survey tree. (eg. DBH, DBH

5 I-Tree Data Models

6 Research Report Comparsion 336 northern gateway research

Pollution removal & human health impacts i-Tree is a state-of-the-art, peerreviewed software suite from the USDA Forest Service that provides urban and rural forestry analysis and benefits assessment tools. i-Tree Eco is a popular tool of tree measurements and other data

to estimate ecosystem services and structural characteristics of the urban or rural forest.

Carbon storage

sequestration

Hydrology effects

Forest Research and Manchester City of Tress have been using i-Tree Eco to explore some relevant surveys.

Tree bio-emissions Avian habitat suitability feects

Ultraviolet

radiation

tree

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2021 CPU[AI] Carbon storage is estimated by multiplying tree biomass by 0.5 (Chow and Rolfe 1989). To prevent carbon storage from overestimation for very large trees, total carbon storage is capped 7,500 kg of carbon in i-Tree Eco and Forecast. To estimate annual gross carbon sequestration, the tree d.b.h. is incrementally increased in the computer model based on an estimated annual growth rate. The carbon storage in the current year (year 0) is then contrasted with carbon storage in the next year (year 1) to estimate the annual sequestration. If a tree’s biomass estimate was capped at 7,500 kg and the tree is alive, carbon sequestration for these large trees is estimated at 25 kg/year.

Calculation

Measurement Trees

There are two assessments of the Northern Gateway, including i-Tree Canopy and i-Tree Eco. Initially, 3200 points were defined as samples plots from randomly located plots across the whole study area. The land cover and tree benefit estimates were roughly calculated by i-Tree Canopy, which is as a guidline draft.

200 points, the surveyed sample plots have a higher proportion of total area, thus still maintaining a statistically robust estimate of the study area. Almost all of the target 25 plots were accessible and those that were not accessible were observed and measured by Google Map. All 25 plots were therefore able to be inventoried.

Next step, land use types were divided into ten parts: park, residential, multi-family residential, institutional, commercial, cemetery, transportation, water, vacant and other to mark and calculate area by QGIS. To gather a collective representation of Northern Gateway’s forest an i-Tree Eco (v6) plotbased assessment was undertaken.

Random plot selection, generated using GIS software ensures that trees on both public and private land are included in the assessment. The information collected for each plot is detailed in table 1, below.

25 in different land uses randomly allocated plots of 0.04ha (400m²) were surveyed , representing 0.51% of the total survey area (of 195.01ha). Although it was only chosen 25 plots, which is far less than

Plot information Tree information

This data was collected by sub-group members on Octobor 2021. Using i-Tree Eco the field data were combined with local climate and air pollution data to produce estimates of the urban forest structure and the benefits by trees. The full list of outputs generated is shown in table 2, below.

Land use, ground cover, % tree cover, % shrub cover, % plantable space, % impermeable surface. Tree species, height in (m), trunk diameter at breast height (dbh), canopy spread, the health and density (or fullness) of the canopy, light exposure to the crown.

All species in the study area have supported data and some part of formulas. species name

wood density tonne/m³

DHB Min

DBH Max

Tree height equations

Acer pseudoplatanus

0.51

53.2

e(B0 + (ln(DBH) * B1))

2.5842

0.54

Aesculus hippocastanum

0.5

Betula pendula

0.52

B0 + (ln(DBH) * B1)

17.7323

10.4284

Carpinus betulus

0.598

Cedrus atlantica 'Glauca'

0.44

Fraxinus angustifolia

0.51

Malus spp

0.61

Metasequoia glyptostroboides

0.28

Prunus cerasifera

0.47

Quercus robur

0.57

Salix matsudana

0.47

Sambucus nigra

0.45

Sorbus aria

0.64

Table 1. Field Data

Urban Forest Tree Structure and Composition

Leaf area and canopy cover, % leaf area by species. Age class, size class, tree condition. Species diversity, species dominance. Urban ground cover types.

Ecosystem Services

Air pollution removal by urban trees for CO, NO₂, SO₂, O₃ and PM2.5 % of total air pollution removed by trees. Current carbon storage. Carbon sequestered. Stormwater Attenuation (Avoided Runoff). i-Tree Eco also calculates Oxygen production of trees, this service is not valued but the figures are included in the report.

Ecosystem Services

Replacement Cost in £. Carbon storage value in £. Carbon sequestration value in £. Pollution removal value in £. Avoided runoff in £.

Crown height equations

Crown width equations

Acer pseudoplatanus

e(B0 + (ln(DBH) * B1))

2.1447

0.5258

e(B0 + (ln(DBH) * B1))

1.9314

0.5685

Betula pendula

B0 + (ln(DBH) * B1)

13.2422

9.4508

e(B0 + (ln(DBH) * B1))

1.5123

0.571

Tilia cordata

e(B0 + (ln(DBH) * B1))

1.4554

0.6788

B0 + (ln(DBH) * B1)

-11.1093

14.6509

Planned Improvements Not all carbon equations are used from from the GlobAllomeTree (2017) database. Only equations that produced whole tree carbon estimates within 2-12 t C at 100 cm d.b.h. were selected to remove outliers Wood density data are also being added to the i-Tree database from the Global Wood Density Database. The new carbon equations and wood density data will produce carbon estimates based on

more equations and a process of weighting wood densities between the actual species measured and the species equation used: Cest = Ceq x WDspp / WDeq

Table 2. Outputs of the study

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species name

Where: Cest = carbon estimate, Ceq = carbon estimates derived from equations, WDspp = wood density of the species measured, and WDeq = average wood density from the carbon equations.

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Tree Growth

Annual tree diameter growth is estimated for the study area based on:

1. Base growth rate - Open grown tree growth rates were based on measured street tree growth (Fleming 1988, Frelich 1992, Nowak 1994b), which were standardized to a 153 day frost free length as follows: standard growth = measured growth × (153/number of frost-free days of measurement).

2. Length of growing season - To determine a local base growth rate, the standard growth rate was adjusted based the local length of growing as follows:

- Based on these data, the average standardized diameter growth rates: for open-grown trees with 153 frost free days are set to 0.23 in/yr for slow growing species, 0.33 in/yr for moderate growing species, and 0.43 in/yr for fast growing species. There are limited measured data on urban tree growth for slow, moderate, or fast-growing tree species, so the growth rates used in i-Tree Forecast are estimates.

5. Tree condition - Growth rates are adjusted for tree condition based on percentage crown dieback. Base growth rates are multiplied by 1 – percentage dieback. For example, a tree with 40 percent dieback, base growth rates are multiplied by 0.6.

340 northern gateway research

Annual tree diameter growth is estimated for the study area based on:

Carbon storage - above ground and grass To estimate below ground biomass, the above ground dry weight ÷ 1.39. a carbon estimate = above and below ground dry weight biomass × 0.45.

base growth = standard growth × (number of frostfree days in area/153). Carbon storage - grass

The average diameter growth rate for open-grown trees with 153 frost free days is 0.33 in/yr.

3. Species growth rates

Grass Calculate

The dry weight of live stubble and the ash-free weight of live roots were converted to a carbon estimate by multiplying by 0.4269, since carbon content in grass averaged 42·69% of the dry weight.

4. Tree competition - Crown light exposure (CLE) measurements are used to represent tree competition. CLE measurements for each tree are based on the number of sides and/ or top of tree exposed to sunlight. Based on a comparison of species growth rates between street trees (CLE 4-5), park trees (CLE 2-3) and forest-grown trees (CLE 0-1) (deVries 1987, Fleming 1988, Frelich 1992, Nowak 1994b, Smith and Shifley 1984), the base growth for trees are as follows (Standardized growth (SG): forest conditions with a closed, or nearly closed canopy: trees with CLE 0-1 = SG × 0.44 park conditions: trees with CLE 2-3 = SG × 0.56; open-grown conditions: trees with CLE 4-5 = SG × 1.

6. Tree height - As a tree approaches “maximum” height, growth rate decreases. Thus, the species growth rates as described above are adjusted based on the ratio between the current height of the tree and the average height at maturity for the species. When a tree’s height is more than 80 % of its average height at maturity, the annual diameter growth is proportionally reduced from full growth at 80 % of maximum height to 2.22 % of full growth at 125 % of height at maturity.

1 m² wet turf will weigh between 10 – 20kg, calculate the dry matter proportion by dividing the final weight by the weight of the fresh material. DM of grass usually is 16% - 22%. (depends on typies of grass and the weather) the dry weight of grass = weight of fresh grass x DM.

Carbon sequestration Annual carbon uptake of stubble and live roots was calculated using the following formula : Net carbon=Cmax(s) where: Cmax(s) Ts+Cmax(r) =maximum carbon in live stubble; Ts Cmax(r)=maximum carbon in live roots Tr =turnover rate of live stubble, =turnover rate of live roots. ; Turnover rate (T) was calculated from the ratio of annual growth to total live stubble (or liveroot) mass.

Economic Valuation The value of carbon storage and sequestration is based on the social cost of carbon as reported by the Interagency Working Group on Social Cost of Carbon (2016). Social cost associated with a pollutant (e.g., CO2) refers to an estimate of total (global) economic damage attributable to incremental increase in the level of that particular pollutant in a given year. The current CO2 value is estimated at $51.23 per tonne based on the estimated social costs of carbon for 2020 with a 3 percent discount rate to reflect 2018 dollars (Interagency Working Group 2016). Users can adjust this value, if they so desire, by taking a ratio of the desired value (DR) per tonne CO2 to the $51.23/tonne CO2. updated value = Tree reported value x DR/51.23

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Field Research

There are ten parks in the Northern Gateway, but four park have been devastation and invasion of weeds. Some paths have grown straws and weeds in these parks. The health level of trees stand at fair. However, brown leaf spot disease is a common symptom. It is attention that Cedrus atlantica ‘Glauca’ is a heritage tree nearby a residential area. Moreover, some public services have been broken. For example, the swing, slide and seesaw have been rust and dirt in Collyhurst. Garbages and trashes have been thrown and piled up at lakes, grasses and streets.

GARBAGE DUMPS

IDLE BUILDINGS

A HERITAGE TREE

RUINED AREAS

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sample plot park

Further Report - i-Tree Eco

residential multi-family residential institutional

Number of trees/ha

commercial cemetery

200 Number Tree/ha

transportation water

100

vacant other

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Tree species composition Apple spp (6.6%) Common ash (10.8%) Sycamore maple (35.9%)

Fastigate hornbeam (9.9%)

Goat willow (7.2%)

Other (7.0%) Cherry plum (2.5%) Oneseed hawthorn (4.1%)

344 northern gateway research

Dawn redwood (6.6%) Horse chestnut (4.9%) European silver birch (4.4%)

For getting more accurate calculation results, 25 plots were set in the whole project to physically measure data from trees, and the site is divided into to 10 parts by landuse. Then use data to simulate the distribution of trees. As the result shows, the whole site has over 21,000 trees. For this project, the highest tree densities occur in riverside

followed by the park and residential areas. Many tree benefits directly equate to the amount of healthy leaf area. There is around 40% percent of trees cover in the site, which also provides over 10 square kilometers of leaf area.

The three most common species in the project site are sycamore (35.9%), common ash (10.8%) and fastigate hornbeam (9.9%).

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Estimated annual gross carbon sequsetration (points) and value (bars) for urban tree species with the greatest sequestration

Grass

Sequestration (metric ton)

Tar Water Herbs Rock Duff/Mulch Other impervious Bare soil

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Percent of Carbon Storage of Trees by Stratum

Building

Unmaintained grass

100

Value (thousands £/yr)

Percent of land by ground cover classes

Estimated carbon storage (points) and values (bars) for urban tree species with the greatest storage

Multi-family residential Vancant Cemetery Water

1500

1200

900

600

300

150

£600

100

£400

£200 £0

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346 northern gateway research

Value (thousands £)

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200

Pa r

Gross Carbon Sequestration (metric ton/yr)

Annual Carbon Sequestration of trees by Stratum

silv

Transportation

Commerical

Residential

Storage (thousand metric ton)

Institutional

Although the three most common tree species provide the largrest leaf area, willow also provides the greater leaf area, which is larger than common ash and fastigate hornbeam. The whole site proivdes over 100,000 ton of carbon storage and the top areas of

carbon storage are park, commercial, transportation and residential. For the carbon sequestration, the whole site provides over 200 tons of carbon sequestration per year. The result shows that the residential area

has better performance on carbon sequestration than transportation area and commercial. The research also counts the carbon storage and sequestration of different tree species in the project site.

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Species Performance Summary

Among the contributions of these trees, the value of carbon storage is equivalent to £4,363,290.69, the value of carbon sequestration is equivalent to £78,118.14 per year and saving £42,304.56 each year through pollution removal. Furthermore, these trees have

great value in themselves, which is equal to £32,106,758.55 replacement value. Carbon storage gross carbon sequestration value is calculated based on the price of £253.00 per metric ton. Pollution removal value is calculated based

on the prices of £956.63 per metric ton (CO), £11,215.98 per metric ton (O3), £1,675.07 per metric ton (NO2), £610.25 per metric ton (SO2), £389,355,57 per metric ton (PM2.5). Replacement value is the estimated local cost of having to replace a tree with a similar tree. Sycamore 4,506.4

112.52

The research shows that the trees in the project site stored 17,246.2 metric tons of carbon. Sycamore and European silver birch have the best performance on carbon storage among these trees. In addition, these trees contribute 308.77 metric tons of annual carbon sequestration. Similarly, Sycamore and European silver birch are better than other trees species on carbon sequestration. These trees also have great contribution on pollution removal which is about 5.32 metric tons each year.

Carbon storage: 17,246.3 ± 4,395 metric ton

1.62 Horse chestnut 900.4 19.92 0.29 European silver brich 4,810.0 77.09

Gross carbon sequestration: 308.77 ± 68.55 metric ton/ yr

0.40 European 215.7; 3.55;0.12 hornbeam: Fastigate hornbeam 968.2 27.21 0.70 Altas cedar: 95.9; 2.18; 0.06 Hawthorn: 358.6; 5.78; 0.16 Narrow 115.1; 2.01; 0.03 -leafed ash: Common ash 2,269.2 39.71

Pollution removal: 5.33 metric ton/ yr

0.64 Apple:

14.3; 2.21; 0.01

Dawn redwood: 113; 5.59; 0.08 Cherry plum: 64.5; 3.73 Common oak: 98.1; 1.68; 0.02 Weeping willow: 2,610.2 1.24 1.19 Elder: 0.73; 0.73 Whitebeam: 2.71; 2.71

348 species performance

Littleleaf inden: 0.90; 0.90; 0.01

349

Tree ID Guide

a. Leaf

b. Fruit or Flowers

c. Bark

d. Twigs

Apple spp.

Atlas cedar

Cherry Plum

Common Ash

Malus spp.

Cedrus atlantica ‘Glauca’

Prunus cerasifera

Fraxinus excelsior

e. Tree shape

2021 CPU[AI]

a b

Carbon Storage (kg): min: 6.2 max: 14.4

average: 10.6

Carbon Storage (kg): min: 440.7 max: 440.7

average: 440.7

Carbon Storage (kg): min: 101.5 max: 145.0

average: 120.5

Carbon Storage (kg): min: 140.9 max: 4301.3

average: 986.36

Gross Carbon Sequestration (kg/yr): min: 1.2 max: 2.0 average: 1.55

Gross Carbon Sequestration (kg/yr): min: 10.0 max: 10.0 average: 10.0

Gross Carbon Sequestration (kg/yr): min: 6.5 max: 7.9 average: 6.79

Gross Carbon Sequestration (kg/yr): min: 7.5 max: 35.8 average: 18.0

Common Oak

Dawn redwood

Elder

European hornbeam

Quercus robur

Metasequoia glyptostroboides

Sambucus nigra

Carpinus betulus

Carbon Storage (kg): min: 1240.7 max: 1240.7

average: 1240.7

Gross Carbon Sequestration (kg/yr): min: 21.2 max: 21.2 average: 21.2

350 species performance

Carbon Storage (kg): min: 36.1 max: 213.9

average: 79.13

Gross Carbon Sequestration (kg/yr): min: 2.5 max: 7.4 average: 3.88

Carbon Storage (kg): min: 159.9 max: 253.4

average: 196.5

Gross Carbon Sequestration (kg/yr): min: 5.5 max: 7.2 average: 6.1

Carbon Storage (kg): min: 157.1 max: 765.7

average: 402.93

Gross Carbon Sequestration (kg/yr): min: 1.7 max: 10.7 average: 6.63

351

a. Leaf

b. Fruit or Flowers

c. Bark

d. Twigs

e. Tree shape

Fastigate Hornbeam

Hawthorn

Horse Chestnut

Narrow-leaved Ash

Carpinus betulus

Crataegus monogyna

Aesculus hippocastanum

Fraxinus angustifolia

Carbon Storage (kg): min: 352.6 max: 663.6

average: 450.73

Carbon Storage (kg): min: 206.0 max: 822.4

average: 384.2

Carbon Storage (kg): min: 271.7 max: 1737.1

Carbon Storage (kg): min: 347.5 max: 1510.0

average: 916.13

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average: 970.57

Gross Carbon Sequestration (kg/yr): min: 10.7 max: 15.5 average: 12.71

Gross Carbon Sequestration (kg/yr): min: 3.3 max: 9.7 average: 8.2

Gross Carbon Sequestration (kg/yr): min: 11.2 max: 30.8 average: 20.12

Gross Carbon Sequestration (kg/yr): min: 10.1 max: 23.2 average: 16.97

Silver Birch

Small-leaved Lime

Sycamore

Weeping Willow

Betula pendula

Tilia cordata

Acer pseudoplatanus

Salix matsudana

Carbon Storage (kg): min: 4196.5 max: 6209.8

average: 5051.78

Gross Carbon Sequestration (kg/yr): min: 72.7 max: 91.7 average: 80.95

352 species performance

Carbon Storage (kg): min: 216.3 max: 577.0

average: 396.65

Gross Carbon Sequestration (kg/yr): min: 8.6 max: 14.2 average: 11.4

Carbon Storage (kg): min: 122.8 max: 1848.6

average: 573.94

Gross Carbon Sequestration (kg/yr): min: 6.2 max: 29.4 average: 14.39

Carbon Storage (kg): min: 381.4 max: 1738.0

average: 1564.38

Gross Carbon Sequestration (kg/yr): min: 0.5 max: 6.4 average: 1.78

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Whitebeam Sorbus aria

Carbon Storage (kg): min: 137.7 max: 153.6

average: 145.65

Gross Carbon Sequestration (kg/yr): min: 7.1 max: 8.1 average: 7.6

Grass Fraxinus angustifolia

Condition of the Most Common Species in Manchester Alder Sycamore Hawthorn Silver Birch Sweet Cherry Socts Pine Goat Willow Carbon Storage (kg/m2): min: 0.68 max: 1.7

average: 1.19

Gross Carbon Sequestration (kg/annual): min: 0.046 max: 0.13 average: 0.088 354 species performance

a. Leaf b. Fruit or Flowers c. Bark d. Twigs e. Tree shape

English Oak Ash Elderberry 0% Excellent

Good

25% Fair

Figure 4. Condition of the Most Common species in Manchester (Source: Manchester City of Trees, 2018:online)

50% Poor

75% Critical

Dying

100% Dead

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Tree Placement Rules Private Area Trees position

Design the windbreak W ind

D>d The sun shines on the northeast and east sides of buildings in the morning, passes over the roof near midday, then shines on the west and northwest sides in the afternoon. Therefore, the west and northwest sides of a home are the most important sides to shade. Sun shining through windows heats the home quickly. Locate trees to shade windows so that they block incoming solar radiation, but do not block views. In most climates the east side is the second most important side to shade. (Source: E.G., McPherson & J.R., Simpson.1999)

Trees distance

2m 9-1 m

3-6

m 5-3

356 tree placement rules

Although the closer a tree is to the home the more shade it provides, the roots of trees that are too close can damage the foundation. Keep trees at least 1.5 to 3 m from the home to avoid these conflicts but within 9 to 15 m to effectively shade windows and walls. (Source: E.G., McPherson & J.R., Simpson.1999)

ak Design the windbreak row to be longer than the building being sheltered because the wind speed increases at the edge of the windbreak. Ideally, the windbreak is planted upwind about 15 m from the building and consists of dense evergreens that will grow to twice the height of the building they shelter. (Source: E.G., McPherson & J.R., Simpson.1999)

15m

Design the windbreak

To maximize summer shade and minimize winter shade, locate trees about 3 to 6 m south of the home. As trees grow taller, prune lower branches to allow more sun to reach the building.

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rea

k ro

Avoid locating windbreaks that will block sunlight to south and east walls. Trees should be spaced close enough to form a dense screen, but not so close that they will block sunlight to each other, causing lower branches to self-prune. Most conifers can be spaced about 2 m on center. If there is room for two or more rows, then space rows 3 to 4 m apart. (Source: E.G., McPherson & J.R., Simpson.1999)

- 4m

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Species selection, summer

Larger

Small - Medium

Trees located to shade south walls can block winter sunshine and increase heating costs, because during winter the sun is lower in the sky and shines on the south side of homes. Thewarmth the sun provides is an asset, so do not plant evergreen trees that will block southern exposures and solar collectors. (Source: E.G., McPherson & J.R., Simpson.1999)

The ideal shade tree has a fairly dense, round crown with limbs broad enough to partially shade the roof. Given the same placement, a large tree will provide more building shade than a small tree. Deciduous trees allow sun to shine through leafless branches in winter. (Source: E.G., McPherson & J.R., Simpson.1999)

Figure 6. Crataegus laevigata, (Source: VAN DEN BERK, onilne0

Species selection, winter

Trees shadowing on building

Use solar friendly trees (As image shows: Engilsh Hawthorn) to the south because the bare branches of these deciduous trees allow most sunlight to strike thebuilding (some solar unfriendly deciduous trees can reduce sunlight striking the south side of buildings by 50 percent). (Source: E.G., McPherson & J.R., Simpson.1999)

Taller

Small Plant small trees where nearby buildings or power lines limit aboveground space. Columnar or upright trees are appropriate in narrow side yards. Because the best location for shade trees is relatively close to the west and east sides of buildings, the most suitable trees will be strong, resisting storm damage, disease, and pests. (Source: E.G., McPherson & J.R., Simpson.1999)

Figure 7. Crataegus laevigata (Source: Tree Guide, online)

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Public Area Small Medium 1.8m

Larger

4.5m 9m 12m

12m 15m

Large trees can shade more area than smaller trees, but should be used only where space permits. A tree needs space for both branches and roots. Small: 1.8m - 4.5m Medium: 9m - 12m Larger: 12m - 15m Specific distance depends on the typies and the size of trees. (Source: E.G., McPherson & J.R., Simpson.1999)

Strong vitality and long life

Because trees in common areas and other public places may not shelter buildings from sun and wind, CO₂ reductions are primarily due to sequestration. Fast-growing trees sequester more CO₂ initially than slowgrowing trees, but this advantage can be lost if the fast-growing trees die at younger ages. Large growing trees have the capacity to store more CO₂ than small growing trees. (Source: E.G., McPherson & J.R., Simpson.1999)

Locate trees in common areas, along streets, in parking lots, and commercial areas to maximize shade on paving and parked vehicles. Shade trees reduce heat that is stored or reflected by paved surfaces. By cooling streets and parking areas, they reduce emissions of evaporative hydrocarbons from parked cars that are involved in smog formation. (Source: E.G., McPherson & J.R., Simpson.1999)

Fast gowth rate

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Proper Placement for trees around the houses

Tall Zone 20m

Medium Zone 12m 15m Building

Lawn

Low Zone 6m

4.5m

Walk

Street

Figure 8. Proper Placement for Trees Around Homes (Source [adapted from]Mc Pherson and Simpson, 1999:online)

Keep trees at least 10 m away from street intersections to ensure visibility. Avoid planting shallow rooting species near sidewalks, curbs, and paving. Tree roots can heave pavement if planted too close to sidewalks and patios. Generally, avoid planting within 1 m of pavement, and rmember that trunk flare at the base of large trees can displace soil and paving for a considerable distance. Select only small-growing trees (<7 m tall) for locations under overhead power lines, and do not plant directly above underground water and sewer lines. Avoid locating trees where they will block illumination. (Source: E.G., McPherson & J.R., Simpson.1999)

362 tree placement rules

Group species with similar landscape maintenance requirements together and consider how irrigation, pruning, fertilization, weed, pest, and disease control can be minimized. Compost litter fall, and apply it as mulch to reduce CO₂ release associated with irrigation and fertilization. (Source: E.G., McPherson & J.R., Simpson.1999)

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Suggestion for improvement

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Wind Direction in Manchester

Green Corridors

100%

80%

20%

60%

40%

In Manchester, winters are long, very cold 40% 60% and windy. According to a study by University of 80% British Columbia that wind pressure is responsible for 20% as much as a third of a building’s energy consumption. Planting windbreak is one the best ways to save 0% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec100% buildings energy with trees and shrubs. Therefore, Figure 9. Medellín (Source: C40 Knowledge, 2019:online) three larger green corridors are set up along the main Wind roads surrounding the whole project site. Meanwhile, some small green roads are set up to pass through the site to connect different areas. These green corridors can contribute great value to carbon storage and sequestration. It also can improve the landscape, isolate noise and increase biodiversity.

Green Corridors - Medellín Medellín is the one of biggest cities in Columbia. As a result of 50 years of rapid urban development, Medellín was experiencing a severe urban heat island effect. Greenhouse gas emissions of the refrigeration industry have increased rapidly for short-term remitting this problem. It also led the burden of urban electricity consumption to be increased. To address this phenomenon, the city authorities transformed the verges of 18 roads and 12 waterways into a green paradise that reduces the impact of the heat island effect. These 30 corridors cover 65 hectares with 8800 trees and over 9000 species of lesser plants. With green corridors were implemented that improved the quality of air and landscape, reduced 2 ℃ of environment temperature. This design also won the 2019 Ashden Award for Cooling by Nature Award. (Source: C40 Knowledge, 2019) Figure 11. Medellín (Source: C40 Knowledge, 2019:online)

Figure 10. Northern Gateway (adapted from) OpenStreet map, 2021:online)

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Figure 12. Corredores Verdes (Source: [adapted from] Municipio de Medellín, 2018:online)

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Green Cycling The four main transport roads surround the whole project site and one main road pass through the site from southwest to northeast. These main roads ensure citizens can travel conveniently to other places by public transportation. Then four cycling roads cross through the site to connect different areas. Through this green network encourage citizens to use public transportation and some ways to take trips. This means the carbon emission from transportation can be reduced.

Garden City - Singapore In addition, as the use of private transportation decreases that it provides more spaces for citizens and animals. This green network allows birds, mammals and insects to travel around the city which can improve the ecosystem to increase the carbon capacity of the natural environment.

Singapore’s vision to become a Garden City was first envisioned in 1967. In few past decades, Singapore’s urban planners have been promoting biodiversity and now all developments must have some form of vegetation such as green roofs, foliage walls or vertical hanging gardens. As Singapore government stated that Singapore aims to plant more than 1,000,000 trees which can store 78,000 tonnes of CO2. With more green spaces, the environment will be more wildlife that it allows humans and wildlife to live in harmony. Meanwhile, expand cycling network to 1320km and increase rail network to 360km to increase trips taken on mass public transport to 75% by 2030. (Source: R., Carnell, 2021)

Figure 14. Oasis Terraces (Source [adapted from] Deoma 12, 2018:online)

Figure 13. Northern Gateway (adapted from) OpenStreet map, 2021:online)

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Figure 15. Singpore’s green cover (Source: [adapted from] Kenneth, 2018:online)

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Executive Summary

Figure 5. The Benefits of Trees inforgraphic (Source: Treeco2nomics, 2020:online) We studied greenspaces’ benefits to urban, especially their contributions to the zero-carbon cities. Through this research, UK forests store around 1 billion tonnes of carbon, the equivalent of around 4 billion tonnes of CO2.

the benefits of green spaces in Northern Gateway. Through physically measuring the trees’ height, DHB and the size of the crown. We calculated the specific benefits of trees, such as carbon storage.

However, it is estimated that the proportion of England’s urban green space declined from 63% in 2001 to 55% in 2018. This makes urban face more difficulties to achieve the goal of zero-carbon.

Through our methods and results that we can construct the model to test differents forms of urban to figure out a better urban plan.

In this chapter, we used different methods to estimate

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Benefits of Green-spaces to Zero Carbon • Prevent flooding • Storage large amount of carbon • Remove carbon dioxide from air • Improve the effects of heat island

• Reduce the impact of wind on building energy consumption • Encourage people take trip by green ways • Increase biodiversity to improve urban system

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Bibliography C40 Cities Climate Leadership Group, Nordic Sustainability (n.d.) Cities100: Medellín’s interconnected green corridors. C40knowledgehub.org. [Online] [Accessed on October 2019] https://www.c40knowledgehub.org/s/ article/Cities100-Medellin-s-interconnected-green-corridors?language=en_US. Carnell, R. (2021) Singapore Green Plan 2030 – Important steps towards a sustainable future. Ing.com. ING Think. [Online] [Accessed on 11 November 2021] https://think.ing.com/articles/singapore-green-plan-2030important-steps-towards-a-sustainable-future/. Conant, R. T., Paustian, K., Del Grosso, S. J. and Parton, W. J. (2005) ‘Nitrogen pools and fluxes in grassland soils sequestering carbon.’ Nutrient cycling in agroecosystems, 71(3) pp. 239–248. Doick K.J., Davies H.J., Ashwood F., Handley P. (2016) Introducing England’s urban forests. E. Gregory McPherson, J. R. S. (1999) Carbon Dioxide Reduction through Urban Forestry: Guidelines for Professional and Volunteer Tree Planters. Forest Research (2021) Forestry Facts & Figures 2021.

Figure 4. Manchester City of Trees. (2018) Condition of the Most Common species in Manchester. [Accessed on 11th October 2021] Figure 5. Treeco2nomics. (2020) The Benefits of Trees inforgraphich. [Online image] [Accessed on 12th November 2021] https://www.treeconomics.co.uk/blog/1535-2/ Figure 6. Ven Den Berk Nurseries. (n.d.) Crataegus laevigata. [online image] [Accessed on 12th November 2021] https://www.vdberk.com/trees/crataegus-laevigata/ Figure 7. Tree Guid. (n.d.) Crataegus laevigata. [Online image] [Accessed on 12th November 2021] http:// www.tree-guide.com/redthorn Figure 8. E.G., McPherson & J.R., Simpson.(1999) Proper Placement for Trees Around the Houses. [Online image] [Accessed on 12th November 2021] https://www.fs.fed.us/psw/topics/urban_forestry/products/cufr_43.pdf Figure 9. Weather Spark. (2021) Wind Direction in Manchester. [Online image] [Accessed on 12th November 2021] https://weatherspark.com/y/39871/Average-Weather-in-Manchester-United-Kingdom-Year-Round

Forest Research (n.d.) Urban Forest Research Group. Gov,uk. [Online] [Accessed on 12 November 2021] https://www.forestresearch.gov.uk/documents/7989/UFoRG_public_facing_document_March2021_v1.0.pdf.

Figure 10. OpenStreetMap. (2021) Northern Gateway. [Online image] [Accessed on 12th November 2021] https://www.openstreetmap.org/search?query=Manchester#map=15/53.4942/-2.0742

Jo, H.-K. and McPherson, G. E. (1995) ‘Carbon storage and flux in urban residential greenspace.’ Journal of environmental management, 45(2) pp. 109–133.

Figure 11. C40 Knowledge. (2019) Cities100: Medellín’s interconnected green corridors. [Online image] [Accessed on 12th November 2021] https://www.c40knowledgehub.org/s/article/Cities100-Medellin-sinterconnected-green-corridors?language=en_US

Manchester City of Trees (2018a) Headline Figures for: Manchester. Manchester City of Trees (2018b) Tree Identification Guide. Nowak, D. J. (2020a) ‘Appendix 10: New biomass equations.’ USDA Forest Service. Nowak, D. J. (2020b) ‘Appendix 11: Wood density values.’ USDA Forest Service.

Figure 12. Municipio de Medellín. (2018) Corredores Verdes. [Online image] [Accessed on 12th November 2021] https://geomedellin-m-medellin.opendata.arcgis.com/datasets/d8443c6265444687918f0d5eea945369/ explore Figure 13. OpenStreetMap. (2021) Northern Gateway. [Online image] [Accessed on 12th November 2021] https://www.openstreetmap.org/search?query=Manchester#map=15/53.4942/-2.0742

Nowak, D. J. (2020c) ‘Appendix 13: Equations for tree height, crown height, and crown width.’ USDA Forest Service.

Figure 14. Deoma 12. (2018) Oasis Terraces. [Online image] [Accessed on 12th November 2021] https:// commons.wikimedia.org/wiki/File:Oasis_Terraces_2018.jpg

Singapore Green Plan 2030 (n.d.) Gov.sg. [Online] [Accessed on 11th October 2021] https://www.greenplan. gov.sg/splash.

Figure 15. Er, Kenneth. (2018) Singpore’s green cover. [Online image] [Accessed on 12th November 2021] https://www.csc.gov.sg/articles/growing-a-biophilic-city-in-a-garden

Figure 1. Forest Research. (n.d.) Areas of expertise in urban forest. [Online image] [Accessed on 12th November 2021] https://www.forestresearch.gov.uk/documents/7989/UFoRG_public_facing_document_March2021_ v1.0.pdf Figure 2. Manchester City Council. (2017) Ecosystem Services. [Online image] [Accessed on 12th November 2021] https://www.manchester.gov.uk/download/downloads/id/25574/manchester_tree_action_plan.pdf Figure 3. UK Ward Canopy Cover map. (n.d.) Percentage of canopy cover. [Online] [Accessed on 12th November 2021] https://forestry.maps.arcgis.com/apps/webappviewer/index. html?id=d8c253ab17e1412586d9774d1a09fa07

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Cities’ efficiency and sustainability are heavily influenced by their urban connectivity. Careful planning for growth can produce benefits such as shorter travel distances, and reduction in motorised transportation and economic social and environmental benefits

INTRODUCTION

SECTION ONE

SECTION TWO

What is accessibility?

Understanding Accessibility

Mobility & Transport

SECTION THREE

SECTION FOUR

Northern Gateway Analysis

Carbon Calculations

CONCLUSION Summary & Conclusion

ACCESSIBILITY CONTRIBUTIONS CONTRIBUTIONS TOWARDS ZERO CARBON

Ladi Timothy Shobowale, Shrida Venkatesh, Jakub Andruszkiewicz

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Zero Carbon Cities

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Introduction The issue

With a population of 2.8 million, Greater Manchester is responsible for 3.6% of the UK’s annual CO2 emissions. The city worked with the UK’s Tyndall Centre for Climate Research to calculate a carbon budget aligned with commitments under the Paris Agreement to keep global warming to “well below” 2°C. Under this budget, emissions in Greater Manchester need to fall by 15% between now and 2038. Carbon budgeting is one of the main tools applied by the city. The Tyndall Centre has calculated that Greater Manchester has a total budget of 71 million tonnes of CO2 between 2018 and 2100 in order to comply with the Paris Agreement, which has been split into individual five-year budgets until 2038. In order to stay within these budgets, Greater Manchester needs to reduce its carbon emissions by about 13% every year―and plans are in place to achieve this. In addition, all ten councils have declared a Climate Emergency, and Manchester City Council plans to reduce carbon emissions from its buildings, energy use and transport by 50% before 2025. A major component of accessibility is transport, which is Greater Manchester’s biggest source of emissions. Under city plans, the share of daily journeys taken by car will fall by 2040 from 61% to 50% with

more sustainable travel methods, such as walking, cycling and public transport, taking precedent. For vehicles remaining on the road, the environment plan expects to see 200,000 plug-in vehicles by 2024, up from 2,800 today, and a 100% electric bus fleet by 2035. A third strand of the plan is to better understand how the city-region generates, uses and trades energy. To do this, the GMCA helped each district draft a local energy plan. The plan helps local decision-makers identify the most promising options for de-carbonisation that fit best with local infrastructure requirements and socio-economic priorities, and highlight where further investment is needed. Accessibility is an important component in undestanding how to achieve a zero carbon city. The use of energy within a city, and the associated production of GHG emissions, is dependent on both the form of urban development (i.e. its location and density) and its design. A significant portion of the world’s greenhouse gases is produced by anthropogenic causes in cities. In order to reduce city emissions, there are a number of policies available. However, one approach can be to promote compact urban development by making cities more accessible (The Total Carbon Footprint of Greater Manchester, 2021).

Manchester 17.3%

17.3%

Carbon Emissions from Manchester

The annual carbon footprint of GM residents is estimated at 41.2m tonnes CO2e3. This makes the footprint of the average resident 15.7 tonnes, roughly in line with that of the average UK resident.

Source: Image created by Author based on information (The Total Carbon Footprint of Greater Manchester, 2021)

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Image Top: THE HIGH LINE, NEW YORK, DILLERISCOFIDIOI+IRENFRO (2009)

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Context

GM resident’s footprint breaks down as follows:

The greenhouse gas footprint of Greater Manchester residents broken down by consumption category (total 41.2 million tonnes CO2e).

Domestic construction 3%

Accessibility relates to land-use and its spatial characteristics; it focuses on how easily individual residents within a city can access amenities and services. Therefore, to understand how Zero Carbon can be achieved through Accessibility, we must first understand the actual carbon footprint of residents in Manchester based on different types of consumption. A 2011 report of the estimates of the carbon emissions of Greater Manchester residents has been studied in order to understand how we can achieve a Zero Carbon Manchester; the report includes emissions resulting directly from energy use and those resulting from the supply chains of the goods and services that we buy and use. This is called the ‘Consumption-based Carbon Footprint’, or the ‘Total Carbon Footprint’. The consumption-based approach includes supply chain emissions associated with the production of goods and services used and consumed by residents, wherever those emissions actually take place excluding the boundaries beyond Greater Manchester.

It does not, in contrast, include vehicle emissions from non-GM residents who visit the city by car. Relying entirely on the incomplete picture presented by production-based carbon metrics has been a major barrier to strategic approaches for developing low-carbon futures. The adoption of a consumption based metrics alongside productionbased accounting opens up a wealth of both opportunity and challenge. Doing so is particularly important when seeking to understand and manage the impacts of lifestyles and of service economies. The consumption-based analysis gives us a framework for policy development: Current carbon reduction policies (and other policies and trends which have a carbon impact) can be mapped onto the framework. This enables us to see which segments are not yet addressed as well as those that are. Developing local supply chains would have a positive impact on emissions in many segments of the footprint.

Also, in this analysis, the carbon footprint of residents’ driving includes not only the direct emissions from their burning of vehicle fuel, wherever that takes place, but also emissions resulting from the extraction, shipping and refining of the fuel, as well as a component for the manufacture of the vehicle itself.

“The adoption of a consumption based accounting opens up a wealth of opportunity” 378

Household Fuel 12%

Public administration and other public services 7% Education 2% Health Care 4%

Domestic vehicle Fuel 8%

Water,Waste & Sewage 3% Other bought services (inc financial services) 5%

Household Electricity 7%

Other non-food shopping 10% Personal Flights 11% Electrical goods 2% Travel by train, bus & other Transport 3%

Eating, drinking and staying away from home 7%

Car Manufacture and maintenance 5% Food & Drink from Retail 13% Source: Image created by Author based on information (The Total Carbon Footprint of Greater Manchester, 2021)

Carbon Footprint of GM residents

23%

Transport related emissions

43%

Amenity related emissions

66%

Carbon Emissions from Accessibility Related 379

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Accessibility Methods

Accessibility is an important factor in achieving a zero-carbon city. While it is linked to transportation, accessibility focuses on who takes trips, to where, how they choose to travel and the ease of which they can reach destinations. Thus, accessibility requires an integrated view of transportation and land use, since decisions made under each discipline will intrinsically affect the other.

The four components we have decided to analyse under the concept of accessibility are:

The most common element of accessibility contains the common element of linking travel to the activity, purpose, or land use at one or both ends of the trip. By supporting an integrated view of transportation and land use systems, accessibility is thus seen as a more balanced, holistic concept focusing on the system as a whole, rather than on aspects of the transport system only (Ferres, 2010).

• Mobility - the transportation systems in which people go to and from a given location.

Land Use

• Population - relating to the people and demographics of an urban area.

Population

• Land Use - referring to the type and number of amenities within an urban area.

• Population Density

• Amenity Type

• Migration

• Location of Amenities

• Agglomeration

• Spatial Configuration - the urban form of cities.

The asserted benefits of using an accessibility framework therefore include reductions in vehicle travel and associated impacts on energy consumption, air quality, and societal and personal costs. Methods, in relation to these parameters can help cities to achieve zero-carbon through the efficient placement of amenities within urban locations, allowing for easy access by the greater population; the reduction in travel time will lead to lower carbon emissions.

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Spatial Configuration

Mobility

• Compact Cities

• Transport Network

• The 15 Minute City

• Walkability

• Superblocks • Transit Oriented Development

• Reducing Car Dependency

Image created by Author

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Urban density

Systems Map

Reduced CO2 emissions

Urban blocks

Liveability

Pedestrianisation

Walkability

Compact Cities The 15 minute city

Super Blocks Car restrictions On the right is the Systems Map showing the different factors which affect and are affected by accessibility. The system contains sub categories which influence accessibility and the carbon emissions generated. This diagram allows for the understanding of relationships that can be modified in order to optimize accessibility and aid cities to becoming net zero. Certain relationships can be adjusted whilst others require careful planning as some are exponentially growing and require monitoring in order to prevent failures in the future.

Government facilities

Public Transport Use

Transit Oriented Development (TOD)

Spatial Configuration

Entertainment Food

Public Transport Recreation

Population Density

Accessibility

Land Use

Population

Growth

Movement

Education Health Essential Amenities

Commuters Migration Emigration

Finance

Mobility CO2 emissons

Vehicles Car Use

Air polluton

Ultra Low Emission Vehicles

Low emission zone Clean Air Zones Zero Emission Zones

Green Vehicles Active Transport

Nitrous oxides

Government policy

Public Transport

Cycling Walking

Light rail Bus

Tram Train Image created by Author

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System Dynamics Diagram

Spatial Configuration

Mobility

This map depicts the continuous simulation models using hypothesized relations across activities and processes related to Accessibility. Image created by Author

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Population Context

Manchester

Greater Manchester

Manchester has a population density of 12,210 people living per square mile (4,716 people living per square kilometre) and is the 9th densest city in the United Kingdom. The area that Manchester encompasses comes to 44.6 square miles (115.6 square kilometres) in total for the city itself.

The Greater Manchester area is the second most populous urban area in the United Kingdom with a population of more than 2.55 million, which includes Manchester as well as several cities. Manchester also has the third largest economy in the United Kingdom and it is the third most visited city in the country by foreigners after London and Edinburgh.

Manchester’s 2021 population is now estimated at 2,750,120. In 1950, the population of Manchester was 2,422,246. Manchester has grown by 20,044 since 2015, which represents a 0.73% annual change. These population estimates and projections come from the latest revision of the UN World Urbanization Prospects. These estimates represent the Urban agglomeration of Manchester, which typically includes Manchester’s population in addition to adjacent suburban areas. Manchester is a city and metropolitan borough and the principal city in the Greater Manchester metropolitan county in North West England. Manchester is the 6th largest city in the United Kingdom with an estimated population of 530,300 in 2016.

During the 2011 census, Manchester was the third fastest-growing area in the United Kingdom with the greatest percentage growth outside of London, increasing 19% in a decade. Manchester is expected to continue its fairly rapid growth in the coming years. The population of Greater Manchester grew by 7.7% (199,900) between 2006 and 2016. Manchester local authority saw its population grow by 16.7% (+77,500) between 2006 and 2016 – double the UK growth rate over the same period (7.9%).  Greater Manchester has the largest travel-to-work area of any conurbation in the UK outside of London, with 7 million people living within one hour’s drive of the city centre (Census: 2011). There are 1.19 million households in Greater Manchester (Census: 2011).

“Manchester was the third fastest-growing area in the United Kingdom” Source: Image created by Author based on information (Manchester Migration, Bullen, E., 2015)

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Population Migration

Between 2009 and 2017, 436,440 people moved into Manchester from other regions in England and Wales and 568,060 moved out, leading to a net outflow of 31,620 people from the city. This was the third largest net outflow from any English or Welsh city during the same time period. In comparison, London experienced a greater net outflow of 340,310 people while Bournemouth saw a net inflow of 15,090 people moving into the city.

There are also considerable net outflows from Manchester to London and the South West, 6,220 and 3,740 respectively. On the other hand, the city experienced net inflows from the North East, West Midlands, Yorkshire, South East and East, but these were small (Bullen, 2015).

Much of this migration was between Manchester and other regions of the North West. Of those moving into Manchester, a third of those came from elsewhere in the region, and a third of those leaving the city stayed within the North West. This resulted in an overall net outflow of 29,200 people to the region.

Source: Image created by Author based on information (Manchester Migration, Bullen, E., 2015) (Source: Bullen, 2015)

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Leis ure ce

Benchmark Distances

ntre

District centre (superstore)

Land Use The amenities selected for benchmark distances have been selected under the basic needs of residents within cities. The amenities are distributed by main groups and each group has its own sub category which holds different small types that fit under each industry.

o ch

0m 190

te th cen Heal tors) c (4 do

1900m

The benchmarks show the maximum lengths people should walk / cycle to amenities, these lengths are based on studies by Soni, K, (2021) and will aid the analysis of accessibility in the Northern Gateway Development.

ar nd o c ) Se rge (la

120

1200m

Pitch

Food market

Theatre

Bicycle rental

Embassy

Electric scooter rental

Fire station

Nursery Library College University

Bureau de Change

Pharmacy Hospital Veterinary Nursing home

800m

Food court

Cinema

Courthouse

Dentist

Community Centre

Nature reserve

Arts centre

Stations

Bank

Pub

Town-hall

Clinic

Sports centre

Tram stop

ATM

Sch

Bar

Police station

School (primary, middle and secondary)

urs

Loc

al c

entr

fice

Playground

Social centre

Bus stop

ery

t of

Restaurant

Post office

Health

Pos

Garden

Community centre

Finance

Cafe

Education

Secondary school

100 800

Park

Entertainment

ary

Hospitality

Public Transport

Prim

Recreation

Government Facilities

m 500 m p Sho 600 l a Loc 800

Amenity Type

Swimming pool

Benchmark accessibility distances for key services and amenities.

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(Readapted from Soni, K., 2021)

Source:

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Spatial Configuration

Relationship with other factors

Introduction

• Compactness is generally promoted as a positive goal for urban planning. The World Bank has argued that ‘density makes the difference’ and adopted this concept as a central tenet of its urban planning policy over many years. Densification also has been promoted to achieve sustainable development within European policy.

Green Space

ba np Fo ar res ks try

Water network

Water

Irrigation

mi ar

Waste network

Compact Cities

Location of Amenities

tion nt transporta

rid

SPATIAL CONFIGURATION

tra

n ce ed lis m ste sy

• The Super-block is an urban model designed by Barcelona City Council in collaboration with the Urban Ecology Agency it aims to reclaim public space for people, reduce motorised transport, promote sustainable mobility and active lifestyles, provide the benefits of urban greening and mitigate effects of climate change (Mueller et al., 2020; Oliver and Pearl, 2018).

15 Minute City

Transport

Transport system

Super-blocks

Green roof

Buildings

• It aims to reduce private car dependence and promotes residents to use public transport; thus, TOD is seen as an important solution to reducing CO2 emissions and combating climate change,

Energy

erg

• Transit-oriented development (TOD) focuses on maximising the amount of residential, commercial, and leisure spaces within walking distance of public transportation nodes, it promotes urban density, compact urban form and public transport use (Cervero et al., 2004).

ruction

Transit Oriented Development

cient const

Water recycling

• In transport-related carbon emissions, there is up to a ten-fold difference between the most energy intensive sprawling cities and energy efficient compact cities (Simon, 2016).

Energy effi

Energy efficie

Compact City

Waste

Food

• The 15 minute city is a concept developed by author Carlos Moreno, he advocates for an urban set-up in which locals are able to access all their basic essentials at a distance that would not take them more than 15 minutes by walking or by bicycle. • With essential amenities being so readily accessible, residents will rely less on private vehicle use - reducing carbon emissions and urban heat. (Moreno et al., 2021)

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Car ownership in different UK urban areas

Compact City

Cars per capita (2019)

Area

Compactness is an important factor in achieving the most efficient and sustainable cities. Research has shown that urban compactness is correlated positively with CO2 economic efficiency. Higher densities in the name of more sustainable living is a policy advocated by the world bank.

In the city centre residents own 0.2 cars, on average, but that is doubled for residents of suburban areas. In city centres that car ownership levels have decreased the most in the past 10 years. As urban areas become less compact, car ownership increases, leading to greater CO2 emissions per capita.

Population change 20102019

2010-2019 change

0.23

-21%

+34%

0.54

+5%

+6%

City centre

Suburbs

Source: BrittleBank, W., 2014

How can compact cities help to achieve Zero Carbon?

0.65

+6%

Hinterland/outside 1

Green Space

• Increases the amount of land available for forestry and agriculture. • The atmospheric concentration of CO2 can be reduced via carbon sequestering through the added greenspaces.

Reduces consumption

Reduces distance

• As more people live on the same amount of land, more people are closer together - reducing the distance needed to travel, which lowers the amount of carbon being emitted.

Reduces building cost

• Compact cities mean that less buildings are required to house the population, this lowers average building costs.

Emissions from new developments

• Compact cities reduces the amount of infrastructure required to spread across a city i.e. water pipes, streets, sewage network etc. • Less energy is required to build and power an extensive infrastructural network

Share of all CO2 emissions new build (tonnes/year) completions (%)

Type

CO2 emissions (tonnes/year)

Share of all new build completions (%)

1.1

0.9

2.2

1.7

1.5

New flats

New houses

Increased local trade

• Local trade is increased as residents are closer to the facilities and amenities that they need most. The demand for vehicular use is thus reduced if residents can access what they need in a short distance.

Suburban sprawl and the construction of single-family, detached housing has negatively affected domestic emissions. New apartments emit 67 per cent less than new houses – flats built (or converted) in 2019 emitted 0.9 tonnes of carbon annually, while houses constructed in the same year were responsible for 1.5 tonnes. his gap has widened in recent years – between 2013 and 2019, emissions from new flats went down by 18 per cent, on average, compared with 11 per cent for new houses

City density versus CHG Emissions per capita 25 Number of perople

20 CHG Emissions (tCO2e/capita)

• Less energy is required to build the city;less materials are needed, and less energy is needed for transport

Reduced infrastructure costs

Washington DC

divded by

15 Portland OR Los Angeles

Shanghai Bangkok

Base land Area

Beijing

Prague New York City

Cape Town

London

Rio de Janeiro

100

Seoul

Barcelona

150

200

250

300

350

There is a general correlation between higher urban density and lower emission levels

Urban density (persons/hectare) Source: Quinio, V. and Rodrigues, G., 2021

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Method of travel to work for workers in Manchester 80

In-commuters

Percentage (%)

Live and work in Manchester Total 40

Source: White.C.2021

Transit Oriented Development Transit oriented development (TOD) is a type of urban development that clusters jobs, housing, services and amenities around public transportation hubs; these developments are designed to be compact, mixed-use and friendly to pedestrians and cycling. For cities to accomplish a significant modal shift away from dependence on private vehicles, pursuing TOD is a key requirement (C40 Knowledge Hub, 2021).

Driving car/van

Bus

On foot

Train

Passenger car/van

Tram

Bicycle

Motor Cycle

Taxi

Source: Adapted from Frost (2016)

Implementing TOD strategies in Manchester could help to reduce the amount of people who use a car to travel to work. Currently, driving a car is the highest method of travel to work, by reducing this amount, the amount of carbon emissions can be cut significantly as commuters opt for public transportation.

TOD schemes can have a significant impact on carbon emissions; evidence from Chicago shows that households located within half a mile of public transport have 43% lower transport related CO2 emission than the average household in the Chicago Metropolitan Area. Furthermore, households located in the downtown Chicago area, with the highest density of jobs and housing and the best public transport connections, have 78% lower transport related CO2 emissions than the wider area.

As shown in the graph below, as population density increases the percentage of car or van use decreases and the percentage of sustainable mode of transport increases.

Mode choice for travel to work against population density

Standard TOD Model

Percentage car or van (driver and passenger)

80 70

Residential

Percentage sustainable mode (public transport and active travel)

Percentage (%)

400

Other

Public/Open Space

50 40 30

- 80

etre

Transit Station Core Commercial

Open Space 10

Office/Employment

0 0

100

120

140

Population Density (number of persons per hectare)

Source: Ritchie and Roser, 2020

Arterial Road Source: Adapted from Frost (2016)

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2021 CPU[AI]

Superblocks Impact of the Barcelona Superblock

Barcelona first introduced its ‘Superblock’ in 2016 and is an ongoing strategy; it was created with the concept of carving out islands of car-free space by routing traffic around multi block areas. The implementation of ‘Super-block’ strategies could be considered by Manchester City Council, whereby large urban areas are given priority to walking and cycling.

67.2%

Superblocks are a grid of blocks and basic roads forming a polygon; they are approximately 400 x 400 m, and contain around 5000–6000 inhabitants within the block. Inside the super-blocks, cars are prohibited or restricted to 20km/h, priority is given to pedestrians and cyclists, and open space is reclaimed or created from parking. The model represents a new model of mobility that restructures the typical urban road network, thereby significantly reducing automobile traffic, and accordingly GHG emissions, while increasing green space in the city and improving the health and quality of life of residents.

Increase in pedestrian space so far

24%

Reduction in average annual levels of ambient NO2 pollution once complete

Source: Escofet,2020

The Superblocks require a low level of intervention as they do not need investment in hard infrastructures, nor do they involve demolishing buildings or undertaking massive development. The city of Barcelona has been implementing Super-blocks as one of the measures to combat climate change with very positive results (O’Sullivan, 2020; López et al., 2020).

Current Model 11% 73%

Current Model

27%

33v% 89%

67%

Superblocks Model

40%

Superblocks Model

Decrease in CO2 emissions per capita once complete

23%

Adapted from Lopez et al., (2020)

77%

Adapted from Lopez et al., (2020) Emergency services

Space for pedestrians versus road

99%

95%

Accessibility

Air quality

(Sidewalks >2.5m)

(emission <40µg/m3 any)

Residents vehicles Reproduced from Lopez et al., (2020)

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2021 CPU[AI]

Emissions in Greater Manchester

15 Minute City

Bus stations (0.1%)

Combustion (34.4%)

The 15 minute city is a concept that promotes the idea of mixeduse, community-based and sustainable infrastructure and development. It relies on the premise that all residents should be able to access their daily needs within a 15 minute walking or cycling radius from their homes – and enjoy a better quality of life as a result (Moreno et al., 2021).

Elements of a 15-minute city

CO2

Rail (3.9%) Air (0.9%) Other (0.9%)

Boilers (6.7%)

Key aims of a 15 minute city

Part Bs (0.2%)

Healthcare clinics and pharmacies

Roads (30.7%)

Part As (22.3%)

Reduced car dependency

Motorway Emissions Primary schooling and nurseries

Lower transport emissions and better air quality

Major Road Emissions Bus <1

OGVs (22.7%) OGVs (36.2%)

Fire fighting/policing/emergency services

Create and grow social and park space

Local government offices

Improve health and well being

Grocery stores and other essential retailers

Improve key service and amenity accessibility

OGVs(22.7%)

Cars (46.1%)

Cars (57.9%) LGVs (14.9%)

Leisure and dining venues

LGVs (16.9%)

Leisure and dining venues Source : GOV, 2021

Public Transport

Car Use in Greater Manchester • In Greater Manchester, road transport accounts for 31% of all carbon dioxide emissions. • Cars are the main source of these emissions, accounting for 58% of motorway emissions and 46% of major road emissions (Transport for Greater Manchester, 2016). • Promoting the concept of the 15 minute city could help to reduce the carbon emissions as it would lessen the number of journeys residents make by car.

400

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2021 CPU[AI] Surface Utilisation

Manchester City Plan 1945 In 1945, the UK was at the beginning of the great transition from war to peace, with many people thinking about the sort of world to be built for posterity. The road proposals in Manchester were based on research work wholly carried out in the city. Two outstanding features which have are important bearing on the ultimate Plan are the forecast of future population and the road proposals for the city.

The city has an incongruous mixture of building types which constitute one commercial centre The grass and trees lead from the green belt on the periphery towards the city centre, insulating residential from industrial zones and dividing the residential zones into more compact and self contained communities.

Problems in the city

Outworn & overcrowded buildings

Dirty, Ugly & Congested Manchester’s war damage

Unhealthy living & working conditions

The commercial area is restricted to the city centre, resulting from increased commercial importance of district and neighbourhood centres, the larger industrial zones have been so located that they lie in the intermediate city belt traversed by the Intermediate Ring road. The object of the location increases the overall efficiency of passenger and goods transport by inducing heavy traffic to avoid the city centre and take advantage of the rapid transit facilities afforded by the construction of this new road through the intermediate and outer areas. Houses Commercial Educational Parks & Open spaces Industrial

Residential

Enable inhabitants of the city to enjoy real health of body and mind

Ease of travelling Character & distribution of workplaces

Opportunity to access recreational spaces

Aims of the 1945 plan

Access to fresh air & sunshine

Good Housing

Improve living conditions to increase vitality & the power to resist infections

Basis of the 1945 plan

Composition of the present population and family units Source: (Nicholas, 1945)

402

Plan sufficiently elastic to permit considerable alterations even in basic concepts

Means of moving about

Domestic & social ways of living

Future influence on size & structure of population Source: (Nicholas, 1945)

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2021 CPU[AI]

Regional Road Communications

Manchester city plan 1945 - Zoning The principle of the zoning: the grouping of commercial, residential and industrial buildings into their respective areas, the relative distribution of their areas, and their separation by belts of open space; and how these areas are served by ring and radial road and by railways.

Manchester’s highways form a part of the communications network for the region. The two major ring roads provide fast and safe by pass routes, avoiding congested areas.

Arterial roads General Industrial zone

Passenger stations

Major ring roads

Central commercial zone

Major road communications Residential zone Railway Communications Park Belt

Light Industrial zone

Source: (Nicholas, 1945)

404

Source: (Nicholas, 1945)

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2021 CPU[AI]

Mobility 50%

of all journeys to be made by public transport by 2040

30%

of all carbon emissions comes from Transport

48%

Carbon reduction 1990-2020 & a target of 80-90% by 2050

In 2019, MCC set out their ambition to improve their transport system so that — by 2040 — 50% of all journeys in Greater Manchester are made by public transport or active travel, supporting a reduction in car use to no more than 50% of daily trips. The GM Transport Strategy 2040 focuses principally on creating an integrated, well-coordinated transport system which supports a wide range of different travel needs. The 2040 Transport Strategy is structured around five types of trip - called ‘spatial themes’ - to enable an integrated set of interventions to be developed to address specific issues in different parts of the cityregion and for different types of travel. In 2017, the Greater Manchester Mayor appointed the city-region’s first Cycling and Walking Commissioner, Chris Boardman. The Commissioner’s, Made to Move, report detailed fifteen essential steps required for Greater Manchester to see a step-change in walking and cycling.

Following this, Greater Manchester’s local authorities used innovative planning techniques to develop the Bee Network: a bold plan to connect all communities in Greater Manchester by the UK’s first fully joined-up cycling and walking network. Importantly, the network was developed by the people who live, work and travel in Greater Manchester, with wide-ranging public consultation to refine and improve the plan. At 1,800 miles in length, the Bee Network will be the country’s largest walking and cycling network, taking 10 years to deliver at a total cost of £1.5 billion. When complete, it will connect every neighbourhood of Greater Manchester. With continuous, high-quality provision for walking and cycling, people will have a viable and attractive alternative to driving, enabling them to leave the car at home, visit friends on foot or ride to the shops (Greater Manchester Transport Strategy 2040, 2021).

Source: GOV.UK(2021)

Source: Barlow.N, 2020

Daily trips (in millions) 0

Now

39%

61%

Sustainable modes

Active Travel Fund cycling schemes Active Travel Fund Active Neighbourhoods

2040

50%

Car or other

Existing Major cycling and walking routes Permanent high quality walking and cycling routes to be delivered by the end of 2021

406

Source: Adapted from Greater Manchester Transport Strategy 2040, 2021

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Manchester Transport Target Mode of Transport

50%

National rail - 41.15g

Motorcycle - 102.89g

30%

48%

MCC Target 2040

Light rail and tram - 35.08g

Of all journeys to be made by public transport by 2040

Of all carbon emissions comes from Transport

Total CO2 Emissions from Transport

Active Travel and Public Transport 257.94 g

Active Travel and Public Transport Target - 257.94 g

Bus- 104.71g

Total Carbon emissions 986.65gC02e

Car (diesel) - 170.61g

Carbon reduction 1990-2020 & a target of 80-90% by 2050

Private Vehicle Use 730.71g Privat Vehicle Use Target -

Source : Transport For Manchester.2021

Car (petrol) - 192.28g Source : Sankey Diagram created by Author using information from GOV, 2021)

Greater Manchester’s transport vision is known as the ‘Right Mix’ - its aim is to reduce car’s share of trips to no greater than 50%, with the remaining 50% made by public transport, walking and cycling. This will mean approximately one million more trips each day using sustainable transport modes in Greater Manchester by 2040. This aim of this strategy is to help the Manchester city-region to achieve its long-term environmental ambition for carbon neutrality by 2038. All ten Greater Manchester local authorities, and GMCA, have declared a climate emergency, making clear that urgent action is needed to put Greater Manchester on a path to carbon neutrality by 2038.

408

The city-region aims to make a fair contribution to a stable global climate, and to the Paris Agreement of holding the increase in global temperatures to well below 2°C. Transport for Greater Manchester notes the importance of acting to reduce the impact of transport on the environment stating that “at every stage, this Strategy takes into consideration the actions needed to protect people’s health, reduce air pollution and tackle the climate emergency.”

Source: GOV.2021

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2021 CPU[AI]

Low Emission Zones Zoning Strategies

Aberdeen

Dundee

Introduction Low Emission Zones (LEZs) exist in many countries, they are defined as areas where the most polluting vehicles are regulated with the aim of improving air quality; in the UK they are commonly known as Clean Air Zones (CAZs;)

Class

Vehicle

Bus

As shown in the table on the right, the UK has four classes of Clean Air Zone. Local authorities can decide what level of restriction to apply.

Taxi and private hire

Key Aims

Bus

Although the main function of LEZs is to improve air quality, they can have a profound impact of carbon dioxide emissions by regulating the most polluting vehicles A key reason for the implementation of LEZs is that by restricting certain vehicles, or commanding payment from them when entering these zones, many drivers will opt for sustainable alternative forms of transport such as walking, cycling or public transport; they may also switch to lower-emitting vehicles like electric cars or plug-in hybrids. Ultra low emission vehicles with significant zero emission range will never be charged for entering or moving through a Clean Air Zone.

Coach

Charges applied to vehicles below this Euro Standard

Edinburgh Glasgow

Euro VI

Euro 6 (diesel) Pre euro 4 (petrol)

Manchester Liverpool

Coach

Euro VI

Sheffield Birmingham

HGV

Oxford Euro 6 (diesel) Euro 4 (petrol)

Taxi and private hire

Brighton Southampton

Bus

Coach

Euo VI

Urban Access Regulations in the UK Urban Road Tolls Low emission zone (includind planned) Other Access Regulations

HGV

Minibus

London

Bristol

LGV

Euro 6 (diesel)

Zero Emission Zone

Euro 4 (petrol) Taxi and private hire

Manchester Clean Air Zone (CAZ) Bus

Coach

Euro VI

LGV

Euro 6 (diesel)

HGV

Minibus

Taxi and Private cars private hire

Euro 4 (petrol)

The Greater Manchester Clean Air Zone is due to be introduced on Monday 30 May 2022. It will be a Class C Zone. High-polluting vans, buses, coaches, taxis, private hire vehicles, minibuses and heavy goods vehicles will be charged for driving around the city region if they don’t comply with NO2 emissions standards. Private cars and motorcycles are not affected by the CAZ. Source: What are Low emission zones, 2018

Euro 3 Minibus

Source: What are Low emission zones, 2018

Mopeds

Source : Assest.GOV. 2021

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Case Study: London

London LEZs

Zoning Strategies ULEZ Central London (from 8 April 2019) ULEZ extension to inner London (from 25 Oct 2021) LEZ London-wide (from 26 Oct 2020)

Impact of the London ULEZ (April 2019) and the LEZ

The London Low Emission Zone is the UK’s largest and most comprehensive LEZ; its implementation has largely been successful which is why it has been chosen as a case study to focus on. Furthermore, the introduction of the Ultra Low Emission Zone has had a significant impact on air quality and CO2 emissions.

13%

However, as no two cities are the same, it is important to note that Manchester must carefully phase the implementation of its Low Emission Zone; this must be done before adopting a policy as expansive as the London ULEZ - this will allow the public sufficient time to adapt to the new changes in policy.

Reduction in carbon dioxide emissions (CO2) (ULEZ April 2019)

40-50%

Class

Vehicle

Reduction in Black Carbon (PM25) (LEZ)

Low Emission Zone

Large van

Minibus

Bus

Reduction in traffic (ULEZ of April 2019)

Coach

Charges applied to vehicles below this Euro Standard

Euro 3 (diesel)

Euro 6 (diesel)

HGV

Minibus Source: What are Low emission zones, 2018

Ultra Low Emission Zone

Mopeds

Taxi and Private cars private hire

Euro 3

Euro 6 (diesel) Euro 4 (petrol)

Small van

Euro 6 (diesel) Large van

Minibus

Greater London Authority Boundary Zero Emissions Zones

Zero Emissions Zones Zero emissions zones (ZEZs) are areas that prohibit diesel and petrol vehicles. Only allowing access to zero emission vehicles i.e. electric vehicles.

Emission standards for cars, vans motorcycles and mopeds.

The scheme is a part of the Mayor of London’s zero carbon London by 2050 plan - it aims to reduce greenhouse gases and harmful air pollution.

Maximum 75g CO2/km

In order to achieve this ambition of zero emission transport, it is necessary for there to be an increase in trips taken by walking, cycling and public transport, the remainder of all trips should be taken by vehicles with zero emissions. The Mayor aims to eventually introduce a larger zero emission zone across inner London by 2040 and London-wide by 2050.

Minimum 20 mile zero emission range

TfL recommends an ‘effectively zero emission’ standard to be implemented in the initial stages of the ZEZ - this is shown on the right. This is to facilitate the gradual progression towards actual ‘zero emissions’ owing to the limited availability of zero emission vehicles. These standards will be tightened as zero emission vehicles become more widely available

Euro equivalent NOX emission standard

Euro 4 (petrol) Source: Zero Emission Zones, 2021

Source: What are Low emission zones, 2018

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2021 CPU[AI]

Problems Associated with Urban Traffic

Motorised Dominance Reclaiming City Streets

Equity

552 Fatal road accidents occurred in 2020.

The existing road networks have not been designed to accommodate the growing population and congestion. With the current population growth estimated to be 3 million by 2030 in Manchester and private car ownership on a constant rise the need for a developed public transport system and the improvement of accessibility to basic amenities to be accessible primarily by walking or cycling in order to decrease the carbon emissions emitted through private car ownership.

Additionally, motorised dominance allows for greater accessibility but at the cost of the environment. The introduction of so called ‘green lanes’ will allow for a greater reduction of GHG’s and with more strategic urban sprawl small communities can be formed. Furthermore, peoples behavioural changes will require attention as the shift from private car ownership to using public transport/walking or cycling may require state incentives and serious interventions if we are to reach net zero emissions.

38,523m2 Of urban space lost to motorized vehicles Source: Commission, 2004

Nearly 50% of households in Miles Platting and Newton Heath have no access to a car yet they pay the price of traffic without enjoying mobility benefits offered by car ownership.

Economic Efficiency Traffic congestion, pollution and accidents results in significant direct and indirect costs.

Diminished quality of the urban environment caused by parked cars/car parks and other infrastructure related to motorised vehicles. Manchester car parks use up nearly 8% of urban space which could be transformed or reused to help its growing population

Noise And Vibration Transport is one of the main sources of urban noise pollution, with the growing rate of population and car ownership it can become a serious problem as nearly 70% of world population by 2050 will reside in major cities.

Loss of Urban Space Waste of limited urban space Modes of Transport utilise space for moving and parking over a operational period of time e.g., buses travel dictated routes and park at a garage. This moving and parking using a study from STI in Switzerland can be aggregated into a unit of measurement which can be translated into the amount of space utilised for a certain amenity. The formula for the measurement is:

In Manchester’s case, the urban space utilised for car parking space could be turned into POI’s and houses for the public. As an example the urban space used by travelling from Collyhurst to City Centre A.Private Car and B.Bus is A = 304.33m2 and B =144.24m2. As the data shows private car uses double the amount of space for a single journey in comparison to a bus.

Space x time = urban space used m2 x hr = m2

Motorise transport infrastructure such as roads, highways and car parks take up highly valuable city centre land, and spoils and threatens existing open spaces.

Energy Consumption Air Pollution Multiple effects including global warming, health problems e.g.. asthma/cancer and building decay. The Department of health in the UK estimates the health costs of particulates in urban areas of Britain to be up to 500 million per year

Accidents Over 552 fatal deaths have occurred as a result of motorised vehicles in Manchester 2020. There is a four time more fatalities occur in urban areas due to congestion and lack of a complex public transport system which will allow for greater accessibility.

414

Visual Intrusion

Transport consumes 4% more energy every year which represents a doubling of energy used every 20 years

Competitiveness Traditional Central Business District face competition from less congested out of town retail centres. The construction of large commercial complexes such as Trafford Centre shifts the congestion and pollution to a different location. Source: Commission, 2004 Source: Council, 2021

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2021 CPU[AI]

Nuremberg Case study

Map Of Pedestrianized Areas in Nuremberg

Reclaiming of limited urban space

36044

vehicles evaporated

15%

decrease in CO2 emissions

Nuemberg’s city centre and the surrounding areas have been transformed into a sophisticated pedestrianised area including a sustainable public transport network. The city since 1970’s struggled with the congestion of private vehicles and worsening air quality within the town. The city with narrow streets and heavily congested areas gave priority to more sustainable, less polluting modes of transport to provide better access to amenities within the area. The strategy that Nuremberg local authority has undertook was to cordon roads within POI’s and provide alternative routes for motorised vehicles. The city reshuffled its own urban plan to accommodate the changes and effectively rejuvenate the area.

The congestion of cars decreased by 51% in 1989 showing a positive impact pedestrianisation has had on the area. The levels of C02 decreased by 15% which resulted in not only cleaner air but a healthier population. (1) The removal of car traffic within the city allowed for renovations of old derelict building and encouraged people to make sustainable choices in terms of modes of transport without the provision of incentives or enforcing of strict rigorous policies. Nuembergs attempt can be seen as a progressive step in reaching net zero emissions and can allow for alternative modes of transport to thrive and sustain the population.

17.6%

Source: Stadt Nürnberg Verkehrsplanungsamt, Mai 2002

Rathausplatz after renovation

Central Market Square after renovation

Increase in quality of life since the implementation of the strategy Source: (Commission, 2004)

Source: (Commission, 2004)

Source: Stadt Nürnberg Verkehrsplanungsamt, Mai 2002

416

417

Public Transport Congestion

2021 CPU[AI]

Key: Low Congestion

Motorised Congestion

High Congestion

Analysis of Motorised Congestion in Manchester

Parameters Taken into Account

The analysis of the existing road network located in the Northern Gateway identifies major issues with the system in place. The designated road network is too congested especially closer to city centre.

Distances between Amenities A B

Public Transport The existing network of public transport connections seems to be sufficient for the needs of the public however in places like City Centre and Cheetham Hill it seems to be too congested allowing for accumulation of CO2 emissions to take place as it mixes with private cars/taxis and other modes of transport. The average CO2 emission from a person travelling from City Centre back home is around 189.4gCO2/km. In comparison a average car journey produces around 315gC02/km. This clearly shows that a more complex and connected public system if placed will help to reduce emissions.

Modes of Transport Miles Platting & Newton Heath Car Ownership 68

Private Car Congestion

Distribution of Amenities

Low Congestion

526

High Congestion

Private Cars With the lack of sufficient amended traffic regulation around the city it creates hotspots for congestion. The private car diagram identifies Rochdale road as congested as Oldham road yet Rochdale road does not connect another major city / settlement.

Key:

Miles Platting & Newton Heath Car Ownership Miles Platting & Newton Heath Car Ownership 68

2642 526

526

4198

Carbon Calculations Using Urbano an analysis tool, the results shown that the need for private cars in Collyhurst does not exist as basic amenities can be accessed within 15 -20 minutes of walking.

2642

2642 4198

No Car Ownership

418

1 Car

No Car Ownership No Car Ownership 1 Car

2 Cars Car 21Cars

23 Cars Cars

3 Cars 3 Cars

4198

4 Cars 4 Cars

4 Cars Source: GOV.2020)

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2021 CPU[AI]

Urban Network Analysis Los Angeles City Lab, 2021

Example Analysis The Urban Network Analysis (UNA) Rhino toolbox offers a way of analysing spatial accessibility, pedestrian flow and facility patronage along spatial networks.

Using the UNA toolbox, the following accessibility analyses has been conducted:

Using UNA metrics in Rhino, we have conducted a series of analyses looking into the spatial accessibility of the Northern Gateway; specifically analysing how different residents are able access to different types of amenities (recreation, health, education, financial, government facilities, food and hospitality, public transport, and entertainment). We analysed the levels of accessibility to these amenities using the distanced that can be walked within a 15 minute time frame.

•

Gravity Analysis:

Select Road Network

Select Origins/ Destination

This is the most popular type of accessibility analysis, visually displaying the ease of which users can access a specified destinations.

Closest Facility • Measure how many households and/ workplaces have a particular facility as their closest facility. Pedestrian Flow: • Measures the level of pedestrian flow to different destinations within a road network. Origins = Households Destination = Amenity Type

420

Analysis

Map showing accessibility from origin to destination

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2021 CPU[AI]

The Gravity Accessibility Index measures the ease with which a set of destinations (amenities such as recreation, health, government, education, finance, transport and hospitality and entertainment facilities) can be accessed from a set of origins (all buildings including households and businesses), within a 1200m radius as this is specified as the average distance a person can be walk within a 15-minute time frame.

Metodology

Amenity

To calculate the accessibility, the gravity index assumes that accessibility at Origin (I) is proportional to the attractiveness (weight) of Destinations (J,) and inversely proportional to the distance or travel cost between (I) and (J). In this tool, the network distance is used as a measure of travel costs.

0 12

1000m

Calculation

Gravity

1 0.9

0.7

d [i,j] = the network distance between i and j, a = is the exponent that controls the Destination weight or attractiveness effect ẞ = the exponent that controls the “distance decay” effect. Thus, the Gravity index captures both the attractiveness of Destinations (W[j ]a).

0.6 0.5 0.4 0.3 0.2 0.1 0

beta = 0.002

Contains OS data © Crown copyright and database rights 2021 Ordnance Survey (100025252). FOR EDUCATIONAL USE ONLYContains OS data © Crown copyright and database rights 2021 Ordnance Survey (100025252). FOR EDUCATIONAL USE ONLY

beta= 0.004 beta = 0.02

Scale 1:20000

0 100 200 300 400 500 600 700 800 9001000 m Projection: British National Grid

Distance(m)

Nov 08, 2021 00:54 Oladipo Shobowale

Manchester Metropolitan University

As distance increases, accessibility drops exponentially, this is known as the distance decay effect.

Government

Scale 1:20000

0 100 200 300 400 500 600 700 800 9001000 m Projection: British National Grid

Nov 08, 2021 00:54 Oladipo Shobowale

Manchester Metropolitan University

Education

Gravity accessibility Index Low Accessibility

422

Health

0 100 200 300 400 500 600 700 800 800 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000

W[j] = the weight of Destination j

Recreation

Amenity

0.8

Gravity[i]r = Gravity index at Origin i within graph G at Search Radius r

Di g im g im a a Dip p g im g im

Gravity accessibility

High Accessibility

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Di g im g im a a Dip p g im g im

Gravity accessibility

Gravity accessibility Index

High Accessibility

Low Accessibility

Process to Reduce Carbon Emissions Time and Distance

Results

Travel cost

The results of the gravity accessibility analysis for the Northern Gateway site shows a high-level of accessibility for all amenities to the south of the site - as this is where the city centre is located towards Manchester Victoria. Most amenities are clustered within this area, in comparison to on the site which is lacking in amenity provision

Gravity Accessibility

Finance

Transport

Scale 1:20000

0 100 200 300 400 500 600 700 800 9001000 m

Low Accessibility

Action required

Projection: British National Grid

Nov 08, 2021 00:54 Oladipo Shobowale

Manchester Metropolitan University

Scale 1:20000

0 100 200 300 400 500 600 700 800 9001000 m Projection: British National Grid

Nov 08, 2021 00:54 Oladipo Shobowale

Manchester Metropolitan University

Increased travel time and distance

High Accessibility

Increase the provision of on-site essential amenities Improve public transport links and active transport network. Increase site compactness to decrease distance to amenities

424

Increased car demand

Increased carbon emissions

Entertainment

Food

425

2021 CPU[AI]

The Closest Facility tool is an analysis and visualisation of which destination facility (i.e. amenity type) are closest to each origin point (households). Each origin point is only linked to one absolute nearest destination, thus no origins are counted multiple times. The tool produces a calculation for each destination; showing how unique origin points (households) are associated with each destination facility (amenity).

Closeness Index

Di g im g im a a Dip p g im g im

Closest Facilities

High Closeness

Low Closeness

Amenities with a high number of origins associated with it indicates that the amenity has many households depending on it as their closest facility. A radius of 1200m has been used to define the maximum distance that each destination can be reached within - as this is the distance which can be walked within 15 minutes.

Recreation

Metodology

Health

Scale 1:20000

0 100 200 300 400 500 600 700 800 9001000 m

1200m The Closest Facility tool is an analysis and visualisation of which destination facility (i.e. amenity type) are closest to each origin point (households). Each origin point is only linked to one absolute nearest destination, thus no origins are counted multiple times. The tool produces a calculation for each destination; showing how unique origin points (households) are associated with each destination facility (amenity).

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Projection: British National Grid

Nov 08, 2021 00:54 Oladipo Shobowale

Manchester Metropolitan University

Scale 1:20000

0 100 200 300 400 500 600 700 800 9001000 m Projection: British National Grid

Nov 08, 2021 00:54 Oladipo Shobowale

Manchester Metropolitan University

1200m

Amenity 6 Amenity 8

Government

Education

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Closest Facilities Results Recreation

Education

Public Transport

The woodland and green space in the The site has an acceptable spread of The main public transport is the bus, which site provides residents with ample green- educational facilities within a 15 minute is accessible for residents; however, space. walking distance. there is the opportunity to extend the tram service to allow for greater accessibility. Health Finance Food and hospitality The north of the site is lacking in health The site is lacking in financial amenities; facilities; there is one facility in this this may create incentives for vehicle use Not enough food and hospitality location and it serves 337 buildings; this as its not accessible within 15 minutes. amenities - these are important for is may be too high. people to access, especially within a 15 minute walk; there is a vital opportunity to Government add more of this amenity. Entertainment

Finance

Entertainment facilities are clustered within the city centre, presenting the opportunity to provide more entertainment amenities on site.

Proximity to Amenities

Yes

No Add Amenities

Accessibility Metric

-Education -Entertainment -Finance -Food -Government Facilities -Health Facilities -Recreational Facilities -Public Transport

g im

Parameters:

Within 15 minutes travelling distance

Transport

Government facilities are clustered closest to the city centre and are lacking within the site; this may encourage residents to use private vehicular travel to access these facilities as it is not within their local area.

Entertainment

Food

Closeness Index

Source: Vigo.M and Brajnik 2011

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Low Closeness

High Closeness

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Pedestrian Flow Analysis Pedestrian flows is modelled using the ‘Betweenness’ metric within the Urban Network Analysis Toolbox. This allows estimates of pedestrian flows along planar street networks. The betweenness analysis describes predicted foot traffic on the streets of the Northern Gateway, using residential buildings as origins, and bus stops, tram stops and railway stations as destinations; this helps to show which street segments are likely to be used by the highest number of pedestrians walking to transit. This analysis can help to determine where best to invest in public space improvement to improve the walkability of the site.

Betweenness works by calculating which path users are most likely to take in a network to reach a particular destination. Betweenness number shows how many people are expected to take walk along a particular street. The higher the number, the more people that are expected to walk along this path. The betweenness tool estimates the number of pedestrians that might potentially cross each network segment. The segment next to the bus stop will most likely experience the most pedestrian traffic.

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1200m

Using the Betweenness tool, the residents were mapped to their nearest public transport facility within 1200m of their home. The results of this analysis shows that the highest pedestrian footfall is to the south, along Rochdale Road, leading to the City Centre. There is the opportunity to provide a transit hub in a more central location on the site - this would encourage public transit rider ship within the Northern Gateway, thus reducing car dependency.

Methodology

Pedestrian Flow Low number of pedestrians

High number of pedestrians

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Carbon Emissions from different Modes of Transport

Carbon Calculations

We have calculated the carbon emissions for different walking_total = x[0] ( 1.2 x 8gC02) = 12g

Modes of Transport

minutes distance away.

methods of transport (walking, cycling, bus, car, tram and taxi) from a point of origin to an amenity that is within 15

35m 3.65m(single lane)

Walk

Speed 2.5mph, 3 people per lane, 1m apart

Primary Fuel

Persons Moved per Hour

CO2 footprint per km

Food

17,600

Bike

Speed 15mph, 2 bikes per lane, 6m apart

Primary Fuel

Persons Moved per Hour

CO2 footprint per km

Food

14,400

11g

cycling_total = x[1] (1.5 x 11gC02) = 16.5g bus_total = x[2] (1.8 x 89gC02) = 160.2g

x_total = x[x] ( amenities within 15mins x C02 emissions car_total = x[3] (2.5 x 123gC02) = 307.5g from mode of transport used) tram_total = x[4] (3.0 x 54C02) = 162g walking_total = x[0] ( 33 x 8gC02) = 264g taxi_total = x[5] (5.0 x 218C02) = 1090g cycling_total = x[1] (48 x 11gC02) = 528g C02e = distance travelled x mode of transport bus_total = x[2] (65 x 89gC02) = 5,785g a = education amenities + entertainment amenities car_total = x[3] (58 x 123gC02) = 7,134g + finance amenities + food amenities + government amenities + health amenities + recreation amenities +

tram_total = x[4] (0 x 54C02) = 0g

public transport amenities

taxi_total = x[5] (78 x 218C02) = 17,002g x_total = x[x] (possible travelling distance within 15min x C02 emissions from mode of transport used)

Car

Speed 20mph, 1 car per lane, 18m apart, occupancy: 1.5

Primary Fuel

Persons Moved per Hour

CO2 footprint per km

Oil

4,400

123 g Source: (Kilograms of CO2 per passenger kilometre for different modes of transport within the UK,2021)

Bus

Speed 20mph, 1 bus per lane, 18m apart, occupancy: 25

Primary Fuel

Persons Moved per Hour

CO2 footprint per km

Oil

52,800

89 g

Carbon Emission from Amenity Type (CO2kg)

Area (m2)

Carbon Emission from Transportation Type (CO2kg)

Number of Units

Distance Travelled (m)

Tram

Speed 20mph, 1 tram per lane, 18m apart, occupancy: 25, tram length: 15m

Primary Fuel

Persons Moved per Hour

CO2 footprint per km

Electricity

66,000

54 g

Taxi

Speed 20mph, 1 taxi per lane, 18m apart, occupancy: 2

432

Primary Fuel

Persons Moved per Hour

CO2 footprint per km

Oil

3,000

218 g

Methodology A X

The method used to calculate the carbon emissions for the accessibility to different amenities consisted of using a residential area which in this instance was Collyhurst, then the point A was fixed and distances to different categories of amenities was measured. The distances were multiplied by different carbon emissions from three modes of transport ( private car, bus and cycling). The results then were compared against the distance and CO2 produced and it is clear that private car usage results in greater CO2 emissions and also due to the lack of amenities the residents of Collyhurst produce 2x more CO2 than the residents of the neighbouring borough of Ancoats.

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Carbon Emissions from Collyhurst (Private Car)

CO2

Train (Manchester Victoria)

2243

Tram Station (Queens Road)

843

2598

NQ Cheetham Fort

1701

193 3310

HMP Strangeways MCC

3057

346 269

1388

158

St.Micheals Flags

1803

Sand Hills

207

1221

138 1456

165

HSBC

2798

Co-op Bank AMENITY TYPES

342

2363

311

2456

Spar ATM

290

2308

263

2450

New Cross Dental Surgery

276

1902

215

KissDental

Health

315 3042

Intergrated Dental Holdings

2644

Dr A Bokhari

297

1645

Cheetham Hill Medical Centre

188

1614

Whitley Road

753

The Surgery

186

82 1069

Cohens Chemist

123

666

Haven Chemist

1383

151

Cohens Chemist Ancoats

2513

Manchester Pharmacy

Education

374

2868

CCA Job Centre Centre

Recreation Financial

214

Corn Exchange

Egghenge

283 2639

Collyhurst Nursery School

663

Manchester Communication College

473

Al Sadiq Academy

1302

146

1407 0

297

Abbot Community Primary School 500

163 1000

Distance and CO2 Emissions 434

304

1894

Etihad

Collyhurst

242

Ancoats

Government Commercial

The graph on this page depicts the distances and CO2 emissions from a point within the residential area of Collyhurst to different amenity types. The mode of transport used was a private car, and it was calculated using the Urbano computational tool to calculate CO2 emissions as described on the previous page.

Public Transport

BUS JOURNEYS FROM COLLYHURST TO NEAREST AMENITIES

1500

2000

2500

3000

3500

DISTANCE AND CO2 EMISSIONS Distance (meters)

C02 Emissions (C02)

Distance (meters)

Carbon Emissions (CO2)

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Carbon Emissions from Collyhurst (Bus)

CO2

Bus lines with stations closest to Collyhurst in Manchester

Government Commercial

Train (Manchester Victoria)

2242

Tram Station (Queens Road)

843

Ancoats

1832

349

2770.42

Cheetham Fort

526

1701

326

Corn Exchange

3310

HMP Strangeways

558

2973

MCC

549

3033

Job Centre Centre

17A

Manchester - Rochadle via Middleton, Stakehill Industiral Estate

466

1468

278

St.Micheals Flags

2126

Village Park

881

Collyhurst Park

472

Sand Hills

408

161 78

662

126 1279

247

Mri - Langley Circular Via Manchester, Middleton

Manchester - Higher Blackley Circular

Financial

3267

Co-op Bank ICICI Bank UK

318 2123 270

2606

New Cross Dental Surgery

349

KissDental

2132

Dr A Bokhari

2912

558

2865

Whitley Road

743

552

140 1298

578

251

96 1666

307

Cohens Chemist Ancoats

2482

Manchester Pharmacy

471

2564

Saviour Primary School

Education

407

Cheetham Hill Medical Centre The Surgery

Eggington Street,

501

1840

Cohens Chemist

Manchester - Rochadle via Middleton

412

1402

Haven Chemist

449

1674

Intergrated Dental Holdings

531

2315

ATM ATM

Manchester Oldham

625

2784

Spar ATM

Health

Manchester - Rochadle via Middleton

583

2342

HSBC

641

2914

CCA

Egghenge

Collyhurst Street,

432

161

Etihad

Recreation

Shown on this page are the results from taking a bus journey in Collyhurst to different amenities instead of taking a car. Taking a local bus emits a little over half the greenhouse gases of a single occupancy car journey and can also help to remove congestion from the roads. Bus emissions will go down further as more cities introduce plans for electric and hydrogen buses.

Public Transport

JOURNEYS FROM COLLYHURST TO LOCAL AMENITIES

587

Collyhurst Nursery School

430

Manchester Communication College

106 80

471

Al Sadiq Academy

1244

St Malachys School

507

587

259

129

Abbot Community Primary School

1403 0

500

280 1000

1500

2000 Distance (meters)

Distance and CO2 Emissions 436

2500 C02 Emissions (C02)

3000

Distance (meters)

3500

4000

4500

Carbon Emissions (CO2)

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Approaches The two examples identify ways of reducing carbon and going towards net zero emissions on a small scale within a small community which has the potential to be adapted in a wider scope.

Urban Fabric Re-adaptation Site Boundary

Reconfigured Street Network

Pedestrianised Network

Urban Fabric Reconfiguration The Urban Fabric of the Northern Gateway can be amended in order to reduce carbon emissions and aim towards a net zero carbon emissions. By pedestrianising the A664, private car dependency can be reduced by 18%. Furthermore by re-adapting the A664 into a greener alternative it may allow many to cycle and use public transport which will further decrease carbon emissions.

Amenities and Accessibility The analysis of the Northern Gateway identified the need for the need of amenity diversity. The site contains a small variety of amenities however it still relies on the city centre to fulfil the basic needs of the public. With the introduction of a diverse mix of amenities the public will be able to fulfil their daily tasks without relying on private vehicles and public transport as the amenities will be within 10/15min walk or cycle. This is also a response to COVID-19 and to encourage the public to live a healthy lifestyle.

Cars Allowed Cycle Lane / Public Transport

Amenities Redistribution Existing

Walkable Cities

Eco-cities

The Superblock

Malmö, Sweden

Vancouver, Canada

The concept of the “superblock” was first introduced by Barcelona in 2016; the concept revolves around the idea of giving pedestrians a more spacious area for walking and cycling, keeping cars inly on the outskirts of blocks. (Köllinger, 2019)

Malmö city has been transformed from an industrial centre, into a vibrant sustainable urban area. The Western Harbour is at the heart of this development, an eco-district and regeneration zone.

Urban planning in Vancouver is focused around the close proximity of varied amenities, promoting liveabiltiy, and sustainability - allowing residents to live, work and play. (Vancouver, 2021)

The city was was developed with the ambition to become climate-neutral by 2020 and to run entirely on renewable energy by 2030. The eco-district concept was envisioned as a model for future sustainable urban development throughout the city. (EBRD Green Cities Policy Tool, n.d.)

The city prioritises sustainable modes of transportation and minimizes dependance on cars. The city's urban design incorporates parks and open spaces, protects the environment and its surroundings, while also allowing for mid and high density urban development. (Fergus Peace, 2018)

Studies estimate that the wider implementation of the superblock model in Barcelona would lead to the reduction of nitrogen dioxide levels drop from current levels of 47 micrograms to 36 micrograms, this is below 40 micrograms (the current legal limit). (Transport Xtra, 2019)

438

Proposed

Compact cities

Key: Finance

Entertainment

Public Transport

Health

Hospitality

Government Facilities

Recreational

Education

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Conclusion The use of energy within a city, and the associated production of GHG emissions, is dependent on both the form of urban development (i.e. its location and density) and its design. A significant portion of the world’s greenhouse gases is produced by anthropogenic causes in cities. In order to reduce city emissions, there are a number of policies available. Our analysis has shown that the promotion of a compact urban development can help make cities more accessible while significantly reducing carbon emission.

Density

Accessibility & the Socio-Economic Dimension

In general, higher urban density correlates with lower emissions since dense urban settlements usually offer opportunities for lower-emission transport modes. Private passenger transport is one of the most energy-intensive modes of transportation, and city density affects GHG emissions significantly.

The compact city can enhance livelihoods for the urban poor through better access to economic opportunities and affordable mobility within the urban environment. The development pattern may lower degrees of social segregation through closer proximity of affordable housing options to places of work. Ensuring that a variety of housing types are within the reach of basic services and infrastructure further helps to ensure the urban poor are not marginalised.

According to one study, doubling the average density of a neighbourhood led to a 20-40 per cent decrease in vehicle use per household and correspondingly lower greenhouse gas emissions (Gottdiener and Budd 2005, cited in Global Report on Human Settlements 2011).

This type of development can also show a powerful and positive correlation with economic development. Agglomeration and proximity of economic activities, which result from compact and connected cities, contribute to these advantages.

Increased density has been linked to a decline in private vehicle use, as investments in urban transportation infrastructure become more feasible with higher densities. The use of sustainable modes of public transportation, such as bus rapid transit systems, light rail and non-motorised transport, contributes to reducing the use of private vehicles.

Walkability Compact development Furthermore, compact development also reduces emissions because of land use changes. Cities consume the surrounding green fields as they grow horizontally; previously vegetated areas (one form of 'carbon sink') are cleared to build new structures. Therefore, compact development might reduce GHG emissions associated with land-use change compared to urban sprawl.

Compact cities are intended to provide all the essentials for living in a community, including employment. When a city is compact, it is possible for people to walk or bike just a short distance to work instead of driving. This reduces fossil fuel consumption as well as emissions and pollutants, as well as traffic density. Therefore, pedestrianization increases the city's accessibility by improving accessibility, mobility, safety, and the environment that make it a good place for everyone in the city.

Environmental Benefits Compact cities also benefit the environment in other ways. As a result of development of land, there may be a reduction in soil permeability, fragmentation of ecosystems and changes in microclimate. Additionally, compact development may reduce those unfavorable impacts if it is done carefully (for example, in a way that takes into account geographical and environmental features such as fragile ecosystems).

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Transportation plays a crucial role in enabling trade, commerce, and communication through the movement from one place to another. As the infrastructure and connectivity between cities increases over the years, so does carbon emissions. How can novel solutions, micro mobility and the use of public transport ensure efficiency and a greener future? INTRODUCTION The car city

SECTION ONE

SECTION TWO

Understanding current emissions

The system

SECTION THREE

SECTION FOUR

SUMMARY

Calculating current emission

A electric way

The road to a clean future SECTION AUTHOR

Michelle Majalang Lon Y Law Sook Wai Lee

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Transportation RIDING TO A ZERO CARBON FUTURE

Michelle Majalang, Lon Y Law, Sook Wai Lee Zero Carbon Cities447

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(Newland, 2012)

Introduction Transportation forms the back bone of modern society connecting people, goods and cities, yet it is also the largest carbon emitter, generating 27% of UK’s total emission. The popularity of the ICE (internal combustion engine) car in 1807 (Michelet, 1965) since its invention led to more dedicated infrastructure, allowing higher speed lanes, making it dangerous and less accessible by other means of travel, encouraging more people buying cars, creating a positive feedback loop while emitting more carbon into the atmosphere. This made the typical caroriented city we know today, where 55.4% of emissions are generated from passenger cars in the UK.

448

The car city

Recent experiments of car-less zones and super-blocks aims to reduce the use of cars and encourage active or shared transport, while low-carbon policies aim to reduce the emissions from cars. Though sound counter intuitive, they help create a more connected city.

old technology. In comparison, a typical BEV (battery electric vehicle) has an electricity to wheel efficiency of 85% (Boloor, 2019). With government subsidies the BEV had become an more lucrative option to ICE cars, helping to further reduce emissions.

While the car is here to stay, the ICE have to leave. Throughout the years every aspect of a car was improved, but the engine has plateaued in gas to wheel efficiency. A F1 race car has an technological pinnacle ICE efficiency of 50% (Kanal, 2019), a typical road legal diesel engine is 40% (Folkson, n.d.) and a typical road legal petrol engine is 20% (Ingram, 2014). Even with incremental advancement, it is using a 200-year-

All these experiments, policies and technologies combined to pave a road to a greener future, but first it is important to understand the current landscape.

Right: Positive feedback loop of how more cars lead to less connectivity.

More cars

More dedicated infrastructure

More dangerous and less accessible to travel by other means

Detailed system map in section two

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Carbon emission by sector in the UK for 2019

Understanding current emissions To be able to identify issues in the system, it is important to understand the full picture of emissions - how much carbon is the whole sector emitting, the running and embodied carbon of cars, fuel options, types of cars that emit the most and the contributing factors to transportation emissions.

ENERGY SUPPLY

TRANSPORTATION

Looking from a national angle, the transportation sector accounts for 27% of the UK’s GHG (greenhouse gas) emission. However, as the UK de-carbonise itself the transportation sector had remained in a similar emission rate (GOVUK, 2019), taking a bigger percentage of the total GHG emissions in the UK. Although efforts have been made to lower the emissions from transport, the rate had been slow.

27% 26.86

26.57

26.59

25.93

24.19

22.99

21.13

20.87

21.67

20.39

21.20

20.14

20.41

19.82

19.59

BUSINESS 17%

RESIDENTIAL 15%

AGRICULTURE 10% WASTE MANAGEMENT 4%

201 5 201 6 201 7 201 8 201 9

201 3 201 4

07 20 08 20 09 201 0 201 1 201 2

% of UK’s carbon emission

Carbon emission percentage of the whole UK’s emissions by the transportation sector

21%

PUBLIC 2%

*LULUCF 2% INDUSTRIAL PROCESS 2%

Year (Tiseo, 2021)

450

Understanding current emissions

(Tiseo, 2021)

451

2021 CPU[AI]

Types of vehicles

Distribution of transportation GHG emissions in the UK in 2019, by source

Cars on the road divided into categories Other mobile (1.9%) Other road (0.6%) Mopeds & motorcycles (0.4%) Aviation (1.1%)

The UK Driver and Vehicle Standards Agency (DVSA) published a series of manuals listing all the technical requirements for Individual Vehicle Approval (IVA). There are different manuals for different types of vehicle and they correspond to their category specific allowed emissions. This categorisation is in line with the EU’s definitions.

TYPES OF VEHICLES

In 2019 (during pre-Covid situation), the total emission by the transportation sector was 120.8MT, where M1 passenger cars emitted 66.9MT, M2 & M3 buses emitted 3MT, N1 light goods vehicles emitted 19MT and M2 & M3 heavy goods vehicles emitted 19.3MT CO2 (Tiseo, 2021), together they compromise nearly 90% of all transportation emissions (diagram on the right).

M Used for the carriage of passengers

Buses & coaches: having a maximum mass not exceeding 5 tonnes (11,000 lb)

Buses & coaches: having a maximum mass exceeding 5 tonnes

Light goods vehicles : having a maximum mass not exceeding 3.5 tonnes (7,700 lb)

Heavy goods vehicles : having a maximum mass exceeding 3.5 tonnes but not exceeding 12 tonnes (26,000 lb)

Heavy goods vehicles : having a maximum mass exceeding 12 tonnes

Light & Heavy Trailer: maximum mass not exceeding 0.75 tonnes (1,700 lb)

Light & Heavy Trailer: exceeding 0.75 tonnes but not exceeding 3.5 tonnes (7,700 lb)

Light & Heavy Trailers

Light & Heavy Trailer: exceeding 3.5 tonnes but not exceeding 10 tonnes (22,000 lb)

Light & Heavy Trailer: exceeding 10 tonnes

(GovUK, 2021)

452

Railways (1.4%) Buses (2.5%) Shipping (5%) Light goods vehicles (15.7%)

Passenger cars : Less than eight seats in addition to the driver seat

Goods Vehicles

Passenger cars (55.4%)

Understanding current emissions

Heavy goods vehicles (16%)

These 4 categories of vehicles account for 89.6% of total GHG emissions in the transportation sector in the UK in 2019.

(Tiseo, 2021)

453

2021 CPU[AI]

CO2 Emission produced by the transportation sector worldwide, 2018 Rail 1%

Other 2.2%

Types of greenhouse gas

Shipping 10.6% Aviation 11.6%

Who are the culprits?

Road (Passenger) 45.1% According to a report by the Royal College of Physicians, in the UK around 40,000 premature deaths each year are attributable to outdoor air pollution. Effects of air pollution have been linked to a number of conditions, with road traffic emissions having a significant impact on air quality.

Road (Freight) 29.4%

Although there are thousands of particles that are released from the tail pipe of vehicles and numerous more that affect the atmosphere, they can be generalised into groups, namely nitrogen oxides and particulates (PMs). Transportation, specially passenger cars (M1) are a huge contributor to CO2 and greenhouse gas (ghg) emissions both in the UK and worldwide. Despite heavier regulations and deeper awareness of the climate emergency, transport emissions have remained a significant contributor of CO2 emissions in the UK with no downward trajectory from 1990 to 2020.

700

NOX

As a result of the high temperatures occurring during combustion, nitrogen combines with oxygen from the air forming oxides of nitrogen (NO, NO2, N2O etc.). These gases are known to have a significant detrimental effect on air quality and thus public health - impacting upon respiratory conditions. Particularly prevalent in large urban areas, around 40% of European NOx emissions come from road transport.

Carbon Dioxide

Transport Total

500

TYPES OF POLLUTANTS

PMS

Particulates

400 300

200

Carbon Monoxide

100

Particulates are fine particles produced by incomplete combustion, the burning of lubrication oil and by the presence of impurities within the fuel. They are known to cause and aggravate human respiratory diseases and are thought to be carcinogenic. The World Health Organisation has issued a report stating that there are no concentrations of airborne micro-sized particulate matter that are not hazardous to human health. Produced during the incomplete combustion of carbon compounds such as fossil fuels, this gas is known to be deleterious to human health. During respiration it readily combines with haemoglobin in the blood thus hindering the body’s ability to take up oxygen. It is thought therefore to aggravate respiratory and heart disease.

19 90 19 9 19 1 92 19 9 19 3 94 19 9 19 5 96 19 9 19 7 98 19 9 20 9 0 20 0 0 20 1 02 20 0 20 3 0 20 4 0 20 5 06 20 0 20 7 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 1 20 9 20

Million Metric Tons of Carbon Dioxide Equivalent

While carbon dioxide is non-toxic, its main environmental effect is as a greenhouse gas which, by enhancing the greenhouse effect, contributes to increases of the Earth’s atmospheric, land and sea temperatures.

Nitrogen Oxides

Net transportation emission compared to total UK emissions 600

CO2

(GovUK, 2021)

454

Understanding current emissions

(Lane, 2021)

455

2021 CPU[AI]

CO2e

GHG emission regulations in the EU & its UK equivalence

CO2e - Carbon Dioxide Equivalent

Understanding UK and EU regulations after Brexit

Measuring CO2 is itself a hard task to tackle, but cars do not only emit CO2, but along with a lot of other different green house gases including but not limited to methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFC), perfluorocarbons (PFC), sulphur hexafluoride (SF6), nitrogen tri-fluoride (NF3) and other Nitrogen oxides (NOx) gases that causes indirect warming effect.

When the UK is in the EU, the regulations on carbon emissions were the same, however after Brexit, the UK needed to separate itself from all of the regulations and legislations from the EU, which include the legislations on the regulation of carbon emissions. The first legislations on carbon emission was introduced in 2009 and made mandatory in 2011, in the same year, Euro 5 came into effect, replacing Euro 4. On 31 December 2019, regulations 443/2009 and 510/2011 were repealed in the European Union and replaced with regulation 2019/631, grace period from 1/1/2020-31/12/2020, after that new cars must adhere to these standards. In the same year, UK is due to exit from the EU, which the government decided to replace existing UK standards with new EU 2019/631 legislations (GovUK, 2021)

To be able to calculate all of them, the IPCC created a unified method that converts other GHG into the equivalent of carbon, in the effect of it affecting the temperature over either 20 years or 100 years, depending on the lifetime of the gas in the atmosphere called the AR (assessment report), with the latest being AR5, published in 2014. The resulting table is called the GWP (global warming potential) and GTP (global temperature change potential).

GWP

Lifetime (yr)

GTP

Year

Cumulative forcing over 20 years

Cumulative forcing over 100 years

Temp. change after 20 years

Temp. change after 100 years

CO2

CH4

12.4

N2O

121

264

265

277

234

CF4

50,000

4880

6630

5270

8040

HFC-152a

1.5

506

138

174

(IPCC, 2014)

456

Different vehicles releases different types of GHG, so to calculate the total GHG emissions they are converted to their CO2 equivalence based on their lifespans.

Understanding current emissions

2011

EU Emission regulations

UK Emission regulations

Introduction of first EU wide mandatory regulation to limit average CO2 levels to be <175g/km, goal towards 2017 (include both M&N cat.) EU 510/2011

2011

EURO5 comes into effect

2015

EURO6 comes into effect

2019

Updated regulation to further limit CO2 emissions, setting standards of 90g/km and 147g/km limits for new registered cat. M&N vehicles

2019

UK decided to replace UK standards with new EU regulation (EU2019/631)

2020

UK left the EU

(ICCT, 2014. EC,n.d.)

457

2021 CPU[AI]

GHG emissions standards

Average CO2 emissions for cars registered for the first time by emissions data source, quarterly, UK, 2016 Q4to 2020 Q4 Transition period

160

A updated measurement method that better reflect real-life emissions on the road

Introduction of WLTP

*GHG: green house gas The New European Driving Cycle (NEDC) was a test designed assess fuel economy and emissions of cars that was developed in the 1980s and had been used by the EU since then. Its methodology was last updated in 1997. Due to the advancement in car technologies and the outdated methodology, it was replaced by a newer test - the Worldwide Harmonised Light Vehicle Test Procedure (WLTP) from September 2017, which came into effect in 2018. While NEDC focused more on theoretical behaviour, WLTP focused on real-lift situation driving. The transition from using NEDC to WLTP as the official measurement procedure used to determine car CO2 emissions has complicated the interpretation of recent trends. It changed the test cycle to a dynamic one which better reflect road conditions, increasing the cycle time to 30 minutes going through 4 instead of 2 phases. However, this change had caused a number of discontinuities to the time series for reported emissions from September 2018 onwards.

Grams per kilometre (g/km) - UK

150 140 130 120 110

COVID-19 measures WLTP

“NEDC”-based annual target for regulations (simplified) e-NEDC* NEDC figure used historically

Reported

100 stricter regulations come into effect from 2020

90 80 2016 Q4

2017 Q2

2017 Q4 2018 Q2 2018 Q4

2019 Q2 2019 Q4

2020 Q2

2020 Q4

Quarter

The use of different testing systems for average reported CO2 emissions of new cars, UK Time period

Comparison of testing methodologies between NEDC & WLTP NEDC

WLTP

Test cycle

Single test cycle

Dynamic cycle

Cycle time

20 minutes

30 minutes

Cycle distance

11km

23.25km

Driving phases

2 phases 66% urban & 34% non-urban

4 dynamic phases 52% urban & 48% non-urban

Average speed

34km/h

46.5km/h

Maximum speed

120km/h

131km/h

Influence of optional equipment

Impact on CO2 & fuel performance not considered under NEDC

Additional features (differ per car) taken into account

Gear shifts

Fixed gear shift points

Different gear shift points for each vehicle

Test temperatures

20-30°C

23°C, CO2 value corrected to 14°C

Testing systme used

Reported figure at point of registration

NEDC

NEDC & WLTP

NEDC & e-NEDC

January 2019 to March 2020

WKTP

e-NEDC

April 2020 onwards

WLTP

Up to August 2018 September 2018 to December 2018

After the change of methodology from NEDC to WLTP, it can be seen that the emission measurement is significantly higher, this is due to WLTP measuring a more accurate measurement that is closer to real-life usage. The change to WLTP allow the system of carbon emission limit and penalties to be implemented better, helping to limit further the emissions of newly registered cars and existing cars. *e-NEDC: Calculated using a WLTP test via the COM2PAS tool developed by the European Commission, for tax and emissions monitoring purposes (can be referred to as NEDC correlated). This is not directly comparable with an NEDC figure as their underlying methodologies are different.

(WLTPfacts, 2017)

458

Understanding current emissions

459

2021 CPU[AI]

Fuel options

OTHER

Understanding what powers every car

This guide contains data on vehicles running on petrol and diesel, as well as alternative fuels, such as Liquefied Petroleum Gas (LPG) and Compressed Natural Gas (CNG), and hybrid and electric vehicles. Descriptions of the different fuel types and technologies are provided in the table. In the current landscape, internal combustion engine vehicles are the dominant type, with petrol being the most abundant followed by diesel, then followed by a medium sized amount of hybrid vehicles and a growing share of battery electric vehicles and a declining share Currently, hybrid vehicles and top-of-the-line battery EV are able to match the range provided by petrol and diesel. However, as range increase the battery size increase exponentially as well, but is not an issue for hydrogen, where it has a similar vehicle weight as range increase due to the hight specific energy capacity of hydrogen. The future of the battle of fuels is promising with more players entering every year with increasing capital investment in new fuel technologies.

ICE

PETROL

CONVENTIONAL INTERNAL COMBUSTION ENGINE VEHICLES DIESEL

- ‘Spark ignition’ engine fuelled by petrol usually obtained from fossil fuel sources - (E5) contains up to 5% ethanol - (E10) contains up to 10% ethanol - All new cars are compatible with E10 petrol which will help to reduce CO2 emissions associated with petrol vehicles

- Compression ignition engine, fuelled by diesel, a heavy petroleum fraction usually obtained from fossil fuel sources (crude oil) - (Biodiesel) contain up to 7% of plant derived diesel

HYBRID

COMPRESSED NATURAL GAS (CNG) LIQUIEFIED PETROLEUM GAS (LPG)

- Gas fuelled vehicles, either CNG (methane) or LPG (propane and/or butane) - A small global market for such vehicles, usually dual fuel (gas/petrol) although few, if any, right hand drive LPG are available in the UK - LPG ‘autogas’ is available from around 1200 filling station forecourts. CNG is available in about six stations.

HYRBID ELECTRICAL VEHICLES (HEV)

- Powered by a conventional petrol or diesel engine and an electric battery - Has a battery and an electric motor but cannot be connected and re charged by mains electricity - Not eligible for a government grant - Most hybrid electric vehicles exceed 75 g/km tailpipe CO2 emissions (current definition of an Ultra low emission EV) - Not eligible for other incentives such as the cleaner vehicle discount allowing free access to the London Congestion Charging Zone.

PLUG-IN HYBRID ELECTRICAL VEHICLE (PHEV)

- PHEVs combine both a plug-in battery pack and electric motor with a conventional engine - Both the electric motor and engine can drive the wheels depending on the mode and requirements - The battery is much smaller than in a battery electric vehicle, tending to drive the vehicle for a limited range - Sufficient in most models to cover the average journey length of the UK driver - After battery is depleted, the hybrid capability allow the journey to continue powered by its conventional engine. - No longer eligible for a purchase grant or subsidies

RANGE EXTENDED BATTERY ELECTRICAL VEHICLES (EREV)

- Has a plug-in battery pack and electric motor and a conventional engine - The electric motor always drives the wheels, with the engine acting as a generator to recharge the battery when it is depleted - Typically have a pure electric battery range of around 40 miles, before the vehicle switches to the range extender mode to continue the journey without range compromise

*usually eligible for a plug-in car grant/ subsidy to help with the purchase cost of a new car

PURE ELECTRIC VEHICLES

460

BATTERY ELECTRIC VEHICLES (BEV*)

- Wholly driven by an electric motor, powered by a battery - Usually recharged from mains electricity through dedicated charge point/ normal domestic supply at home/ business/public charging network - Rely entirely on electricity, 0 tailpipe emissions - New BEVs typically offer ranges between 150 miles and 250 miles with ranges continuing to increase as new models and variants come to market.

HYDROGEN FUEL CELL ELECTRIC VEHICLE (FCEV*)

- FCEVs use a fuel cell to produce electricity to drive its electric motor - Diominately use hydrogen - There are different types of hydrogen generation: green hydrogen: 0 emissions, only water as by-product blue hydrogen: emissions are captured, stored or re-used grey hydrogen: hydrogen produced by natural gas brown hydrogen: hydrogen produced by coal - Hydrogen have a higher energy density than batteries, allowing longer range with minimal weight increase

Understanding current emissions

(Vehicle Certification Agency, 2021)

461

2021 CPU[AI]

Fuel Economy

Emission based on fuel type

Understanding the best fuel economy

Fuel by-products when powering the car

Licensed Cars by Fuel Type (2020)

On the road today petrol dominate the fuel market with diesel following. Although a lot of attention have been paid to battery EV, it still only takes up 6% in the fuel market. Alt. fuel on the other hand, because it include LPG as well, its share stands at 3.4%.

58.4%

38.2%

*Alternative Fuel Types include Hydrogen, Biofuels, Liquified Petroluem Gas (LPG)

3.4%

2.0%

Petrol

Diesel

Hybrid Electric

0.6%

0.1%

Plug-in Hybrid Electric

Battery Electric

Gas

Conversion factor

Petrol

(X (in L/100km) * 2392gCO2/L)/100 = Y gCO2/km

Diesel

(X (in L/100km) * 2640gCO2/L)/100 = Y gCO2/km

CNG (Low Calorific)

(X (in L/100km) * 2252gCO2/L)/100 = Y gCO2/km

CNG (High Calorific)

(X (in L/100km) * 2666gCO2/L)/100 = Y gCO2/km

Sample calculation

0.6%

Alt. Fuel*

Fuel Type

the average M1 petrol car:

0 Emission

(Efficiency (L/100km) * 2392gCO2/L ) /100= Emission gCO2/km = (7.85 * 2392) /100

Car Fuel Type

= 187.72g CO2 emitted per km

Average Fuel Economy by Fuel Type Petrol Diesel Plug-in Hybrid Diesel Hybrid Petrol Gas/Natural Gas (CNG) Plug-in Hybrid Petrol Battery Electric

Aligning with the fuel options mentioned previously, petrol has the lowest fuel economy as it has the worst energy to wheel conversion. The fuel economy of battery electric is more than doubled of plug-in hybrid petrol and hydrogen is more than 4 times of it, due to its high energy density. This proves that the move to electric not only benefit the planet but also the wallet.

36mpg 43mpg 54.85mpg 56mpg 57.7mpg 61.1mpg 132mpg

Other factors that might affect fuel economy & efficiency • Driving Style - Driving at 75mph instead of 60mph increases fuel usage by up to 18% (Vehicle Certification Agency, 2021) • Condition of Tyres • Traffic Congestions (more starts and stops) • Age of car

Hydrogen 269mpg

(Ecoscore, 2021)

462

Understanding current emissions

(Vehicle Certification Agency, 2021)

463

2021 CPU[AI]

Types of road

Manchester road networks

A straight road from unclassified to Motorways

In and out of Manchester's biggest development - Victoria North

MAJOR

There are 5 types of categories for roads in the UK, from the smallest unclassified road that connects residential streets to bigger C roads that connect these residential streets to B road, which link up regional towns, A roads that connect cities to motorways that connect the country. Motorways - Links major towns to cities and connects cities - Comprises of ≥3 lanes - No footpaths or cycle lanes - Presence of road shoulders (Except Smart Motorways) - Smart Motorways uses tracking and cameras to adjust speed limits and open road shoulders in times of congestions and accidents

Primary road network (PRN)

Strategic road network (SRN)

- Designate roads between places of traffic importance, determined by population, attractions etc

- Nationally significant roads for distribution of goods & services

- These places are not end point of roads but are a part of a larger network, feeding into other routes - Always consist of A roads - Example: Manchester airport, city center

Key Route Network

- All roads on SRN form part of the PRN - Utilises major A roads and Motorways - Most heavily used part of national road network, carrying 1/3 of all traffic & 2/3 of all freight

Major Route Network

Motorway

A Roads - Links regional towns to cities - Comprises both single and dual carriageway - Presence of cycle lanes and footpaths on the side - Found in rural and urban areas - Mixture of junctions, exits and roundabouts - Speed Limit of 20-70mph

A663

A56

A665 A664

B Roads - Links small towns to regional towns - Single carriageway or single lane with passing places littered - B Roads feed into A Roads and smaller networks

MINOR

- PRN feeds into SRN for cross country journey

C Roads - Links a housing estate or village with the rest of network - Single carriageway or single lane with passing places littered - Connects U Roads to B Roads - Together with U Roads, consist of 82% of all roads in England

Victoria North

M60 A62

Salford City Centre

Manchester City Centre

A662

U Roads - Unclassified Roads - Typically residential streets and rural lanes - 60% of roads are U Roads

A576

(GovUK, 2012)

464

Understanding current emissions

465

2021 CPU[AI]

Speed limits

Fuel Consumption with relation to Speed 14

Increase in speed can lead to faster car, intuitively thinking it uses less fuel. That is true only to a certain point, before air resistance becomes too big and slows the car down. Driving at different speeds also lead to different type of particles being emitted for different fuel, for example an increase in speeds when driving with diesel emits higher CO and lower NOx but lower CO and higher NOx for petrol. (EEA, 2020. NAEI, 2021)

Fuel Consumption (L/100km)

Optimum speed to drive for least carbon emission

Optimal Range

12 10 8 6 4 2 0

Avg Speed (km/h)

Max Speed (km/h)

Fuel Consumption (L/100km) Diesel Petrol

“Real” World 120

120

8.0

Optimal 110

110

7.0 (-12%)

7.9 (-18%)

“Real” World 110

110

7.8 (-2%)

9.3 (-3%)

100

110

120

Average Speed (km/h)

Simulation on fuel consumption from a -10km/h in speed Driving Pattern

(Sims, 2020)

When plotting average speed with fuel consumption, it can be seen that the optimum range for the best fuel consumption is 55-80km/h, where air resistance on the car increases exponentially as the car increases over 80km/h. However, most motorways in the UK has a speed of 68mph, equivalent to 109km/h (Statista, 2015). This is also supported by the graph below, which showed that the least emissions come from speed of 40 km/h to 72 km/h. 2000 1800

To understand the effects of fuel consumption driving at different speed, a study was done in 2020 (above) where a simulation shows how a reduction of 10km/h affects fuel consumption. The “real” world driving pattern accounts for people breaking speed limits and acceleration/deceleration where the optimal pattern has smooth traffic with no breaking and no speed limits. As shown, while optimal results can decrease fuel consumption up to 18% for petrol, there is only a -3% reduction for the ‘realistic’ situations and even less reduction for diesel (2%). This showed that slowing down does not save fuel and generally speed and speed limits do not play a huge factor in fuel economy compared to traffic conditions and human driving behaviour.

CO2 (g)

1600 1400

Real World Activity

1200

Optimal Conditions

1000 800 600 400 200 0

104

112

120 128 136 144

Averge speed (km/h)

(EEA, 2020)

466

Understanding current emissions

(Barth and Boriboonsomsin, 2010)

467

2021 CPU[AI]

Tax rates for Petrol, Diesel & Alternative Fuel Cars First licence rates for cars registered on or after 01/04/21 based on CO2 emissions and fuel type

Tax bands

Petrol/Diesel car (tax class 48,49)

Diesel car (tax class 49)

Alternative fuel car (tax class 59)

CO2

12 months

£0

1 to 50

£10

£25

£0

51 to 75

£25

£115

£15

76 to 90

£115

£140

£105

91 to 100

£140

£160

£130

101 to 110

£160

£180

£150

On or after 1 April 2017

111 to 130

£180

£220

£170

Between 1 March 2001 and 31 March 2017

131 to 150

£220

£555

£210

151 to 170

£555

£895

£545

171 to 190

£895

£1,345

£885

191 to 225

£1,345

£1,910

£1,335

226 to 255

£1,910

£2,245

£1,900

Over 255

£2,245

£2,235

Paying according to emissions

If you own a car, van, or motorhome, you must pay Vehicle Excise Duty (VED) or car tax every year. The cost of Vehicle Excise Duty is directly tied to your car, van, or motorhome, and it varies according on the vehicle's age, list price, and CO2 emissions. Car tax bands, road tax bands, and VED bands are the various rates. Depending on when these vehicles were first registered, different tariffs are applied.

Tax Rates

Before 1 March 2001

For cars over 40 years old, there's no tax to pay. As of 1 April 2020, all cars built before 31 March 1980 are tax exempt, but still need to be registered with the DVLA

On or after 1 April 2017 There are 2 different payments. The first payment or “showroom tax” is based on the official CO2 figures when the car was built. It’s followed by an annual renewal based on the fuel type. As well as this, there’s a premium for vehicles with a list price of over £40,000 (excluding zero emission vehicles).

Tax rates for Heavy Goods Vehicles The HGV road user levy applies to heavy goods vehicles (HGV) of 12 tonnes or more. The levy aims to make sure these vehicles contribute to reducing the wear and tear of the road network. The levy varies depending on: weight, axle configuration, levy duration.

Tax rates for Motorcycles

Tax rates for Light Goods Vehicles Private LGVs Tax Class 11

12 months

6 months

Private LGVs Tax Class 11

12 months

6 months

Not over 1549cc

£140

£75

Not over 150cc

£21

Over 1549cc

£225

£123.75

141 - 400cc

£45

401 - 600cc

£69

£37.95

Over 600cc

£96

£52.80

468

Understanding current emissions

"Heavy Good Vehicles play a key role in supporting the UK’s economic recovery and growth. Which is why from 1 August 2020 to 31 July 2022 the HGV levy is suspended" 469

2021 CPU[AI]

Tax rates for Petrol, Diesel & Alternative Fuel Cars Cars registered on or after 01/03/01 and before 01/04/17 based on CO2 emissions and fuel type

Tax bands Paying according to emissions

Band

Between 1 March 2001 and 31 March 2017 For vehicles that are registered between dates 1 March 2001 and 31 March 2017, the tax rates depend on the based on the car's official CO2 emissions and fuel type. Tax rates for Light Goods Vehicles Private LGVs Tax Class 11 Vehicles registered on/ after 1 March 2001

12 months £220

Euro 5 LGVs Tax Class 36

12 months

Vehicles registered between 1/1/2009 and 31/12/2010

£220

6 months £121

CO2 emissions (g/km)

Petrol car (tax class 48) & Diesel car (tax class 49) / Alternative fuel car (tax class 59) Non-direct debit Direct debit Single 12 12 monthly Single 6 month 12 months 6 months month payment installements payments

Up to 100

£0 / £0

- / -

£0 / £0

101 to 110

£20 / £10

- / -

£20 / £10

111 to 120

£30 / £20

- / -

121 to 130

£130 / £120

131 to 140

£21/£10.50

£30 / £20

£31.50/£21

£71.50/£66

£130 / £120

£136.50/£126

£68.25/£63

£155 / £145

£85.25 / £79.75

£155 / £145

£162.75/£152.25

£81.38 /£76.13

141 to 150

£170 / £160

£93.50 / £88

£170 / £160

£178.50/ £168

£89.25/ £84

151 to 165

£210 /£200

£115.50 / £110

£210 / £200

£220.50/£210

£110.25/£105

166 to 175

£250/£240

£137.50/£132

£250 / £240

£262.50/£252

£131.25/£126

176 to 185

£275 /£265

£151.25/£145.75

£275 / £265

£288.75/£278.25

£144.38 /£139.13

186 to 200

£315 /£305

£173.25 / £167.75

£315 / £305

£330.75/£320.25

£165.38/£160.13

201 to 225

£340/£330

£187/£181.50

£340 / £330

£357/£346.50

£178.50/£173.25

226 to 255

£585/ £575

£321.75/£316.25

£585 / £575

£614.25 /£603.75 £ 307.13/£ 301.88

Over 255

£600/£590

£330/£324.50

£600 / £590

£321.75 / £619.50

£ 315 /£ 309.75

Tax rates for Heavy Goods Vehicles Tax rates for Motorcycles Key Table to Heavy Goods Vehicle (HGV) tax bands for rigid and articulated vehicles

470

Private LGVs Tax Class 11

12 months

6 months

Not over 150cc

£17

141 - 400cc

£37

401 - 600cc

£57

£31.35

Over 600cc

£78

£42.90

Understanding current emissions

Standard (Tax Class 01)

Reduced pollution (Tax Class 45)

HGV Tax Band

12 months

6 months

12 months

6 months

£165

£90.75

£160

£88

£200

£110

£160

£88

£450

£247.50

£210

£115.50

£650

£357.50

£280

£154

£1,200

£660

£700

£385

£1,500

£825

£1,000

£550

£1,850

£1017.50

£1,350

£742.50

471

2021 CPU[AI]

Tax bands

Fun Facts

Paying according to emissions

What is the £40,000 car tax rule? You have to pay an extra £335 a year for 5 years after the first year if you have a car or motorhome with a ‘list price’ (the published price before any discounts) of more than £40,000 (excluding zero emission vehicles).

Before 1 March 2001 For vehicles thar are registered before 1 March 2001, the tax rates depend on the based on the car's engine size. Tax rates for Light Goods Vehicles

Engine Size

Single 12 month payment

*Single 12 month payment

Single 6 month payment

*Single 6 month payment

Not over 1549

£170

£93.50

£82.95

Over 1549

£280

£154

£147

*Payment made through direct debit

Tax rates for Motorcycles Private LGVs Tax Class 11

12 months

6 months

Not over 150cc

£21

141 - 400cc

£45

401 - 600cc

£69

£37.95

Over 600cc

£96

£52.80

Fuel Type

Standard Annual Rate

Additional Rate

Total Annual Rate

Petrol/ Diesel

£155

£335

£490

Alternative

£145

£335

£480

Electric/ Hydrogen (Zero Emission)

£0

Do you pay car tax on electric cars? Electric cars (as well as hydrogen fuel-cell automobiles like the Hyundai Nexo) are zero-emission vehicles that are currently exempt from any sort of vehicle tax. Electric vehicles that were registered before April 2017 are likewise free from paying vehicle taxes. The £40,000 expensive-car criterion was first applied to electric cars, as mentioned above. For example, if you bought a new Tesla Model X (an electric automobile starting at £75,000), you had to pay this premium from the second to the sixth year of ownership. However, the 2020 Budget indicated that owners of zero-emission cars purchased before March 31, 2025 will no longer be required to pay the additional rate.

What is an RDE2 diesel? When a new car is certified for sale in the UK and Europe, it must undergo strict emissions testing. Current standards state that, under standard laboratory testing, a new diesel or petrol car must emit no more than 0.080g/km of nitrogen oxide (NOx). RDE stands for Real Driving Emissions. This is the test that can be used by vehicle manufacturers to test the emissions a car produces under real driving conditions (e.g. not in a laboratory).

472

Understanding current emissions

473

2021 CPU[AI]

Corporate Incentives Super Credit

Grants & Incentives

Super credits are intended to incentivize automakers to produce ultra-lowcarbon automobiles. They achieve this by artificially doubling the sales of ultra-low carbon cars (ULCVs) so that each ULCV counts as multiple vehicles under the Regulation. The multiplier used determines the quantity of fictional sales.

less emissions = pay less money, fancy a discount?

Tax Incentives

Plug-in Van Grant

Company Car Tax (CCT) rates are lower for zero and ULEVs, making it more attractive for staff to choose cleaner cars

Zero emission vans are exempted from Vehicle Tax rates since April 2021. Grant of up to 35% pf the purchase price for eligible vans Category B drivers who have gone for training are allowed to drive alternatively fuelled vehicles up to 4.25 tonnes.

Beneficial rates can save users up to £2,000 & exempted from Vehicle Tax Rates 100% cost of cars can be written off as taxable income until March 2025

The flow of super credits is depicted in the diagram on the right. Without a multiplier, selling one battery electric vehicle (BEV) with potential CO2 emissions of 0 g/km allows a car maker to sell one gas guzzler (190 g/km) and still meet a 95 g/km target on average. Figure 1 depicts the effect of a two-fold multiplier: one BEV sale counts as two sales, allowing car makers to sell two gas-guzzlers while still achieving a 95 g/km average.

95g

No multipliers

95g

+ 0 g/km

Multiplier 2

190g/km

Thus, from 2025 onwards, the super credits system is replaced by a benchmark set at 2%. The 2030 benchmark level will have to be set in the context of the 2022 review.

+ 0 g/km

The Super Credits scheme has proved to be inaccurate in the threshold for each vehicle.

190g/km

Super credits allows manufacturers to sell more gas-guzzlers with high emissions while also weakening their aim, allowing them to avoid using such efficient equipment. The money saved might theoretically be used to subsidise ultra-low carbon vehicles. The table below shows the commitments made by various companies to Electric Vehicle fleets

Consumer incentives

Plug-in Car Grant The plug-in car grant provides up to £2,500towards the purchase of a zero emission car priced under £35,000. This grant is now made longer and available to more drivers until 2022/23

474

Understanding current emissions

Affordable '0' emission vans Legislations have been changed to make it easier to drive alternatively fuelled vans. Through plug-in van grants and tax incentives, the zero emission van market is supported and shown in the 71% increase in registrations between 2019 & 2020.

Company

Size of fleet

Astrazeneca

17,000

Fully electric fleet by 2025

Royal Mail

41,500

Only new EVs bought by 2030

Mitie

5,300

Fully electric fleet by 2025

Openreach

27,000

Fully electric fleet by 2030

Ocado

1,700

Net zero emissions by 2035

Centrica

15,000

Fully electric fleet by 2025

DHL

7,500

Zero logistics related emissions by 2050

Lloyds Bankinf

350,000

Net '0' emissions customer & corporate fleet by 2030

Rentokil

19,000

Fully electric fleet by 2030

Tesco

5,500

Fully electric van fleet by 2030

Zenith

48,000

Fully electric by 2030

Fleet Alliance

37,000

Fully electric by 2030

EV Commitements made to date

475

2021 CPU[AI]

Deadhailing Empty uber, no customer

For some, a sensible-seeming solution would be to turn to taxis and ride hailing through apps such as Uber and Lyft. But these may be higher carbon emitters than you realise. One recent report by the Union of Concerned Scientists in the US found ride-hailing services emits 69% more climate pollution on average than the journeys they displace, and 47% more than an equivalent private car ride due to the extra passenger-free driving they do while waiting for a fare – known as “deadheading”. But pooling rides, choosing rides in electric vehicles, or using ride hailing to connect with public transport all produce less emissions than a private car, the report found. And ride hailing will also reduce the need for on-street parking – freeing up more space in dense cities.

Emissions relative to a private vehicle

900

180%

800

160%

700

140%

600

120%

Private vehicle: 464g CO2e/ trip-mile

100%

500 400

80% 60%

300

40%

200

20%

100

0 Private vehicle

Non-pooled ride Pooled ride hailing hailing Passenger vehicle

(BBC,2019)

476

Emissions per trip-mile (g CO2e)

200%

Understanding current emissions

Bus

Deadheading

Rail

Walking & Biking

Pooled ride hailing & Rail

Mass transit

(Harding, 2020)

477

2021 CPU[AI]

The system Understanding the different factors in transporation

While each part of the system have been presented in the previous section, it is also crucially important to understand all the factors in play in a larger system that can visualise all the connections between all the actors and factors, in how vehicles, carbon emissions, energy, infrastructure, legislations, costs modes of transport and the end user link together.

Type

ENERGY Slow

Fast

Rapid

Hydrogen Electricity

EREV FCEV

CNG LPG

BEV

Type PEV

OTHER

Diesel

PHEV

COSTS

Charging points Petrol

HEV HYBRID

ICE

VEHICLE

LEGISLATION

Charging/ Fueling up

Policies

Petrol stations Bus Routes Tram Routes Grants

Railways

Factors Weight

Tax bands

Routes

Category

Adopting LCEV

M1 M2

Size

M3 Age

Road conditions

N1 Mileage Engine

Tram

Train

Public connectivity

Road connections

Bus

MODES OF TRANSPORTATION

INFRASTRUCTURE

Public

Varying speed

Private

Bicycles

Travelling habits

Walkability Shortest

E-Scooters

Quickest Factors

CARBON EMISSION

Data Tracking Internet

USER Type of pollutants

Carbon dioxide

Nitrogren Oxide

Particulates

Carbon Monoxide Accessibility

Affordability

Choosing the ‘best’ transportation

478

The system

479

2021 CPU[AI]

System dynamics map Understanding all positive and negative feedback loop

EV charging stations

ICE passenger car usage

The layout of the city is a fundamental component in driving the use of vehicle types, the congestion, and quality of life of people living inside and outside of the city

road construction settlement dispersion

micro transportation usage

tax brackets for passenger EV adoption

EV passenger cars usage

carbon emission caps

carbon emissions

ICE passenger car usage

fuel efficiency

road tolls & fuel taxes

quality of life

public transport budget

public transport fleet size

average EV mileage

efficiency

ICE passenger car cost low carbon policies

quality of life

research in battery/ alternative fuel

public transport usage

The main lever point to increase rider-ship is reliability & punctuality of a fleet, which will kick-start a positive feedback loop that increase the people who want to use it

reliability & punctuality

public transport budget

public transport fleet size

public transport usage

road construction

settlement dispersion

micro transportation usage

reliability & punctuality funding for alternative transportation

research in battery/ alternative fuel low carbon policies

480

The system

funding for alternative transportation

Research, policies, funding and grants from governments, institutions and private sectors are important components to kick-start the system

481

2021 CPU[AI]

Calculating current emissions Calculating current running and embodied emissions from the transportation sector The emissions that are calculated would be site-specific, meaning that it is calculating the total emissions of Victoria North, previously known as the Manchester northern quarter. The calculations primarily utilises data and censuses from the UK government, European commission, IPCC and other private research entities such as Statista, therefore it can only be used as a reference and estimation, below are a list of calculation assumptions and known uncertainties that affect the calculation results.

Uncertainty in embodied carbon calculations

Uncertainties in running carbon calculations

Data based uncertainty & assumptions

482

Assumption of vehicle count on site contribute to local emission (ignored possibility of passing-bys)

Victoria North

Other uncertainties & assumptions Assumption of all vehicles abiding to emission rules (inclusive)

Assumption of vehicle age distribution to be same as UK average (ignored the fact of nonnormalised

Assumption of all licensed vehicles to be always on the road (active vehicles)

Distribution of age of cars, throughout the site & UK, ignored hotspot skew from social reasons)

non-inclusive calculation of all types of air pollutant gases (only main 6 ones)

Assumption of percentage of certain type of vehicles to be same as UK-wide distribution

Exclusion of “unknown” in calculations (for M vehicles)

Assumption of all energies and carbon from the table is accurate

Assumption of all energy used are generated from natural gas & grid electricity

Assumption of all materials used to manufacture a vehicle are listed in the study & its methodology

Ignored remaining 5% of material transformations, energy used and carbon emitted

Assumption of material transformation methods are the same as 2010 (year of study conducted)

Possible uncertainty in mass of vehicles

Calculating current emissions

483

2021 CPU[AI]

Energy and carbon required for each process in the production factory

Embodied energy & embodied carbon

Energy Consumption (MJ/kg)

The energy and carbon required to produce a car

Processs

avg.

weight

avg.

weight

Stamping

5.1

0.59-9.69

0.31

0.03-0.44

Aluminium

55.3

33.1-88.4

3.08

1.83-4.95

Iron

32.0

24.0-36.1

1.69

0.45-2.46

Copper Wire Production

7.1

0.43

Brass from scrap

7.4

0.42

Secondary lead production

8.5

0.49

Machining

2.015

1.73-2.30

0.115

0.10-0.13

Forging

45.1

2.61

Glass Pane Forming

16.0

0.93

Welding

920

920-1093

62.0

62.0-73.6

Painting

4167

2141-8175

268

123-472

HVAC & Lighting

3335

2587-3565

225

174-240

Material Handling

690

690-805

39.5

39.5-46.1

Heating

3110

2141-8175

268

123-472

Compressed air

4167

2141-8175

268

123-472

Rubber

12.9

0.74

Thermosets

4.79

0.27

26.4

1.53

PVC

24.3

1.56

Blow Mold

HDPE

19.7

1.13

Calendaring

PVC Sheet

6.25

0.36

Extrusion

HDPE Pipe

7.03

0.42

Shape Casting Embodied energy means the energy required to produce something, accounting from cradle to recycle all the processes that is required in the production chain. However, though it accounts for a vast amount of data, it also has a lot of limitations. For example, the method that is used below did not account for the energy and carbon emitted from mining raw materials and did not account for recycle and waste. It also do not account for the worker's caloric intake and their energy burnt while working.

Polymers Pellets, Resins & Slabs PVC TPO ABS ABS

Ancillaries Sand Fluids Paints

Polyethylene Polyurethanes Nylons Natural Rubber

Metal Forming

Energy

Stamping Extruding Casting

Adhesives Others

Assembling & Fastening

Drawing Machining Forging

Welding Bolting Gluing

Polymer Forming Injection Molding Compression Molding

Extruding Calendering

Metals Sheets, Ingots & Billets Steels Aluminium Copper Magnesium

Lead Brass Zinc Iron

HVAC Light Assembly Line Compressed air

Product

Painting

Waste

Moldings

Injection Mold

Blow Molding

Part Manufacture & Vehicle Assembly

CO2 emission (kg/kg)

Float Glass

All energy values are low heat values (LHV) In many cases, CO2 was calculated from listed energy assumed to be natural gas and grid electricity only

484

Calculating current emissions

485

2021 CPU[AI]

Calculation methodology n

Calculating embodied energy for each categpry of vehicles

VM {V Mn}}j + {VnM } {V {MVA} =n ∑ {V MnA} }M +}j{∑+ V {M M A} = {∑ {V V}nM j= nA} ∑{∑ {n= V M A} {nj Vn{+ M = }j∑ V{VMM } j}+ {V M } j=1 {V M A} {=V∑M {Vj=1M }∑ { V M } M A} {VM M }+j +{{V nV n nj=1 A} = {V M } + V{V M }= n= ∑ {V j∑j=1 { V M A} M } + { V M } j=1 j=1 j=1 { V M A} = {V M } + { V M } ∑ j { V M A} = {V M } + { V M } ∑ ∑ j=1 j} } VM M {V + {V Mn A} =V{V{M {V }=j∑number +{V {j=1 V A} =nM==∑ MM }M +jj}j+j{components V{V{MVM }M A}A} {V }of = {number of components number of components jj=1 n n = j=1 j=1 j=1 n n =ofof number of components n = number components j=1 j=1 j=1 n = number of components n = number components n = number of components n j = b urden vector of components number of components n = of components vector of components M A} =j =∑jb=urden {Vburden M }vector {V={M }M n number of components jn+= ∑ V A} = {V M } + { V Mof } n = number of components number of components j n = number of components = number of components j vector =∑vector burden vector jcomponents urden of j = nbj=1 urden of bA} urden of components {+=jV=bof =j=1 {V Mburden }components + {energy V(lighting M }components nwelding) number components =(painting of components bn=urden vector of components j j =/vector burden vector of components =number j burden + vehicle assembly f actory burden (lighting /heating) mbly (painting fM actory energy +welding) ssembly (painting welding) f actory energy (lighting heating) / /heating) / /burden j = b urden vector of components j = b urden vector of components j=1 j = b urden vector of components jassembly =urden burden vector of components urden vector ofvehicle components =jassembly +energy {=jV==vehicle Mbvehicle } {VM}* assembly (painting welding) f actory energy burden (lighting + (painting welding) burden (lighting +vector (painting f actory energy burden heating) +f actory M }=assembly (painting welding) f (lighting actory energy (lighting / /heating) jwelding) bvehicle of components = burden vector of components / /heating) assembly (painting/welding) + factory energy burden (lighting/heating) =/welding) / / / /heating) n}bly number of components + le (painting f actory energy burden (lighting /heating) n/welding) = number off actory components +factory vehicle assembly (painting energy burden (lighting heating) / = + vehicle assembly (painting welding) f actory energy burden (lighting heating) n = number of components + hicle assembly (painting welding) f energy burden (lighting heating) / / / / + hicle assembly (painting welding) actory energy burden (lighting heating) + bly (painting welding) f actory energy burden (lighting heating) /= burden / q q/welding) /(painting / (lighting/heating) m q+ +f actory m components le assembly (painting icle assembly f actory energyburden burden(lighting m burden vector of /jwelding) /heating) vector ofenergy components qvm m+ q{ q} }} of m∑ m j==}{T bklurden vector components VP∑ Mmjkl}Pj{T {T ∑ ∑kl{mP {qvm }j { V M } vm = ∑ + { V M } } = + { qjkl jkl kl j j j j nting welding) energy /+{heating) mM qM }kl =(lighting ∑{T P {vm }j(lighting /heating) = /vehicle + (painting actory energy m {{T V{∑ }+j}q{=l=1 {T }∑ vm ∑V}burden ∑}+∑ +jkl }j}+j burden qk=1 }j ={V∑assembly }M vm ∑+ Pf actory }actory vm ∑ {{T l=1 k=1 m /={welding) l=1 k=1 m mM jkl jkl j}Pj{P j{T jkl kl }qV vm ∑ }fvm qV qkl qPqjkl mm m= + } {V=Mvehicle assembly (painting welding) f+ energy burden (lighting /heating) j = kl jkl / { M } {T } ∑ ∑ P + { } l=1 k=1 l=1 k=1 l=1 k=1 l=1 k=1 { V M } {T } vm = ∑ ∑ P { } j jkl kl j { V M } = ∑ ∑ P {T } + { vm } l=1 j P+P{ j {T =∑ ∑∑ {vm}klj}jj}jj {V M }j ={V{∑ {T }k=1 vm ∑ Pjj}j= jkl }M {T vm V{MVM {T}l=1 }klkl}+kljkljkl ∑ ∑ Pkl∑ +{+ {vm jk=1 jkl jkl l=1 j}= jkl kl jkl jkl k=1 m q k=1 l=1 l=1 k=1 k=1 l=1 m qparts via process (l) f or component (j) l=1 l=1 k=1 k=1 l=1 k=1 of material (k) made into material (k) made parts via process f orf component (j) (j) q (l) (l) of made into parts or component mprocess kl }j =material {T=into }M =M∑ass ∑ P(k) +{ass {vm }=jvia jkl kl V M } {T }klinto vm ∑ ∑into P(l) + {into }via P of material (k) parts process (l) (l) f orfor component (j)(j) = M P ass of material (k) made parts via process f or component (j) terial (k) made into parts via process f or component (j) = M P ass of material (k) made into parts via process (l) fprocess or component (j) j jklmade j}(l) jkl Mass of material (k) made parts via component = jkl jkl { V M } {T } vm = ∑ ∑ P + { l=1 k=1 ass of material (k) made into parts via process (l) f or component (j) jinto jkl j in l=1 k=1 {M Tof }ass urden vector to transf orm (k) tokl(j) (l) f(l) or (j) =ofbto urden vector transf orm (k) to (l) f parts or use in =Pbass M made parts via process fuse or component (j) (j) }= urden vector to(k) transf orm (k) to (l) ffprocess or use in (j) = bass klmaterial = material (k) made into via process (l) f or component kl M of material (k) made into parts via process (l) f or component (j) l=1 k=1 jkl M ass of material (k) made into parts via (l) f or component (j) aterial (k) made into parts via process (l) or component (j) M into via process (l) f(k) or component (j) ass ofmaterial material (k) into process (l) ftoor (j) Tburden }transf urden vector transf orm (k) touse (l) f(j) or =parts bparts {T{to }(k) urden vector to orm (k) (l)component in =made vector (k) to (l) fvia or use into (j) bass }transf urden vector totransf transf orm (k) to (l)f or f oruse (j)use in (j) =bmade b{orm vector to transform to (l) for use inin (j) =transf kl kl {qurden T=}qofkltotal urden to orm (k) to (l) f or use in (j) qbTurden =klvector total number ofto transf ormation process number of ormation process ={}=Ttotal number of transf ormation process }b== vector to transf orm (k) to (l) f or use in (j)in (j) =urden { T } urden vector transf orm (k) to (l) f or use = b kl { T vector to transf orm (k) to (l) f or use in (j) b kl { T } urden vector to transf orm (k) to (l) f or use in (j) b urden vector to transf orm (k) to (l) f or use in (j) b q number =orm total number transf ormation process (j) k) (l) formation or number of transformation process qparts = =process qvia total number ofcomponent transf = total number of transf ormation process q= total of transf ormation process {T urden vector to transf (k) to (l)process or use (j) {made T}jklkl}klkl urden vector to transf orm (k) to (l)formation fof or(j) usein inprocess (j) binto bass ==qklkl= M P material (k) into parts via process (l) f or component =M total of transf knumber =made raw materials =of materials knumber =material raw materials qkof = total number of transf ormation process Ptotal ass (k) made into parts via process (l) f or component (j) qraw =number total of transf ormation process jkl =number q = total of transf ormation process raw materials k = q = total number of transf ormation process = of transf ormation process k = raw materials k = raw materials k = raw materials k = raw materials q = total number of transf ormation process q = total number of transf ormation process vector lto= transf orm toraw (l) materials fsorburden in (j) orm urden to transf (k) to (l) f or use in (j) = bkl(k) ==urden pmaterial rocessed material sorm burden lp{=rocessed suse burden kl k vector = raw materials processed material’s burden lT{p=T}rocessed =bmaterials kpmaterials = raw materials }raw vector to=transf to (l) fsorburden use in (j) =kmaterial kk= = raw materials klormation = raw materials ktransf l p rocessed material l = p rocessed material s(k) burden l = pof rocessed material s burden l = rocessed material s burden = raw materials k raw number process l =number material smaterials burden ==of total number transf ormation process mpq=rocessed total number ofof inburden vehicle m =m total number materials in vehicle = total of materials in vehicle total number of materials in vehicle m = l p rocessed material s burden l = p rocessed material s q = total number of transf ormation process processed rocessed material ssburden burden lp==rocessed pm rocessed material burden l = pmrocessed material smaterial burden m =vehicle total number of in materials in vehicle = =total of materials m = ktotal number innumber m total of materials invehicle vehicle ltotal = material s sburden l l= ={vmaterials number of materials in vehicle knumber = raw materials }pof ==materials vvehicle vm ehicle assembly burden (exhaustive) assembly burden (exhaustive) }=j =}raw vm{vm ehicle assembly burden (exhaustive) ehicle burden (exhaustive) j assembly m = total number of materials in vehicle jv= m = total number of materials in vehicle k = raw materials m = total number of materials in vehicle m = total number of materials in vehicle m = total number of materials in vehicle }burden =assembly v ehicle vm assembly burden (exhaustive) }assembly {vm ehicle burden (exhaustive) }j = v ehicle assembly (exhaustive) }==j {of = vmaterials {number vm ehicle burden (exhaustive) mm= in(exhaustive) =total total of materials invehicle vehicle processed material snumber burden j assembly {vm ljburden pvrocessed material s burden j = v}ehicle =ehicle v}ehicle {}vm assembly burden (exhaustive) =burden {assembly vm assembly burden (exhaustive) lvassembly =ehicle processed material s burden j vv } = vm burden (exhaustive) j } = {ehicle vm ehicle assembly burden (exhaustive) }j {=vm mal number (exhaustive) j } = v ehicle assembly burden (exhaustive) } = v {v{vm ehicle assembly burden (exhaustive) ofj materials vehicle ntotal n number nof materials in vehicle jj j m = in n vehicle total number of materials in n ∵PP =nkl =∑ P ∵P ∑jkl =(exhaustive) ∵klPm njkl kl = ∑ P jkl n v ehicle assembly burden nj=1 v= ehicle assembly burden ∑(exhaustive) = (exhaustive) P jkl P ∑ n=∑∵ = P P ∵ P{klvm = ∑ P=jkl P ∵ P n∵ j} j=1 kl n kl jkl ∑ kl jkl P ∵}nj=1 P = v {vm ehicle assembly burden j kl ∵ P n nn=jkl∑ P ∑j=1j=1 j=1 = P ∵ P q ∑ kl jkl q Pq = j=1 mP = P ∵ P m m∵ ∑ ∑ j=1 kl jkl jkl P Pklkl=klkl=∑=∑PPjklj=1 ∵∵P∵Pkljkl kl jkl jkljkl nP q∑∑ mP m+ ∑kl} ∑ ∑ {T M A} =qklj=1 j=1 {T }{T M A} =m ∴ Vklj=1 M }klmc +j=1 Vq{V {qj=1 {MVMM}c }} + {V M } ∴{V M A} = {V Vqc}M }+{n+ m∑ j=1 klP kl+ {j=1 q m n ∑∴ qA} ∑∵c ∑ + }+{V {V MM =q= P{T P ml=1 P= {T + ∴ {V M A} =+{T V{}V MklM k=1 qq∴ P }∑ +V∑ {M M A} =∵∑M }{P V}∑c∑ M }kl+ {T }klP}klP+ +{VM {VM {V A} ={∑V}∑ l=1 c M}}+} {V M } m l=1 k=1 c }c} kl m mk=1 kl ∑ kl kl= + {{{T ∴{V A}∑ V qM m m mjkl klk=1 kl∑ kl{T ∑klqqP ∑ P{T }P +V {l=1 +V {M ∴{V M A} =∑l=1 V M }M{{M V M}}{V}M } =V Pjkl{}jkl ∵ P j=1 l=1 c}V+ l=1 k=1 l=1 k=1 ∑k=1 ∴ {V M A} = P {T } + } + ∑ ∑ kl∑ kl kl{ P } + ∴ {V M A} = M c j=1 ∑ ∑ ∑ k=1 c kl kl P {T } + { + ∴ {V M A} = M V M P {T } + { + { M A} = V M } V M kl kl c c ∑ ∑ ∑ ∑ {T + +{V{VMM + +{V{VMM } } Pkll=1 ∴∴ {V{VMM A}A}= = kl k=1klP∑ kl} } cj=1 cc} } kl c kl kl kl{T klkl l=1 k=1 m wqhere k=1 ∑l=1 P w here weight of vehicle P∑klk=1 c=urb weight vehicle l=1 P= cl=1 wk=1 here urb weight of vehicle q urb m kl =of l=1l=1 k=1 l=1 k=1 klk=1 q m ∑ ∑ P = w here urb ofMvehicle ∑ P kl ∑where ∑{T ∑ P = c w here urb weight of vehicle } + { + { V M } V M } P = c urb weight of vehicle P = c w here urb weight vehicle kl {cV kl kl∴kl{V∑M PA} cc ∑ where urb weight of}vehicle Pklklweight {T Mofcweight } + {V } klA} kl of+vehicle ∑==P= =urb c∑klurb w{V here ∑ ∑ P {T } + { ∴ M V M =1 l=1 ∑ P = c w here urb weight of vehicle c } + {V M } ∑ kl P = c w here weight of vehicle kl kl ∑ l=1 k=1 P = c w here urb weight of vehicle = c where ∑wPw urb weight of vehicle =klkl==curb curb here of vehicle ck=1 here∑∑PPkl klkl∑ urbweight weight of vehicle where weight of vehicle kl l=1 (k) by ∑ =m p∑ m Pofkl of airing of(k) (k) aterials transf ormed aterials transf ormed process (l)by =airing pairing materials transf ormed by process (l)process (l) ∑(k) ∑ = of pof∑ mweight Pofhere airing ofcby aterials (k) transf ormed process (l) ∑P ∑ =∑ mtransf Paterials airing of aterials (k) transf ormed by =∑cmurb weight vehicle of transf ormed process (l) =p=pairing p(k) m P airing aterials (k) transf ormed byprocess process kl materials transformed by(l) process (l)by(l)(l) kl kl kl = p m Pring airing of aterials (k) ormed by process P = w urb of vehicle kl P = pairing of ∑ kl (k) m aterials transf ormed by process (l) ∑ P = c w here urb weight of vehicle ∑ = p m P airing of aterials (k) transf ormed by process (l) ∑ kl = p m P airing of aterials (k) transf ormed by process (l) kl ∑ pairing m aterials (k) transf ormed byprocess process mklaterials (k) transf(k) ormed byormed process ∑∑m∑m p=airing Pring ofofof aterials transf byby(l) process (l)(l)(l) pairing PklPklkl=klkl=of aterials (k) transf ormed M {V {MVcM}c =}∑= urden ={bV∑ bburden urden c } = ∑ burden ∑ = burden {V M }ormed ∑ burden {∑aterials V{process ∑ materials bcofurden {PV (k) M=ctransf }{=V ∑ =∑transf M }=(l) cburden ormed c c}(k) bVM M }∑=by urden pairing m by process (l) ∑urden = b=urden {bM Vurden }M c}Vm ∑ Pkl klM=c p}airing ofcM aterials (k)burden transf ormed by process (l) {∑ }urden ∑ = VVM } cb ∑ ∑ = b M {V c ∑ ∑ = b = b {V{={V{M } urden } urden c cc

((( ( ( ( )()() )(( () ) ))( )) ) (( )) ( ) (( ))

)

b ∑ VM urden b∑ bT M (V Vi bM A})(iT=+)i{∑+ )+ci }+{}+ V MM {V{{M =b}∑=={P∑ VP{MVi{cbVM }c M V{}= P(biT {MV VA} McA} } + {V M } ∑b}c urden b}urden ∑=)+ ∑ (TM + }+{V V M ∑ + {V T=()T V M i=1 PA} (T∑ {M +P {iA} V M A} {=V M ){biVb{b+ VbA} M }{{∑ Vic(cM }i P+ P +{VM {VM A})=c{b= c M}}+} {V M } bV c)} i{V ic} bM bi=1 i i i=1= P ( + { T V M } M i ∑ P i∑i=1 { V M A} = ( T ) + { V M } + { V M } i=1 c i=1 i=1 P ( + { + { { V M A} = T ) V M } V M } ∑ i i P ( + { + { { V M A} = T ) V M } V M } c ∑ ∑ c} i+ PiiV(}iiTM {VM M Tpiiburden )+ VV M (roduction {vector V M{A} =V{cVM Ti=1 M {= Vp=)∑ roduction vector =A} p== V {M }cP i} roduction vector ∑ P+Pic{i=1 +}+{+ (=burden {V{M A} V V{V{MVM }}} T)(i=1 M i{+ i}A} iM cM cic}cburden ic)+ i=1 = p { V M } roduction burden vector i=1 = p { V M } roduction burden vector = p {bV M c }i=1 roduction burden vector = p { V M } roduction burden vector c b c c i=1 i=1 i=1 =M p}roduction V}+M burden vectorvector aM {}M Vssembly }=burden ssembly burden =}{{acV= V ssembly b vector aM {MV{M P{M {=pV}burden = ∑ } (vector V }M+ roduction burden vector cM c}V= = p { roduction burden vector i (T})= i {{p ∑ p V M } roduction burden vector P + { + { { V A} = T ) V M } V M } c c c = p V M roduction burden vector { V roduction burden vector = a { V M } ssembly burden vector i i c c = a { V M } ssembly burden vector = a { V M } ssembly burden vector = a { V M } ssembly burden vector V vector pssembly {iVVM M roduction burden vector production cspecif cc}}{}= =roduction Pburden (burden + {Vvector V A} =i=1∑ormation T )vector M c pairing } + {V M } ==ic aransf {ic M burden i transf ipairing = material ormation tpM =i=1 pecif ic{material pairing ta= is= specif material ransf aormation {M VM }burden ssembly burden vector =smaterial aburden V M }= ssembly burden vector = {V V }}{pecif ssembly burden vector i=1 = a { V M ssembly burden vector = a { V M } ssembly vector t i pecif ic material ransf ormation t i = s ic material ransf ormation pairing assembly burden vector t s pecif ic material ransf ormation pairing t i s pecif ic ransf ormation pairing pairing = a { V M } ssembly burden vector = a { M } ssembly vector = p } roduction burden vector = c transf i = specif ormation pairing total weight production {V M burden vector Psic weight ==material P total weight =pecif cP i}=}= = ipecif tpransf i ss=pecif ic material ormation pairing i total t i s ic material ransf ormation pairing { V M roduction burden vector t i = ic material ransf ormation pairing c t i = pecif ic material ransf ormation pairing t = s pecif ic material ransf ormation pairing P total weight = P total weight = P total weight = P total weight = i specifi c material-transformation pairing = t}ransf ia= icicmaterial ormation transf issembly =specif specif material ormation i pairing M T} =T i ssembly P or total weight =Vvector = amaterial M burden vector M A burden specif icpairing material specif ic ATburden burden or icafior material VAMi burden P total weight = i = Vfi{ i = iV=M PT total weight i specif == {fi=V M }weight ssembly burden vector P total weight =total iweight P total weight = P total weight = M A burden f or specif ic material = V T M A burden f or specif ic = V P total weight P total = = M A burden f or specif ic material = V T M A burden f or specif icmaterial material = V i i t cT material ransf ormation pairing i ii iii ic fmaterial i Ti = V M A burden or specif ic material t i = s pecif ransf ormation pairing ∴ ∴ ∴ T M A burden f or specif ic material = V T M A burden f or specif ic material = V t i = s pecif ic material ransf ormation pairing iV T M A burden f or specif ic material = i T M A burden f or specif ic material = V T i =P V M A burden f or specif ic material ∴ i ∴ VMA burden for specifi c materiaL = ∴ ∴ AAburden f or icicmaterial Ti =ii =iV17 burden∴ f or specif material weight VMM 17 i = Ttotal 17 Pspecif weight = total ∴ Pi(%) total weight = ∴ 17 ∴ 17 17 i 17 ∴ ∴ t= otal(V M A) = P ∑ M Energy MAA) P ∑ M (%) Energy + { V }E }+E {V M }E l(V M = P ∑ M (%) Energy + {MV M ∴ ∴ 17 E i x M burden f or specif ic material EA) i x x(avg) x(avg) E i x(avg) TM M A burden fV or specif ic material =A) V=x17 total(V M A) = P ∑ M (%) Energy ix∑ 17 M A) P ∑ M (%) Energy + +{V{V MM }+E}{EV M }E x=1 Mtotal(V A)E = M P iA)total(V ∑17 MPx=1 (%) Energy + { M }Energy t= otal(V = P ∑ M (%) x=1 17 E i x material T M A burden f or = V 17 E i x x(avg) E E(%)x x(avg) i Energy xspecif M + { V ic M x(avg) 17 17 17 i E i E x(avg) ∴ t otal(V M A) = P ∑ M (%) Energy +VVx(avg) {M V}+M }M x=1 x=1 x=1 x=1 t otal(V M A) = P ∑ M (%) Energy { V }E E i x E t otal(V M A) = P ∑ M (%) Energy + { } x(avg) ∴ x=1 E i x t otal(V M A) = P ∑ M (%) Energy + { M } Mtotal(V A) = P ∑ M (%) Energy + { V M } a nd x(avg) a nd E i x E a nd x(avg) A) (%) Energy + +{EV{VMM }E}EE E total(V (%) ix ∑MM x Energy E MM i A) x(avg) ∴ x=1 E EE=E=PP i ii ∑ x x=1 xxx(avg) x(avg) x(avg) x(avg) 17 x=1 a nd x=1 x=1 17 a17 a nd ndx=1x=1 a nd 17 17 x=1 and 17 PM ∑ A) M Energy +aCarbon {nd V M }{V and 17M} } {V + aynd 17 i A) xP M ECarbon 17(%) ∑ x(avg) nd tPotal(V M A) P ∑ M Energy ∑ total(V A) =17 P M (%) M+{V{}VM V =(%) (%) Carbon M ∑ aM nd al(V M = 17 M E(%) ia x {V C CM }E} y= i=a C x(avg) y(avg) nd a nd y(avg) i M y17 C y(avg) A) P ∑ M (%) Energy x=1C C tiotal(V Energy E i x ∑ E M Embodied x(avg) ∑ t otal(V M A) = PM M (%) Carbon }C ∑ ∑ x=1 17 t otal(V M A) = P M (%) Carbon {V M }C}{V y=1 Mtotal(V A)C = P M (%) Carbon {V } t otal(V M A) = P M (%) Carbon {V M y=1 17 C i y 17 C i y y(avg) ∑ i A)C17= Py=1 y C C i y C y(avg) M M (%) Carbon {V M } y(avg) y(avg) 17 17 x=1 i = P17 ∑ M y ∑ C y(avg) t otal(V M A) (%) Carbon {V M } y=1 y=1 a nd y=1 y=1 t otal(V M A) = P M (%) Carbon {V M } ∑ C i y C t otal(V M A) = P M (%) Carbon {V M } y(avg) ∑ ∑ y=1 a{V ndyM y(avg) i (%)y(avg) C total(V A) Piiy C∑M M Carbon {V M}C}CC}CC Mtotal(V A) PM (%) Carbon }{V y(avg) CM= yy Carbon A) (%) MM total(V A) M (%) C =M iM C{V y=1 CC i ii ∑ y yy Carbon C=C=PP and y(avg) 17

y=1

y=1 y=1

y=1 17

Total(VMA)E

= = [ (Pi•0.377 • 5.1) + (Pi • 0.002 • 5.1) + (Pi • 0.086 • 32) + (Pi • 0.047 • 55.3) + (Pi • 0.006 • 7.4) + (Pi • 0.008 • 8.5) + (Pi • 0.038 • 45.1) + (Pi • 0.014 • 55.3) + (Pi • 0.14 • 2.015) + (Pi • 0.012 • 7.1) + (Pi • 0.028 • 16) + (Pi • 0.002 • 19.7) + (Pi • 0.074 • 12.9) + (Pi • 0.026 • 4.79) + (Pi • 0.016 • 7.03) + (Pi • 0.002 • 6.25) + (Pi • 0.047 • 26.4) ] + (920 + 4167 + 3335 + 690 + 3110 + 1380)

Total(VMA)E

= 13.10402Pi + 13602 Pi = weight of vehicle

Embodied energy (MJ) (x•106J) (VMA)E (type M1) (M= <6500kg) (VMA)E (type M2) (M= <5000kg) (VMA)E (type M3) (M= >5000kg) (VMA)E (type N1) (M= <3500kg) (VMA)E (type N2) (M= 3500~12000kg) (VMA)E (type N1) (M= <3500kg)

= 13.10402 •

1509 3100+ 11000* 1951 11892 24042

+ 13602

= = = = = =

33376MJ 54225MJ 157746MJ 36168MJ 169435MJ 328649MJ

+data for M2 not found, took average weight of 16-seat minibus *data for M3 not found, took average weight of single decker & double decker bus

In electricity: (VMA)E (VMA)E (VMA)E (VMA)E (VMA)E (VMA)E

P[W/h]=W [MJ]T [s]=W•10660•60

(type M1) (type M2) (type M3) (type N1) (type N2) (type N1)

= = = = = =

33376 •106 54225MJ 157746MJ 36168MJ 169435MJ 328649MJ

/3600

92.7 150.6 438.2 100.5 470.7 913

MW/h MW/h MW/h MW/h MW/h MW/h

y(avg) y(avg) y(avg)

y=1 y=1 y=1 = P i ∑ M (%) M17M}(%) y Carbon C total(V M A)C y(avg) = P {V ∑ y Carbon y(avg) {V M }C total(V M A)C = Pi i y=1∑ M (%) y=1 y Carbony(avg) {V M }C

Embodied Carbon

y=1

486

Calculating current emissions

487

2021 CPU[AI]

Calculating embodied carbon for each categpry of vehicles

T otal(V M A)C Total(VMA)C

== P i

∑ M (%)y Carbony(avg) {V M }C

y=1

= [ (Pi • 0.377 • 0.31) + (Pi • 0.002 • 0.31) + (Pi • 0.086 • 1.69) + (Pi • 0.047 • 3.08) = [+(P ⋅ 0.377 ⋅ 0.31) + (P ⋅ 0.002 ⋅ 0.31) + (P ⋅ 0.086 ⋅ 1.69) + (P ⋅ 0.047 ⋅ 3.08) + (Pi ⋅ 0.006 ⋅ 0.42) (Pii • 0.006 • 0.42) + (Pii • 0.008 • 0.49) + (Pii • 0.038 • 2.61) + (Pii • 0.014 • 3.08) + (P ⋅ 0.008 0.49) + +(P(Pii ⋅ •0.038 Pi • ⋅ 0.014 Pi • ⋅ 0.14 • 0.14⋅ • 0.115) 0.012⋅•2.61) 0.43)++((Pi 0.028 ⋅•3.08) 0.93)++ ((Pi 0.002⋅ 0.115) • 1.13) + + (Pi ⋅ 0.012 ⋅ 0.43) + i(Pi 0.074⋅•0.93) 0.74)++ ((Pi 0.026 ⋅•1.13) 0.27) ++ (Pi 0.016 •⋅ 0.74) 0.42) ++(Pi (Pii ⋅•0.028 + (P Pi•⋅ 0.002 (Pi•⋅ 0.074 (P•i ⋅0.002 0.026•⋅ 0.36) 0.27)++ (Pi ⋅ 0.016 ⋅ 0.42) (Pi • 0.047 • 1.53) ] + (62 + 268+225 + 39.5 + 195 + 93)

+ (Pi ⋅ 0.002 ⋅ 0.36) + (Pi ⋅ 0.047 ⋅ 1.53) ] + (62 + 268+225 + 39.5 + 195 + 93)

Total(VMA)C

=T otal(V 0.74702Pi M A)+C 882.5 = 0.74702Pi + 882.5 Pi- = weight of vehicle P = weight of vehicle i

Embodied carbon (kg)

Embodied carbon (kg) (VMA)C (type M1) (M= <6500kg)

1509 + 2010kg =3100 * 3198kg =11000 =1951 9100kg 11892 = 2340kg =24042 9766kg

(VMA) (VMA)C (type M1) (M= <6500kg) 1509 C (type M2) (M= <5000kg) (VMA) (type M3) (M= >5000kg) = 0.74702 ⋅ (VMA)C (type M2) (M= <5000kg) 3100+ C (VMA) (VMA)C (type M3) (M= >5000kg) = 0.74702• 11000* + 882.5 C (type N1) (M= <3500kg) (VMA) (type N2) (M= 3500~12000kg) (VMA)C (type N1) (M= <3500kg) 1951 C (VMA) (type N3) (M= >12000kg) (VMA)C (type N2) (M= 3500~12000kg) 11892 C +data for M2 not found, took average weight of 16-seat minibus = 18842kg (VMA)C (type N1) (M= <3500kg) 24042 *data for M3 not found, took average weight of single decker & double decker bus Average CO2 emission kg per car per year in site +data for M2 not found, took average weight of in 16-seat minibus CAT[M1] = 9188.02 ⋅ 1000 / 10175.7 (cp avg no. of cars) 2 emissions *data for M3 not found, took averageCO weight of single decker & double decker bus CAT[M2&3] CO2 emissions = (100+9845) ⋅ 1000 / 183 (cp avg no. of cars) CAT[N1] CO2 emissions = 2138 ⋅ 1000 / 684 (cp avg no. of cars) CAT[N2&3] CO2 emissions = 27029 ⋅ 1000 / 170 (cp avg no. of cars)

+ 882.5

= 2010 kg = 3198 kg = 9100 kg = 2340 kg = 9766 kg = 18842kg

= 902.9 kg/car/year = 54344.3 kg/ca/year = 3125.7 kg/car/year = 158994.1 kg/car/year

average age of a car in the UK Passenger car : 8.6 years old LGV : 8.5 HGV : 7.5 Buses & coaches : 11.2 (https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/985555/vehiclelicensing-statistics-2020.pdf)

Lifetime carbon emission in site

488

CAT[M1] CAT[M2] CAT[M3] CAT[N1] CAT[N2] CAT[N3]

2010 + (902.9 ⋅ 8.6) 3198 + (54344.3 ⋅ 11.2) 9100 + (54344.3 ⋅ 11.2) 2340 + (3125.7 ⋅ 8.5) 9766 + (158994.1 ⋅ 7.5) 18842 + (158994.1 ⋅ 7.5)

Calculating current emissions

= 9775.3kg CO2 = 611845.5kg CO2 = 617756.2kg CO2 = 28908.5kg CO2 = 1202221.8kg CO2 = 1211297.8kg CO2

= 9.8 TCO2 = 611.8 TCO2 = 617.8 TCO2 = 28.9TCO2 = 1202.2TCO2 = 1211.3TCO2

Victoria North, Photo by author

489

2021 CPU[AI]

Annual average daily flow from different count points on site vehicle type

Calculating running carbon

The Department for Transport (DoT) releases road travel statistics that contains street-level data for major and minor road networks. The table on the below (Department for Transport, 2020) illustrates the data. The data is taken from manual count of different vehicle types along certain points within the network. This data will be used to calculate the emissions on-site from different vehicle types in 2020.

count point

Carbon emitted when driving

K J

490

Calculating current emissions

M2 & M3

N2 & N3

1869

259

3388

271

8960

463

1152

163

111

10933

1944

366

434

12084

390

473

27951

342

1338

248

18165

376

1786

308

27951

342

745

201

Vehicles with at least 4 seats and a load area not exceeding 40% of the length of the vehicle and a weight limit of 6500kg max mass. e.g. passenger cars

Vehicles with 4 or more wheels used for the carriage of passengers, with more than 8 passenger seats in addition to the driver’s seat and a maximum DGW not exceeding 5,000kg. e.g. dual purpose vehicles, motor caravans and ambulances.

Vehicles used for the carriage of passengers, comprising more than eight seats in addition to the driver’s seat, and having a maximum mass exceeding 5 tonnes. e.g. Buses

Light goods vehicles, up to 3,500kgs

Vehicles for the carriage of goods and having a maximum mass exceeding 3.5 tonnes but not exceeding 12 tonnes

Vehicles for the carriage of goods and having a maximum mass exceeding 12 tonnes

F C

“In 2020, there was an estimated 48,345 T CO2e emitted* within Victoria North"

*Based on the data from DoT, statistics regarding vehicle emissions and ages a calculation of the emission on site was made. The estimated total emission on the site from cat. M & N combined (which accounts for 89% of all emissions): 9188+100+ 9845 +2138+27029 =48345 T CO2e/yr

491

2021 CPU[AI]

Carbon emissions of M1 vehicles

Calculation method

The UK government implemented the Vehicle Excise Duty (VED) tax to encourage purchasing lower emitting vehicles by taxing them lower. Different bands of emission have a different price of taxation. By using data from VEH0206, the graph below that illustrates the varying percentage of vehicles registered under the different tax bands. (Gov.uk, 2021) The average mileage table at the bottom uses data from NTS0901 (Department For Transport, 2020), give an average number for calculations.

∑ all M1 vehicles / number of count points = Average no. of M1 Vehicles on site

Calculate each category of carbon emission: (Average no. of M1 vehicles on site * % of licensed cars in each category) *(Average mileage in 2020 * Median emission)

Percentage of Licensed Cars Based on Emissions Category (2020)

Total Emission = ∑ all carbon emission across all categories

26.6%

Utilising data from Manual Count Points around the site: ∑ all passenger cars / number of count points = (27951 + 18165 + 27951 + 1869 + 3388 +8960 + 87 + 111 + 10933 + 434 + 12084) / 11 = 10175.73

22.1%

Carbon emissions based on % of each category of licensed carbon emissions: (Average Cars on site * % of Emission Category) * ( Average Mileage in 2020 * Median Emission gCO2/km) / 100000

13.6% 11.0%

6.7%

6.4%

4.6% 0.6%

0.6%

0.2%

1.2%

1-50

51-75

76-90

3.3% 1.6%

91-100

1.5%

101-110 111-130 131-150 151-170 171-190 191-225 226-255

gCO2/km

Over 255

unknown

(10175.73 * 0.6%) * 0*6800) = 0 TCO2 (10175.73 * 0.6%) * (25*6800) = 10.4 TCO2 (10175.73 * 0.2%) * (63*6800) = 8.72 TCO2 (10175.73 * 1.2%) * (83*6800) = 68.9 TCO2 (10175.73 * 6.4%) * (95*6800) = 420 TCO2 (10175.73 * 11.0%) * (105*6800) = 799 TCO2 (10175.73 * 26.6%) * (120*6800) = 2208 TCO2 (10175.73 * 22.1%) * (140 * 6800) = 2141 TCO2

(10175.73 * 13.6%) * (160*6800) = 1505 TCO2 (10175.73 * 6.7%) * (180*6800) = 834 TCO2 (10175.73 * 4.6%) * (208*6800) = 662 TCO2 (10175.73 * 1.6%) * (240*6800) = 266 TCO2 (10175.73 * 1.5%) * (255*6800) = 265 TCO2

Total Carbon Emissions from M1 Passenger Cars on Site = 10.4 + 8.72 + 68.9 + 420 + 799 + 2208 + 2141 + 1505 + 834 + 662 + 266 + 265 = 9,188.02 T CO2 /yr

Count Point Data for M1 Vehicles (2020) Count point

1869

3388

8960

111

10933

434

12084 27951 18165 27951

Average mileage for M1 vehicles (2020)

Business Mileage

Community mileage

Other mileage

Total mileage

200

2400

4100

6800

Based on 2020 data, 9,188T CO2e/year is emitted within the Northern Gateway from M1 vehicles

(GovUK, 2021)

492

Calculating current emissions

493

2021 CPU[AI]

Carbon emissions of M2 & M3 Vehicles (buses and coaches)

Calculation method

For M2 & M3 vehicles, the methodology differs. Firstly, as the data from the count points combines both M2&M3 together, statistics needed to differentiate the M2 & M3 is required. The VEH0601 shows the makeup for M2 & M3 vehicles in UK (Department for Transport, 2020) The age of these vehicles are also taken into consideration as this has a huge contributing factor to how much emission they are estimated to have due to the varying standards implemented through the years. The table at the bottom shows the percentage of M2&M3 age from VEH 0607. (Department for Transport, 2020)

Count Point Data for M2&3 Vehicles (2020) Count point

M2&3

463

390

342

376

342

0.3% Other

Amount of M2 and M3 vehicles on site Utilising data from Manual Count Points around the site: 27.7% Single Deck Bus (M3)

Percentage of licensed Bus and Coaches by Types in UK (2020)

∑ all buses and coaches / number of count points = (13+ 1 + 463 + 0 + 0 + 91 + 0 + 390 + 342 + 376 + 342) / 11 = 183 buses and coaches on site

Estimated M2 on site:

55% Minibus (M2)

55% * 183 = 100 nos 16.7% Double Deck Bus (M3)

Estimated M3 on site: (16.7% + 27.7%) * 183 = 81.2 nos

Calculation: Total % of vehicle registered under Euro4/5/6 regulation* no. of vehicle on site = no. of vehicle that abides by Euro4/5/6

Percentage of ages of Buses and Coaches since first registration (Q4 2020)

Convert each type of pollutant gas into CO2e: 36.3%

Mass of pollutant gas * conversion factor into CO2e = Carbon Emission CO2e 30.9%

∑ all converted CO2e

Total Emission: ∑ all converted CO2e * (nos. of vehicle on site * annual mileage)

Annual Mileage:

11.2%

Total vehicle miles / Total no. of vehicles (Department for Transport, 2021) 3.5%

4.5%

5.1%

5.3% 3.2%

≤1

1≤2

2≤3

3≤4

4≤6

6≤13

>13

unknown

years old (VFH, 2021)

494

Calculating current emissions

495

2021 CPU[AI]

M2 Emissions Tables were created based on emission standards from Euro 6 and 5 guidelines. (The European Parliament, 2007) A paper covering how to convert polluting gases from vehicles into CO2 equivalent (CO2e) was summarised in the table at the bottom. (IPCC, 2015)

Euro 5 Standards were implemented right at the start of 2012 - roughly 9 years from Q4 2020. 42% was taken from the 6-13 year old vehicle data from the bar graph on the page before. 42% was taken by taking 3/(13-6) * 100. Thus, assumption is made that there is an even distribution of vehicles from each year.

Euro 6 Standards

Euro 5 Standards

For vehicles registered on or after 01/09/2016

For vehicles registered on or after 01/01/2012

Based on bar graph before:

3.5% + 4.5% + 5.1% + 5.3% = 18.4% * Number of cars on site

11.2% + (36.3 * 0.42)%= 26.446%

18.4% * 100

26.446% * 100 = 26 M2 vehicles on site that abides by Euro 5 standards

= 18 M2 vehicles on site that abides by Euro 6 Standards

Euro 5 Standards for M2 Vehicles

Euro 6 Standards for M2 Vehicles

Mass of Nitrogen Oxides (mg/km)

Mass of Nitrogen Oxides (mg/km) Vehicle Category M2

Mass of Carbon Monoxide (mg/km)

Mass of Total Hydrocarbons (mg/km)

500

1000

100

CI = Compression Ignition (Diesel) PI = Positive Ignition (Petrol)

Conversion Factor for Euro 5 Standards

Vehicle Category M2

Mass of Carbon Monoxide (mg/km)

Mass of Total Hydrocarbons (mg/km)

180

500

1000

100

CI = Compression Ignition (Diesel) PI = Positive Ignition (Petrol)

Utilising data from tables above: For NO’s CO2 equivalent value:

GWP100 of Carbon Dioxide

265

180 * 265 = 47 700 mg of CO2eq/km GWP100 = Global Warming Potential of gas over 100 years compared to carbon dioxide

Utilising data from tables above: CO has no direct GWP, but is still being disputed in its effects in indirect GWP (IPCC, 2001) (Daniel and Solomon,1998)

CO2e on site per year: 47 700 * (26 Vehicles * Annual Mileage) = 47 700 * (26 * ( 1 397million miles travelled / 136.7thousand total vehicles)) = 47 700* (26 * (10219 miles)) = 47 700* (26 * 16446km) = 20,396,329,200 = 20.4 T CO2 /yr

HC has negligible GWP (IPCC, 2021) For NO’s CO2 equivalent value: 80 * 265 = 21 200 mg of CO2eq/km

CO2e on site per year: 21 200 * ( 18 Vehicles * Annual Mileage) = 21 200 * (18 * ( 1 397million miles travelled / 136.7thousand total vehicles)) = 21 200* (18 * (10219 miles)) = 21 200* (18 * 16446km) = 6 275 793 600 = 6.28 TCO2eq

496

Calculating current emissions

≤5 year old M2 Vehicles emitted on site 6.28T CO2e /yr ≤9 years old M2 vehicles emitted on site 20.4T CO2e /yr 497

2021 CPU[AI]

M2 Emissions

M3 Emissions

Euro 4 Standards apply to vehicles more than 9 years old, which is a significant proportion of the M2 population. The table below illustrates the standards for the Euro 4a and 4b. (The European Parliament, 1998) Due to the range of ages within each category in the bar graph, there is some uncertainty whether certain vehicles fall within A or B standards. Thus an average of the emissions for A and B are used for these vehicles instead.

Similar to M2 vehicles, M3 follows the Euro4/5/6 standards depending on the age. However, M3 differs from M2 in that the calculations includes Methane and its conversion into CO2e, as illustrated in the tables below. (The European Parliament, 2009) (IPCC, 2015)

Euro 4 Standards

For vehicles registered on or after 01/09/2018

For vehicles registered before 01/01/2012

Based on bar graph before:

Euro 6 Standards

3.5% + 4.5% = 8% * Number of cars on site

Based on bar graph before: (36.3 * 0.58)% = 21 vehicles that abides by Euro 4 B Standards

8% * 81.2

30.9 vehicles that might abide by either A or B Standards

= 6.5 M3 vehicles on site that abides by Euro 6 Standards

Euro 4 Standards for Cat. M Vehicles Vehicle Category

Euro 6 Standards for M2 Vehicles

Mass of Nitrogen Oxides (mg/km)

Mass of Carbon Monoxide (mg/km)

Mass of Total Hydrocarbons (mg/km)

M (2005-2011)

250

500

1000

100

M (2000-2004)

500

150

640

2300

200

Mass of Nitrogen Oxides (mg/km) Vehicle Category M3

400

500

CI = Compression Ignition (Diesel) PI = Positive Ignition (Petrol)

Utilising data from tables above: For NO’s CO2 equivalent value: 250 * 265 = 66 250mg of CO2eq/km

CO2e on site per year for Euro 4B: 66 250* (21 Vehicles * Annual Mileage) = 66 250* (21 * ( 1 397million miles travelled / 136.7thousand total vehicles)) = 66 250* (21 * (10219 miles)) = 66 250* (21 * 16446km) = 22,880,497,500= 22.9 T CO2 /yr

For vehicles that might use A or B:

Mass of Methane (mg/km)

Conversion Factor for Euro 6 Standards GWP100 of Carbon Dioxide

GWP100 of Carbon Dioxide

GWP100 of Methane

265

GWP100 = Global Warming Potential of gas over 100 years compared to carbon dioxide

Utilising data from tables above: For CH4’s CO2 equivalent value: 500 * 28 = 14,000mg = 14g of CO2eq/km

Average of Euro 4 Standards A(2000) and B(2005) = (500+250) /2 = 375mg/km

Utilising data from above: For NO’s CO2 equivalent value: 375 * 265 = 99 375mg of CO2eq/km

CO2e on site per year: 99 375* (30.9 Vehicles * Annual Mileage) = 99 375 * (30.9 * ( 1 397million miles travelled / 136.7thousand total vehicles)) = 99 375* (30.9 * (10219 miles)) = 99 375* (30.9 * 16446km) = 50,500,526,625= 50.5 T CO2 /yr

Total Carbon Emission Equivalent from M2 Vehicles:

For NO’s CO2 equivalent value: 400 * 265 = 106,000mg = 106g of CO2eq/km Total CO2e: 106 + 14 = 120gCO2eq/km

CO2e on site per year: 120* (6.5 Vehicles * Annual Mileage) = 120* (6.5 * ( 1 397million miles travelled / 136.7thousand total vehicles)) = 120* (6.5 * (10219 miles)) = 120* (6.5 * 16446km) = 12,827,880 = 12.8 T CO2 /yr

6.28 + 20.4 + 22.9 + 50.5 = 100 T CO2e /yr

498

Calculating current emissions

499

2021 CPU[AI]

B1 Euro Standards

M3 Emissions For the older M3 vehicles which still take up a significant percentage of the population, they follow B2 or B1 Euro Standards as illustrated below. (The European Parliament, 1996) (IPCC, 2015)

For vehicles registered from before 01/10/2008 Based on bar graph before: (36.3*0.14)% + 30.9% = 35.9% 35.9% * 81.2 = 29.2 M2 vehicles on site that abides by B1 standards

B2 Euro Standards

Utilising data from tables above:

For vehicles registered on or after 01/10/2008

For CH4’s CO2 equivalent value:

Based on bar graph before:

1,100 * 28 = 30,800 mg of CO2e/km

5.1% + 5.3% + 11.2% + (36.3*0.86)%= 52.818% 52.818% * 81.2 = 43 M2 vehicles on site that abides by B2 standards

For NO’s CO2 equivalent value:

Older Euro Standards for M3 Vehicles

3,500 * 265 = 927,500 mg of CO2eq/km

Vehicle Category

Mass of Nitrogen Oxides (mg/kWh)

Mass of Methane (mg/kWh)

M (2008-2018)

2000

1100

M (2005-2007)

3500

1100

M (2000-2004)

5000

1600

Total CO2e: 30,800 + 927,500 = 958.3 gCO2eq/km

CO2e on site per year: 958.3* (29.2 Vehicles * Annual Mileage) = 958.3* (29.2 * ( 1 397million miles travelled / 136.7thousand total vehicles)) = 958.3* (29.2 * (10219 miles)) = 958.3* (29.2* 16446km) = 460,197,892.56 = 460.2T CO2e

Conversion Factor

Total Carbon Emission Equivalent from M3 Vehicles:

GWP100 of Carbon Dioxide

GWP100 of Methane

265

12.8 + 396.5 + 460.2 = 869.5 T CO2 /yr GWP100 = Global Warming Potential of gas over 100 years compared to carbon dioxide

Total Carbon Emission Equivalent for Cat. M Vehicles: 9188.02+100+869.5 = 10,157.52 T CO2 /yr

Utilising data from tables above: For CH4’s CO2 equivalent value: 1,100 * 28 = 30,800 mg of CO2eq/km For NO’s CO2 equivalent value: 2,000 * 265 = 530,000mg of CO2eq/km Total CO2eq: 30,800 + 530,000 = 560.8gCO2eq/km

CO2 eq on site per year: 560.8* (43 Vehicles * Annual Mileage) = 560.8* (43 * ( 1 397million miles travelled / 136.7thousand total vehicles)) = 560.8* (43 * (10219 miles)) = 560.8* (43 * 16446km) = 396,585,422.4 = 396.5 TCO2eq

500

Calculating current emissions

Total CO2e from M2 vehicles 100T CO2e/yr Total CO2e from M3 vehicles 869.5T CO2e/yr Total CO2e from all M vehicles 10,157.52T CO2e /yr 501

4220.4

4123.2

4009.9

3898.1

3782

3633.6

3353.9

3280.6

3248.3

3207.8

3184.5

3191.4

3148.9

3023.1

3000

2943.4

Thousand licensed vehicles

4000

3471.3

5000

Thousand licensed vehicles

2000

485.9

501.5

500.3

499.4

493.6

483.4

473.9

468.9

465.5

Number of LGV registered in GB (2005-2020)

470.1

508.2

1000

477.8

Number of HGV registered in GB (2005-2020)

495.9

To calculate the N1 Light goods vehicle emissions, the number of cars are taken and divided by the total carbon that is emitted, giving an average emission per car emitted, which is then multiplied by the total number of cars in the site, giving the final result. The methodology is the same for N2 and N3 heavy goods vehicles.

510.8

N2&3 Emissions

508.3

Carbon emissions of N1 Light goods vehicles & N2 & N3 Heavy goods vehicles

460.6

2021 CPU[AI]

500

0 2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

1000

Greenhouse gas emissions attributable to HGV in the UK (2009-2019) 0 2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

Average carbon emission of registered LGV on the road in the UK (2020)

Count point

259

271

1152

1944

390

1338

1786

745

Utilising data from Manual Count Points around the site: ∑ all buses and coaches / number of count points = (13+15+1944+1152+271+68+390+259+745+1786+1338) / 11 = 683.8 = 684 LGV on site

Cat N1 LGV:

12800 miles ≈ 20600km*151.76(CO2 g/km) = 3,126,256g CO2 = 3126.3kg (yearly emission/km)

20 Million Metric Tons CO2e

Data took from 193685 records and their respective NEDC testing results, calculating the average of emission: 151.7g/km

20.1 20.3 20.1 19.5

2007

0 0 19 91 19 92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08 20 09 20 10 20 11 20 12 20 13 20 14 20 15 20 16 20 17 20 18 20 19

2006

19 9

2005

Total emission in UK:

4220200(nos)*3126.3(kg) = 13,193,612,260kg/yr = 13,193,612T/yr = 13 MT CO2 /yr

Emission on site:

684(nos)*3126.3(kg) = 2,138,389.2kg/yr = 2,138T/yr = 2138 T CO2 /yr

502

Calculating current emissions

503

2021 CPU[AI]

Carbon emissions of alternative transportation

N2&3 Emissions

Alternative transportation although accounts for a small amount in the UK, is a growing sector and more people are choosing to use them. They generally include bikes, e-bikes, scooters and e-scooters. Here a calculation for e-bikes is calculated.

Count point

N2&3

163

366

473

248

308

201

Amount of HGV on site

UK bike market share

In 2019, the UK sold 2,613,000 cycles (including e-bikes) and sold 101,000 ebikes, manufactured around 137,000 units of bikes (include ebike)

E-bike: (6%) 156,780

Bike market share 2019: (2,613,000)

Utilising data from Manual Count Points around the site: ∑ all buses and coaches / number of count points = (17+8+366+163+23+2+54+473+201+308+248) / 11 = 169.36 = 170 HGV on site

Embodied energy of bicycle: 2380kWh +325+50 = 2755kWh (Dave, 2010)

Hybrid: (16%) 418,080

Cat N2&3 HGV: 1

6,400,000,000 total miles / 485900 nos of HGV = 33751.8 miles ≈ 54318.3km*

Average CO2e emissions from HGV:

19500000000kg / 54318.3 = 358995 CO2ekg/km

Emission on site:

170(nos)*158995(kg) =27,029,150CO2kg/yr = 27,029 T CO2e /yr

Mountain bike: (40%) 1,045,200

E-bike growth: 2015 2019 2020

= 40,000 = 101,000 = 160,000

Road bike: (20%) 522,600

2015-2019 = +150% 2019-2020 = +58.4%

City bike: (21%) 548,730

Total Carbon Emission Equivalent for Cat. N Vehicles: 2,138+27,029 = 29,167 T CO2e /yr Average battery size:

Based on 2020 data, total emission from N1 vehicles on site is 2 138T CO2e/yr N2 vehicles on site is 27 029 T CO2e/yr Total Emissions from N Vehicles 29 167 T CO2e/yr 504

Calculating current emissions

25V 10Ah = 250W/h [0.26 (avg elec cost)] 250W=legal limit of power before considered as motorcycle mileage fuel efficiency Avg mileage of one ebike charge = 60km Speed limit of power assist = 15.5mph Avg time spent commuting = 25mins Avg commute round trip miles = 6.4= 10.3km Avg household = 230v, 2A(charger) Charging time = 10Ah/2A=5hrs =18000s =4.5 MJ to charge every 5.8 times (approx. every week) Typical ebikes last around 10 years Embodied energy = 2755kW/h Total life cycle energy: 2755e3 + 250*52*10 = 2885000 = 2.9 MW/h

505

2021 CPU[AI]

Metrics in transportation Unifying the calculation

In order to compare the different metrics, data and calculations across all the different types and categories of transportation, a calculator had been developed in a computer software that parametrises and normalise all the data into a comparable state, which was chosen as the CO2 emitted per kilometre in a year by each passenger. Total Carbon Emission per passenger (gCO2/km/year/passenger) Vehicle Category & Features M1 Passenger Cars M2, M3 Buses & Coaches Number of Vehicles on Site 2020

Vehicle (km/year)

LGV, N2, N3 Heavy Goods Vehicles

Average mass per car

167.181504

4 people

41.795376

16 people

3.187053

80 people

41.485116

16 people

20.632965

1 person

6663.874281

8 people

1665.96857

Private Bikes

1 person

6.455843

Life Cycle Analysis N2, N3 Running carbon

(kg)

Private Bikes & E-bikes

Maximum No. of People in the vehicle

Dockless sharing e-scooters

Private E-bikes

1 person

10.04262

Battery size (Wh)

Private Bikes & E-bikes

Dockless sharing e-scooters

1 person

90.942845

Trams

212 people

6.074267

Trains

631 people

1.753738

Trams Trains

506

Total Carbon Emission (gCO2/km/year)

LGV, N1 Light Goods Vehicles

Average Mileage per

1 person M1

Calculating current emissions

Embodied carbon

507

2021 CPU[AI]

Vehicle emission analysis Unifying the calculation

The diagram below translates the amount of running carbon emission and embodied carbon in each type of vehicle. Although the total carbon emitted per mode of transport may be high, the total carbon emitted per person in said transport may be low, assuming that the occupancy is at its maximum. For example, the total carbon emission for tram is high but the total carbon per person in a maximum occupancy at 212 people is only 1.75g.

Vehicle Category

Total Carbon Emission per vehicle (gCO2/km/year/vehicle)

Total Carbon Emission per person (gCO2/km/year/pp)

1106.61 50.99

TRAIN M2 MINIBUS

1.75 3.18

(631 people) (16 people)

1287.74

TRAMS

6.07

(212 people)

6.46

(1 person)

10.04

(1 person)

20.63

(16 people)

41.48

(80 people)

19.05

(4 people)

90.94

(1 person)

38.54

(4 people)

Carbon M VEHICLES

6.46

BIKE

10.04

E-BIKES

165.06

N1 LIGHT GOOD VEHICLES

3318.81

M3 BUS

76.21

M1 BEV

90.94

E-SCOOTER

N VEHICLES

154.17

6663.87

M1 PASSENGER CAR

N2 N3 HEAVY GOOD VEHICLES

OTHERS

6663.87

TRAIN

(1 person)

1165.97

TRAM

(8 people)

508

Running Carbon

Carbon emission above 50g

Embodied Carbon

Carbon emission lower than 50g

Calculating current emissions

509

2021 CPU[AI] Number of public charging points by speed (2016-to date) 30,000

An electric way

Slow

20,000

Fast Rapid 10,000

Building a world-class public infrastructure network

Ultra-rapid Locations

2016

2017

2018

2019

2020

2021(YTD)

Total devices: 260558 Updated: 04 October 2021

The vast majority of electric vehicle drivers choose to charge their cars overnight at home (and 85% of dwellings in rural areas have off-street parking) or increasingly at work. Whilst the overall number of charge points is important, getting the right infrastructure into the right places is key to meet motorists needs. For those without access or undertaking longer journeys, public charging is key. The UK has one of the largest public networks in Europe. There is a wide network of public charge points across the UK. The growth of device locations since 2015 can be seen below:

2015

April 2021

Number of rapid public charging points by type (2011-to date) 12,500 10,000

CHAdeMO

7,500

CCS

5,000

Type 2 Tesla (Type 2 & CCS)

2,500 0

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

Total rapid connectors: 11151, Updated: 04 October 2021

Rapid Chargers

1151

CONNECTORS

4881 DEVICES

3098 LOCATIONS

Today, a driver is never more than 25 miles away from a rapid charge point anywhere along England’s motorways and major A roads.

148

LAST 30 DAYS

2021 (YTD)

Market share of UK charging points by network Ubitricity

Tesla Supercharger

Pod Point

Charge Your Car

BP Pulse

Genie Point

Charge Place Scotland

InstaVolt

Source London

Vend Electric

Tesla Destination

Zero Net

char.gy

Other Networks

Distribution of UK charging points by geographical area Greater London

North East

South East

Isle of Man

Scotland

Channel Islands

South West West Midlands Yorkshire & the Humber

(GovUK, 2021. Zapmap,2021)

510

An electric way

Wales

(GovUK, 2021. Zapmap,2021)

511

2021 CPU[AI] Charging up in changing seasons The weather affects how much energy your electric car consumes. You have a larger range in the summer and a smaller range in winter.

Charging & charger types Building a world-class public infrastructure network

TETHERED CHARGE POINT

SOCKETED CHARGE POINT

A tethered charge point comes with a cable attached to the unit, available with both Type 1 or 2 connector. Most newly manufactured EVs in the UK use a type 2 connector.

A socketed charge point comes without a cable, they are universal and any EV with a fast charging cable can use it. The benefit is that it accommodate all EV types provided with a correct cable.

The benefit is that it can be plugged into the car. However, it is limited to vehicles with that connector Type.

Charging cables have connectors that can be plugged into the vehicle and/or the charge point. The type of charging connector depends on the vehicle and the power rating of the charge point. The most famous example is the Tesla supercharger, however it can only be used by Tesla cars, but is an example of a charger that battery electric vehicles use to charge.

Charging connector

Charger connector

2.3-3 kW AC UK 3 PIN PLUG

THREE PIN PLUG A standard three-pin plug that for connecting to any 13amp socket

Approx. range from 30 mins Power rating/current of charging

SOCKETED A charge point where a type 1 or 2 cable can be connected

TETHERED A charge point with attached cable with either a type 1 or 2 connector

WIRELESS Wireless charges the EV without any cables, unavailable in the UK

Single phase (standard charge)

3-7 kW AC TYPE 1

Single phase (slow/fast charge)

5 Miles

- Standard UK domestic electricity outlet - Not designed for prolonged use - Very low charging - Homes, on-street locations, destinations

12 Miles

- Only available in single phase - Less common among modern EVs - No locking mechanism - Homes, on-street locations, destinations

75 Miles

- Set to become the EU connector standard - Compatible to single/three phase charging - Has built-in locking mechanism - Tesla has a 120 kW DC version of type 2 - Homes, on-street locations, destinations

85 Miles

- Old type of rapid charger - Compatible with most Japanese manufactures - Most popular due to popularity of Nissan Leaf - Motorway Service Areas / destinations

85-200 Miles

- Most versatile rapid charging connector - Set to become the most popular DC connector - Enables higher power delivery to support large ultra-rapid-chargers - Motorway Service Areas / destinations

Typical Charging time for EVs SLOW...

3-43 kW AC

8-10 hours

Typically rated up to 3kW. Often used to charge overnight or at the workplace

FAST

TYPE 2

3-4hours

Typically rated at either 7kW or 22kW. Tend to be installed in car parks, leisure centres, supermarkets and houses with off-street parking.

RAPID

30-60 minutes

Time based on Nissan LEAF with battery size: 40 to 62 kWh

CHAdeMO

Typically rated from 43kW. Only compatible with EVs with rapid charging capability

Single/three phase (fast charge)

50 kW DC Three phase (rapid charge)

50 kW-350kW DC Rapid chargee

(EDF, n.d.. Lane, 2021)

512

An electric way

COMBINED CHARGING SYSTEM (CCS)

Charging cable features

513

2021 CPU[AI] Usage and payment comparisons Excluding Homechargers, all chargepoints have a system to allow you to access them. Below is an overview of the common types. (Podpoint, 2021)

Charge Point Locations Charge Points currently near and on-site

Access

Pros

Cons

Typically found in:

“Plug and Play” Just plug in and the car charges

No sign up, instant access

- No control over access - Can’t collect usage data or bill for usage

- Some workplaces - Some public destinations

- Any user with a smart phone can access - Can manage usage and billing, where necessary - See charge point details/ location in app

- Numerous apps needed for different networks - Issues in areas of poor signal

- Public destination chargers - Rapid chargers

-Can manage usage and billing, where necessary - Easy to use, even in areas of poor signal

- No card, no charge - you have to wait for it to arrive in the post - Numerous cards needed for different networks - Poor security, cloning of cards

- Workplaces - Public destination chargers - Rapid chargers

- Secure card readers make charge points expensive - Each usage incurs a transaction fee = no free charging

- Rapid chargers

App enabled Access via smart phone app The table below shows there are currently only public 2 charge points on site. Both are located near each other and on the southwest of Victoria North, towards the city center. (Carwow, n.d.) This is currently understandable the rest of the site are mostly residential and industrial areas. However, more charge points are required upon development of the site into an extension of the city.

RFID card Specialist card that allows access

Contactless Payment Card Pay with tap of debit or credit card

- No sign up, instant access - Easy to use, even in areas of poor signal

Future plans for infrastructure The UK's phase out dates for new petrol and diesel cars and vans has sent a clear signal of the UK’s direction of travel. This certainty has already unlocked private sector funding – which will expand charge point provision and provide opportunities to create jobs and investment across the country. Since the announcement of the Prime Minister’s 10 Point Plan, a number of industry leaders have come forward with ambitious commitments. (HM Government, 2021)

A B

Axial Map

Type 2

514

50kW: 1 43kW: 1

3.7kW: 2

An electric way

CHAdeMO

50kW: 1

PAGE | 38

Membership Needed Yes Yes

BP Pulse

Aiming to double the size of its network in the UK to 16,000 charge points by 2030 and install a number of rapid charging hubs.

Shell

Plans to install 5,000 rapid and ultra-rapid electric vehicle chargers on forecourts by 2025.

Motor Fuel Group

Investing £400 million to install 2,800 high powered chargers (150 kWh and 350 kWh) at 500 UK locations by 2030.

InstaVolt

Aims to deliver 5,000 chargers by 2024/25.

Gridserve

Has acquired the Electric Highway from its original developer, Ecotricity. Gridserve will invest over £100 million to open 50 electric hubs, 300 rapid chargers at motorway services and over 100 electric forecourts.

EVBox

Announced that 500 chargepoints will be installed across UK car parks in a boost for destination charging.

Engie/Premier Inn

Over 1,000 chargepoints will be installed at Premier Inn sites allowing more flexibility to charge while away from home.

Podpoint

Partnered with VW and Tesco to deliver chargepoints at Tesco locations throughout the UK.

Allstar/Gronn Kontakt

Forming a partnership to launch the first EV charge payment card for fleets which can be used across 3,700 charge points in Britain.

515

2021 CPU[AI]

Cost Factors

Cost variables (Diesel/Petrol vs. Electricity) The cost variables between the two are illustrated below. (Petrolprices, n.d.) The main difference between the two is that the variables for diesel/petrol are largely out of the consumer's control, whereas for electricity it is within their control and is thus can be seen as more predictable and stable.

How much it costs to charge up an electric vehicle

Diesel, Petrol

public charging

Unlike with petrol/diesel cars when you only have the forecourt fuel price to consider, there are lots of variables when it comes to the cost of charging an electric car or plug-in hybrid. This is illustrated below. (Autoexpress,2020) (Podpoint, 2021)

Employee Benefits

Type of Charger

Some organisations provide free charging for staffs in order to promote a greener way of commuting to work

Certain types of chargers like the Rapid Charger can cost £6.50 for a 30 min charge, ~90 miles

Service Provider Companies like Pod Point cost 25p/kWh. Tesla's supercharger network are free of charge for Tesla owners

domestic charging

Cost Factors

Electricity Rate The average domestic electricity rate is 17p/kWh. Depending on your local rates, you could be paying £9-£9.90 for a 60 kWh vehicle. By subscribing to tariffs targeted towards EV drivers, the cost could be as low as 4.5p/kWh

•Market forces (inflation, seasonal demands, taxes, cost of crude oil and refined fuel) •Global events (wars, gas shortages, security threats to oil supplies) •New technology (alternative fuel sources, new types of vehicles

•Time (off-peak/ peak) •Tariff/ Charging Network (Ubitricity, Tesla) •Battery size •Energy Required

Cost (Petrol, Diesel & Electric) The table below shows the cost to fuel/charge up the average petrol, diesel and electric car. (Gov.uk, 2021) It shows that electric cars are clearly the more economical way due to its lower cost per mile.

Battery size

40 kWh

100 kWh

13.8kWh

168 miles

388 miles

28 miles

Cost to fully charge*

£6.12

£16.15

£2.11

Cost per mile

4.3p

4.7p

8.9p (electric mode**)

Approximate “real-world” electric range

Petrol

Fuel Type Engine Size (cc)

"Fully charging a 60kWh electric car will cost between £9.00 and £9.90"*

Electricity

Mean MPG

≤1400

1401-2000

>2000

≤1600

1601-2000

>2000

54.2

46.1

30.8

65.4

52.9

43.5

134.8p

Fuel Price/L Cost per mile

Diesel

11.6p

13.6p

136.8p 20.4p

9.8p

12.1p

14.8p

*(depending on where you live)

(Autoexpress, 2020)

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Proportion of new vehicles

The rise of Battery Electric (BEVs)

Covid-19 measures & recession

3 2 1 0

Recession 1980

Recession 1988

1996

2004

2012

Alt. fuel +87% 518

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120,000

169%

80,000 40,000

82% 46% 2012

2013

2014

2015

2016

2017

2018

2019

2020

New Car Registration Annual change in 2020

Petrol -35%

160,000

Battery Electric Vehicle (BEV) Plug-in Hybrid Electric Vehicle (PHEV) Other fuel types

2.1 million vehicles were registered for the first time in Great Britain during 2020, 27% lower than during 2019.Despite the promising drop in car sales in 2020, it would be shortsighted to attribute it only to shifting attitudes. The drop in sales is more likely attributed to the pandemic and lockdowns, which would close showrooms and vehicle dealerships. The car sales is likely to stay lower through the year, due to economic recession as seen in history.

Diesel -51%

200,000

Recession

"New registrations of Battery Electric cars nearly tripled in 2020 (+184%) compared to 2019, with more registered than in all previous years combined (2001 to 2019)"

The fading trend of diesel and petrol In 2020, there was a sharp decline in the purchase of diesel and petrol cars amidst the rise in BEV and ULEVs. New diesel car registrations fell by 51% in 2020 compared to 2019 and 35% for petrol cars. Thousands of cars registered for the first time

Millions of vehicles of registered for the first time

The recent trends in this statistical series have been heavily affected by the measures implemented from March 2020 onwards to limit the impact of the coronavirus (COVID-19) pandemic. (Department for Transport, 2021)

Ultra Low Emissive Vehicles registered for the first time- UK

Despite the 27% drop in car sales, there were some strong trends in 2020. Across all new alternative fuel car registrations in Great Britain, there were 164 thousand Hybrid Electric (HEVs), 107 thousand Battery Electric (BEVs), 67 thousand Plug-in Hybrid Electric (PHEVs), and fewer than 1 thousand using other alternative fuel types. New registrations of BEV cars nearly tripled in 2020 (+184%) compared to 2019, with more registered than in all previous years combined (2001 to 2019 new registrations: 101 thousand), which equates to 51% of all new BEV car registrations since 2001 occurring in 2020.

Purchasing trends in vehicles based on fuel type

2400 2000 1600 1200 800 400 0 2002

2005

2008

2011

2014

2016

2020

(Department for Transport, 2021) Diesel

Petrol

Alternative Fuel

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Proportion of new vehicles Purchasing trends in vehicles based on fuel type

"More alternative fuel cars (338 thousand) were registered for the first time in Great Britain during 2020 than diesel cars (295 thousand), following a 87% annual increase in alternative fuel cars year on year, amidst a sharp decline for both petrol and diesel car" -Department for Transport, 2021

Proportion of vehicles registered for the first time GB

Ultra Low Emission Vehicles (ULEVs) 9%

0% 2011

2014

2017

2020

Even though there is no observable trend of a fall in newly purchased vehicles (excluding times affected by COVID-19), we can clearly see a marked rise in purchasing of alternative fueled vehicles such as BEVs, and that consumers are turning away frommore 'traditional' fuel types like petrol and diesel.

(Harding, 2020)

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New ULEV Registration

Ultra-Low Emission Vehicles Observing the increase in ULEV ownership

Definition

% increase

Battery Electric Cars

107,878

37,932

184

6.5

Plug-in Hybrid Electric Cars

63,048

34,591

3.8

Light Goods Vehicles (LGVs)

6,208

3,625

2.1

Battery Electric LGVs

5,650

3,419

1.9

-16

2,358

1,706

2.0

317

121

162

6.1

Other

1,123

2,254

-50

2.5

Total

181,090

80,578

125

8.4

Motorcycles Buses & coaches

The majority of ULEVs licensed at the end of 2020 were either BEVs (50%) or PHEVs (45%). (Department for Transport,2021)

"There were more new Battery Electric cars registered for the first time in 2020 than in all previous years combined"

2019

Heavy Goods Vehicles (HGV)

Ultra Low Emission Vehicle (ULEV): Recognising advances in technology from 2021, the UK Government expects to define an ULEV as a car or van that emit less than 50 g/km CO2, rather than the current 75 g/km. In addition, vehicles would only be considered ULEVs/PiVs in these statistics if they could reasonably be expected to make significant use of the public highway as a mode of transport. This would result in the removal of mobility scooters (class 3 invalid carriages), forklifts, agricultural vehicles, road maintenance vehicles, construction vehicles, and vehicles of an unknown structure.

Range extended Other 2% electric

2020

New ULEV Registrations

Battery Electric

50%

"At the end of 2020, there were 432 thousand ultra low emission vehicles in the UK. There were 60% more licensed Ultra Low Emission Vehicles (ULEVs) at the end of 2020 compared to the previous year"

Licensed ULEVs by Fuel Type Plug-in Hybrid Electric

45%

ULEVs registered for the first time 200,000

Battery Electric Vehicle (BEV) Plug-in Hybrid Electric Vehicle (PHEV)

160,000 Despite the fall in new registrations, ULEVs saw large year on year UK increases in 2020 from June onwards (see Table 2), ranging from +89% to +250% each month. Consequently, the overall proportion of new vehicle registrations that were ULEVs in the UK also increased significantly during the course of 2020. The proportion grew from 5.1% in January 2020, up to 17.8% in December 2020. The overall proportion for 2020 was 8.4%, compared to 2.7% in 2019. (Department for Transport,2021)

Other Fuel Types 120,000 80,000 40,000 0

(Department for Transport,2021)

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Proportion (%)

2012

2013

2014

2015

2016

2017

2018

2019

2020

(Department for Transport,2021)

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Road to zero The road to zero strategy by the UK government

The Road to Zero Strategy considers the importance of the choice of fuel options in meeting the UKs carbon and air quality objectives and advice presented here is drawn from the strategy. The Government remains committed to policies and incentives that are technology neutral. But it is essential that we understand the relative environmental performance of different technologies in the real world.

Infrastructure

Drivers of Change

Hydrogen fuel cell electric vehicles also have zero tailpipe emissions. Like battery electric vehicles, their ‘well-to-wheel’ (the overall assessment of climate change impact) greenhouse gas emissions depend on the method of energy production. Although the environmental performance of range extended, plug-in, and non-plug-in hybrids depends on their use and zero emission range, these vehicles are amongst the cleanest vehicles on the market and can bring significant environmental benefits. They are an important way of helping motorists make the switch to a different way of powering their vehicles.

ROAD TO

ZERO STRATEGY Vehicle supply & demand

Battery electric vehicles are highly energy efficient and have zero tailpipe emissions. The assessment made in the Road to Zero Strategy, shows that battery electric vehicles also have substantially lower greenhouse gas emissions than conventional vehicles, even when taking into account the electricity source and the electricity used for battery production. Assuming the current UK energy mix, battery electric vehicles produce the lowest greenhouse gas emissions of all the energy sources and fuels assessed, irrespective of vehicle type and operation. As electricity generation is de-carbonised the vehicles being driven by electricity are effectively de-carbonised as well.

Leadership at all levels

Drivers of change: considers the factors that are driving the global transition to zero emission vehicles. Vehicle supply & demand: to reduce the emissions from the vehicles on roads today, to drive uptake of the cleanest new cars and vans, to set a clear pathway to reduce emissions from HGVs and progress to zero emission solutions, all to put the UK in the forefront of the design & manufacturing of zero emission vehicles Infrastructure: to develop one of the best electrical vehicle infrastructure networks Leadership at all levels: to support ultra low emission vehicles in the devolved administrations (Scotland, Wales and Northern Island)

Petrol cars and vans tend to have higher greenhouse gas emissions than their diesel equivalents but significantly lower emissions of NOx. Real world particulate emissions from petrol cars and vans are variable, with some petrol cars and vans (particularly those with direct injection engines) emitting higher levels of particulates than diesel equivalents. We expect this to be addressed by the introduction of the Real Driving Emission (RDE) standards. Cleaner diesel cars and vans can play an important part in reducing CO2 emissions from road transport during the transition to zero emission vehicles whilst meeting ever more stringent air quality standards. RDE has seen a significant reduction in real-world NOx emissions in diesel vehicles meeting those requirements and brings them much closer to petrol equivalents in terms of NOx emissions. Liquid petroleum gas (LPG) vehicles have similar well-to-wheel greenhouse gas emissions as diesel equivalents but generally have lower air pollutant emissions. Although a niche market, LPG vehicles may be a good current alternative to diesel in urban driving conditions.

(GovUK, 2018)

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Case Studies The road to zero strategy by the UK government 26

Case study — ‘Opportunities for regeneration’

In examining how city agglomeration and compactness assist in reducing emissions for transportation, 3 case studies were studied, which each of them had steps that had achieved lower carbon emissions and better connectivity, they include Oslo in Norway, Strasburg in Germany and Wolverhampton in the UK.

& M6( N)

Queen’s Square: before (left) and after (right) renovation

RESULTS

A449 STAF FO

RD, M 54

WOLVERHAMPTON CITY CENTRE

LV E ST RHA AT M IO P N TO

IELD

S ST

PRIN

REET

BUS STATION

CES

ON ST

INGT

DARL

ET TRE

REET

LIC

N EE

TRE

A454

RIA

STR

EET

ORTH

IDGN

1, BR

RD A4

TELFO

VIC

METRO TERMINUS

CLEVE

LAND

STREET

LEGEND A4

Pedestrian streets

BIL

Metro line

O N

Traffic Access

W .B

RO M

Parking

RING ROAD

Cordon on roads within the ring road

81 500

Bus only lanes

69 750

-11 750 (-14.42 %)

Source: Wolverhampton City Council. A 459

One way streets Bus only lanes

After Phase 4 in which all through traffic was removed from the city centre, the data

suggestswere that the traffic absent from the inner ring road had fallen by - Private Cars gradually phased outcordon from(which yellow areas from 14 % between 1990 before the closure and 1996) appears not to have transferred to 1990-1996 the outer ring road, where the cordon count went down by just over 1 %. Some of traffic appears to have ‘evaporated’. - 14.42% the reduction of cars within ring road, 1.17% reduction on Effects of road closure on trafficoutside flows cordons on approach road - Buses, taxis, pedestrians, cyclists were allowed into the city centre 24-hour, two-way November November 1996 Total - Priority bus lanes linking city 1990 centre to outskirts change traffic flows before Phase 4 after Phase 4 - Service vehicles were allowed restricted access Cordon on 900 220 300 -2 600 (-1.17 %) - Ample parking provided222along periphery approach roads - Public Transport (buses, trams) close to centre were promoted instead outside ring road

Promotion of public transport

new road layout and any initial congestion was short-lived.

DLE

500m

Wolverhampton City With each phase, after anCentre initial ‘adjustment’ period, drivers soon became used to the IELD & LICHFIELD WEDNESF A4124

- 8.8% reduction of ghg from 2012-2017 - Reached target emission of 74gCO2e/passenger/km (EU’s target is 95g/km) - 96% of electricity from Norway’s grid comes from hydropower - Incentives given to EVs (free tolls and parking, access to bus lanes etc.) - Developed infrastructure to support rise of EVs - Investing in charging points - Some charging points are free - ~10% of cars on Norwegian roads are EVs in 2020 (UK has 0.6%)

Traffic flows

Car free zones

TO M54 & STAFFO RD

Oslo, Norway

A 44 9

Electrification of vehicle fleet

Strasbourg City Centre, Germany - Two new tramlines were built on where highways were - Prioritising public transport - Through traffic access to centre removed - Trams were largely successful - Led to 17% reduction in traffic - Significant shift away from private car 1989, 72.5% of all trips made with car, 11% by public transport 1999, 60% made with car, 30% public transport Traffic Access

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Pedestrianised Areas

Tramline A

Tramline B

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(Harding, 2020)

Summary This chapter explained carbon emissions and their equivalences as well as examining the emissions by the transportation sector, where the de-carbonisation of the sector had been extremely slow, amounting to a growing percentage of all emissions in the UK. It also looked at the different factors that affect the emissions and efforts trying to lower the emissions. Detail breakdown of the different categories and calculations of embodied and running also showed majority of emissions are by passenger cars and in worst cases 154 times the emission compared to some public transport. While BEVs are gaining popularity, carrying FCEVs along, it is still

528

Scale of Improvement a niche market compared to the petrol and diesel market, even though BEVs are 3.5 times more fuel efficient and hydrogen FCEV being 7.5 times. The transition to electric not only reduce the carbon emitted and create a cleaner future but also save money for consumers. Yet as the system dynamics map showed it is more than shear will but is related to how our cities had been built and those yet to be built. The layout and design of cities need to change - prioritise active and public transport more and increase their densities, which will create a positive feedback loop that ultimately increase connectivity with better public transport services, ultimately achieving

The road to a clean future

Manchester City Council's 2038 zero carbon goals. However, 2020 had been a year with results. For the first time electric vehicles sales are higher than other ICE vehicles, signalling a change in consumer choice, and manufactures would have to catch up The vastness that the system extends to requires everyone to be do their part in order to decrease the sector's emissions and drive everyone to a cleaner future and together we can make a change.

GLOBAL EFFORT GOVERNMENT

Financial budget & allocation to improving infrastructure Providing grants Charging varying tax band according to vehicular emissions

PRIVATE COMPANIES

Super credit

THE ROLE OF DESIGNERS

spatial strategies and solutions within the transport network system

USER LEVEL

using low carbon emitting cars reducing dependency on private vehicles walking more using public transport

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Statista. 2015. Average speed in Great Britain, by road and vehicle type | Statista. [online] Available at: <https://www.statista.com/ statistics/303443/average-speed-on-different-roads-in-great-britain-by-vehicle-type/> [Accessed 12 October 2021]. Statista. 2021. Global transport CO2 emissions breakdown 2020 | Statista. [online] Available at: <https://www.statista.com/ statistics/1185535/transport-carbon-dioxide-emissions-breakdown/> [Accessed 16 November 2021]. Statista. 2021. UK: transport CO2 emissions 1990-2020 | Statista. [online] Available at: <https://www.statista.com/statistics/311522/ transport-co2-emissions-in-the-uk/> [Accessed 16 November 2021]. Statista. 2021. UK: GHG emissions shares by sector 2019 | Statista. [online] Available at: <https://www.statista.com/ statistics/1227356/uk-greenhouse-gas-emissions-shares-by-sector/> [Accessed 16 November 2021]. Statista. 2021. UK: transport emission shares by source 2019 | Statista. [online] Available at: <https://www.statista.com/ statistics/1233533/transport-ghg-emissions-sources-united-kingdom-uk/> [Accessed 16 November 2021]. The European Parliament. (1996) Directive 1999/96/EC: laws of the Member States relating to measures to be taken against the emission of gaseous and particulate pollutants from compression ignition engines for use in vehicles, and the emission of gaseous pollutants from positive ignition engines fuelled with natural gas or liquefied petroleum gas for use in vehicles. The European Union. [Online] [Accessed 10 October 2021) https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:31999L0096&from= EN The European Parliament. (1998) Directive 98/69/EC: Measures to be taken against air pollution by emissions from motor vehicles and amending Council Directive. The European Union. [Online] [Accessed 10 October 2021) https://eur-lex.europa.eu/LexUriServ/ LexUriServ.do?uri=CONSLEG:1998L0069:19981228:EN:PDF The European Parliament. (2007) Regulation EC 715/2007: Approval of motor vehicles with respect to emissions from light passenger and commercial vehicles (Euro 5 and Euro 6) and on access to vehicle repair and maintenance information. The European Union. [Online] [Accessed 10 October 2021) https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32007R0715&from=en The European Parliament. (2009) Regulation EC 595/2009: Approval of motor vehicles and engines with respect to emissions from heavy duty vehicles (Euro VI) and on access to vehicle repair and maintenance information. The European Union. [Online] [Accessed 10 October 2021) https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32009R0595&from=en Theicct.org. 2014. [online] Available at: <https://theicct.org/sites/default/files/publications/ICCTupdate_EU-95gram_jan2014.pdf> [Accessed 10 October 2021]. Theicct.org. 2021. [online] Available at: <https://theicct.org/sites/default/files/publications/ICCTpolicyupdate11_ EUemissions_2011.pdf> [Accessed 16 November 2021]. Tiseo, I., 2021. UK: GHG emissions shares by sector 2019 | Statista. [online] Statista. Available at: <https://www.statista.com/ statistics/1227356/uk-greenhouse-gas-emissions-shares-by-sector/> [Accessed 5 November 2021]. Tiseo, I., 2021. UK: GHG emissions 1990-2020 | Statista. [online] Statista. Available at: <https://www.statista.com/ statistics/326902/greenhouse-gas-emissions-in-the-united-kingdom-uk/> [Accessed 5 November 2021]. Tiseo, I., 2021. UK: transport sector GHG emissions 1990-2019 | Statista. [online] Statista. Available at: <https://www.statista.com/ statistics/710459/uk-transport-sector-emissions/> [Accessed 6 November 2021]. Tiseo, I., 2021. UK: transport CO2 emissions 1990-2020 | Statista. [online] Statista. Available at: <https://www.statista.com/ statistics/311522/transport-co2-emissions-in-the-uk/> [Accessed 4 November 2021]. Tiseo, I., 2021. Global transport CO2 emissions breakdown 2020 | Statista. [online] Statista. Available at: <https://www.statista. com/statistics/1185535/transport-carbon-dioxide-emissions-breakdown/> [Accessed 3 November 2021] Tiseo, I., 2021. UK: transport emission shares by source 2019 | Statista. [online] Statista. Available at: <https://www.statista.com/ statistics/1233533/transport-ghg-emissions-sources-united-kingdom-uk/> [Accessed 1 November 2021].

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Vehicle Certification Agency. 2021. Vehicle Certification Agency. [online] Available at: <https://www.vehicle-certification-agency.gov. uk/fuel-consumption-co2/fuel-consumption-guide/cars-and-fuel-options/> [Accessed 16 November 2021]. Vehicle Certification Agency. 2021. Vehicle Certification Agency. [online] Available at: <https://www.vehicle-certification-agency.gov. uk/fuel-consumption-co2/fuel-consumption-guide/cars-and-fuel-options/#topic-title> [Accessed 1 November 2021]. Vehicle-certification-agency.gov.uk. 2021. [online] Available at: <https://www.vehicle-certification-agency.gov.uk/wp-content/ uploads/2021/03/New-Car-and-Van-CO2-Regulations-Guidance-2020.pdf> [Accessed 4 October 2021]. WLTPfacts.eu. 2021. From NEDC to WLTP: what will change? - WLTPfacts.eu. [online] Available at: <https://www.wltpfacts.eu/fromnedc-to-wltp-change/> [Accessed 8 November 2021]. (Zap-Map), A., 2021. How many charge points are there in the UK 2021. [online] Zap-Map. Available at: <https://www.zap-map. com/statistics/> [Accessed 30 September 2021].

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As an overall, buildings contribute significantly to carbon emissions through a variety of processes ranging from material processing and manufacture through construction methods, systems, and use.. It’s critical to consider where these huge impacts occur so that they can be reduced to allow Manchester to meets its net-zero goals.

INTRODUCTION

BUILDINGS

CONTRIBUTION CONTRIBUTION TOWARDS ZERO CARBON

Overview of Considerations

SECTION ONE

SECTION TWO

SECTION THREE

Material Considerations

Construction Process

Operational Use

CONCLUSION

Summary and Comparison

Hannah Byrom, Thomas Cooper, Yasamin Salimi

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Introduction Overview of research areas This chapter investigates the total impact of buildings, including material use and construction methods, as well as energy use. To assess the overall carbon footprint and the procedures that are the most intensive, it is essential to look at every part of the process. The diagram below gives an overview of all the areas and considerations that will be covered in this section with each of the yellow boxes highlighting the separate sections.

CONSTRUCTION

INPUT BUILDING DESIGN PARAMETERS

EMBODIED ENERGY (EE) CONSTRUCTION ENERGY (CE) 1. On-site construction installation, welding, fabrication and assembly. 2. Construction operational energy (machinery). TRANSPORTATION ENERGY (TE) 1. Transportation of materials and labour. 2. Site construction processes. MATERIAL ENERGY (ME) 1. Material extraction, production, packaging. 2. Material transport to site / manufacturing factory.

MATERIALS

OPERATION AND MAINTENANCE

DEMOLITION

OPERATIONAL ENERGY (EE) 1. Lighting 2. Heating and Cooling 3. Operating MEP

1. Renovation, retrofitting 2. Additional and partial demolition

Reuse, recycle, and disposal

1. Transport of building materials 2. Transport of labour 3. On-site renovation

Transportation of materials to storage

1. Material extraction, and production 2. Material transport to manufacturer

Extraction, production

OUTPUT ENERGY (EE + OE)

CONSTRUCTION PROCESS

DESIGN

PERFORMANCE

“all new buildings in the city from 2023 should be zero carbon” 538

Introduction

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Scale of Improvement What are the contributing factors to emissions? IRON AND STEEL (7.2%)

This page outlines the scale and impact that building construction, materials and energy use of buildings altogether make up a huge portion of total carbon emissions. The boxes outline all areas which relate to the building sector.

NON-FERROUS METALS (0.7%)

Diagram adapted from (Our World in Data, 2020.)

IND

US TRI AL

AGRICULTURAL (11.2%)

PETROCHEMICAL USE (3.6%)

EN ER

Y US

LAND USE

OTHER INDUSTRY (12.7%)

18.4%

DEFORESTATION (3.6%) MATERIAL WASTE PROCESS AND END OF LIFE

.2 24

CROP BURNING (5.5%)

LANDFILL (1.9%)

WASTE

WATERWASTE (1.3%)

3.2%

CHEMICAL USE (2.2%)

INDUSTRIAL

5.2%

CEMENT (3%)

ENERGY USE

FISHING (1.7%)

N (1

6.2%)

73.2%

PO RTA TIO

FUGITIVE EMISSIONS (5.8%)

ROAD TRANSPORT

TR AN S

INCLUDING MATERIAL (11.9%)

FUEL COMBUSTION (7.8%)

AVIATION (1.9%)

SHIPPING (1.7%)

%) 5 . 7 (1 I N GS

ENE RGY U SE IN BUILD COMMERCIAL SECTOR 6.6%)

RAIL (0.7%) HEATING

RESIDENTIAL SECTOR 10.9%) LIGHTING VENTILATION

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Wider Systems Map What are the building factors involved? This wider systems map takes into account all the main areas/themes and considerations when looking at carbon emissions in the built environment. There are also links to other topics and chapters which have an impact and link in with the content of this chapter.

Bio-based Materials

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Low-Carbon Scaling Energy consumption in the UK

1. ESTABLISH NET ZERO CARBON SCOPE

1.1

Net-zero carbon - construction

1.2

Net-zero carbon - operation energy

2. REDUCING CONSTRUCTION IMPACTS

1970s

2010s

2020s

2050s

OPERATIONAL ENERGY

2.1

To achieve carbon reduction, construction projects will undergo a whole-life carbon assessment.

2.2

Carbon emissions from materials and building stages are monitored and offset at the point of practical completion.

3. REDUCE OPERATIONAL ENERGY USE

EMBODIED ENERGY

There has been a lot of research done over the years on the need for net-zero methods to be implemented.In the past, references to zero-carbon buildings frequently only included operational energy. There have been more conversations recently about embodied energy. This can be seen in the graph above, where the quantity of operational energy within buildings has decreased dramatically since the 1970s, but there is predicted to be a rise in embodied energy in the future. The problem is that embodied energy is rarely evaluated or taken into account, despite the fact that it is critical to the UK’s ability to achieve its net-zero carbon objective. Embodied carbon has recently received more attention, with an emphasis on the construction phase, when there is a greater understanding and range of data. From looking into the UBCGB Framework, it can be seen that the key components of a net zero carbon building should focus on: • Reducing the demand for energy through optimisation of building fabrics and materials. • Reducing the embodied carbon mostly through the material selection and construction phases. • Measuring the building performance whilst in use to establish whether the building and fabric is performing as efficiently as initially thought.

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Material Process

• Looking into low carbon energy alternative sources. The summary of the current framework is shown on the right. The 5th point is an area of consideration since in the zero carbon scope, offsetting as shown would be more of a final resort provinding the other areas do not allow for compromise. It is important that there is clarification on the scope for achieving net-zero in buildings. The main areas are as follows: • Net Zero Carbon in operation: This takes into account the total emissions from general building activity in use and types of energy used on a daily basis. • Net Zero Carbon in construction: This considers the carbon emissions (especially embodied carbon) associated with the construction and transportation processes. • Net Zero Carbon Whole Life: This is important as it takes into account all the emissions that come from building construction, operation, maintainance, repair, and material replacement or end of life. (Manchester Climate Change Partnership, n.d.)

3.1

Prioritize reductions in energy demand and consumption.

3.2

In-use energy consumption should be calculated and publically disclosed on an annual basis.

4. INCREASE RENEWABLE ENERGY SUPPLY

4.1

On-site renewable energy source to be considered and prioritised.

4.2

Additionality should be demonstrated for off-site renewables.

5. OFFSET ANY REMAINING CARBON

5.1

Any remaining carbon should be offset using an offsetting framework.

5.2

The amount of offsets used should be publically disclosed.

Diagram adapted from (The Government Workplace Design Guide, n.d.)

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EMBODIED CARBON

Cycle & Process

Manufacturing, transportation, construction & end of life

Zero-carbon issues & factors

Embodied carbon means all the CO2 emitted in producing materials. It is estimated from the energy used to extract and transport raw materials as well as emissions from manufacturing processes. The embodied carbon of a building can include all the emissions from the construction materials, the building process, all the fixtures and fittings inside as well as from deconstructing and disposing of it at the end of it’s lifetime. The main types that should be considered when referring to materials are Upfront Carbon, Embodied Carbon and End of Life Carbon. As well as understanding the types of carbon, it is important to understand the reasons for the high levels of carbon in the building industry (Giesekam et al., 2016). The below summarises the current views and reasonings:

1 | INSTITUTIONAL & HABITUAL • More established practives may have preferred specifications for material selection. • Including more focused training means familiar materials will be utilised more. • Lack of time in the design process may result in materials being chosen due to familiarity rather than research into low-carbon alternatives. • Lack of knowledge of low carbon suppliers sometimes due to lack of promotion. • Material transport and co-ordination lacking compared to more established companies. • Material selection may not always be down to the discretion of the designer.

2 | ECONOMIC • Generally, low carbon materials may have a higher cost than known common materials. • Cost association with material training and time used for research into alternatives.

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• Money invested in known manufacturers in which a good relationship and reliability is already established. • May be greater financial risk with unknown materials and products. • Small low-carbon producers find it difficult to compete with more etablish companies.

3 | TECHNICAL & PERFORMANCE • Lower abundance of design guidance, standards and details with low carbon alternatives. • Lack of material performance data and comparative case studies. • Contractor may lack skills or ability to use and implement certain low carbon alternatives due to lack of practical experience. • Lower local availability of alternatives may add to carbon emissions in transporting them making them less beneficial. • Lower/less insurance that material will perform as expected for the amount of time it is expected to last.

END OF LIFE CARBON

UPFRONT CARBON

Emission from deconstruction, demolition and disposal

Extraction & manufacture of building materials and products

OCCUPATIONAL EMBODIED CARBON

OPERATIONAL CARBON

Building maintenance and refurbishment

Energy for operating building (services such as heating, lighting and cooling).

Diagram: Types of carbon across whole building lifecycle

4 | KNOWLEDGE & PERCEPTION • Limited knowledge of low-carbon alternatives. • Negative perception or lack of trust in alternatives by both designers/practitioners and clients. • Risk associated with specifiying unknown alternatives rather than known materials from known manufacturers. • Issue with material sourcing. • Low-carbon material selection and processes may seem low priority in the given time frame over other things such as the design itself.

MATERIAL QUANTITY ESTIMATE

EMBODIED CARBON PER MATERIAL (EDPs)

BUILDING EMBODIED CARBON (EC) ESTIMATE

Diagram: Embodied carbon process adapted from (Zero Waste Scot., n.d.)

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“not reduce, minimise or avoid waste, but eliminate the very concept, by design” Image from (EDGE, n.d.)

Building regulations and policies mostly address operational carbon emissions, leaving embodied carbon as a large unsolved issue. The materials, construction, destruction, and recycling of buildings, all of which generate significant carbon emissions, are not addressed by the majority of existing energy consumption and carbon emissions-related standards in the buildings and construction sector. To achieve sustainability, circular economic principles must become an integral part of the built environment. Disassembly design, product recovery management, life cycle evaluation, deconstruction, flexibility, dematerialization, and closed materials

Image Top: EDGE Olympic Building, Netherlands

loops are among some of the principles. Whole Lifecycle Carbon (WLC) emissions are those that occur from the construction and use of a building over the course of its entire life. These include embodied carbon emissions from raw material extraction, manufacturing and transporting building materials, construction, as well as emissions from maintenance, repair, and replacement, as well as deconstruction, demolition, and material disposal. Another concept that could be used is the notion of “materials passports,” which is an innovative method for tracking and documenting the full circular perspective of materials, systems, and products by providing

stakeholders with accurate information on various features associated with the circular design of products and their composition. Certain projects, such as the EDGE Olympic Building, have already begun to address building through the circular economy concept, which reuse and repurpose materials and can also be disassembled for future use. Other structures, such as the ICE house, make use of limited materials that can be easily disassembled and reassembled, reducing end-of-life waste and waste that occurs in using bespoke building elements. (Plastic Smart Cities, n.d.)

Image Bottom: ICEhouse, Davos, Switzerland

1 Building embraces circular zero-waste design principles and smart digital infrastructure to optimize energy use. 2 50% of the materials used were recycled from the original building, including the natural stone taken from the façade, repurposed for use as flooring. 3 The top two floors are constructed from wood, which can be disassembled relatively easily for future reuse. (ICEhouse™, n.d.)

Image from (ICEhouse™, n.d.)

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construction

43% in use

end of life

2 | CARBON COMPARISON • Overview: Compare design options for carbon, with proposals and set improvements against baseline. + Pros: Most cost-effective way. Design options must be understood and viable before implementing. - Cons: Comparing does not mean the most efficient will be built. Formality. • Refer to: Examples shown in BREEAM UK & LEED v4

REPLACE

REFURBISHMENT

REUSE / RECOVERY AND RECYCLING

REPAIR

WASTE PROCESS

TRANSPORT

DE-CONSTRUCTION

MAINTENANCE

CONSTRUCTION & INSTALLATION

USE

TRANSPORT

20%

23%

GRAVE

END OF LIFE

50%

COMPLETE

Overview: Calculate the embodied carbon of a project and report. Pros: This is a simple process which helps build skills and knowledge Cons: Design may not improve if reporting is the only measure taken Refer to: Examples shown in BREEAM International

BEYOND LIFE CYCLE

END OF LIFE

B6 OPERATIONAL ENERGY & B7 OPERATIONAL WATER

SITE

• + •

GATE

1 | CARBON REPORTING

MANUFACTURE

product processing

TRANSPORT

50%

There are several methods to consider to reduce the amount of carbon within the designing and building process. These examples are mostly things to consider throughout the design process fo evaluate, calculate and set targets for carbon figures which should be met to satisfy the net-zero goal.

RAW MATERIAL SUPPLY

Considerations, methods and workflow

CRADLE

Life Cycle

USE

DISPOSAL

CONSTRUCTION PROCESS

PRODUCT

Diagram of Life Cycle Assessment (‘Life Cycle Assessment explained: an introduction to building LCA,’ 2020)

BUILDING GEOMETRY

MATERIAL VOLUME

LIFECYCLE OF EMBODIED (kgCO2)

3 | CARBON RATING

BUILDING CONTEXT

TRANSPORTATION

YEARLY EMBODIED CARBON

• Overview: Evaluate carbon performance and scale from best to worst. Fixed scale or methodology. + Pros: Incremental performance improvements to incentivise better rating. - Cons: Less ambitious projects will not improve as poor ratings are allowed. • Examples shown in DGNB

BUILDING QUALITY

BIOGENIC STORAGE

TRANSPORT CARBON

STRUCTURAL STRATEGY

CARBON ABSORPSION

BIOGENIC / CARBON STORAGE

MATERIAL SELECTION

MAINTENANCE LIFECYCLE

MAINTENANCE

4 | CARBON CAP • + •

Overview: Calculate embodied carbon to show it does not exceed CO2e target. Pros: Projects have to reach the set threshold. Cons: Setting cap at level that reduces carbon yet cost-effective is difficult. Refer to: Examples shown in MPG

5 | DECARBONISATION • + •

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Overview: Carbon reduced to a minimum and buying offsets. Pros: Charging projects with higher carbon emissions helps as incentive to reduce, Cons: Aim for complete decarbonisation needs widely applied incentives. Refer to: Examples shown in Living Building Challenge.

Workflow Process

KEY

Diagram: Embodied carbon process adapted from (Zero Waste Scot., n.d.)

USER INPUT

CARBON CALCULATIONS

EMBODIED CARBON OUTPUT

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Material Type

The embodied carbon in varies depending on the mix (amount of aggregates etc. and also whether substitutes are used for the cement.

Understanding carbon emissions

Embodied carbon means all the CO2 emitted in producing materials. It’s estimated from the energy used to extract and transport raw materials as well as emissions from manufacturing processes. The embodied carbon of a building can include all the emissions from the construction materials, the building process, all the fixtures and fittings inside as well as from deconstructing and disposing of it at the end of it’s lifetime. When we discuss the impact of material consumption, according to BREEAM, the construction industry accounts for around 55% with buildings which contributes to the overall 50% of total CO2 emissions. Further to this, it is important to understand that 55% of industrial emissions globally are a result of material processing and five key materials specifically: • • • •

Steel (25%) Cement (19%) Paper (4%) Plastic and Aluminium (3%)

Of all the above materials, the building industry is a primary consumer of cement and is responsible for consuming approximately 26% of aluminum, 50% of steel, and 25% of plastic. Paper is harder to measure due to it being a by-product.

1 | CONCRETE As already shows, the environmental impact comes from cement which makes up 10% of the mix but is responsible for 80-90% of concrete’s embodied carbon. Portland Limestone Cement is better as it displaces some cement and reduce GWP.. It is a heat intensive process with fossil fuels, generating CO2..

2 | INSULATION High embodied carbon due to the hydrofluorocarbon (HFC) blowing agents. Consider using insulation materials that naturally sequester carbon, such as cellulose, wood fibre.

3 | TIMBER

Thermal mass can help with the overall operational carbon benefits.

Material Process

(Ganguli, 2020) (Randi Pokladnik, 2020)

Long-lasting and recyclable

Post-tensioned slabs and volided concrete are better and reduce concrete needed in system.

CONCRETE PROS & CONS

Demand fluctuates a lot with timber where it is allocated almost as quickly as it is being produced and imported into the UK. This is because there are never any indications on whether the demand with suddenly increase or decrease.

TIMBER Needs to be sustainably sourced.

4 | STEEL Best is electric arc furnaces, low-carbon electricity grid, high-recycled, such as wide-flange members and channels. 90% carbon emissions from steel production and only 10% from transportation and fabrication. Basic oxygen furnace or electric arc furnace. Oxygen furnace is more emissions-intensive, burning coal and natural gas (Sergent, 2019) (NBS, n.d.)

Reuse and potential reassembly of components and steel buildings is easier.

STEEL With crosslaminated timber (CLT) larger spans can be achieved.

Long lasting, durable and highly recyclable.

The embodied carbon of recycled steel is still around 50% of that of new steel.

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No alternatives are available for some applications such as building foundations.

Normally a high tonnage and embided carbon per building..

Lower emissions compared to concrete and steel most of the time but not always . Locks in captured carbon for a long time. Wood specified should come from sustainably managed forests not primary growth. Discussions around wildfires, climate change and is foresty sector plays role in decreasing or increasing wildfire risk.

Post-tensioned slabs and volided concrete are better and reduce concrete needed in system.

High strength to weight ratio allows for less material and less concrete in foundations.

CLT has higher embodied carbon than regular timber and cannot be used in taller buildings due to low strength-toweight.

Discussions around wildfires, climate change and is foresty sector plays role in decreasing or increasing wildfire risk.

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Material Process Raw to product quantities (Life cycle)

STEEL The diagram on the left summarises the breakdown of raw material to produce 1 ton of steel and the right diagram summarises the end-of-life for materials and by-products.

1t Steel

64% Steel product

3.8%

57.1%

28.6%

1.6 Tons of Iron Ore

14.3%

0.8 Tons of Coal

59.6%

Re-use

Recycle

2.7%

32.9% By-products such as cement, asphalt, zinc, iron, electricity, heating, plastics and paint.

Waste

0.6%

Disposal

0.4 Tons of Limestone

CONCRETE The diagram on the left summarises the breakdown of raw material to produce 1m3 of concrete and the right diagram summarises the end-of-life for materials and by-products.

1m3 Concrete

60.9%

27.4%

Concrete product

52.2%

12.2%

30.4% 10.9% 6.5%

1200kg Aggregates

700kg Sand

250kg Cement

Recycle

45.7%

Downcycle

Aggregates for Landscaping

Deposit onto Land

4.6% 0.2% Technological material

Waste Deposit Reclamation

0.1%

Disposal

150l Water

TIMBER The diagram on the left summarises the breakdown of the amount of trees needed to produce a certain number of planks and the right diagram summarises the end-of-life for materials and by-products.

Tree at 0.5m Diameter and 10ft Tall

54%

25%

Timber product

0.35m3 554

Material Process

Plank: 3.9 x 0.225 x 0.038m = 0.033345

Re-use

5.4%

Downcycle

Recycle

Diverted for Energy Generation

31.3% Disposal

16%

By-products Repurposed

Waste Disposal

Waste Recycled

3.2%

Incineration

= 10.5 planks (NCWRP, n.d.) (Greenspec, n.d.) (Reclaimed construction materials, n.d.)

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Material Process Raw to product quantities (Life cycle)

CONCRETE

CO2

1. Process of mining and extracting aggregates needed for cement mixture such as limestone, silica and gypsum. 2. Cement manufacturing is the most energy and carbon intensive part of the process where temperatures of up to 2000 degrees celcius is needed in cement production. 3. Cement mixing process includes combining cement with water and aggregates. 4. Concrete is then transported onto site for use or to another place for fabrication of panels. 5. Concrete holds a high amount of embodied carbon, but is generally a robust material. 6. At its end of lifem concrete can be ground up to make aggregate for new concrete. If exposed to air it will absorb CO2.

CO2

1. RAW MATERIAL MINING

2. CEMENT MANUFACTURING

3. MIXING CONCRETE

CO2

4. TRANSIT / LOGISTICS

CO2

5. USE

CO2

6. END OF LIFE

(Imperial College London, n.d.)

OXYGEN FURNACE (BOF)

STEEL

ELECTRIC ARC FURNACE

CO2

1. Process of mining raw material or procuring recycled steel. 2. In manufacturing either a BOF is used which produced more CO2 using iron ore, and limestone ot an EAF which uses more recycled steel and has 50% less emissions.BOF makes up 71% of global steel production whereas EAF make up 29%. 3. Transportation of manufactured steel to site. 4. Steel mainly used for building structure and some panelling. 5. Most steel memeber are recycled at the end of the buildings life cycle.

CO2

1. MINE RAW OR PROCURE STEEL

2. MANUFACTURING ON EITHER AN EAF OR A BOF FURNACE

3. TRANSIT / LOGISTICS

4. USE

5. END OF LIFE

4. USE

5. END OF LIFE

(‘Steel Production,’ n.d.)

KILN DRIED WITH FOSSIL FUELS

TIMBER 1. CO2 is stored and released during the logging and milling process through stumps left behind and bark residue. 2. Timber is then either kiln dried with fossil fuels or residues. Many mills kiln dry with residue from milling process called biogenic carbon. 3. Timber is then transported onsite for use. 4. May need to be replaced more often than steel or concrete during building lifecycle. 5. At end of life, most wood products are disposed of and any stored co2 is release through decomposition or incineration. Very few can be reused and recycled.

KILN DRIED WITH RESIDUES

CO2 STORED

CO2

LOGGING AND SOIL

CO2

1. LOG RAW OR PROCURE RECYCLED WOOD

2. MANUFACTURING WOOD PRODUCTS

3. TRANSIT / LOGISTICS

(Forest Learning, n.d.)

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Diagram adapted from (‘Carbon Smart Materials Palette, n.d.)

Material Process

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Material Supply Supply chain process and waste

MINING & LOGGING

PROCESSING

RAW MATERIAL

TRANSPORT

KILN/ FURNACE

TRANSPORT

DRYING/ COOLING

FINISHES

MANUFACTURE

LOGISTICS / DISTRIBUTION

TRANSPORT ONTO SITE

END PRODUCT

Diagram on Material Supply Chains (‘Carbon Smart Materials Palette, n.d.)

It is important to understand the general supply chain process that materials undergo and identify where the most waste occurs so that the issue can be mitigated and so that any waste that does occur can be dealt with in an appropriate way.

unacceptably unacceptable as the world strives to discover a more sustainable and ecologically friendly way to manufacture and create goods. As much as 30% of all building materials delivered to a typical construction site can end up as waste.

The issues that arise from excessive material production and the accumulation of building waste are numerous; however, one major issue with transporting waste to landfills is that we are running out of capacity to store it. There’s also the financial issue: the more waste a project generates – including the expense of purchasing resources that aren’t used – the lower the profit margin. Some organisations tackle this by factoring in waste from the start; however, this is a self-defeating strategy that is becoming increasingly

Many ideas come to mind while discussing the answer to building waste; nevertheless, the solution can be simplified down to a single concept: material efficiency. A focus on material efficiency will, by definition, reduce the quantity of waste created in any given project. And the sooner you start focusing on it, the more money you can save. As an added “bonus,” early deployment of a material efficiency-focused approach has a lower environmental impact and reduces natural resource depletion.

(Designing Buildings, n.d.) (Homebuilding, n.d.)

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Material Process

PREVENTION

Less material during design and manufacture (DfMA strategy). Keep durable and non-hazerdous products for future re-use.

PREPARE FOR USE

Check, clean, repair, refurbish, repairing and reusing whole and spare parts.

RECYCLING

Using waste to turn into new useable product or composting it.

RECOVERY

Energy recovery and materials from waste.

DISPOSAL

Landfill and incineration of waste products with no energy recovery.

Diagram on Waste Processes adapted from (SteelConstruction.info, n.d.) (NBS, n.d.)

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Developing and producing Orb (Organic Refuse Biocompound), a series of carbon-neutral building materials

Future of Materials Looking at biofabrication and repurposing of materials

Examples include pulp and paper, wood, and leathers along with crop based materials such as flax, hemp, bamboo and coconut fibres.

Evolution is continually refining and optimizing solutions to overcome life's continuous challenges.

Mycelium prototypes (the thin strands of filaments that are a part of fungi) as a natural insulation material Biobased materials are about closing and creating short loops. While fossil fuels have long cyclical lifecycles

An insulating clay plaster with enhanced moisture buffering properties.

(Construction 21 International, n.d.) (MaterialDistrict, n.d.) (Writer, 2020)

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Material Process

Sustainablyharvested lumber and wool insulation sourced from regenerativelygrazed herds.

Biohm is a UK-based startup

Material Sourcing

Material Growth Insulating lime render utilising a high proportion of hemp shiv as aggregate;

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Bio-economy by producing products using renewable biological resources

BIOFABRICATION AND REPURPOSING

Material Process Natural is not always better

Material Structure Low-impact panels

ISOBIO board – bio-based insulation hemp bound board with a bio-based binder

"Biological house," is where the majority of materials used for construction are sustainably sourced

e.g Pine lumber that is sourced from clear cut forests, treated with dangerous wood preservatives

Need standard quality requirements for biobased products such as strength, flexibility, permeability and organic degradability?

Pragmatic material in reduction of the carbon, energy emissions, thermal comfort with less energy consumption for the functioning of the buildings to replace the conventional materials

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Material Performance 6.0

Clay Bricks

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Solid Timber Door

ECCs (kgCO2/kgz

CEMENT

CONCRETE

MASONRY

STEEL

STEEL (RECYCLED)

TIMBER

Maxima

0.196

0.033

0.074

1.340

0.160

0.200

Minima

1.050

0.295

0.550

1.670

0.720

536%

894%

743%

284%

1044%

360%

Table above adapted from (Zero Waste Scot., n.d.)

MATERIAL PERFORMANCE (U-VALUE PERFORMANCE M2k/W)

5.0

Galvanised Iron Sheet and PVC

Single Glazing Polyurethane Flexible Foam

4.0

Polyurethane Rigid Foam

3.0 Standard Double Glazing

MOST EFFICIENT

Insitu piling

2.0

Standard UK Brick

Aluminium

Timber CLT

1.0

0.0

Mineral Wool Fibre Rock Wool

Plasterboard

0.0

Plastic

Autoclaved Lightweight Concrete

Concrete Slab Calcium Silicate Board

0.5

Low-e Double Glazing

Steel

Metal Facade Cladding Precast Concrete

Fibreglass Insulation Low-e Triple Concrete Blocks Glazing Fibre Cement Panels, Uncoated

1.0

1.5

Zinc

Glass Mineral Wool

2.0

2.5

KEY

EMBODIED CARBON (kgCO2/kg) STEEL TIMBER CONCRETE /MASONRY GLAZING

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INSULATION

Material Process

OTHER

Waterproofing Membrane (Roof )

Copper

SIP Panels

Fibreglass Panels

Mineral Wool Fibre

Rock Wool

3.0

Extruded Polystyrene

3.5

Foam Glass

4.0

4.5

5.0

This shows the way in which material in terms of u-value and thermal performance can be campared against the embodied carbon or energy. The best performing materials in this case can be taken as the ones with the lowest u-value as this means the material is a better insulator and requires less energy to maintain comfortable conditions as well as having a low embodied carbon value. Please note that this table plots only general approximate figures to demostrate this which will vary depending on specific types.

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Process mapping for products

Comparison

Caps and boundaries established

Relating factors and themes

Product data requested from factories

17.5% energy in use

16.2% transportation

24.2% industrial energy

Information from (Our World in Data, 2020.)

From all the research chapters in this booklet, when looking deeper into the material process, there are a few which also contribute considerable and so are highlighted on the diagram shown on the right. This diagram highlights the overall process which would occur when choosing materials for a design project up to testing the embodied energy of each and coming to an overall final embodied energy figure in which alternatives would then be tested through the same process to find the optimum product for the project. As mentioned previously, processes such as energy in use and industrial energy already account for around 41% of the total emissions. This includes the manufacturing process of materials and also depends on the quanitity of materials that are needed. These are both highlighed as integral parts of the process on the right. Another aspect is the air pollution /emissions that are associated in the manufacturing of the product which is one of the most emission intensive processes. Depending on the material type and the specific process, some can be more carbon intensive than others. For example, the manufacturing of steel can be done by electric arc furnace or by an oxygen furnace which can increase emissions by up to 50% more.

The final additional consideration is the transportation process. This chapter goes into depth on the material processes but not so much on the transportation emissions that are involved within this, which would cross over more and be mentioned in the next section and within the transportation chapter. Depending on the material type, some may need to be shipped or transported from a long distance. A good example is timber which would mostly be imported rather than locally sourced, although a seemingly more carbon friendly material due to the carbon storage capacity, the transportation process can make this almost negligible when the whole process is considered. Also depending on the amount of this material needed, more trips may need to be made or with more transportation vehicles which adds to the overall embodied carbon in the process of that material. It is important to consider all of these aspects together to weigh up the option on which materials will result in an overall lower emission factor.

Data for material performance over time

Materials chosen and purchased

Manufacturer energy consumption in factory (emissions for product)

Allocation of emissions and resources for making product

Transportation of materials (type, distance)

Review other alternatives for lower carbon value

Transportation of materials

Calculating embodied carbon

Calculating carbon footprint of product

Review of total figures

Information from (De Wolf et al., 2017)

Embodied carbon of end product

KEY

Other Themes

Considering quantity of products needed

TRANSPORT / MOBILITY

AIR POLLUTION

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Material Process

ENERGY: GENERATION, CONSUMPTION, EMISSION, STORAGE

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Context

Zero-Emission Construction Opportunities for achieving net zero carbon buildings Share lessons learnt in achieving net zero carbon in construction. Communicate operational requirements.

Verify net zero achievements and outcomes.

Balance between the investors & occupier of homes and their net zero goals. Communicate the impact on occupier comfort of homes.

RIBA Stages of Work

Programme extra time to test net zero strategies.

Identify the positive outcomes from design changes.

Maximise reuse, building with timber and design within an iterative process.

BARRIERS

OPPORTUNITIES

Achieving net zero carbon buildings requires reconceptualisting the current process of delivery of buildings.

Changes to the design & construction processes to create net zero carbon buildings.

Changes in the supply of building materials may take a long time. Smaller businesses may find it difficult to compete with larger companies on net zero targets due to cost.

Designers can make use of new technolgolocal advances which can speed up construction. They can also design using new better performing materials.

Compressed construction timelines can lead to poor performance outcomes. Finanacial penalites of not meeting deadlines lead to carbon inefficient outcomes.

Airtight construction, heat pump systems, modular building components. Simplifying building designs to include low carbon opportunities.

Developers only just beginning to implement low carbon strategies so this can be challenging.

Developers can strengthen their value chain: communicate net zero design ambitions, contractors & suppliers to consider low carbon solutions first.

Procure materials, workers, machinery with net zero. Diagram adapted from: (UKGBC, 2021). Diagram adapted from: (UKGBC, 2021).

Here are some of the main factors which are big problem areas and produce a lot of emissions within the material production, the construction process and the building in use.

Traditional On-Site Construction

Design engineering

Permits & Approvals

Construct building on site Internal, external & groundworks

Civil works & foundations

Modular Construction

A local Manchester based construction company - Willmott Dixon have created a list of targets they are doing to help cut carbon emissions: • • •

Design engineering

Permits & Approvals Civil works & foundations

Diagram: Comparison between during of traditional construction methods vs. modular construction methods adapted from: (Salama, 2018).

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Construction

Construct building components in factory

Image bottom: ENERGY SOURCES FOR THE UK ANNUAL & ALL TIME AVERAGES

Civil works & foundations

• Time saved in comparison to traditional

Modular, prefabricated elements or DfMA processes can reduce construction time by 30-50%

• •

Construction sites fossil fuel free Reduce site cabin electricity usage by 65% Reduce absolute milage by 65% and have 100% electric fleet of vehicles. Transparent carbon emissions reporting externally supported by clear internal actions and performance reporting. Offices will be zero-carbon in operation They will generate renewable energy for their own use. (Wilmott Dixon, 2021).

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Image Top: (Wolstenhome, 2021)

CONSTRUCTION PROCESS

The internet of things includes advancing the possibilities of smart construction through:

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Construction

The aims are to create less disruption and waste, enable more reuse and greater resource efficiency which in turn is a key enabler of the circular economy in the built environment (Walters, 2019). BIM - Improves the working progress through project life cycle by: • Improved field productivity • Reduced sourcing costs • Reduced security incidents • Construction progress tracking (Sun and Park, 2020).

TRANSPORTATION Another area within the construction process which should be considered when trying to reduce the embodied energy of a building is the transportation of materials to site. Within this section the areas considered should be: 1) Distance to site - some materials are imported from different countries or transported long journeys. The benefit of this could be for more sustainable materials to be used that are not available in the immediate vaccinity of the construction site.

2) The vehicles being used to transport the materials - these should all be electric in a bid to reduce carbon emissions to zero. MACHINERY Through the use of electric machinery on site this can reduce the amount of emissions produced by machinery to zero. This is only possible if the source of the energy being used to charge or power the machinery is renewable. Electric generators are now available to use to power machinery and site cabins when required.

TRANSPORT

Cyber-physical modelling Offsite manufacturing Onsite assembly Handling/logistics Waste minimisation Real time monitoring/control Health & saftey Information management Energy management Remote inspection The use of dogital twins (A digital twin is a digital replica of a physical entity. The Centre for Digital Built Britain is currently running the National Digital Twin programme which is working towards building a digital twin of the UK.

SITE

Smart construction involves the augmentation of construction resources such as machinery, devices, components & people with digital technologies for transforming the construction industry.

• • • • • • • • • •

CONSTRUCTION & INSTALLATION

Digitised construction is the use & application of digital tools to improve the process of delivering & operating the built environment in the hope that it will make delivery, operation & renewal of the built environment safer, more efficient & more collaborative.

COMPLETION

Transportation & Machinery

Digitised Construction

Image: EMISSION % IN BUILDING LIFE CYCLE DURING TRASNPORTATION OF MATERIALS & CONSTRUCTION & INSTALLATIONS

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Methods Life-Cycle Assessment Sections of the life-cycle assessment we have carried out

EMBODIED CARBON Manufacturing, transportation, construction & end of life

END OF LIFE CARBON

UPFRONT CARBON

Emission from deconstruction, demolition and disposal

Extraction & manufacture of building materials and products

Image Top: Source: (Ellingsen, 2021)

OCCUPATIONAL EMBODIED CARBON

Case Study The first zero-emission urban construction site was: ‘Olav Vs gate’ in Oslo, Norway. The project involed converting a busy road in the city centre into a pedestrianised area. The construction company used all electric machinery (Keegan, 2021). Through using all electric equipment there was a reduction in emissions of 99% compared to if they had used diesel powered equipment. The benefit Norway has in the zero emission construction industry is they have 98% renewable comapred to a very low UK renewable energy sources. The UK infact imports renewable energy from Norway and several other countries (Ellingsen, 2021).

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Construction

One way to power the machinery is by using an ‘Ampd Entertainer’ - a compact battery system instead of a diesel generator - this reduces carbon emissions by 85%. As well as electric machinery, when this was not possible they utilised a wheel loader for heavy duty operations which was powered by hydrotreated vegetable oil (HVO diesel) as a fossil fuel alternative (Keegan, 2021). It is possible to apply the same methods of reducing emissions to zero on construction sites, however with the context of Manchester this would be dependant on the availability of electric machinery, the scale of the project and the source of energy used in construction.

Building maintenance and refurbishment

FINDINGS:

OPERATIONAL CARBON Energy for operating building (services such as heating, lighting and cooling).

Diagram: Carbon production across the whole building life cycle

1 Using all electric machinery on-site where possible 2 Use renewable energy sources to power electric machinery 3 Use electric powered generators to power site offices 4 Use HVO diesel where electric vehicles not possible

Life-cyle Assessment (LCA) is a scientific methodology used to calculate the environmental impacts, including carbon footprint, of a product, service, or process. It can support the efforts of green building professionals to build more sustainable buildings. For the materials it is possible to carry out an Environmental Product Declarations which means calculating the LCA of a product, from the extraction of the material through manufacture, use, replace or repair to disposal and recycling.

You can measure the impacts of potential building sites, use it for land sales competitions, contests, refurbishments, or city planning, perform the Life Cycle Assessment of an Infrastructure project, or achieve credits for green building certification schemes like LEED and BREEAM. Building Life Cycle Costing is the analysis of the costs of your building over its whole life cycle and can help to assess long-term savings and costs (Schwartz et al., 2016).

Who uses Life-cycle assessment: • DGNB and DGNB DK both include Life Cycle Assessment credits • BREEAM has included Building Life Cycle Analysis in all their schemes. • LEED has the MRc1 Building life-cycle impact reduction • Whole-Building Life-Cycle Assessment credit (Schwartz et al., 2016)

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Calculations Calculating emissions produced in transportation & machinery on site

Inputs for machinery, energy sources & transportation of materials to site

M ac h in e ry use d o n s it e - El e c t ric

INPUT

CARBON CALCULATIONS

DISTANCE TRAVELLED TO SITE

AMOUNT OF TRUCKS

MATERIAL VOLUME

TRANSPORTATION OF MATERIALS TO SITE

NO. OF DAYS ON SITE

METHOD OF CONSTRUCTION

NO. OF DAYS ON SITE

EMISSIONS PRODUCED

CO2 EMISSIONS PRODUCED IN THE TRANSPORTION OF MATERIALS TO SITE (Kg CO2)

EMISSIONS FROM DIESEL POWERED EQUIPMENT USED ON SITE

CO2 EMISSIONS PRODUCED IN CONSTRUCTION PROCESS (kgCO2)

EMISSIONS FROM ELECTRIC POWERED EQUIPMENT USED ON SITE

CO2 EMISSIONS PRODUCED IN CONSTRUCTION PROCESS (kgCO2)

METHOD OF CONSTRUCTION

Typ e

B a tter y Ca p a city

E nergy source used

Hours used

Excavator Typ e

15kWh B a tter y Ca p a city

Input from Energy source table E nergy source used

Input per project Hours used

Pile RigExcavator Liebherr drill rig

15kWh 265kWh

Input from Energy source table

Input per project

Pile Access Rig Liebherr drill rig platform

265kWh 24kW

Input from Energy source table

Input per project

Dumper Access platform

10kWh 24kW

Input from Energy source table

Input per project

Crawler crane Dumper

255kWh 10kWh

Input from Energy source table

Input per project

Electric power pack Crawler crane

46kWhr 255kWh

Input from Energy source table

Input per project

Electricpower truck mixer Electric pack

340kWh 46kWhr

Input from Energy source table

Input per project

Electric truck mixer

340kWh

Input from Energy source table

(JCB, 2021) Input per project

So u r ce o f ener g y Coal Natural Source of egas nergy Renewable Coalsources Any other sources Natural gas

Kg o f CO2 E m issio ns p er g W h 0.408 En erg y so urc e s 0.215 Kg o f CO2 E m issio ns p er g W h 0 0.408 Amount 0.215

% of energy used Input per project %Input of enper ergproject y used Input per project Input per project Input per per project project Input

Input per project Input per project P a ylo a d k g 18100 P a13000 ylo a d k g 13000 18100 Amount from input 13000

Renewable sources Any other sources Typ e Truck mixer Open/flat Typ e truck Covered truck Truck mixer Any other trucks Open/flat truck

KEY

Covered truck Any other trucks Typ e Excavator Pile TypRig e Access platform Excavator Dumper Pile Rig Crane Access platform Truck mixer Dumper Crane Truck mixer

M ac h i n e ry us e d o n s i t e - El e c t ri c

En erg y so urc e s

Mac hAmount in ery used on site - Fuelled F uel ta nk ca p a city Litres Mac h in290 ery used on site - Fuelled F uel ta nk 2000 ca p a city Litres 2000 290 Amount 2000

2000 13000 t e - F uefrom lledinput Amount M ac h in e ry use d o n s iAmount F uel ta nk ca p a city Litres F uel used p er hour ( Litres) 345 Mac h in ery used on sit e - F u45.42 elled 870 F uel ta nk ca p a city Litres F uel used 23.84 p er hour ( Litres) 132 11.44 345 45.42 480 9.06 870 23.84 400 10.23 132 11.44 290 13 480 9.06 400 10.23 290 13

No. of hours used Input per project NInput o. of per houproject rs used Input per project Input per project Input per per project project Input Input per project Input per project Input per project Input per project Input per project Input per project

USER INPUT CARBON CALCULATIONS

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EMBODIED CARBON OUTPUT

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Embodied Energy Calculation Emissions calculation of embodied energy produced during fabrication of materials and the construction process of a building.

INPUT

CALCULATIONS

AMOUNT OF STRUCTURAL MATERIALS REQUIRED FOR BUILDING SIZE

OUTPUT

AMOUNT OF TRUCKS REQUIRED TO TRANSPORT THE MATERIALS TO SITE

TOTAL

TOTALS COMBINED

CO2 EMISSIONS PRODUCED IN THE TRANSPORTION OF MATERIALS TO SITE (Kg CO2)

FLOOR AREA (m)

METHOD OF CONSTRUCTION NUMBER OF FLOORS

TYPE OF MACHINERY REQUIRED FOR THE PHASES OF CONSTRUCTION

AMOUNT OF MACHINERY USED IN CONSTRUCTION PROCESS

CO2 EMISSIONS PRODUCED IN CONSTRUCTION PROCESS (kgCO2)

AMOUNT OF MATERIALS REQUIRED FOR BUILDING SIZE

CO2 EMISSIONS PRODUCED IN THE MANUFACTURE OF MATERIALS (Kg CO2)

TOTAL EMBODIED ENERGY AMOUNT IN CO2 (KG)

STRUCTURAL GRID SIZE

MATERIALS USED

STRUCTURE INTERNAL WALLS INSULATION WINDOWS DOORS FLOOR ROOF

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Construction

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Embodied Energy Sankey Inputs and parameters needed for total embodied carbon This sankey diagram helps to summarise the main process and considerations in calulating the total embodied energy of a building. It goes from material breakdown by density to construction and transportation processes to them give a final figure for each element.

PARAMETERS Input of Material Type, Density and Embodied Carbon/m3

Processes and Typology Inputs

Total Areas and Process Emissions Outputs Material Span

Door Embodied Carbon (M3)

Beams

Transport Type (CO2) Machinery Type (CO2)

Roof

Windows

Material Size

Material Area

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Transportation Process

Embodied Carbon (M3)

External Wall

Typology Attributes

Quantity

Insulation

Construction Process

Fuel Type (CO2)

Construction

Door Columns Beams Roof

Windows

Floor

Internal Wall

Total Embodied Carbon (kgCO2)

Foundation

Columns

Embodied Carbon per Element

Internal Wall

Total Embodied Carbon (kgCO2)

External Wall

Insulation

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Performance Factors Whether a new building or renovation, these factors apply. Image Top: (Framework, n.d.)

Energy Use as Electricity

Natural Gas

Factors Affecting Energy Use

Operational Energy Solutions

Use - Artificial lighting. Reduce -Maximum natural lighting Energy efficient lights Motion sensored lights

Use - Cooking Reduce -Electric cooking Microwave cooking

Design factors to reduce air escaping the building: Insulation efficiency in all areas Roof,Walls,Windows Thermal bridging Facade envelope air tightness

Passive Design Stratergies. Passivehaus standard design Envelope tightness/Insulation Solar gain Stack effect Passive ventilation

Use - Heating (Radiator, Floor heating). Reduce -Maximise passive solar gain Heat recovery ventilation Efficient insulation Tight envelope/Minimal thermal bridging Use - Regrigeration. Reduce -Energy supply by Renewable Energy sources (RES) Efficient technology. Use - Other (TV's, Computers ect.). Reduce -Supply by RES. More energy efficient

Use - Space heating. Reduce -Electric space heating through RES Passive heating as stated previosuly

(Energy in buildings, n.d.)

Energy In

Behaviour of building users such as overusing heating

Variables

Energy Reduction Strategies More energy efficient technologies Energy Production/Renewable Onsite Solar Biomass for electricity/space heating Offsite Wind, Hydro, Geothermal. (1 Angel Square / 3D Reid, 2013)

(Energy in buildings, n.d.)

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Zero Carbon Buildings Performance

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UK Energy Use Breakdown

Typology Operation Energy Use Energy use and change per typology

40%

of annual global carbon emissions are from the built environment

(‘Why The Building Sector? – Architecture 2030,’ n.d.)

28%

of the 40% is from building operations

(‘Why The Building Sector? – Architecture 2030,’ n.d.)

50%

of the UK’s energy use by sector is by buildings energy use (Energy in buildings, n.d.)

With building’s operational energy use contributing to 28% of building’s global carbon emissions annually and half of the UK’s annual energy need (‘Why The Building Sector? – Architecture 2030,’ n.d.) it is clearly a vital area to focus on reducing to improve carbon emissions. Breaking this down further reveals different building sectors have varying energy uses and therefore need different solutions and attention. Other than changing from non renewable energy sources to renewable ones, making buildings more efficient in their function is the best approach. Identifying the largest problems helps approach these solutions. Of building types, service sector typologies such as offices schools and shops typically use more energy (Energy in buildings, n.d.). There are many reasons such as the difference in use having shop and office lights on constantly throughout the day. As well as their operating hours potentially being longer than homes as people are either at home or using service buildings and therefore its energy instead of their homes. This shows that a focus on reducing lighting especially during the day could be efficient. Such as utilising passive natural lighting as a

way to reduce artificial lighting. The residential sector also varies in sub typology from types of houses, to apartments at low, mid and high rise levels. Each with varying effects on operational energy use. However they naturally use less energy per meter squared than the service sector (Energy in buildings, n.d.) which is good but should and can still be improved on. In this case heating is a large factor that accounts for over 70% of energy used. Unfortunately many old homes in the UK have poor insulation requiring more energy to constantly heat the home when hot air escapes easily. By simply improving insulation and air tightness, the heating needed is reduced significantly.

Energy used PetaJoules (PJ)

UK Building Energy Use Breakdown

Energy used KiloWatts per meter squared (KW/m2)

All buildings overlap in other energy use areas that could partially be improved with more efficient technology with energy use designed for. Whilst heating and lighting for example of large contributors can be designed against to reduce their effect. Whilst being unique in each typology, site and brief, some rules to reduce will be constant whilst others will need adapting per case.

UK Building Sector Energy Use Breakdown

Energy used KiloWatts per meter squared (KW/m2)

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Zero Carbon Buildings Performance

Graphs adapted from (Energy in buildings, n.d.) and (Benchmarking commercial energy use per square foot | Twinview | Insights, n.d.)

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Context: Manchester Climate policy aims and current carbon acheivements

Image Top: (One Angel Square, n.d.)

Manchester City Council

aim to be carbon zero by 2038 and want to do more to reduce Co2 emissions. They say buildings should be adapted to the changed climate and increase their climate resilience (What we are doing: Projects | Zero Carbon Manchester | Manchester City Council, n.d.). Their influence is through policy and funding powers in Manchester. Aiming for a 50% reduction in building emissions by 2025 by example of a change in how buildings a heated. More ambitiously asking for buildings after 2023 to be carbon zero in performance but not completely in its construction process, without being able to offset carbon tax.

Manchester’s Climate

is not ideal for the use of solar energy gain in panels or passive heating. The cost to efficiency ratio will need to be tested. Yet over time it could be beneficial to have as small reductions contribute. As well as Biomass onsite renewable energy that does not

have the ideal climate. Whilst better insulation and envelope tightness will be more efficient at decreasing energy use in heating in cold climates. As well as energy using systems improved efficiency.

Co op Headquarters passive system diagram

Current Developments

are not very carbon zero or energy efficient with profit and user comfort coming first. With little current council policy encouraging low energy design developers focus on their aims. Co op Headquarters in Manchester is however one of a few exceptions. It is BREEAM excellent standard using passive strategies such as hot air stack effect and dual skin facade to control overheating and solar gain (1 Angel Square / 3D Reid, 2013). Showing how Manchester projects can be improved with passive strategies incorporated.

Double skin facade solar shade

Fresh air Earth duct cools air

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Zero Carbon Buildings Performance

Warm air

Passive ventilation stack effect

Cool air

Diagram adapted from (1 Angel Square / 3D Reid, 2013)

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Methods to Quantitative Data

Converting energy uses into calculable figures

Energy Use

Equipment

Energy use Watts

Affecting Factors

Affecting Factors Data

Lighting (Lux)

LED lightbulbs CFL lightbulbs Incadescent lightbulbs

6-7W (500Lux) 8-12W (500Lux) 40W (500Lux)

Natural daylight reduces need for artificial lighting. Motion detection switch off.

Wall to glazing ratio ideally: Around 30% reduces artificial lighting needed.

Heating (Watts)

Radiator Underfloor

950-1750W

Better insulation and envelope tightness with passive solar heat.

Wall U value: 0.18 W/(m²K) Solar gain reduces heating.

(U-values., n.d.) (admin, 2016)

Ventilation

Mechanical extract vent (MEV) Mechanical ventilation with heat recovery (MVHR) Passive stack ventilation (PSV)

SFP 0.19-0.45W/m3/h

Fan efficiency

Passive ventilation

(Mayer, 2007) (‘MVHR unit energy efficiency | Blog | CVC Direct Ltd,’ 2019) (MVHR Heat Recovery Ventilation MVHR, n.d.)

Other

TV's PC's ect.

Percentage of total household energy use per person

Renewable energy source RES

(Thomas, n.d.) (How much energy does my home use?, 2015) (B. I.D, n.d.) (‘Comparing LED vs CFL vs Incandescent Light Bulbs,’ 2017)

(U-values., n.d.) (admin, 2016)

Lighting Lightbulbs light are measured in lumens Energy is measured in Lux = 1 lumen per square meter (Dalsgaard, n.d.) (‘Comparing LED vs CFL vs Incandescent Light Bulbs,’ 2017)

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Heating Calculation Approach Using building parameters for annual heating energy

Interior temp: 21 degrees

Exterior temp: 10 degrees

Roof

=11 degree days

Window

Energy Use - Heating Parameters - U values of wall, floor, windows/doors, roof - Areas of each - Number of air changes per hour - Annual degree days (temperature differance internal/external) - 0.33 Energy needed to heat 1 m3 of air 1 kelvin Total fabric heat loss rate = (Sum of U values x fabric areas ...) x Change in Temp Floor = 25m2 x U 0.25 = 6.25 Wall = 50m2 x U 0.35 = 17.5 Win/Door = 5m2 x U 2 = 10 Roof = 25m2 x U 0.16 = 4 sum = 37.5 WK-1 Ventilation heat loss = 0.33 x Number of air changes per hour x Volume x Change in Temp 0.33 x 0.5 (More if required for wellness) x 125 = 20.625WK-1 Whole house heat loss coefficient = Total fabric + Ventilation loss 37.5 + 20.625 = 58.375WK-1

Wall Door Floor

Heat leaving a building through different materials/ areas at different amounts.

Internal temperature 20c, External -2c, Change in temp = 22K Estimated heating = Whole house heat loss x Change in temp 22 x 58.375 = 1284.25W House annual heating energy=Heat loss coefficient xDegree daysx24(hours) /1000 (KW) (58.375 x 2070.2 x 24) / 1000 = 2900.35KWh annualy Changes dependant on solar gain / ratio of glazing+orientation

(Energy in buildings, n.d.)

Month Jan Feb Mar Apr 586

Zero Carbon Buildings Performance

Degree Days 319.5 286.5 274.8 197.6

May Jun Jul Aug Sep

110.8 48.4 27 30.3 69.9

Oct Nov Dec Total

155.5 252.2 297.7 2070.2

(Heating & Cooling Degree Days – Free Worldwide Data Calculation, n.d.)

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Lighting Ventilation Calculation Approach

Energy Use - Lighting

From building inputs to annual energy use

Parameters - Lightbulb type (varies watts used for the same lux) - Lux required for space (300 house average) - Hours artificial light is required (Calculated monthly) One lightbulb gives 500 lux

One 1m2 residential square needs 300 lux

Lux = 1 lumen per square meter Residential average need 300 lux = 300 Lumens per m2

Lightbulbs quantity = (Room Length x Width x Lux required for space)/Lightbulb type lux (5 x 5 x 300)/500 = 12.5 lights Total energy used by lights (Watts) = Lightbulb quantity x lightbulb watts 12.5 x 6 = 75W Annual energy used (Watt Hours) = total light energy x annual hours used (1701hours) 75 x 1701 (less if bad natural lighting) = 127575Wh/1000 = 127.5KWh

(Thomas, n.d.) (How much energy does my home use?, 2015) (B. I.D, n.d.) (Energy in buildings, n.d.)

rs e t e

ete

Energy Use - Ventilation Lux = 1 lumen per square meter Residential average need 300 lux = 300 Lumens per m2

5 meters

Parameters - Specific fan power (efficiency of fan power to air movement), 0.3W/m3/hr - Number of air changes per hour, 0.5 per hour - Space volume of air, 125m3

125m cubed air

ete

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Zero Carbon Buildings Performance

rs ete

Fan efficiency= Volume per Watt per Hour

Specific fan power x Volume per hour x 24 (to days) x 365 (to annualy)= annual energy 0.3 x (125x0.5) x 24 x 365 / 1000 = 164.25KWh annually

(Energy in buildings, n.d.) (‘MVHR unit energy efficiency | Blog | CVC Direct Ltd,’ 2019) (MVHR Heat Recovery Ventilation MVHR, n.d.)

Month Jan Feb Mar Apr

Light Hours 248 168 155 90

May Jun Jul Aug Sep

62 60 62 93 120

Oct Nov Dec Total

155 240 248 1701

(Sunrise and sunset in the United Kingdom, n.d.)

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Calculation Overview Steps to calculate total energy use from a parametric building model Simplified calculations from generative building models to annual operational energy use by adding its heating, lighting ventilation and electronics. Each area uses the previous formulas to get accurate results and subtracts any passive or energy saving strategies used without the use of plugins or unkown processes.

INPUT

CALCULATIONS

OFFSET/REDUCTION

OUTPUT

TOTALS

TOTAL BUILDING FABRIC HEAT LOSS AND TEMPERATURE DIFFERENCE

HEATING SOLAR GAIN INSULATION QUALITY VENTILATION HEAT RECOVERY ENVELOPE TIGHTNESS

HEATING ENERGY REQUIRED TO KEEP SPACE COMFORTABLE

ANNUAL HEATING ENERGY USE

LIGHTING REQUIRED FOR BUILDING SIZE AND WATTS USED

NATURAL LIGHTING LIGHT MOTION SENSORS

ENERGY USED TO LIGHT THE HOUSE DAILY LIGHT BULBS REQUIRED

ANNUAL LIGHTING ENERGY USE

TOTALS COMBINED

FLOOR AREA (m)

ROOF AREA (m)

EXTERNAL WALL AREA (m)

TOTAL ANNUAL ENERGY USE PER BUILDING KW/H/M2

WINDOW AREA (m)

MATERIAL U VALUES

VENTILATION OF AIR CHANGES PER HOUR TO VOLUME OF BUILDING

NATURAL VENTILATION STACK EFFECT

ENERGY USED TO MAKE AIR CHANGES PER DAY

ANNUAL VENTILATION ENERGY USE

ELECTRONICS USED PER PERSON + NUMBER OF PEOPLE IN BUILDING

MORE EFFICIENT TECHNOLOGY RENEWABLE ENERGY

ENERGY USED BY TOTAL PEOPLE

ELECTRONIC ENERGY USE

GLAZING SHGC

SOLAR GAIN MONTHLY

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Annual Energy Use Sankey Inputs and parameters needed for total energy use Sankey diagram displays the quantitive contributions each component of the buildings operational energy has. Showcasing that the air changes loose the most heat resulting in heating energy needed.

Main Areas of Energy Use

794

Roof fabric heat loss Door fabric heat loss

20,383

Annual building energy use

Lighting energy use Ventilation energy use

Solar gain

6,990

1,242

Floor fabric heat loss

201

Lighing required

Heating energy use

Passive ventilation

303

5,520

Wall fabric heat loss

1,314 2,449

7,936

Window fabric heat loss

2,449

Total Energy Use (KW)

Air changes per hour

23,913

9,511

Input of Material Type and U value to get Fabric Loss

Passive energy saved - Reduced from energy use

Calculations adapted from (Energy in buildings, n.d.) but made into own script and results.

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System Dynamics Map What are the contributing factors to emissions? This is a systems dynamics map which helps to summarise the main cause and effect impacts that different process have on each other. These can either be positive or negative impacts with direct or indirect effects on other areas. Heating Lighting Ventilation Existing Homes

Building Energy Use

Waste Heat Recovery

Renewables

Onsite Site Storage

+ New Homes

Machinery Fuel

Total CO2 Emissions

Net Growth

R R

Climate Change

+ Construction Process Emissions

Population

Environmentally Friendly Alternatives

+ +

Population Control

Material Use/ Demand -

Bio-based Materials

Use of Electric Machinery

- Energy Related Emissions

Gap

Transportation

Building Construction Demand

Building Performance

Total CO2 Emissions

GDP

Blend Additives

Energy Consumption

R +

Cement Demand

Vehicular Pollution

Less Carbon Intensive

+ Gas

Pressure to Reduce + Emissions

Energy Efficiency

Electrical Grid

Less Intensive Method of Construction

Calcination

R + +

Cement Production

Clinker Consumption

Raw Material

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Summary ISSUES - Where Carbon Emissions are Produced

Here are some of the main factors which are big • Some materials are imported problem areas and produce a lot of emissions within the material production, the construction 4) CONSTRUCTION PROCESS: • More traditional methods of process and the building in use. construction take a lot longer on site. • The use of diesel or fossil fuel 1) ENERGY PRODUCTION: • Mining & burning coal machinery on site. • Use of non-renewable energy sources • 8.7% imported by pipe 5) BUILDINGS IN USE: • 61% of UK's fuel to produce • Not enough glazing on the South • Orientation of buildings not efficient. electricity imported • The use of less efficient ventilation systems. • Clean water wasted within 2) MATERIAL PRODUCTION: • Kiln & calcination uses a lot of fossil fuels buildings. • Steel - smelting & form • The use of ireidescent lightbulbs manufacturing • Timber kiln drying process 6) END OF BUILDING LIFE: • Waste of materials not being 3) MATERIAL TRANSPORTATION TO SITE: recycled. • Some are transported long • Demolition of buildings. distances

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Building Contribution Summary

SUGGESTIONS - Where Carbon Emissions could be Reduced

Here are potential solutions to ways in which 4) CONSTRUCTION PROCESS: carbon emissions can be reduced through the • Modular construction reduces energy whole building life-cycle. consumption by up to 65%. • Use of electric machinery on site 1) ENERGY PRODUCTION: • Power the electric machinery with renewable Only use renewable energy sources: energy sources • Source from hydroelectricity • From wind turbines 5) BUILDINGS IN USE: • Solar pv panels • Use of efficient MVHR systems, more efficient 2) MATERIAL PRODUCTION: • • Reducing CO2 emissions is to mix blast furnace slag with water ormix fly ash with cement to reduce the CO2 emissions by • 40% • The use of bio-based materials • 3) MATERIAL TRANSPORTATION TO SITE: • Transport using electric vehicles • Source materials locally where possible

than MEV Orientation of buildings to achieve best solar gain - glazing on south side - shelter with nearby trees. Use of grey water systems to save clean water Use LED lightbulbs

6) END OF BUILDING LIFE: • Recycle materials • Repurpose buildings

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Bibliography MATERIAL PROCESS Best ways to cut carbon emissions from the cement industry explored | Imperial News | Imperial College London (n.d.) Imperial News. engineering. [Online] [Accessed on 16th November 2021] https://www.imperial.ac.uk/ news/221654/best-ways-carbon-emissions-from-cement/.

NCWRP (n.d.) ‘Waste wood in the UK.’ Community Wood Recycling. [Online] [Accessed on 16th November 2021] https://communitywoodrecycling.org.uk/what-we-do/waste-wood-in-the-uk/.

‘Carbon Smart Materials Palette – Actions for reducing embodied carbon at your fingertips’ (n.d.). [Online] [Accessed on 16th November 2021] https://materialspalette.org/.

Randi Pokladnik (2020) ‘The Pros and Cons of Building Materials and Their Carbon Footprints.’ Ohio Valley Environmental Coalition. 15th April. [Online] [Accessed on 16th November 2021] https://ohvec.org/the-pros-andcons-of-building-materials-and-their-carbon-footprints/.

Cities, P. S. (n.d.) EXCESS MATERIALS EXCHANGE. Plastic Smart Cities. [Online] [Accessed on 16th November 2021] https://plasticsmartcities.org/products/excess-materials-exchange.

Reclaimed construction materials (n.d.). [Online] [Accessed on 16th November 2021] http://www.greenspec. co.uk/building-design/reclaimed-materials/.

Construction Materials Shortage: Material Prices Rise Again | Homebuilding (n.d.). [Online] [Accessed on 16th November 2021] https://www.homebuilding.co.uk/news/construction-materials-shortage.

Recycling explained - Designing Buildings (n.d.). [Online] [Accessed on 16th November 2021] https://www. designingbuildings.co.uk/wiki/Recycling_explained#Conservation_of_raw_materials.

Construction waste and materials efficiency (n.d.) NBS. [Online] [Accessed on 16th November 2021] https:// www.thenbs.com/knowledge/construction-waste-and-materials-efficiency.

Scotl, G. I. T. Z. W., Scotl, L. R. in, Floor, G. and Office: 01786 433 930, M. H. F. W. S. F. 1QZ (n.d.) Zero Waste Scotland. Zero Waste Scotland. [Online] [Accessed on 16th November 2021] https://www.zerowastescotland.org.uk/.

De Wolf, C., Pomponi, F. and Moncaster, A. (2017) ‘Measuring embodied carbon dioxide equivalent of buildings: A review and critique of current industry practice.’ Energy and Buildings, 140, April, pp. 68–80.

Sector by sector: where do global greenhouse gas emissions come from? (n.d.) Our World in Data. [Online] [Accessed on 16th November 2021] https://ourworldindata.org/ghg-emissions-by-sector.

EDGE | Case study (n.d.) EDGE. [Online] [Accessed on 16th November 2021] https://edge.tech/case-study. Find a Resource (n.d.). [Online] [Accessed on 16th November 2021] https://forestlearning.edu.au/find-a-resource. html.

‘Steel Production’ (n.d.) American Iron and Steel Institute. [Online] [Accessed on 16th November 2021] https:// www.steel.org/steel-technology/steel-production/.

Forestry Sustainability School Activities, Lesson Plans & Resources | Forest Learning (n.d.). [Online] [Accessed on 16th November 2021] https://forestlearning.edu.au/.

Sustainable construction legislation, regulation and drivers - SteelConstruction.info (n.d.). [Online] [Accessed on 16th November 2021] https://www.steelconstruction.info/Sustainable_construction_legislation,_regulation_ and_drivers.

Ganguli, S. (2020) ‘Building Materials List : Uses | Advantages | Disadvantages.’ Building Materials. 24th July. [Online] [Accessed on 16th November 2021] https://civilwale.com/types-of-building-materials/.

The Government Workplace Design Guide (n.d.) GOV.UK. [Online] [Accessed on 16th November 2021] https:// www.gov.uk/government/publications/the-government-workplace-design-guide.

Giesekam, J., Barrett, J. R. and Taylor, P. (2016) ‘Construction sector views on low carbon building materials.’ Building Research & Information, 44(4) pp. 423–444. Growing Biobased Building Materials - MaterialDistrict (n.d.). [Online] [Accessed on 16th November 2021] https://materialdistrict.com/article/growing-biobased-building-materials/.

CONSTRUCTION PROCESS

Hammerson Positive Places - Welcome to Positive Places (n.d.). [Online] [Accessed on 16th November 2021] http://sustainability.hammerson.com/.

1 Angel Square / 3D Reid (2013) ArchDaily. [Online] [Accessed on 8th November 2021] https://www.archdaily. com/337430/1-angel-square-3d-reid.

ICEhouseTM (n.d.) William McDonough + Partners. [Online] [Accessed on 16th November 2021] https://mcdonoughpartners.com/projects/icehouse/.

admin (2016) ‘Electric Radiator Running Costs And Energy Usage |.’ 30th March. [Online] [Accessed on 29th September 2021] https://www.electrorad.co.uk/blog/electric-radiator-running-costs-and-energy-usage.

‘Life Cycle Assessment explained: an introduction to building LCA’ (2020) One Click LCA® software. 28th July. [Online] [Accessed on 16th November 2021] https://www.oneclicklca.com/life-cycle-assessment-explained/.

Benchmarking commercial energy use per square foot | Twinview | Insights (n.d.) Twinview. [Online] [Accessed on 8th November 2021] https://www.twinview.com/insights/benchmarking-commercial-energy-use-per-square-foot.

Low impact bio-based construction materials ready for the mass market (n.d.). [Online] [Accessed on 16th November 2021] https://www.construction21.org/articles/h/low-impact-bio-based-construction-materials-ready-forthe-mass-market.html.

B. I.D, I. and P. D. (n.d.) Ergonomic Lighting Levels by Room for Residential Spaces. ThoughtCo. ThoughtCo. [Online] [Accessed on 29th September 2021] https://www.thoughtco.com/lighting-levels-by-room-1206643.

Manchester Climate Change Partnership adopts and endorses a Roadmap to Net Zero Carbon New Buildings in Manchester | Manchester Climate Change (n.d.). [Online] [Accessed on 16th November 2021] https://www.manchesterclimate.com/news/2021/08/ZCNB.

‘Comparing LED vs CFL vs Incandescent Light Bulbs’ (2017) Viribright® LED Lights. 5th April. [Online] [Accessed on 29th September 2021] https://www.viribright.com/lumen-output-comparing-led-vs-cfl-vs-incandescent-wattage/.

Material procurement - Designing Buildings (n.d.). [Online] [Accessed on 16th November 2021] https://www. designingbuildings.co.uk/wiki/Material_procurement.

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BUILDING PERFORMANCE

CONSTRUCTION PROCESS CONT. Dalsgaard, K. (n.d.) ‘What is the difference between lumens, lux and watt?’ Suprabeam. [Online] [Accessed on 30th September 2021] https://suprabeam.com/technology/light-clarification/. Energy in buildings (n.d.) OpenLearn. [Online] [Accessed on 30th September 2021] https://www.open.edu/ openlearn/nature-environment/energy-buildings/content-section-0. Framework (n.d.) Northern Gateway. [Online] [Accessed on 8th November 2021] http://northerngatewaymanchester. co.uk/framework/. Heating & Cooling Degree Days – Free Worldwide Data Calculation (n.d.). [Online] [Accessed on 15th November 2021] https://www.degreedays.net/#generate. How much energy does my home use? (2015) TheGreenAge. [Online] [Accessed on 8th November 2021] https:// www.thegreenage.co.uk/how-much-energy-does-my-home-use/. Mayer, P. (2007) What it costs: mechanical ventilation. Building. [Online] [Accessed on 30th September 2021] https:// www.building.co.uk/focus/what-it-costs-mechanical-ventilation/3079316.article. MVHR Heat Recovery Ventilation MVHR (n.d.). [Online] [Accessed on 12th November 2021] http://www.solarcrest. co.uk/heat-recovery-ventilation.asp. MVHR unit energy efficiency | Blog | CVC Direct Ltd’ (2019) CVC Systems. 24th May. [Online] [Accessed on 1st October 2021] https://cvcsystems.co.uk/specific-fan-power/. One Angel Square (n.d.) 3DReid. [Online] [Accessed on 8th November 2021] https://www.3dreid.com/project/oneangel-square/. Sunrise and sunset in the United Kingdom (n.d.) Worlddata.info. [Online] [Accessed on 5th October 2021] https:// www.worlddata.info/europe/united-kingdom/sunset.php. Thomas, A. (n.d.) kW vs. kWh: How much energy is my lighting using? [Calculator]. [Online] [Accessed on 5th October 2021] https://insights.regencylighting.com/kw-vs-kwh-how-much-energy-is-my-lighting-using. U-values (n.d.). https://www.designingbuildings.co.uk. [Online] [Accessed on 29th September 2021] https://www. designingbuildings.co.uk/wiki/U-values. What we are doing: Projects | Zero Carbon Manchester | Manchester City Council (n.d.). [Online] [Accessed on 15th November 2021] https://secure.manchester.gov.uk/info/500002/council_policies_and_strategies/3833/zero_carbon_ manchester/2. ‘Why The Building Sector? – Architecture 2030’ (n.d.). [Online] [Accessed on 8th November 2021] https:// architecture2030.org/why-the-building-sector/.

‘Carbon footprint calculators for construction’ (2021) Circular Ecology. [Online] [Accessed on 15th November 2021] https://circularecology.com/carbon-footprint-calculators-for-construction.html. Ellingsen, H. (2021) The quiet, clean and green pilot project. KlimaOslo.no. [Online] [Accessed on 15th November 2021] https://www.klimaoslo.no/2021/02/09/new-pedestrian-street-brings-new-life-to-oslo-city-centre/. HOLICIM (2021) Building a net zero future. Holcim.com. [Online] [Accessed on 15th November 2021] https://www. holcim.com/climate-responsibility. JCB (2021) JCB | E TECH. [Online] [Accessed on 15th November 2021] https://www.jcb.com/en-gb/campaigns/ etech-range. Keegan, M. (2021) The Scandinavian way to zero-carbon construction. [Online] [Accessed on 15th November 2021] https://www.bbc.com/future/article/20210622-the-scandinavian-way-to-zero-carbon-construction. Morley, K. (n.d.) National Grid: Live Status. [Online] [Accessed on 15th November 2021] https://grid.iamkate.com/. National Grid Group (2021) Can we achieve carbon-neutral construction by 2026? | National Grid Group. [Online] [Accessed on 15th November 2021] https://www.nationalgrid.com/stories/journey-to-net-zero-stories/can-weachieve-carbon-neutral-construction-2026. Pei Ling, G. (2012) Europe’s ‘First Carbon-Neutral Neighborhood’: Western Harbour. Environment. Environment. [Online] [Accessed on 15th November 2021] https://www.nationalgeographic.com/environment/article/europesfirst-carbon-neutral-neighborhood-western-harbour. Salama, T. (2018) (PDF) Optimized Planning and Scheduling for Modular and Offsite Construction. ResearchGate. [Online] [Accessed on 15th November 2021] https://www.researchgate.net/publication/328828003_Optimized_ Planning_and_Scheduling_for_Modular_and_Offsite_Construction. Schwartz, Y., Eleftheriadis, S., Raslan, R. and Mumovic, D. (2016) ‘Semantically Enriched BIM Life Cycle Assessment to Enhance Buildings’ Environmental Performance.’ In. Sun, H. and Park, Y. (2020) ‘CO2 Emission Calculation Method during Construction Process for Developing BIM-Based Performance Evaluation System.’ Applied Sciences. Multidisciplinary Digital Publishing Institute, 10(16) p. 5587. Tomasetti, T. (2020) ‘Carbon Calculator | CORE studio.’ [Online] [Accessed on 15th November 2021] http://core. thorntontomasetti.com/carbon-calculator/. UKGBC (2021) Building the Case for Net Zero. UKGBC - UK Green Building Council. [Online] [Accessed on 15th November 2021] https://www.ukgbc.org/ukgbc-work/building-the-case-for-net-zero/. Walters, A. (2019) National Digital Twin Programme. [Online] [Accessed on 15th November 2021] https://www. cdbb.cam.ac.uk/what-we-do/national-digital-twin-programme. White Arkiteker (2021) Carbon Neutral Buildings – Creating Value Through Architecture. White Arkitekter. [Online] [Accessed on 15th November 2021] https://whitearkitekter.com/carbon-neutral-buildings-creating-value-througharchitecture/. Wilmott Dixon (2021) Our zero carbon ambition. Willmott Dixon. [Online] [Accessed on 15th November 2021] https://www.willmottdixon.co.uk/how-we-do-it/carbon-management-our-commitment. Wolstenhome, R. (2021) Hexagon enhances its Smart Manufacturing autonomous and digital twin capabilities with the acquisition of CADLM. Hexagon Manufacturing Intelligence. [Online] [Accessed on 15th November 2021] https:// www.hexagonmi.com/about-us/news/media-releases/2021/april-2021/hexagon-enhances-its-smart-manufacturingautonomous-and-digital-twin-capabilities.

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With rising populations, water consumption will begin to stress the water cycle in urban and city environments, synchronously increasing the operational costs contributing to CO2 emissions. Therefore, we must explore alternate systems to reduce and monitor human usage before it’s too late.

INTRODUCTION Water In City & URBAN LIFE

SECTION ONE

SECTION TWO

SECTION THREE

Typology & WATER USAGE

Water Harvesting & SUDS

Water Type & CARBON CALCS

CONCLUSION Centralised vs DECENTRALISED

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CARBON WATER CONTRIBUTIONS CONTRIBUTIONS TOWARDS ZERO CARBON

Harry Chan, Payam Malakouti, Jemma Baldwin

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Zero Carbon Cities

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Introduction How Important is the Water Sector to Acheiving Zero Carbon?

Although this seems less significant than other industry contributors reducing the emissions associated with water will aid Manchester Council in reaching their Net Zero target by 2038.

UK Context Manchester City Victoria North Site

Residential Interventions

Neighbourhood Interventions

Calculations

The primary area of greenhouse gas emissions in the domestic water sector is the use phase. A 2008 Environment Agency Study into domestic water use stated that 89% of emissions are produced in the use phase, with 11% produced by water utilities (Clarke, 2009}. Therefore, we will focus on water use within the home and subsequent reduction strategies before looking at neighbourhood and regional scale interventions.

Introduction

Analysis

Net Zero is described as no net release of greenhouse gases into the atmosphere. Currently, the UK’s Water Industry annually contributes 0.8% of annual Greenhouse Gas Emissions. However, if this were to include heating water in the home this would increase to 5.5% (Reffold et al, 2008).

Suggestions and Summary

“89% of domestic GHG emissions are produced in the use phase” Image: Matthew Nichol Photography (2018) River Irwell Crossing

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Introduction

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Image created by author from information: Anglican Water, United Utilities, Yorkshire Water (2019)

Problem Identification Challenges for the UK Water Industry within 25 Years

Investor Confidence and Availability of Finance

Population and Household Growth

Affordability

Environmental Legislation

There are many long term uncertainties which could affect the UK’s water industry in the next 25 years. Some of these uncertainties such as environmental legislation will have a direct impact on the possibility of the sector to reach Net Zero. The diagram (right) shows a systems mapping for these interrelated problems and their positive or negative effects on other elements of the system. Increased population growth will result in an increased demand for water and sewerage services. In turn ageing assets will require increased maintenance to cope with the greater demand. This

will result in less investor confidence which could be mitigated with technological changes. In addition, an increased population will decrease the availability of water especially in summer with climate predictions for Manchester estimating a reduction from 12 days to 9 days of rain per month in summer. This is the inverse problem in winter which increased days of rainfall compared to the current average (Met Office, n.d). This means that flooding will be more prevalent in winter with potential water shortages in summer. The above map shows the current flood zones in Manchester which will likely increase with the climate change effects (Environment Agency, 2019).

This research will focus on water for Net Zero

Resource Costs and Availability

Rising Energy Costs

Climate Change

+ Technological Change

Changing Customer Profile and Legislation

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UK Context

Ageing Assets

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Issues

1 in 3 have no access to improved sanitation. 1 in 7 practice open defecation Up to 7% loss of GDP due to inadequate sanitation

70% of water consumption used for agriculture 85% increase in water demands caused by rising energy production by 2035

Sanitation & Hygiene

Water Efficiency

Safe Drinking Water

Water Quality

Every 15 seconds 1 child dies from water born disease Women and children spend 200 Million hours retriving water each day

80% of wasterwater worldwide is directed into water supplies untreated 2 Million tons of human waste disposed in water systems each day

Groundwater provides drinking water to at least 50% of global population Climate change and urbanisation will impact the water-cycle and groundwater reserves

Water Ecosystems Water Resources Management 2/3 of population could endure water difficulties by 2025 Water access risk over next decade

Sustainable Issues and Goals S DRINKING WATER SAFE

Universal and equitable access to safe and affordable drinking water for all

608

Introduction

hazardous chemicals and materials, untreated wastewater

2030 Water & Sanitation Goals

Implement integrated water resources management at all levels.

-50% pollution,

AGM E

Above Image created by author from information: United Nations (n.d) Goal 6 Right Image created by author from information: United Nations (n.d) Water Facts

Sustainable withdrawals and supply of freshwater to address water scarcity

WATER EFFIC I E NC Y

One solution to this is simply to produce less pollution in all sectors that link to water usage. However, using a circular approach could create a more sustainable economy where wastewater is another valuable source instead of discarding it. After appropriate treatment this could improve economic and financial benefits in the long term, and safe wastewater management could help protect our ecosystems and give us energy, nutrients and other recoverable materials that will lead us into a carbon zero future (United Nations, n.d, Water Facts).

Access to adequate and equitable sanitation and hygiene for all

Over recent decades environmental and societal pressures have been focusing on water usage reduction and treated before before discharged. Urban growth will require development of new wastewater management to aid the challenges of

industrial needs which can improve the health of workers and pathogen exposure.

TE WA

This is being affected by the rapid urbanization and economic development with the increase in demand from population growth. The cost of maintaining this is increasing just as rapidly and leading to more

infrastructure and energy costs that contribute to carbon emissions. Unfortunatly low-income or developing cities discharge untreated wastewater back into the closest surface water drains in parallel to the industrial sector who dump highly toxic chemicals and medical waste into the waste water system. To make any kind of steps towards a zero carbon future we must look to new or better methods of cycling the water in the ecosystem.

WA TE RQ

Y LIT UA

The future of water is in question as it is essential that we are able to maintain good quality water into the ecosystem alongside our social and economic development and health. Monitoring the treatment cycle is crucial from abstraction and pre-treatment to it’s distribution, collection and posttreatment. Currently far too much poor quality water is being re-directed into the water cycle which means chemicals and unsanitary water is polluting both drinkable water and water sources.

IENE HYG & N TIO TA I AN

Protect and restore water-related ecosystems, including mountains, forests, wetlands, rivers, aquifers and lakes.

ER WAT

TE YS S O EC

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UK Carbon Emissions

Transport 0.21

Sankey Diagram of Emission Flows

Emissions (MtCO2e)

Drinking Water 1.29

Grid Electricity 2.05 Carbon Dioxide 2.54

Admin 0.09 Wastewater 1.74

Type (MtCO2e)

Burning of Fossil Fuels 0.28

Nitrous Oxide 0.34

Process Emissions 0.70

Methane 0.45

Image created by author from information: Water UK (2020) Net Zero 2030 Routemap

Emissions from the UK water industry consist of primarily Carbon Dioxide, followed by Methane and then Nitrous Oxide. These emissions come from the transportation of water, administration, grid electricty, burning of fossil fuels and process emissions. The use of grid electricity produces the most emissions. This highlights an oppurtunity for the UK water sector to significantly reduce emissions by further investigating alternatives to grid electricity or by reducing the energy consumption of appliances. The UK water sector produces 2.54 MtCO2e of Carbon Dioxide compared to 0.45 MtCO2e of

610

UK Context

Methane and 0.34 MtCO2e of Nitrous Oxide. With transport, grid electricity and the burning of fossil fuels being the main contributors in the production of CO2. Strategies such as decentralised water systems could reduce transport emissions by keeping the source and treatment of water local. Furthermore, the use of renewable energy sources such as hydro-power could reduce the burning of fossil fuels and further reduce the emissions from the UK water sector. These figures contribute 0.70% CO2 emissions, 0.82% CH2 and 1.48% N2O emissions to the UK’s overall greenhouse gas emissions.

0.70% CO2 0.82% CH2 1.48% N2O

UK Water Industry’s percentage of Greenhouse Gas contribution

F-Gases 13.64

N2O 22.94 CH2

CO2 363.84

54.58 UK Water Industry Emissions MtCO2e

Image created by author from information: Wren et al (2021)

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Water-Energy Nexus Petroleum

Transportation

Produced Water

Residential

Biomass

Commercial

Natural Gas

Energy Services

Energy Dissipated

Industrial

Coal Surface Discharge

Hydro Geothermal

Energy Generation

Wastewater Treatment

Wind/ Solar Fresh Surface

Ocean Discharge

ThermoElectric Cooling

Saline Surface Agriculture

Fresh Ground Public Supply

Saline Ground

Injection

Energy Systems The diagram above illustrates the complex relationship between water and energy in terms of inputs, processes and outputs. Within the framework of the Paris Agreement, the EU intends to be climate neutral by 2050. In addition to this, Manchester City Council states that they aim to be zero carbon by 2038 (Europa). If Manchester City Council and the wider UK government is to achieve these goals then significant

612

UK Context

Consumed Water

Image created by author from information: U.S. Department of Energy (2014) energy must be saved, existing processes optimised and innovative new technologies employed within the water sector (European Commission, 2018). Water wastage via means such as leakage and inefficient systems consequently causes large amounts of energy wastage in the journey of water from the source to the end-use. Reducing the water wastage would

result in less energy consumption which in turn reduces operational carbon. The energy saving from this could potentially offset population increases. Similarly, “pumping systems account for a significant part of the total electricity consumption in a plant” the increased performance of which in crucial for the energy generation involved with water.

Renewables

Air Cooled

Nuclear UK Electricity Generation Thermal

CCGT Sea Water

UK Thermoelectric Cooling Sources

Freshwater

Tidal Water

Image created by author from information: Byers et al (2014)

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UK Demand and Losses

62L

For shower or bath

Water Usage

The UK uses approximately 840 billion litres of water each year for a population of 67.22 million. Within this population the average person should drink at least 2-2.5 litres of water a day. However, drinking water is a tiny fraction of water used in the UK. At home, the average UK person uses 142 litres of water per day and a house of 4 uses around 349 litres per day. And during the COVID-19 lockdown this value increased in some parts of the UK by 25%, to approximately 175 litres of water per day per person. One of the main sources of water use in the UK is having a shower or a bath. When you take an 8 minute shower you use about 62 litres of water; that’s almost half of your daily water use. And if you have a power shower you’ll use even more water. So a shorter shower is one of the best ways of reducing your personal water usage at home. That’s approximately 2700 litres of water a day to produce the food you eat and the drinks you, well, you drink. This is equivalent to showering 44 times per day. And about 62% of this hidden total consumption happens outside of the UK, from water used in agriculture and industry to the water consumed when you go on holiday.

It’s estimated that the UK as a whole uses around 14 billion litres of water per day in total. This is over 25% water lost due to leakage. Leakage can occur primarily with ageing assets that water companies are yet to fix but the number of ageing assets is increasing. In the same way the population of cities in the UK such as Manchester are vastly increasing which puts greater strain on existing resources.

142L

of water consumed per capita

The best approach is to view demand and losses through the lens of a city and in greater detail through the Victoria North site in order to assess how improvements can be made. Agriculture

14Billion L

Domestic

Water Consumption

Industry

3.7Billion L Water Lost to Leakage

614

UK Context

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Systems Diagram Water Plus Carbon Relationships National Policy The water cycle and the wider factors such as the impact of politics, environmental, social and the built environment could in itself be considered a wicked problem because of the interdependancies of factors. The areas illustrated in the systems diagram (right) are only the primary factors impacting the water cycle. If the systems mapping were to attempt to define every relationship the urban scale would be lost in favour of the global scale. The use phase is the primary area of the water cycle this research is focused on. How water is used can affect a building typology. It can be used in a traditional way with pipes and water tanks or it can become an integral part of the building. For instance, the indoor waterfall at the Jewel Changi Airport by Safdie Architects or The Building on the Water by Álvaro Siza and Carlos Castanheira. The use of water in architecture can be both functional and aestethic. The use of water is also affected by the behaviour of people, particularly true of the residential sector. Behavioural changes such as taking shorter showers, having less baths or installing a water meter to keep track of how much water you use has a significant impact of the amount of water used per person per day. Wastewater treatment is another area of the water cycle which can be significantly improved. Surface water urban runoff from impermeable surfaces can result in flooding of cities. One mitigation method is to utilise sustainable urban drainage systems (SuDS). Whilst this may not have a direct reduction on carbon emissions and has costs in terms of operational and embodied carbon, employing these systems reduces the carbon used post-flood. The population of an area has the largest efffect on greenhouse gas emissions. More people simply equals more water used at a residential and urban scale.

Flooding Urban Runoff

POLITICAL Building Regulations

Zero Carbon Legislation

Sustainable Urban Drainage

ENVIRONMENTAL

Embodied Carbon

Operational Carbon

Nutrient Reuse

Aqueduct

Wastewater Treatment

End Use

Discharge

Distribution WATER CYCLE

Appliance Efficiency

Greenhouse Gas Emissions

Source

Energy Used

Use Water Treatment

Public Building Typologies BUILT ENVIRONMENT

Household

Industrial

Population Commercial

SOCIAL

Residential Behaviour Abstraction

Water Reduction Strategies Image created by author

616

Manchester

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Manchester Supply

Reservoir to Tap

2035 3.0mil people

The Thirlmere Aqueduct was completed in 1955, with the latest improvements being in the 1970s; it runs for 96 miles, carrying approximately 285 million litres of water a day. Haweswater Aqueduct began construction in 1935 and runs for 56 miles underground, carrying approximately 570 million litres of water a day. The underground aqueducts can be observed above ground via insepction hatches and some buildings which are to

release trapped air. 31 miles of Haweswater Aqueduct is large enough to drive through before splitting into a series of smaller 1.2m and 1.4m diameter pipes. The weight of the water over a 550m drop from the Reservoir sucks the water through the aqueduct and over the uphill sections towards Manchester (Hidden Manchester, n.d). In order to keep up with growing demand additional water sources closer to Manchester such as the Longendale Reservoir augment the original supply. The population of Manchester is as of 2021 at 2.7 million. If the population trend seen since the 1990s continues then this will reach 3 million by 2035 (World Population Review, 2021).

THIRLMERE RESERVOIR SHAP AQUEDUCT

Manchester Reservoir Supply NWW Area Reservoirs

BARROW

Pumped Supply Gravity Supply Connections From Aqueducts to Local Supply Areas BLACKPOOL BURNLEY

2021

2021 2.7mil people

The city of Manchester is primarily provided with water from Thirlmere Reservoir and Haweswater Reservoir in the Lake District. Water is then transported via two primary aqueducts to Manchester.

HAWESWATER RESERVOIR

3.0

Services Reservoirs Water Treatment Works

BLACKBURN

Manchester Population (million)

SOUTHPORT

B O LT O N

2.8

OLDHAM

LONGDENDALE RESERVOIRS

2.6

LIVERPOOL

MANCHESTER WARRINGTON

LONGDENDALE AQUADUCT

STOCKPORT

2.4

2.2 1950

CREWE

1960

1970

1980

1990 Year

2000

2010

2020

2030

Image created by author from information: World Population Review (2021)

618

Manchester City

Image created by author from information: Hidden Manchester (n.d) Haweswater Aqueduct Fowler and Kilsby (2007)

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Manchester Treatment Greater Manchester Wastewater Treatment

Information: Littlewood and Bennett (2019)

Manchester City

er se y

Moss Side WWTW

Work 9

W ork

One Shot

10 Work 11

Chorlton Brook Platt Brook

Slim Pickings

Work 4

HF Little Brother

Hulme Flume

A Packing Heat

Outfall A

River Medlock B

Takeaway

SSSI

River Irwell

Terminal Velocity

A2B

DavyHulme WWTW

Work 8

2035 serving 1,301,230 people

Manchester Ship Canal

Riv

620

Manchester Water Network

Moston Brook

Work 6

Existing

Work 2C

The existing water system of Manchester connects assets such as Davyhulme Wastewater Treatment Works with the River Mersey, River Irk and local brooks to meet the water and wastewater requirements.

r Irk

Rive

Lock Stock

The new structures required on site for the project utilised Design for Manufacture and Assembly (DfMA) because of the time, cost, safety and environmental benefits when compared to traditional construction.

2019 serving 1,030,591 people

Packing More Heat

Continuous upgrades are necessary to keep up with the growing demand of Greater Manchester with population increases. The project also tackled inefficiencies within the system from outdated assets, “Davyhulme now generates enough renewable energy to power the plant and put energy back into the grid” (Littlewood and Bennett, 2019).

Following the improvements made in the modernisation project, Davyhulme has a population equivalent of 1,030,591 which is expected to rise to 1,301,230 for 2035.

Upgrade

Davyhulme Wastewater Treatment Works operated by United Utilities is located in Greater Manchester and serves upwards of 1.3 million people. It was originally built in 1894 and has been consistently upgraded to reflect industry changes. The latest of these upgrades was the Davyhulme Modernisation Project from 2015-2020.

Work 5

21 21 Gore Brook

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Policy EN14: Flood Risk

Manchester Policy

“All new development should minimise surface water run-off, including through Sustainable Urban Drainage (SuDS) and the appropriate use of Green Infrastructure. Developers should have regard to the surface water run-off rates in SFRA User Guide. In CDAs, evidence to justify the surface water run-off approach / rates will be

Manchester City Council

Policy EN8 describes the council’s aproach to adapting for climate change which briefly mentions flood risk. Flood risk is then evaluated further in Policy EN14 with the introduction to sustainable urban drainage systems (SuDS). However, Policy EN14 does not link mitigating the effects of flooding with carbon emission reduction. The final policy in Manchester’s Core Strategy document is regarding water quality which again mentions surface water drainage but also minimising groundwater contamination. In summary, Manchester’s Core Strategy analyses the following areas of water: flooding,

drainage, contamination, rainfall and watercourses. Although these issues are covered by policies there is a lack of policies relating the sourcing of water for Manchester, the treatment, the use and the wastewater treatment with regards to carbon emissions and/or operational and embodied carbon of systems. The document does include a section on ‘Energy Statement Methodology’ yet this is primarily concerned with the energy generation sector. This could be expanded on in the future to encompass other sectors such as water systems. Although it is achknowledged that the aim of the Core Strategy document is to provide general policies for Manchester, an increased number of policies regarding carbon emissions and accountability would benefit Manchester Council’s aim to be carbon-zero by 2038.

Policy EN17: Water Quality Manchester's Core Strategy

Manchester’s Core Strategy is the key document in the Local Development Framework for 2012-2027. Within this document there are numerous references to Carbon emissions however, little references to operational or embodied carbon. The document sets out some key policies with regards to water including Policies EN8, EN14 and EN17.

“Development should minimise surface water run-off from development and associated roads, and maximise the use of appropriate sustainable drainage systems, to minimise groundwater contamination, and to avoid pollutants reaching watercourses.”

Policy EN8: Adaption to Climate Change FLOOD RISK ANALYSIS

CARBON ACCOUNTING METHODS

SURFACE WATER DRAINAGE

CARBON RELATED TO WATER

GROUNDWATER CONTAMINATION

EXISTING WATER INFRASTRUCTURE

EXPECTED RAINFALL INCREASE

HOME APPLIANCE EFFICIENCY

RIVER MANAGEMENT

WATER ACCOUNTABILITY

“Minimisation of flood risk by appropriate siting, drainage, and treatment of surface areas to ensure rain water permeability.”

WATER QUALITY

22 622

Manchester City

Image created by author from information: Manchester City Council (2012) Manchester’s Local Development Framework

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Building Typology The Victoria North site contains a mixture of uses which in the below map is split into industrial, commercial, residential, public services, education and churches. Whilst industry and commercial uses have a significant impact on water consumption, we will be focusing

on the rdomestic water usage and water reduction strategies at both a household and a neighbourhood scale. The current estimated population for the site is 6925. The use of water is broken down further in the following pages.

INDUSTRIAL

COMMERCIAL

RESIDENTIAL

PUBLIC SERVICES

EDUCATION

CHURCHES

LOWER IRK VALLY

1828

3586

COLLYHURST

MANCHESTER CITY

NEW CROSS

1511

624

N Image created by author

Victoria North Site

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Image created by author

Residential Water Usage

Per Person for Victoria North The population of Manchester will continue to grow year by year, but for the EU residents who account for a small number in the region, their settlement will undoubtedly be affected due to Brexit.

Lower Irk Valley

United Utilities usage rates of water for each occupancy can be seen where the average litres of water used per day has been calculated through water meters. To address carbon reduction within this development, regulatory measures of water consumption would need to be explored which aims to reduce usage. 40% Non-Residential

Approx Water Usage at Victoria North

Collyhurst

60% Residential

Average Daily Water Usage X1

150 L

270 L

360 L

450 L

Manchester City

New Cross

520 L

590 L

Map Legend: Residential Low Rise Residential High Rise Left Images created by author from information: DEFRA (2013)

626

Victoria North Site

9% 4% 1% 8% 25% 22% 7% 1% 1% 22%

Washing Machine Hand wash Dishes Dishwasher Bath Shower Toliet Bathroom Hot Tap Car Garden Other (Cold Taps)

Water Consumption per Household

Image created by author from information: Clarke (2009)

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System Dynamics Relationships between Water and Carbon

+ +

WF of Conveyance and treatment energy use

+ TOTAL WF OF UWS

WF of water treatment chemicals

Comercial, Institutional and industrial (CII) Agriculture

+ Comercial, Institutional and industrial (CII)

WF of Hot Water Energy Use

CII Outdoor Use

EMBODIED CARBON FOR BUILDING SYSTEM

WATER USE

PW Source

+ Distribution Energy

+ +

Comercial, Institutional and industrial (CII)

+ + +

WATER AND WASTEWATER CONVEYANCE /TREATMENT ENERGY USE

+ +

WW transport energy

Energy for CII indoor hot water use

+ Residential Indoor Use

Reclaimed Water

+ +

Residential Water Use

Rainwater

CII Indoor Use

CII Water Use

Water Harvest

Treatment Energy

CF of Water Treatment

Parks

Direct Water Use

Energy for residential hot water use

Residential Outdoor Use

WASTEWATER

Dwelling units

+ Water appliances

GHG emissions from hot water energy use

+ +

Energy Treatment

+ The system dynamics diagram illustrates the relationship between each aspect of the water cycle and their impacts on water use and carbon emissions on other aspects. The plus and minus signs indicates whether the relationship has a positive effect or a negative effect on another aspect. This diagram summarises the elements considered in the following carbon calculations.

628

Interventions and Calculations

Total energy for UWS GHG Emissions from conveyance and treatment energy use

Population

Comercial, Institutional and industrial (CII)

Legend: PW = Potable Water WW = Wastewater UWS = Urban Water System WF = Water FootprinT CF = Carbon Footprint GHG = Green House Gas CII = Comercial, Institutional and Industrial Typology

+ +

Water Cycle TOTAL GHG EMISSION FROM UWS

Off-Grid Water Embodied Carbon Operational Carbon GHG Emission

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Combi-Boiler Shower

Negative Head

Shower Usage Operational Carbon Pie Chart of UK Households with Showers

Pie Chart of UK Shower Types Standard Power

66%

Bath only

14% 8%

Shower only

12%

Seperate shower and bath

Image created by author from information: AMA Research (2015)

Within the average UK household, showers use of the most water out of all appliances. Approximately 25% of water usage in the home is due to showering. Behaviour has a large impact on the water use of showers, reducing the time of the shower produces less operational carbon as does choosing a lower KW shower. However, behavioural changes are hard to implement at a policy level by Manchester City Council. Instead we will explore through carbon calculations the impact of both time spent showering

18% 35%

Eco Mixer Shower over bath

Cold Water Storage

Electric

11%

Eco Power

5% 31%

Standard Mixer

Image created by author from information: Statista (2014)

and the type of shower used. Some considerations that will affect this calculation is what percentage of the Victoria North site have showers. According to AMA Research (2015) 86% of UK households have access to a shower either by itself, over a bath or seperate from a bath. Extrapolating all these figures to the estimated residential population of the Victoria North site we will be able to calculate the yearly operational carbon saving if all those currently using a combi-boiler power shower switched to an electric shower with some given assumptions.

Behaviour has a large impact on water use

Switching from a Combi-Boiler Power Shower could save operational carbon

Image altered by author from information: LivingHouse (2014)

Electric Shower Switch Shower Unit RCD

Fuse or MCB

Meter

Incoming Supply Fuse

Image altered by author from information: Triton (n.d)

630

Interventions and Calculations

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2021 CPU[AI]

Shower Calculation Operational Carbon

Reduction Device Info

Digging deeper into individual water saving measures, we have calculated the water saved and energy saved from using different water saving devices. The calculations are carried out by measuring their operational time, water consuption of the device as well as each of the individual embodied carbon.

Site Info

Device Power

Shower - Operational Energy Output

Water used = 150L Time Used = 5mins People per House hold = 2.39

= 1345kg Net Carbon Saving/Household/Year through Electric Shower Water Meter Mass of Material x Embodied Convertion Factor = Product Embodied Carbon

Supply Water EC Conversion factor = 0.149

Hammond (2011) ICE

Water Saved = 21.3L/day Carbon Reduction = 0.00317kg/day = 1.15705kg/year

Time x % of Device Usage x Population x Device Power

plastic = 1kg Plastic EC Conversion Factor = 2.73

x 365

Brass = 1kg Brass EC Conversion Factor = 4.47 Average Life Expectancy = 20 years Hammond (2011) ICE

Carbon Produced = 7.2kg/unit = 0.36kg/unit/year

Yearly Operational Carbon of Standard Device

Yearly Operational Carbon of Water Saving Device

Output

Average Daily Water Consumption = 142L

Daily Energy Consumption

Calculation

Electric Shower Carbon output = 3168930kg/year = 1272kg/household/year

2617 - 1272

Average Metering Water Saving = 15%

Households

Electric Shower power = 7.5kW

Population = 6925 Household with shower = 2491

Combi-boiler Carbon output = 6518900kg/year = 2617kg/household/year

Water Consumption

Power of shower x time / water mass = Energy/water mass Combi-boiler power = 30kW

Population

Input

Time Used

1.15705 - 0.36

= 0.79705kg Net Carbon Saving/Year through using a water meter 632

Interventions and Calculations

633

2021 CPU[AI] 90 80

Shower Results

Time has a large impact

The results in the graph illustrate that the lower the kW of shower the less operational energy is used. However, a more unexpected result is that if the time spent showering is over 15 minutes for a 10.5kW electric shower or over 20 minutes for a 7.5kW electric shower approximately the same amount would be used for a 5 minute combi-boiler power shower. In conclusion, if a home already has a combi-boiler power shower reducing the length of time spent showering would prevent unnecessary embodied carbon costs. However, if a household is looking to replace their shower, then 7.5kW is best.

4,889,175 kWh/m3 Operational Carbon yearly saving*

634

Interventions and Calculations

60 50 40 30 20

Level of Environmental Benefit

7.5kW is best

The graph (right) shows the relationship between the operational energy (kWh/m³) and the time in minutes of three different types of showers. As previously identified, combi-boiler power showers are the most energy intensive at 30kW, following additional research there are two standard types of electric shower at 10.5kW and 7.5kW readily available for purchase. Both electric showers have been compared against the combi-boiler power shower in terms of operational energy.

Operational Energy (kWh/m³)

Where is the most saving?

Decrease Time Spent Showering

10 0 5

Time (mins) 7.5 kW Electric Shower Use

Operational Energy Combi-Boiler Power Shower 30kW (kWh/m³) Operational Energy Electric Shower 10.5kW (kWh/m³) Operational Energy Electric Shower 7.5kW (kWh/m³)

Replacing Energy Inefficient Showers

*Assumptions for model: 1. Five minute showers 2. Water litre usage of showers is equivalent 3. kW for shower types 4. Victoria North site is representative of overall UK data for shower ownership and type usage 5. Existing electric showers are 7.5kW to provide low estimate

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Precedent Green Square Town Centre Sydney Green Square has created a water engineering project in helping with flood prevention and reducing potable water use. 4 kilometres south of the CBD, which was previously a network of marshes and rivers, is prone to flooding during heavy rain. The idea was to construct a 2.4km underground stormwater drain from Epsom Road in Zetland to an existing stormwater system at Alexandra Canal, capable of conveying 30,000 L of water per second. The project, which took four years to build and was awarded the 2019 Infrastructure Project Innovation Award at the Australian Water Association’s NSW Water Awards earlier this year, was produced by the City of Sydney and Sydney Water. Micro-tunnelling allowed tunnel boring equipment to insert 1.8 m diameter pipes up to 12 m underground,

allowing life to go on as usual above ground while development was underway. The water is purified on-site at the Green Infrastructure Centre before being stored in tanks beneath Matron Ruby Grant Park. It is then carried via a line of purple pipes to the Green Square town centre and adjoining apartment complexes, where it is used to flush toilets and water green spaces, making it easy to identify from potable water. It is estimated that drinking water in town centre could be reduced by half through implicating this scheme. The recycled water at Green Square will be less expensive than Sydney Water’s drinking water, saving residents and businesses an average of $20 per year on their water bills. The recovered water will also be used to irrigate Matron Ruby Park, which is located on the grounds of the former South Sydney Hospital, as well as the planned library in Green Square (IWA, n.d).

Green Square Area

Water Storage Tank

636

Interventions and Calculations

Images altered by author from information: IWA (n.d)

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Rain Water Harvesting Rainfall - Annual Average Jan 3.8 0.0038 5318.651 534.4441676 534444.1676 229.020547 229020.547

Rainfall(mm) Rainfall(m) Rainfall(m3) Water harvest all building(m3) Water harvest all building(litre) Water harvest all residential(m3) Water harvest all residential(litre)

River and Brook

Feb 3.2 0.0032 4478.864 450.0582464 450058.2464 192.859408 192859.408

Mar 3.1 0.0031 4338.8995 435.9939262 435993.9262 186.8325515 186832.5515

Apr 2.9 0.0029 4058.9705 407.8652858 407865.2858 174.7788385 174778.8385

May 3 0.003 4198.935 421.929606 421929.606 180.805695 180805.695

Jun 3.5 0.0035 4898.7575 492.251207 492251.207 210.9399775 210939.9775

Jul 3.5 0.0035 4898.7575 492.251207 492251.207 210.9399775 210939.9775

Aug 3.6 0.0036 5038.722 506.3155272 506315.5272 216.966834 216966.834

Sep 3.2 0.0032 4478.864 450.0582464 450058.2464 192.859408 192859.408

Oct 3.7 0.0037 5178.6865 520.3798474 520379.8474 222.9936905 222993.6905

Nov 3.7 0.0037 5178.6865 520.3798474 520379.8474 222.9936905 222993.6905

Dec 4.1 0.0041 5738.5445 576.6371282 576637.1282 247.1011165 247101.1165

Rainfall

LOWER IRK VALLY

COLLYHURST

MANCHESTER CITY

NEW CROSS

638

N Image created by author from information: Climate-Data.Org (2021) Climate Manchester

Interventions and Calculations

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Evapotranscription Green Roofs

Evaporate

Urban Drainage (Suds) The existing Northern gateway site in Manchester is 52.5% permeable surfaces which allow water drainage and 47.5% impermeable surfaces. A high percentage of impermeable surfaces can exasperate climate change effects such as flooding which causes increased carbon usage in the city. Sustainable urban drainage systems (SuDS) can mitigate these effects by lowering water flow rates, increasing water storage capacty and enhancing the amenity and biodiversity value.

Source Control

Retention

Water storage ponds

Store Permeable Surface 814,156m2 Site Surface Type Filter

Distribute Impermeable Surface

Pre-treatment System

Infiltration System

735,844m2

Vegetated swales and filter trenches

Soakaways and trenches

Distribute

Waterways and rivers encouraging sustainable transport

Infiltration System

Retention

Source Control

Runoff rainwater from roofs

Stored surface water in ponds increases amenity

Discharge

River Irk

Source control methods such as using rainwater run-off from roofs help to decrease the volume of water entering the drainage/ river network. This is particularly useful in areas with high impermeability of surfaces. The captured water is then stored and/ or green roof evapotranscription takes place.

Pre-treatment System

River Irk

Pre-treatment remove pollutant from surface water and discharge into watercourses or aquifers from vegetated swales or filter trenches.

Groundwater as a resource for heating and cooling

Retrofitting existing buildings with water-efficient fixtures and appliances

Infiltration systems such as soakaways and infiltration trenches allow he ground to reabsorb water. Retention systems such as ponds stores water before discharging to watercourse.

Isometric of existing site with potential SuDS locations

640

Interventions and Calculations

641

2021 CPU[AI]

Demand + CO2e Method Emissions and Usage

Typology Info

Building Info

Typology

Floor Level

Population

Input

We have developed a tool that would allow designers to input there building information into our script that estimates the water usage and carbon emission of the building. The results are driven by water usage after water demanad reduction methods are apply along with the embodied carbon and operational carbon output.

Floor Height

Water Consumption

Property Area

Source

Input

Output

Property Floor Height (m)

Property Area (m2)

Water Consumption (L)

Operational Emission (kg CO2 e)

(

Potable Water + Black Water Grey Water

Embodied

(

Operational

Water tank Supply Pumping

Initial System

End Use

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Embodied Emission (kg CO2e)

Precipitation (mm)

Total Carbon Emission (kg CO2e)

Replacement & Maintenance Potable Water Needed

Treatment

WasteWater Treatment Needed

Emission Conversion Factor (kg/L)

Potable Water: - Drinking - Kitchen Taps - Shower - Basin Taps

Interventions and Calculations

Non-Potable: - WC Flushing - Irrigation - Laundry - Car Wash

Grey Water: - Shower - Basin Taps

Dark Water: - WC Flushing - Irrigation - Laundry - Car Wash

Water Carbon Emission

Embodied Carbon Emission

Operational Carbon Emission

Output

Waste Treatment

Water Consumption (L)

Calculation

Treatment

Water Consumption & Treatment

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Water Reuse Systems Rainwater Harvesting

Property Footprint(m ) x Drainage Coefficient x Annual Rainfall x 0.05 = Recommended Tank size 2

Service Life Most of rainwater tanks for systems offered in the United Kingdom have a 15-year manufacturer’s warranty. The tanks, on the other hand, are built of inert materials and have no moving parts. The service life of rainwater tanks is likely to be substantially greater than the guarantee period if they are not damaged by impacts or movement. During the investigation, several vendors predicted tank life to be up to and beyond a hundred years. Other static parts are frequently covered by twoyear warranties from suppliers, which differ from manufacturer

warranties. Suppliers predict that the actual service life will be substantially longer. However, For the calculation later on, the life expectancy of the water tank shall be capped at 15 years for the ease of calculation.

3.0

Main Water energy intensity (25%)

2.0

Main Water energy intensity (50%)

1.0

Pumps and control systems in rainwater collection systems are powered by electricity. This operational energy use, primarily for pumping, accounts for a large amount of a system’s carbon footprint, with the remainder resulting from embodied carbon in system materials and transportation for system delivery and maintenance. The mid-range estimates for rainwater system energy intensity, as well as individual reported figures, clearly exceed the range of mains water energy intensity. Assuming that these results do

Bronchi 1999

BSRIA 2001

Bronchi 1999

Retamal (CS)

FBR 2001

CIRIA 2001

BSRIA 2001

CLG 2008

0.0 BSRIA 2001

The Water Tank size depends on the area of your property and the annual rainfall amount. According to Owlshall, the recommended Water Tank size could be defined by the following equation.

Main Water energy intensity (75%)

BSRIA 2001

Water Harvest Tank Size

4.0

Ratamal 2009

A storage tank is included in all rainwater systems, which collects rainwater via a filter and cooled entrance from the roof and any other suitable collection sites. Tanks can be put fully or partially underground, at ground level, or within a structure, typically in a basement or ground floor plant room.

Main Water energy intensity (Max)

5.0

Ratamal 2009

Rain Water Storage Tanks

Operational Energy

Nash 2009

Rainwater systems must perform two things at their most basic level: collect and store rainwater and convey stored rainwater to locations of consumption. Building water supply systems feature a mains backup system. When rainwater is not available, this assures an uninterrupted supply to the end users connected to the system.

Rainwater operational intencity, Upper

energy

Rainwater operational intencity, Lower

energy

not include any energy used for UV treatment (as is the case), this means that pumping water from the rainwater tank to end users resulted in higher carbon emissions than the provision of mains water to buildings in the UK for the vast majority of the systems studied.

Typology

Components Component

Description

Storage Tank

Variable size and materials (RC, GRP or PE)

Telescopic Dome Shaft Pipework

Used for access External usually PE, Internal PVC / MDPE

Filter

Stainless steel mesh, PE surround

Calmed inlet

Polyethylene part

Overflow siphone

Polyethylene part

Float Switch & Flow Regulator

Two types of pumps submersible and multistage selfpriming centrifugal pump used as standard

Pump Control

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Polyethylene ball, Brass connecting parts, stainless steel clamps

Mains top up controls

Interventions and Calculations

House

Larger System

According to a study in Australia by Retamal et al. (2009). A whole house would require an average pump energy of 0.9 - 1.5 kWh/m³ which is considered as lower monitor energy intensities for rainwater systems, but mostly above the range of mains water energy intensities.

In larger and taller structures, more pumping is required to supply water to end users. In contrast to most residences, where water is delivered under mains pressure, these types of buildings would almost always have a pumped mains water supply in any event. As a result, a decision must be taken on how much more pumping in larger structures is acceptable.

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Water Reuse Systems Grey Water Recycle

Greywater recycling ststems very greatly in their complexity and size from small systems with very simple treatment to large systems with complex treatment process. Greywater systems come in a variety of sizes and treatment levels, making them suited for a variety of applications. Lowlevel treatment systems, such as short retention systems, can be used in houses and hotels, and they may also be used in non-domestic buildings to some extent. They are less useful in buildings with modest greywater yields, such as offices.

Biological and biomechanical systems are developed for use at many sizes of construction and development. The Aquacycle system, for example, is designed for single-family homes; biological membrane systems are designed for communal and commercial applications; and medial filtration is designed for much larger applications such as high-rise buildings, mixed-use developments, and multiple-building developments.

Main Water Supply Untreated Grey Water Treated Grey Water Pump

System Types Direct Reuse Systems

No treatment is used in direct re-use systems, and greywater is only held for a brief time to prevent bacteria development and deterioration of water quality.

Short Retention Systems

The treatment for short retention systems is quite straightforward. The wastewater drained from the bath or shower is collected and kept in part. Simple treatment procedures such as particle settlement and surface skimming are used to ‘treat’ the water in the storage tanks. The greywater in these storage jars is only used for toilet flushing.

Basic Physical and Chemical Systems

This type of method uses chemical disinfectants such as Chlorine or Bromine. However, this type of method often results in negative impact of the enviornment. The high maintenance cost has also caused this type of system to be declined in the market

Bio-mechanical Systems

Self-cleaning filters or membrane technology, a sequence of treatment tanks, and biological treatment are typically used in these systems. They have advanced treatment methods, and the resulting water quality frequently meets or exceeds EU bathing water standards.

Components Component

Description

Collection Tank

Collection of pre-treated grey water ,

Treatment Tank

Usually polyethylene

Clean Water Tank

Usually polyethylene

Diverter Valve

PE part (domestic systems), Steel/brass & PE composite (commercial systems)

Isolation valve

Brass part

Solenoid valve

Brass, stainless steel and plastic part

Overflow

Polyethylene pipes

Float switch

High-level for flood protection, low-level for dry-run protection of pumps (Polyethylene, brass)

UV Treatment

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Interventions and Calculations

For sterilisation (Glass bulb, stainless steel)

Short Retention Systems

Basic Physical and Chemical Systems

The components of the water system contrubutes to the Embodied Carbon of the whole system. Inspection and replacement frequency could affect how efficient your system is. The draft British Standard for greywater recycling BS 8525-1 (2009) estimated the frequency of component replacement. The table on the side lists out some of the most common used components within the system and its corresponding life expectancy. Most of these components can also be applied to the Rainwater Harvesting System.

Bio-mechanical Systems

1 = Pre-treatment 2 = Reed Beds 3 = Post-treatment

System Maintenance

1 = Pre-treatment 2 = Aerobic Treatment 3 = Ultrafiltration 4 = Clean Water Storage

Components

Frequency

Filters, membranes, biological support media and strainers

Annually

Biocide, disinfectant or other consumable chemical

Monthly

UV lamps (where fitted)

Every 6 months

Storage tank/cisterns

Every 10 years

Pumps and pump controls

Annually

Pipework

Annually

Supports and fixings

Annually

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Calculations Parameter Embodied Carbon Emission For Water Harvesting

Operational Carbon Emission

Carbon Footprint = (Material + Manufacturing + Distribution + Delivery to Site) footprint

Conversion Factor

Material Footprint = Unit footprint (ICE Database) x Mass of Material Manufacturing Footprint = Material footprint x % Manufacturing overhead

Boiler

Energy

Carbon Emission (kg/kWh)

Object

Energy Used (kWh)

Electricity

0.21233

Hotwater Boiler

*For full calculation please refer to “Energy and carbon implications of rainwater harvesting and greywater recycling”

Operational Carbon Emission for Water Recycling The components of these system types are a mix of materials and of static, mechanical and electrical operations. As such it is not appropriate to model the systems as single entities with a particular operational life. Instead the individual operational life of each component was included which resulted in a model consisting of “umbrella” systems under which individual components were replaced as and when required to maintain the system integrity. This Carbon Calculation study would only focus on the embodied carbon of the Water Tank

Operating Carbon Footprint = Sum of Energy used for (pumping +Treatment) x electricity emissions The following figures for are obtained from “Energy and carbon implications of rainwater harvesting and greywater recycling”

Water Harvesting System Systems

Component Material

Rainwater harvesting

See Previous Page

Grey Water Recycle

See Previous Page

Water Collection Tank Mass According to the report “Energy and carbon implications of rainwater harvesting and greywater recycling” Poly Ethline (PE) Tanks appears to have the least carbon foot print, our estimation for tank embodied will be based on PE.

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System

Carbon Emission (kgCO2e/m3)

Energy Consumed (kWh/m3)

Direct Feed

0.82

1.5

Header Tank

0.55

1.0

System

Carbon Emission (kgCO2e/m3)

Energy Consumed (kWh/m3)

Grey Water System

Tank Size (L)

Tank Mass (kg)

GW Small -Scale MBR

1.9

3.5

1000

1500

GW Short Retention, 1WC

0.34

0.6

3000

GW Small-scale biological

0.34

0.6

5000

100

GW Small-scale biological

0.82

1.5

7200

150

GW Larger Scale, Multi Media

1.4

2.5

10000

200

GW Larger Scale, MBR

1.4

2.5

14500

275

24500

400

30000

550

37200

700

50000

900

Interventions and Calculations

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Calculations Parameter

Water Usage Carbon Emission The Conversion factors are published by the UK Government for Carbon Emission estimation use. The factors are suitable for UK-based organization of all sizes. These calculations are based on data from the UK water companies Carbon Accounting Workbooks.

Conversion Factor

Outline Methodology In this calculation, we will try and quantify as many of the mentioned parameters as said in the methodology as possible. The water usage and people’s water usage habit is un predictable therefore calculations are based on average results. More accurate results can be deduced if a specific building is being looked at. We will be looking into different devices and for water saving measures and their impact in carbon and water reduction. at the end of the chapter, we shall be able to calculate the potable water supply and wastewater treatment offset within the input building. This could then be used to add onto the total carbon output. A major study within the calculation would be the Embodied Carbon and Operational Carbon of the water reduction systems. Different systems for Rainwater Harvesting and Greywater Reuse shall be looked into. Most of the findings are concluded from the document “Energy and carbon implications of rainwater harvesting and greywater recycling” (Parks et al, 2010).

Water Type

Carbon Emission (kg/L)

Potable Water Supply

0.000149

Wastewater Treatment

0.000272

Water Saving Devices These are the average water saving measures that we have applied to the calculations when comparing normal homes and homes that uses water saving devices. Saving Device

Water Saving(%)

Metering

0.15

Washing Machine

0.816

Tap

0.64

Dish Washer

0.769

Bath

0.667

Shower

0.775

Toilet

0.5

Hot Tap

0.64

Cold Tap

0.64

Typology Water Demand Benchmarks A few different types of typologies are investigated, the following data shows the Water Demand of each typology.

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Interventions and Calculations

Typology

Water Usage (L/Person/Day)

Daily Non Potable Water Demand (L)

Potential GW yield

GW Demand (L) WC,Laundry & Others

House

142

51.9

91.9

51.9

Apartment

142

61.3

27.7

Hotel

54.8

18.7

18.1

School

10.5

1.1

8.2

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Calculations Demonstration All outcome are measured in days

Typology

Water Used (L/Person/Day)

Building population

Property Roof Area (m2)

Potable Water consumption (L)

Water Feeding Type

House

142

2.39

29.2

Direct Feed

Output

Typology

Water Used (L/Person/Day)

Building population

Property Roof Area (m2)

Potable Water consumption (L)

Water Feeding Type

Apartment

142

286

91.9

40725.6

GW Larger Scale, Multi Media

Output

Total Water Waste Water Consumption Output(L) (L)

PW CE(kgCO2e)

WW CE(kgCO2e)

Tank size(L)

Operational Carbon (kgCO2e)

Embodied Carbon (kgCO2e)

Total Water Waste Water Consumption Output(L) (L)

PW CE(kgCO2e)

WW CE(kgCO2e)

Tank size(L)

Operational Carbon (kgCO2e)

Embodied Carbon (kgCO2e)

Without Water Saving Devices

339.38

0.050

0.092

8.493

Without Water Saving Devices

40725.6

40318.344

6.068

11.077

27.337

With Water Saving Devices

158.15

122.1

0.023

0.033

1393.84

10.393

0.019

With Water Saving Devices

19448.5

14654.7

2.897

3.987

12445

28.737

0.127

All outcome are measured in days

Potable Water Offset = 339.38 - 158.15 = 181.23L Wastewater Offset = 339.38 - 122.1 = 217.28L Water Carbon Offset = (0.051+0.092) - (0.023+0.033) = 0.087 kgCO2e Operational + Embodied = 10.412 kgCO2e 652

Interventions and Calculations

Potable Water Offset = 40725.6 - 19448.5 = 181.23L Wastewater Offset = 40318.344 - 14654.7 = 217.28L Water Carbon Offset = (6.068 +11.077) - (2.897 + 3.987) = 10.261 Operational + Embodied = 28.864 kgCO2e 653

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Demand and CO2e Results Domestic Water Use

Domestic Water Use Kitchen Sink 13.6L Dishwasher 3.4L Bath 27.1L

Carbon Emissions

Type of Water Water Output

Carbon Emissions

Shower 84.8L

Carbon Supply Emissions 0.0236 kgCO2e

Potable Water 227.4L

Bathroom Cold Tap 74.7L Greywater 105.3L

Blackwater 105.3L

Carbon Wastewater Emissions 0.0332 kgCO2e

Bathroom Hot Tap 23.8L Washing Machine 30.5L Rainwater Harvesting

Groundwater Dispersal Toilet 74.6L

Greywater Reuse 105.1L

The above sankey diagram shows the output of our calculations to include rainwater harvesting and greywater reuse for residential use. Carbon supply emissions relates to the supply of potable water. Potable/ drinking water typically also supplys water for the washing machine, toilet, garden and car but in our model these sources are supplied by rainwater and greywater harvesting. Our sankey diagram shows that an additional 105.3L of greywater is available for reuse in addition to the 105.1L which is already reused.

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Interventions and Calculations

Garden 3.4L Car 3.4L

However, the average needs of a household show that this is in excess of what is required therefore the 105.1L of greywater joins the blackwater sewage. This illustrates that there would be a significant reduction in the requirement for potable water if localised treatment of greywater allowed for it to be reused in situations that currently require potable water. Domestics uses such as the kitchen sink, dishwasher, washing machine and toilet all go directly into blackwater due to the organic matter, grease and chemicals present in the wastewater.

Image created by author

Greywater Reuse 105.1L

Another considerable saving could be made with localised treatment systems of blackwater into grey water, for example, reed beds. The blackwater flows into a collection tank where it settles and microbes break down the materials - similar in concept to a septic tank. As a purifying step the water is given a settling period which usually occurs in another chamber of the tank. The resulting water is rich in nitrogen and can be discharged into Phragmite reed beds. The Phragmite reeds pump oxygen from their leaves to their submerged roots and encourage large

quantities of microbial growth which clean the water to a high standard (Sustainable Build, 2013). In summary, with rainwater harvesting and greywater reuse both the carbon supply and wastewater emissions have reduced however, there is still potential to optimise the water usage and wastewater treatment further. The increased optimisation would be individual to each circumstance for example some residential homes may have the garden space for a reed bed whereas others may not.

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Emissions Summary

33%

Calculation Summary

Supply Water Carbon Emissions (kg)

55%

33% Fresh Water Saving*

For every household whether in a house or in an apartment by utilising rainwater harvesting and greywater reuse, they could save 33% of fresh water, 33-35% of water supply carbon emissions and 55% of wastewater carbon emissions.

Wastewater Carbon Emissions (kg)

*for both a house and apartment per day

55%

Wastewater Carbon Emissions (kg)

35%

Supply Water Carbon Emissions (kg)

Drinking Blackwater Rainwater Grey water

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Interventions and Calculations

Ultrafiltration UV Light

Filter Membrane

Storage

Ultrafiltration

Drinking Water Supply Centralised & Decentralised

UV Light

Filter Membrane

Storage

Image created by author

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Water Treatment Systems Decentralised

Centralised

Image created by author

Characterised by large-scale plants that serve expansive municipal or regional service areas

Uses smaller plants placed close to the water supply or treatment need, serving a more localized area

The UK has over 416,175 kms of water mains and more than 393,460 kms of sewers – combined, that’s enough to stretch to the moon and back. The UK delivers 16.6 billion litres of highquality water every day to 63.9 million people. The UK’s water and sewerage utilities provide some of the cleanest drinking water in the world. 99.97% of water samples in England and Wales met the Drinking Water Inspectorate’s standards in 2013.

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Interventions and Calculations

Well-developed technology

Reduce installation cost

Requires less energy

Off grid water supply

Economy of scale

Scale as you grow

Can use distant water sources

Lower operating cost

According to a new study, reusing waste water for non-drinking purposes in decentralised plumbing networks can increase the efficiency of water delivery in urban areas. Researchers in San Francisco determined that, depending on the local terrain, a decentralised water supply might result in energy savings and a 30 percent reduction in greenhouse gas emissions from water treatment. Improvements in developing watertreatment technologies are projected to result in even more savings, which could help improve the efficiency of city water delivery (Kavvada et al, 2016).

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Decentralized Treatment System Pre-treatment

Bar Screen

Grinder

Grit Chamber

Primary and Secondary

Flow Equalization

Disinfection

UV Disinfection

Membrane Bioreactors

Chlorine

Storage

Sludge

Centralized Treatment System

Wastewater

Primary and Secondary Treatment

Tertiary

Coagulation

Decentralised System The water utility industry is under enormous pressure to meet the challenges of increasing demands due to population growth and lifestyle changes, and depleting freshwater resources. Deteriorating supply infrastructure makes the task of meeting water demands even more challenging. The combination of source and supply challenges encouraged the consideration of sustainable and reliable alternatives for future water supply management. On-site greywater reuse is one such alternative that is becoming increasingly popular for its sustainable benefits such as ready availability,

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energy savings, reduced freshwater withdrawals and less effluent runoff. While the treatment technologies for making it economically viable are currently being investigated by other researchers, this paper investigates the improvement in supply reliability when traditional water supply systems are complemented by on-site greywater reuse. A robust computational model is developed for quantifying reliabilities of traditional and on-site greywater reuse systems for a given study area. The results revealed that there is up to 17% of improvement in supply reliability due to the on-site greywater reuse systems. A

Interventions and Calculations

Flocculation

Water Reuse

Rapid Sand Filtration

Chlorine

Storage

Landfill, Land Application

one-way sensitivity analysis conducted on the results indicated that the observed reliability improvement is sensitive to system age, pipeline roughness, treatment efficiency and allowable use of reclaimed water. Further research is needed to investigate the value of this reliability improvement by considering the life cycle cost and energy implications of on-site greywater reuse alternative.

4 Image created by author

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Waste Water Treatment Circular Metabolism

5 4 3

1 Attention has increasingly focused, over the last decade, on circular economies that are associated with the alleviation of environmental pressures to promote sustainable development. Making cities inhabitable, safe, resilient and sustainable while ensuring sustainable consumption and production patterns don’t degrade the environmental resources is key for the long term goal of reaching carbon zero cities. Circular metabolism lays out steps to ensure initial input of resources that can be reused to reduce as much waste as possible and this concept can be applied to the water cycle. Waste water

662

Interventions and Calculations

Image created by author

treatment plants can go beyond just cleaning water to harness methane for energy and nutrients to enrich soil. Recirculating the resources within the city would reduce resource imports and wastes. Transitioning fully to the circular metabolic approach in the water sector using decentralized technologies is essential to meet growing urban needs and will require major changes in the way we plan, design and fund our infrastructure. We must problemsolve complex urban water issues in creative and sophisticated ways, and work to embed future ready urban water systems in cities (Lucertini and Musco, 2020).

1 2

Water Source Industrial

3 Water Purification 4 Residential

5 Farming 6 Commercial

7 Agriculture 8 New WWTW

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Scale Of Improvement

High Carbon Reduction Potential

How do we improve?

Low Carbon Reduction Potential

Appliances

Building

Urban

County

National

Global

Water Metering Efficiency Rating of Appliances Low-flush toilets Low-energy Electric Shower Pump Type

Rainwater Harvesting Grey Water Reuse Green Roof Evapotranscription Water Heating Efficiency

Decentralised Systems Sustainable Urban Drainage Greater Surface Permeability Leakage Reduction Nutrient Reuse

County Council Policy Change Transport of Water Wastewater Treatment

UK Government Policy Change Water Source Changes

National water shortages Potable water quality

Improvements can be made to every scale of the urban water systems in Manchester and in the UK. Whilst strategies at the appliance and building scale are effective they need to be replicated at a much broader level to have a significant impact. Our project focuses primarily on the appliance, building and urban scales. To summarise, the most effective carbon reduction strategy for water is National and County Policy changes which enforce greater appliance, building and urban water efficiencies as choicedefaults.

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Suggestions and Summary

We need UK and greater building

Manchester policy changes for and urban water efficiency Images altered by author from information: Google Earth (2021) 665

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Executive Summary Recommendations from Reseach to reach Net Zero

We need to reduce CO2 release from the water sector

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• Manchester council needs policies that set carbon emission reduction goals for the water sector. • We need to promote the scale of impact behavioural change can have on everyday carbon and water usage reduction. • Replace energy inefficient appliances with low kW using appliances (especially showers and toilets) for the least carbon impact. • Basing the water supply and wastewater treatment systems of new developments on a circular metabolism model that is potentially decentralised and selfsufficient would reduce costs, allow for scalability and reduce operational carbon. • Being aware of the amount of water used and by extension the carbon usage is the first step to reduce the amount. Smart water meters could be installed to give residents tips to reduce their footprint based on their consumption levels.

Suggestions and Summary

Repacement of Energy Inefficient Devices

• Efficient use of existing water through rainwater harvesting and greywater resuse significantly reduces the potable water required by a household and therefore a household’s carbon emissions. Schemes that reward households who adopt these strategies could have a considerable positive impact. • Reduction of water wastage in other sectors such as energy generation will help to mitigate water shortages which is an effect of climate change.

Water Use Monitoring

• Sustainable Urban Drainage Systems should be employed in areas of high impermeability in order to mitigate flooding and carbon used in the clean up.

Rainwater Harvesting and Greywater Reuse

Towards Net Zero

Sustainable Urban Drainage

Behavioural Change

Reduce Water Usage

Manchester Policy

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IWA. (n.d.) A Resilient, Cool and Green City. [Online] [Accessed on 14th November] https://iwanetwork.org/city/sydney/ Johnson, P. (2019) Why Private Residential Water Recycling has Stalled in Sydney. [Online] [Accessed on 14th November] https://thefifthestate.com.au/urbanism/environment/why-private-residentialwater-recycling-has-stalled-in-sydney/ Kavvada, O., et al. (2016) ‘Assessing Location and Scale of Urban Nonpotable Water Reuse Systems for Life-Cycle Energy Consumption and Greenhouse Gas Emissions.’ Environmental Science and Technology, 50 pp. 13184-13194. Littlewood, J. and Bennett, D. (2019) Davyhulme WwTW Modernisation Project. [Online] [Accessed on 14th November] https://waterprojectsonline.com/custom_case_study/davyhulme-wwtwmodernisation-project-3/ LivingHouse. (2014) Positive or Negative Shower Pumps. [Online] [Accessed on 16th November] https://www.livinghouse.co.uk/blog/shower-pumps/?fbclid=IwAR3tpYpBLJAP4uAAbP7aQT0UYv VKUI55CDljcsPk466Et_enbSNJeAoaCEA Lucertini, G. and Musco, F. (2020) ‘Circular Urban Metabolism Framework.’ One Earth, 2 pp. 138142. Majid, A., et al. (2020) An Analysis of Electricity Consumption Patterns in the Water and Wastewater Sectors in South East England, UK.

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Manchester City Council. (2012) Manchester’s Local Development Framework: Core Strategy Development Plan Document.

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Matthew Nichol Photography. (2018) River Irwell Crossing. Photograph. (25th July): Structurae.

Water and Wastewater Companies for Climate Mitigation. (2018) The Roadmap to a Low-Carbon Urban Water Utility. p. 51. London: IWA Publishing.

Met Office. (n.d.) UK and Global Extreme Events - Heavy Rainfall and Floods. [Online] [Accessed on 14th November] https://www.metoffice.gov.uk/research/climate/understanding-climate/uk-andglobal-extreme-events-heavy-rainfall-and-floods

Water Source. (2019) Benefits flow from Green Square Water-Saving Drain Project. Built Environment. [Online] [Accessed on 14th November] https://watersource.awa.asn.au/environment/builtenvironment/benefits-flow-from-green-square-water-saving-drain-project/

OFWAT. (2010) Playing Our Part – Reducing Greenhouse Gas Emissions in the Water and Sewerage Sectors. Birmingham: OFWAT.

Water UK. (2020) Net Zero 2030 Routemap.

Owlshall. (2018) What Size Rainwater Tank Do I Need? : [Online] [Accessed on 17th November] https://www.owlshall.co.uk/rainwater-harvesting/knowledge-base/what-size-rainwater-tank/

World Population Review. (2021) Manchester Population 2021. [Online] [Accessed on 16th November] https://worldpopulationreview.com/world-cities/manchester-population

Parkes, C., et al. (2010) Evidence: Energy and Carbon Implications of Rainwater Harvesting and Greywater Recycling. Bristol.

Wren, G. and Christensen, T. (2021) UK was First Major Economy to Embrace a Legal Obligation to Achieve Net Zero Carbon Emissions by 2050. Climate Scorecard. [Online] [Accessed on 28th October] https://www.climatescorecard.org/2021/07/uk-was-first-major-economy-to-embracea-legal-obligation-to-achieve-net-zero-carbon-emissions-by-2050/

Reffold, E., Leighton, F., Choudhury, F. and Rayner, P. S. (2008) Greenhouse Gas Emissions of Water Supply and Demand Management Options. Environment Agency. Ryan, S., Fitzsimons, B., Fawcett, C. and Melling, A. (2019) Environmental and Social Costs of Water Resources Management Plan 2019 Supply Demand Options. United Utilities. Statista. (2014) Household Shower Type in the United KIngdom (UK) from 2010-2012. Statista Research Department. Sustainable Build. (2013) Grey (and Black) Water Recycling Design. Sustainable Design. [Online] [Accessed on 28th October 2021] https://sustainablebuild.co.uk/grey-and-black-water-recyclingdesign/#Blackwater_Recycling Triton. (n.d) Electric Showers. [Online] [Accessed on 16th November] https://tritonshowers. co.nz/?fbclid=IwAR27YyBUAe4uN3aJ28tIIVRUJRVrdgYj8khDxPvjp_lLjdEjgOMZSsBU3P4 UN Environment Programme. What is Urban Metabolism. (2017) Video, 31st August. YouTube. 2:40. [Accessed on 14th November 2021] https://www.youtube.com/watch?v=uu-a1hFEV7Q United Nations. (n.d) Goal 6: Ensure Access to Water and Sanitation for All. [Online] [Accessed on 16th November] https://www.un.org/sustainabledevelopment/water-and-sanitation/?fbclid=IwA R3tpYpBLJAP4uAAbP7aQT0UYvVKUI55CDljcsPk466Et_enbSNJeAoaCEA United Nations. (n.d) Water Facts. [Online] [Accessed on 15th November] https://www.unwater. org/water-facts/?fbclid=IwAR1oC_8j8PrP0DxP9mRjV-_7LQwraAtaTv6ScbjmFyXVHGjc6Rt9pLXEv us

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Smart cities rely on data and digital technology to work towards making bette decisions and improve the quality of life More comprehensive, real-time data gives agencies the ability to watch events as they unfold, understand how demand patterns are changing, and respond with faster and lower-cost solutions. INTRODUCTION What are smart cities?

SECTION ONE

SECTION TWO

SECTION THREE

Smart city systems

Sensing the city

BIG DATA and smart dashboards

CONCLUSION Summary and barriers

SMART CITIES

CONTRIBUTIONS CONTRIBUTIONS TOWARDS ZERO CARBON

Irina Balan, Jordan Bartlett

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Zero Carbon Cities673

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Introduction Definitions

Smart Cities+ are being redefined as places where different actors employ technology and data to make better decisions and achieve a better quality of life. (McKinsey Global Institute, 2018)

Big Data+ The large volume of structured and unstructured data that is now available from buildings, transport systems, people, etc. that cannot be analysed using traditional data - processing techniques. (Fleming, 2017)

ICT+ (Information and Communication Technology) encompass all the devices, networks, protocols and procedures that provide access to information through telecommunications. (Bwalya et al., 2011)

Internet of Things+ is defined as a global web to which all physical devices with sensing and processing abilities are connected and through which they communicate and exchange data. (Fleming, 2017)

Sustainable Development + is a development that meets the needs of the present without compromising the ability of future generations to meet their own. (Höjer and Wangel, 2015)

Smart Sustainable Cities+ use ICTs to improve quality of life, efficiency of urban operation and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social and environmental aspects. (Höjer and Wangel, 2015)

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Definitions Smart city initiative – streetlighting

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Introduction What is a Smart City?

The Earth’s population living in cities, surpassed the rural one in 2008 as a result of the rapid urbanisation phenomenon(UN, 2008). The United Nations Population Fund stipulates that the number of urban inhabitants is expected to increase to 70 per cent by 2050, which highlights the challenges faced by cities due to urban growth: economic risks, increased migration, urban sprawl, social disparity, demographic ageing (Drápalová and Wegrich, 2020; UN, 2008). The increasing rate of urbanisation coupled with global environmental problems and technological developments have resulted in a critical necessity and fundamental chance to reconsider the ways in which cities are managed and built. The Brundtland commission report in 1987 introduced the concept of sustainable developments with the slogan “think global, act local” to subside the global environmental and social problems (Höjer and Wangel, 2015). Currently, the most pressing issue in the previously mentioned category is climate change which is driven by human activities. Here, cities are considered to be responsible for more than 70% of greenhouse gas emissions and therefore, the systems contained within play a major role in the decarbonisation of the global economy, i.e. in order to ensure that the future of the next generations is not compromised (Wei et al., 2021). Moreover, 25 megacities emit are responsible for 52% of the world

urban GHG emissions. The Paris Agreement introduced in 2015, represents a global effort for climate action aimed towards reaching carbon neutrality by 2050 to avoid an increase in temperature by 1.5 Celsius degrees scenario (Rogelj et al., 2019). Therefore, a top priority for cities is to find ways to address these issues and, as a result, to improve the quality of urban life. One approach to the resolution is established on the use of new technologies which enabled the rise of an emerging paradigm, that of the smart city. Among the first public smart city initiatives were Cisco’s Connected Urban Development Program in 2005 and IBM’s Smarter Cities campaign in 2009, which promised to make cities thriving and sustainable with the help of innovative technologies (IBM, no date; Villa and Wagener, 2008). While there is no agreed consensus on their definition, Smart Cities are generally defined by the fusion of conventional infrastructure with Information and Communication Technologies (ICT) to make better decisions and improve citizens’ quality of life. They use big data and Internet of Things (IoT) to manage the infrastructure and to facilitate a feedback and dialogue loop with the actors involved in and affected by the smart city initiatives (Dhakal and Ruth, 2017).

Rapid urbanisation

Urban growth & related issues

Relience on hinterlands for resources

Carbon emissions

Global perspective of local actions / inactions

Climate change

+ ICT spikes consumption

Technological developments

New ways to build cities

IoT Improved quality of life

Smart systems efficiency

SMART CITIES

ICT Big Data

Digitalisation to drive down emissions

THE FACTORS WHICH LED TO SMART CITIES FORMATION

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Introduction What is a Smart City?

From a different angle, the smart city concept looks to address the issues of the 6 dimensions within its structure: smart governance, smart economy, smart mobility, smart living, smart environment and smart people to improve their efficiency via technical solutions. However, there is no hierarchy within them meaning that they are all assigned the same value which makes it difficult to assess whether smartness delivers the outcomes or not (Höjer and Wangel, 2015). Smart cities epitomise a redefinition of municipalities into technology challenges. Technophiles often consider all urban problems to be an outcome of ineffectiveness and have a smart solution. As a result, the Smart City is at present a concept led by the business sector. It is a catchword that attracts interest in exploitation from companies involved in ICT and infrastructure (Höjer and Wangel, 2015). In 2021, there were 118 cities worldwide implementing smart initiatives and therefore, considered smart cities according to the Smart City Index 2021 report (IMD, 2021). However, they implement different numbers of initiatives which makes a comparison between cities impossible. Such initiatives include: smart street lighting systems, smart grid platforms, data-driven traffic management, smart leakage management and repair system, smart electric cars chargers, intelligent workspaces etc. These can help achieve carbon neutrality through

digitalisation of the systems involved, which is enabled by a transition to wireless networks and connection of devices to IoT. Data generated by these systems can then be analysed and drive future decisions. While these smart initiatives are of significant importance in mitigating the environmental impact of cities, they do not represent an indicator of city performance but rather a reflection of the efforts aimed at achieving a better quality of life (Höjer and Wangel, 2015). This highlights the lack of framework in the labelling and assessment of smart cities. Therefore, smartness does not hold any value other than denoting systems and products in which ICT is a key component. Here, a definition of sustainability is crucial in knowing for what purposes smart technologies should be used. While ICT have changed the way society functions, they have also led to cheaper products and a spike in consumption which coupled with the dependency of cities on ‘global’ hinterlands for resource extraction, has led to the consideration of global responsibility of the actions within cities (Höjer and Wangel, 2015). Therefore, smart sustainable cities are a solution for a low-carbon future.

SMART CITIES

Smart initiatives

Mitigate environmental impact X

Smartness not an indicator of city performance

Sustainability - know what to strive for (technologies)

Competitiveness SMART SUSTAINABLE CITIES Improved quality of life

Efficiency of urban operations

Meets the needs of present and future generations

DECARBONISATION

FROM SMART CITIES TO SMART SUSTAINABLE CITIES

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What is a Smart City?

679

CITY FORMATIONS

SPRAWL CITY

SATELLITE CITY

SMART CITY

1853

1960s

2000+

2021+

Industrial Economy Initiated to reduce transport costs Rapid growth brought health and safety dangers Awful sanitation

Industrial Economy Low density, single family dwellings significant car dependency Unsustainable growth

Post Industrial transition Own local governments Not an extension of nearby city High proportion of workers commute to parent city

Characteristics

2 Characteristics

1 Characteristics

Characteristics

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Disruptive Economy Technology centric Seeking short term efficiencies

The evolution of city growth In order for us to look at smart cities, we first must understand how cities formed, and how they evolved. Manchester initially was one of the cornerstones to Britains industrial revolution, with much of the city forming from much of what is the origins of the cotton industry H.B. Rodgers (2020) Yet, Manchester can now be seen as a city in transition. It is facing an ongoing battle of identity, huge redevelopments which are transforming the city, and its

680

What is a Smart City?

dependence on the insecure base of textiles is declining. H.B. Rodgers (2020) However, Manchester has a strong and resilient digital sector, which is often cited as being the second technology city, outperforming all other cities out side of London (The Data City, 2019). Taking this into consideration, we can begin to develop the thinking of how might the city further implement smart city technologies,. Following its consultation period, MCC want to ensure that the city can be more inclusive, sustainable, and resilient with digital inclusion at its heart (Manchester City Council, 2020)

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System

A future roadmap Green Net-Zero

ADVANCING OFFSURE WIND

DRIVING THE GROWTH OF LOW CARBON HYDROGEN

UK HM Governent - Race to zero Our strategy for net zero is to lead the world in ending our contribution to climate change, while turning this mission into the greatest opportunity for jobs and prosperity for our country since the industrial revolution. Removing dirty fossil fuels from the global economy will lead to the creation of vast new global industries from offshore wind to electric vehicles and carbon capture and storage. By moving first and making the United Kingdom the birthplace of the Green Industrial Revolution we are building a defining competitive edge. Through our Ten Point Plan we have already attracted over £5.8 billion of new inward investment in just over ten months, and will create and support hundreds of thousands of new high skilled, high wage green jobs. This strategy sets out how we will make historic transitions to remove carbon from our power, retire the internal combustion engine from our vehicles and start to phase out gas boilers from our homes. But it also shows how we will do this fairly by making carbonfree alternatives cheaper. We will make sure what you pay for green, clean electricity is competitive with carbon-laden gas, and with most of our electricity coming from the wind farms of the North Sea or stateof-the-art British nuclear reactors we will reduce our vulnerability to sudden price rises caused by fluctuating international fossil fuel markets.

The United Kingdom is not afraid to lead the charge towards global net zero at COP26, because history has never been made by those who sit at the back of the class hoping not to be called on. Indeed, as we set an example to the world by showing that reaching Net Zero is entirely possible, so the likes of China and Russia are following our lead with their own net zero targets, as prices tumble and green tech becomes the global norm. For years, going green was inextricably bound up with a sense that we have to sacrifice the things we love. But this strategy shows how we can build back greener, without so much as a hair shirt in sight. In 2050, we will still be driving cars, flying planes and heating our homes, but our cars will be electric gliding silently around our cities, our planes will be zero emission allowing us to fly guilt-free, and our homes will be heated by cheap reliable power drawn from the winds of the North Sea. And everywhere you look, in every part of our United Kingdom, there will be jobs. Good jobs, green jobs, well-paid jobs, levelling up our country while squashing down our carbon emissions. That is the clean and prosperous future that awaits every one of us as the UK leads the world in the race to net zero.

NEW AND ADVANCED NUCLEAR POWER

SHIFT TO ZERO EMISSION VEHICLES

GREEN PUBLIC TRANSPORT

JET ZERO + GREEN SHIPS

GREENER BUILDINGS

The Rt Hon Boris Johnson MP

PRIME MINISTER

Existing model for a self sustaining city:

INVESTING IN CARBON CAPTURE GOV STIMULATION

INDUSTRIAL REVOLUTION INVESTEMENT

INNOVATION

Key Drivers

PROTECTING OUR NATURAL ENVIRONMENT

NEW CITIES JOBS + GROWTH

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Race to Zero

PRIVATE WEALTH

GREEN FINANCE + INNOVATION

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Smart City Industry Who owns the city?

Currently, there is a growing number of companies which develop smart solutions, such as: Cisco, IBM, Siemens, Microsoft, Hitachi, Huawei etc. Townsend (2013: 63) emphasises three main developers in the smart cities market, i.e. Cisco, Siemens and IBM and the scope of their involvement: “[i]f Siemens and Cisco aim to be the electrician and the plumber for smart cities, IBM’s ambition is [to] be their choreographer, superintendent and oracle rolled into one”. Although the smartness of the products is not related to their performance but to the efforts made in increasing the quality of life, the smart city market

leveraged on the false assumption of the meaning of smart as intelligent, efficient and the solution to all problem humanity may face. It is a growing market, with a wide range of proposals from tools which make the urban systems ‘smart’ to utopian proposal of cities as test beds for new technologies.

CISCO SIEMENS

Example of initiatives and proposals: • Toyota - largest automaker in the form of the Woven City in Japan. A fully autonomous community designed to test new technologies like automated driving, robotics, and artificial intelligence (AI) in a real-world environment (Marr, 2021). • IBM - test systems for monitoring city infrastructure and detecting problems in city of Markham, Canada (GlobalData Thematic Research, 2020).

MICROSOFT IBM EXECUTION

The Smart Cities are generally considered to be a concept owned by the business sector. This aspect has wider implications in the development of cities due to the push for the privatisation of the public domain through the privately funded smart city proposals. The first smart city initiatives, as stated in the introduction, were created by Cisco in 2005 and IBM in 2009 which adds further emphasis to who owns the city. Unknowingly, every time people interact with a smart device or system, they are encouraged to experience the urban streetscape and residential space from the manufacturer’s perspective. The smart initiatives are developed as out-of-the-box solutions to be sold to municipal administrations as products part of the smart city framework. Most of the ICTs needed to enable the smart city already exists. However, the interconnection and synchronization of these technologies, so that they can collaborate, are not as developed. This aspect represents a challenge and what makes the market attractive to the corporate sector.

SAP

HUAWEI

ERICSSON PANASONIC

• Cisco - created tools for its smart city framework: Cisco Kinetic Systems. It offers solutions for cities network architecture and smart systems management. The company has also developed a method to turn smart metering technology into an open, enterprise-class network for utilities (ibid.). • Siemens - developed city performance tools to monitor GHG emissions and built a baseline for the generating systems. The company also developed tools for digital urban mobility as well as smart building solutions for monitoring and control purposes (ibid.).

HITACHI

SCHNEIDER ELECTRIC

ORACLE BOSCH STRATEGY CORPORATE LEADERS IN SMART CITY SOLUTION SUPPLIERS LEGEND: LEADERS

CONTENDERS

CHALLENGERS

Source: Graph [adapted from] Navigant, 2017:online)

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The City as an Experiment

Not scalable to smaller urban areas amplify social inequality + cities competitiveness

Utopian visions Lack of adaptability planned infrastrcuture can become obsolete

The approach needed towards smart cities is holistic. Citizens must be more than just consumers of smart products, have their needs fulfilled, and the municipal benefits of smart solutions carefully considered to inform the evolution, distribution, and implementation of disruptive technologies. Technology itself can create significant breakthroughs in the way cities operate, like preventing crime, minimising water and energy losses from the urban grids, efficient waste collections and decreased traffic congestion. Nonetheless, the underlying problem for deploying technologies and smart solutions is the scale at which they are conceived. Clark (2020) argues that if they are not scalable to smaller urban areas, they only amplify social discrepancy by supplying citizens with unequal distribution of resources, highlighting a different expression of the underlying economic issue, not the urban one. As a result, smaller urban agglomerations and secondary cities to the primary smart city will suffer from economic competitiveness. They will be forced to embrace the projects designed and customised for another city – with different state and quality of infrastructure, priorities, and challenges – an approach demonstrated in the design of various smart urban schemes and solutions (Clark, 2020). As a result, cities like Masdar and Songdo cannot attract enough inhabitants, while in Toronto, citizens’ privacy was put in jeopardy, and the proposal was withdrawn. These are technological utopias developed by the private sector in which governments often do not intervene. Thus, they push the boundaries of intervention and regulations for their own benefit, not for the citizens upon which the technology is tested. Architects have highly contributed alongside technology suppliers to design utopian cities in the name of human evolution, transforming cities in living laboratories (e.g Tesola by BIG and Woven City by Toyota).

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Utopian visions

Initiated and owned by private companies not governments - limited intervension A product / business model for worldwide replication

Data privacy concerns / Surveillance + Monetisation of data

Narrow vision technology the solution to what cities need to fix

City as living laboratory for companies and architects to test new technologies and concepts

Built from scratch - no need to offer solutions for municipal issues

Dessert cities unsustainbale but justified as a reasearch effort for extraplanetary replication

Desolated landscapes inability to attract residents

High cost + Built for capital flow for the initiative owners

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Smart City Systems An introduction: Public Transport

Smart Economy Created by Adrien Coquet from the Noun Project

Waste Smart Mobility Created by Nithinan Tatah from the Noun Project

IT connectivity Smart Environment Created by Nithinan Tatah from the Noun Project

Power

Air Quality

Intelligence Weather

Smart People

Created by zafdesign from the Noun Project

Smart Living Created by Jan Alexander from the Noun Project

Smart governance

Created by Kamin Ginkaew from the Noun Project

Sewer

Created by Lima Studio from the Noun Project

Smart vs Intelligent systems When we think of smart cities, and smart thinking, we can often refer to them instead as Intelligent systems. This intelligence is rooted in the collective combination of smart systems. Smart or intelligent systems allow for more malleable components to create a dynamic play of mutual responsiveness, while suiting themselves to contextual adaptation (Patrik schumacher 2017)

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Smart City Systems

The diagram on the right page shows elements of our city systems for which can be monitored and made smart through smart city technologies. For example, Intelligence can be derrived from evaluating ‘smart environment’which is a system of interconnected devices and sensors across a network which feeds data to be analysised about, air quality to name one, which informs the city of what the state of the system is, in order to execute change.

Water

Traffic

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Would you trade reduced privacy for better services?

42%

YES

How do you compare smart cities?

Smart City Index: “What strange phenomena we find in a great city, all we need do is stroll about with our eyes open.” Charles Baudelaire Mademoiselle Bistouri

For more than thirty years, the IMD World Competitiveness Center has pioneered research on how countries and companies compete to lay the foundations for sustainable value creation. The competitiveness of nations is probably one of the most significant developments in modern management and IMD is committed to leading the field. On the methodological side, IMD pursue efforts to make the SCI methodology and coverage ever better and more relevant to decision makers and analysts. IMD also strive to maintain the degree of coherence and continuity that will progressively allow the index to generate the longer-term time series required for urban policies and strategies. Fundamentally, the approach has not changed: In line with previous and ongoing efforts initiated and carried out by IMD’s World Competitiveness Centre, the Smart City Index presented here remains a holistic attempt to capture the various dimensions of how citizens could consider that their respective cities are becoming better cities by becoming smarter ones. Part of the SCI’s uniqueness is to rely first and foremost on the perceptions of those who live and work in the cities covered by the index, while providing a realistic recognition that not all cities start from the same level of development, nor with the same set of endowments and advantages. In SCI’s context, a ‘smart city’ continues to be defined as an urban setting that applies technology to enhance the benefits and diminish the shortcomings of urbanization for its citizens. (IMD, 2021)

Should data privacy be relaxed to progress smart cities? YES NO

54 SMART CITY RATING

AAA FACTORS RATING

AAA STRUCTURES

AAA TECHN.

GROUP

The IMD-SUTD Smart City Index (SCI) assesses the perceptions of residents on issues related to structures and technology applications available to them in their city.

This edition of the SCI ranks 118 cities worldwide by capturing the perceptions of 120 residents in each city.

There are two pillars for which perceptions from residents are solicited: The Structures pillar referring to the existing infrastructure of the cities, and the Technology pillar describing the technological provisions and services available to the inhabitants. The cities are distributed into four groups based on the UN Human Development Index (HDI) score of the economy they are part of.

43% 39% REFERENCES: White & Case 2020

Smart System SMART CITY RANKING

33%

H/Safety

Mobility

Technologies

Structures

Online reporting of city maintenance Residents App to give unwanted items Free public wifi CCTV cameras App for residents to monitor air pollution medical appointments online

Basic sanitation meets the needs Recycling services are satisfactory Public safety is not a problem Air pollution is not a problem Medical services provision is satisfactory rent 30% or less of a monthly salary

Car-sharing Apps/ lower congestion Apps for an available parking space Bicycle hiring Online scheduling and ticket sales information on traffic congestion

Traffic congestion is not a problem

Online purchasing of tickets to shows and museums has made it easier to attend

Green spaces are satisfactory

Online job listings IT skills are taught well in schools Online services provided by the city internet speed and reliability meet -connectivity needs

Employment finding services children have access to a good school Lifelong learning opportunities Businesses are creating new jobs Minorities feel welcome

Online public access to city finances Online voting has increased participation online platform where residents can -propose ideas Processing Identification Documents online

Information on local government decisions Corruption of city officials not a problem Residents contribute to decision making Residents provide feedback

Public transport is satisfactory

Cultural activities (shows, bars, and museums)

Activities

Opportunities

Governance 690

Smart City Systems - SCI

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Zurich 410,000

Manchester 550,000 Barcelona 1,600,000 Toronto 6,200,000

ZU BC

Singapore 5,900,000

Smart Cities - World View A map to show the number of smart cities, and thier locations, that we will explore. Although there are over 119 defined smart cities by the SCI, the ones chosen to explore offer a variety of initiatives that they are exploring in order to improve the performance of the city.

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Smart City Systems - SCI

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Smart Initiatives Case Studies - SMART CITY Zurich Singapore Toronto Barcelona Manchester

Smart City Index Population: 410k Life Expectancy: 84 GDP: 69,300

At number two on the SCI, Zurich is a leader in its ambition to become one of the greatest cities in the world. Smart city hub switzerland (2018) suggests that their approach is to promote cooperation and knoweldge sharing. Zurich aims to extend themselves as smart city which has the possibility to reduce time and costs for both the city, and its businesses. Zurich also aims to boost their city by encouraging dialogue and cooperation, through innovative citizen-oriented solutions. For Zurich, smart means connecting people, organisations and infrastructures in order to create social, ecological and added economic value (SCHS 2018) This smartness intends to offer the city through sensors and data networking to find more efficient solutions to urban infrastructures. The core principle for this rollout is to further a dialog between the city’s adminitstration and its citizens to strengthen participation and foster direct democracy. The SCI report shows that Zurich could leverage their smart city to reduce vehicle congestion.

Smart System H/Safety -Overview-

Pollution

Categorising city systems which affect citizens health, or ability to feel more comfortable.

Mobility -Overview-

Transport

Categorising city systems which help citizens move around the city, be it for work or pleasure.

Activities -Overview-

GreenSpaces

MIN

avv score

Technologies Online reporting of city maintenance Residents App to give unwanted items Free public wifi CCTV cameras make feel one feel safer App for residents to monitor air pollution medical appointments online

Car-sharing Apps/ lower congestion Apps for an available parking space Bicycle hiring Online scheduling and ticket sales information on traffic congestion

Traffic congestion is not a problem

Online purchasing of tickets to shows and museums has made it easier to attend

Green spaces are satisfactory

Categorising city systems which affect citizens ability to enjoy the city.

Opportunities -Overview-

Employment Categorising city systems which affect citizens ability to acquire skills, education and employement.

Governance -Overview-

Transparency Categorising city systems which affect citizens ability to engage with democratic decision making.

Structures

Public transport is satisfactory

CITY

MAX

avv score

Rent not affordable 70 100

Traffic Problem 59 100

Cultural activities (shows, bars, and museums)

Improve green spaces 77 100

Online job listings IT skills are taught well in schools Online services better public transport internet speed and reliability meet -connectivity needs

Online public access to city finances Online voting has increased participation online platform where residents can -propose ideas Processing Identification Documents online

Employment finding services children have access to a good school Lifelong learning opportunities Businesses are creating new jobs Minorities feel welcome

Information on local government decisions Corruption of city officials not a problem Residents contribute to decision making Residents provide feedback

Not enough new jobs 74

100

High Gov corruption 71 100

REFERENCES: https://switzerland-tour.com/tours/the-land-of-tales

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Smart Initiatives

Tool for calculating the energy saving of smart street lights:

SMART street Lighting Zurich

50 Billion IoT lights by 2030 LED bulbs: 100,000 hours of life vs sodium 12,000 20% less Crime

Benefits:

The smart streetlight is, however, just one piece of the puzzle. Baumann explains: “A smart city affects all areas of life – it allows flexible working patterns, shared mobility concepts and efficient management processes”. The economic area of Zurich is again a role model in this regard: the cities of Zurich, Winterthur, Schaffhausen and Zug, for example, are all realizing Smart City strategies, with top-class infrastructure in the form of a fiber-optic network now ready to handle complex applications in many places. Communication-enabled street lights allow solutions developed within the context of the Internet of Things (IoT). The Zurich-based start-up Loriot specializes in developing the networks associated with such objects and has realized IoT infrastructure projects in countries such as the Czech Republic, among others. Baumann states that the Zurich University of Applied Sciences (ZHAW) is an important proponent for the ecosystem and has participated in many projects of this nature. In this way, the Smart City ecosystem collects experiences and brings functioning solutions to the wider world.

System Parameters:

STREET GRID HEIGHT DISTANCE BETWEEN LAMPS

1. Time spent on 2. Distance between lamps 3. Lamp height 4. Cost of energy per KWH 5. Lamp type - LED, Sodium

1. Reduced maintenance, and lower costs

CALCULATE NUMBER OF LIGHTS HOW FREQUENTLY ARE LIGHTS ON/ HOW OFTEN ARE THEY AT 100%

4. Energy savings 5. Lower life running costs 6. Automatic switching between states, further reducing energy use

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RUN SIMULATION

ALTER VARIABLES VARIABLE ENERGY COST PER KWH

Perception

Network Layer

Application Layer

Calculations: 1. Formula, lamp seperation: {h}height

{3} distance factor

2. Streetlight efficiency Sim: N

e(N) =

INPUT EFFICIENCY CALCULATION

2. Reduction in C02 emissions 3. Reduction in light pollution

POSITION LAMPS

N=0

Pmax

e(N) - Energy consumed after N timesteps.

OUTPUT

Pmax = maximum rated power

‘X’ KWH/PER DAY ‘X’% MORE EFFICIENT COSTS + SAVINGS CO2 PRODUCED

T = duration of illuminance output by timesteps

1. Wireless Sensor Networks (WSN's) - Light sensors - Precipitation sensor - Pollution sensors

20% lower running costs

2. WSN's able to recieve and transmit data from gateways, to create a mesh network. - WIFI/5G / Cloud technology - GPS

65% lower Energy use

3. Responsive measures can be taken based on gathered data - Dimming street lights

5G Network

Peer2Peer

Wifi+

Open Data 697

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Smart Initiatives Case Studies - SMART CITY Zurich Singapore Toronto Barcelona Manchester

Smart City Index Population: 5.9m Life Expectancy: 83 GDP: $88,000

As a far eastern city, Singapore is making bold strides towards maintaining their position as the world leading smart city. However, even as a leading city, the SCI report shows that singapore still has a long way to go in order to make a perfect score. The report suggests that Singapore could benefit by further investing in technological infrastructures, to offer services like bike hiring and public transportation information, including online interfaces. In a report by the singapore government (2020) they suggest that the conditions are now ripe to take the digital and technological transformation to the next level. This particularily includes the use of Big Data, Internet of Things (IoT) and Artificial Intelligence (AI). This transformation is said to be in the aim of making the city more responsive to any impending crisis, with covid 19 having a dentremental impact on global economies.

Smart System H/Safety -Overview-

Pollution

Categorising city systems which affect citizens health, or ability to feel more comfortable.

Mobility -Overview-

Transport

Categorising city systems which help citizens move around the city, be it for work or pleasure.

Activities -Overview-

GreenSpaces

MIN

avv score

Car-sharing Apps/ lower congestion Apps for an available parking space Bicycle hiring Online scheduling and ticket sales information on traffic congestion

Traffic congestion is not a problem

Online purchasing of tickets to shows and museums has made it easier to attend

Green spaces are satisfactory

Categorising city systems which affect citizens ability to enjoy the city.

Opportunities -Overview-

Employment Categorising city systems which affect citizens ability to acquire skills, education and employement.

Governance -Overview-

Transparency Categorising city systems which affect citizens ability to engage with democratic decision making.

Structures

Public transport is satisfactory

CITY

MAX

avv score

High pollution 69 100

Traffic Problem 62 100

Cultural activities (shows, bars, and museums)

Improve green spaces 77 100

Online job listings IT skills are taught well in schools Online services better public transport internet speed and reliability meet -connectivity needs

Employment finding services children have access to a good school Lifelong learning opportunities Businesses are creating new jobs Minorities feel welcome

Online public access to city finances Online voting has increased participation online platform where residents can -propose ideas Processing Identification Documents online

Information on local government decisions Corruption of city officials not a problem Residents contribute to decision making Residents provide feedback

Not enough new jobs 75 100

Little Resident Feedback 68 100

REFERENCES: https://www.openaccessgovernment.org/singapore

698

Smart City Systems - SCI

699

2021 CPU[AI]

They Key Driver:

Improved performance of the grid system, in order to help predict and produce only the power that is needed, with greater efficiency.

Smart Initiatives

Basic principle, smart energy grids:

SMART Energy Grids Singapore

WIDE AREA NETWORK

One way to help meet the carbon zero goal of cities is by introducing smart energy grids. Smart grids were first developed to promote the sharing of best practices in order to enhance the quality and reliability of the energy delivering system. This in turn reduces costs, and pushes the industry towards creating a more sustainable environment.

NEIGHBORHOOD AREA NETWORK

Higher efficiency

HOME AREA NETWORK

+0 +11

Improved data analytics

However, since the invention of smart energy grids, many developed cities are now pushing towards grid modernisation. Rather than just focusing on the first stage, advanced metering infrastructure, modernisation adds more elements such as sending data in two directions, and adding power to the grid from de-central sources in the opposite direction. The smart grid seeks to capitalise on unused renewable energy created by consumers and businesses. A further improvement to the system will come in the form of microgrids. These play a vital role in building our low carbon future since they bring resilience, optimise energy use and allow for renewable energy hosting (i-scoop, 2020)

6% increase in performance

GAS COAL NUCLEAR SOLAR WIND

Energy Security

GENERATION

Economic Competitiveness

Environmental Sustainability

Benefits: 1. More efficient transmission of electricity

SMART METER

ENERGY CONTROL CENTER

THE GRID

THE GRID NETWORK

TRANSMISSION

DISTRIBUTION

CONSUMPTION

Adapted from: https://www.mdpi.com/2078-2489/12/8/328/html

Aims:

1. Better facilitate the connection and operation of generators of all sizes and technologies

2. Quicker restoration of electricity after power disturbances

2. Allow consumers to play a part in optimising the operation of the system

3. Reduced operations and management costs for utilities, and ultimately lower power costs for consumers

3. Provide consumers with greater information and options for how they use their supply 4. Significantly reduce the environmental impact of the whole electricity supply system

4. Reduced peak demand, which will also help lower electricity rates 5. Increased integration of large-scale renewable energy systems 6. Better integration of customer-owner power generation systems, including renewable energy systems

700

Smart City Systems

5. Maintain or even improve the existing high levels of system reliability, quality and security of supply 6. Maintain and improve the existing services efficiently

701

2021 CPU[AI]

Smart Initiatives Case Studies - SMART CITY Zurich Singapore Toronto Barcelona Manchester

Smart City Index Population: 6.2m Life Expectancy: 82 GDP: $48,000

Perhaps one of the most controversial smart cities, mainly due to the way in which google-sidewalks labs imagined the implementation of Toronto’s newest district. The transportation system of the future is going to require public mass transit — assuming we solve COVID-19 — that integrates smoothly with public micro transit and private transit. That means walking, scooters, bikes, buses, trains, light rail, and yes, cars. Part of Sidewalk Lab’s goal was specifically solving how to make all those components work together. (Koetsier, 2020) The SCI report shows that Toronto has similar issues to other cities, namely unaffordable rents and traffic congestion issues. Smart city technologies, through sensing will aim to solve those problems. Toronto also plans to become a truely digital city, with more integration of online services, to provide a better service for residents. However, this was shown through the sidewalks labs project to be littered with issues. In order to move smart cities forward, we first need to develop and manage data ethis, and ensure user privacy.

Smart System H/Safety -Overview-

Pollution

Categorising city systems which affect citizens health, or ability to feel more comfortable.

Mobility -Overview-

Transport

Categorising city systems which help citizens move around the city, be it for work or pleasure.

Activities -Overview-

GreenSpaces

MIN

avv score

Car-sharing Apps/ lower congestion Apps for an available parking space Bicycle hiring Online scheduling and ticket sales information on traffic congestion

Traffic congestion is not a problem

Online purchasing of tickets to shows and museums has made it easier to attend

Green spaces are satisfactory

Categorising city systems which affect citizens ability to enjoy the city.

Opportunities -Overview-

Employment Categorising city systems which affect citizens ability to acquire skills, education and employement.

Governance -Overview-

Transparency Categorising city systems which affect citizens ability to engage with democratic decision making.

Structures

Public transport is satisfactory

CITY

MAX

avv score

Rent not affordable 53 100

Traffic Problem 37 100

Cultural activities (shows, bars, and museums)

Improve green spaces 74

Online job listings IT skills are taught well in schools Online services better public transport internet speed and reliability meet -connectivity needs

Employment finding services children have access to a good school Lifelong learning opportunities Businesses are creating new jobs Minorities feel welcome

Online public access to city finances Online voting has increased participation online platform where residents can -propose ideas Processing Identification Documents online

Information on local government decisions Corruption of city officials not a problem Residents contribute to decision making Residents provide feedback

100

Difficult to find new jobs 66 100

High Gov corruption 59 100

REFERENCES: https://www.sidewalklabs.com/toronto

702

Smart City Systems - SCI

703

2021 CPU[AI]

Smart Initiatives Case Studies - SMART CITY Zurich Singapore Toronto Barcelona Manchester

Smart City Index Population: 1.6m Life Expectancy: 83 GDP: $40,00

Barcelona put itself years ahead of smart city neighbors Copenhagen, Amsterdam and Vienna with its innovative tech: a parking system that guides drivers to available spots, people and weather-adjusting LED lights, smart waste bins that reduce odors… the list goes on. (Reimer, 2020) Overall, The Internet of Things (IoT) was Bria’s key ingredient: a network of connected, communicating sensors that feed data into the city’s larger sensor network called Sentilo. Just one of many examples is their air quality and noise detection sensors which are used to influence city-level policy making. The effort to use data differently has saved the city roughly €500,000 per year. Barcelona is also experimenting with a hybrid of online and offline participatory democracy (Bria, 2018) since there is a crisis in confidence with the government. This use of technology begins to respond to the SCI report which shows fairly high levels of corruption with little user feedback.

Smart System H/Safety -Overview-

Pollution

Categorising city systems which affect citizens health, or ability to feel more comfortable.

Mobility -Overview-

Transport

Categorising city systems which help citizens move around the city, be it for work or pleasure.

Activities -Overview-

GreenSpaces

MIN

avv score

Car-sharing Apps/ lower congestion Apps for an available parking space Bicycle hiring Online scheduling and ticket sales information on traffic congestion

Traffic congestion is not a problem

Online purchasing of tickets to shows and museums has made it easier to attend

Green spaces are satisfactory

Categorising city systems which affect citizens ability to enjoy the city.

Opportunities -Overview-

Employment Categorising city systems which affect citizens ability to acquire skills, education and employement.

Governance -Overview-

Transparency Categorising city systems which affect citizens ability to engage with democratic decision making.

Structures

Public transport is satisfactory

CITY

MAX

avv score

Rent not affordable +pollution 46 100

Traffic Problem 46 100

Cultural activities (shows, bars, and museums)

Improve green spaces 68 100

Online job listings IT skills are taught well in schools Online services provided by the city internet speed and reliability meet -connectivity needs

Employment finding services children have access to a good school Lifelong learning opportunities Businesses are creating new jobs Minorities feel welcome

Online public access to city finances Online voting has increased participation online platform where residents can -propose ideas Processing Identification Documents online

Information on local government decisions Corruption of city officials not a problem Residents contribute to decision making Residents provide feedback

Not enough new jobs 59 100

High Gov corruption 42 100

REFERENCES: https://www.vox.com/2016/8/4/12342806/barcelona-superblocks

704

Smart City Systems - SCI

705

2021 CPU[AI]

They Key Driver:

People centred cities, with reduced personal vehicles, increased public transport, and thus better urban mobility.

Smart Initiatives

Basic principle, smart blocks and congestion:

SMART Blocks Barcelona “…when you start with technology without a strong idea of why you are deploying the technology, and for what kind of needs, then you only end up solving technology problems.” – Francesca Bria, Chief Technology and Digital Innovation Officer, Barcelona

Benefits:

Meanwhile, of course, more streetlevel solutions continue to be rolled out. For instance, the popular Superblock idea will be expanded to cover the entire city. By restricting car traffic within each Superblock, neighborhoods become less polluted and noisy, and the streets are freed up for children, pedestrians, and small businesses. But even as car traffic is limited, mobility is increasing. For example, line 9 of the Barcelona subway system was updated with smart elevators that use real-time data to adapt to the needs of commuters. The movement of the elevators is optimized for passenger use, and they automatically move to the platform level just before a train arrives. This speeds up passenger mobility, reduces crowding and lowers energy consumption – for an estimated 30 million passengers per year. Superblocks entail the virtual creation of small villages within large cities. Car traffic can enter these areas, but under low-speed and other restrictions. By eliminating most of the traffic, people-centered activity flourishes. (Urban Hub, 2018)

30% reduced energy use 600+ less deaths annually 13% green space increase

1. Reclaims Public space 2. Lower Noise levels within the superblocks 3. Lower emissions, but increased mobility 4. People centred urban planning 5. Reduce health related burdens, increase average life span (less Nox)

REFERENCES: (BNC Ecologica, via Cities of the Future)

Aims:

1. More sustainable mobility 2. Revitalisation of public spaces 3. Promotion of biodiversity and urban greening 4. Promotion of urban social fabric and social cohesion 5. Promoting self-sufficiency in the use of resources 6. Integration of governance processes

706

Smart City Systems

707

2021 CPU[AI]

Smart Initiatives Case Studies - SMART CITY Zurich Singapore Toronto Barcelona Manchester

Smart City Index Population: 550k Life Expectancy: 81 GDP: $46,000

Following on from consultation with partners and local networks over the past six months, Manchester City Council wants to ensure that Manchester can be a more inclusive, sustainable, and resilient smart city with digital inclusion and skills at its heart. The proposed new Digital Strategy and Vision aims to support more jobs and skills across the city’s digital economy as well as enabling local people to access digital services more easily and effectively, says the council. Improving digital skills for everyone will be key to creating “smart people” in a “smart city” with everyone being able to participate fully in the digital world (Ilovemanchester, 2021) Like many of the other cities, Manchester can utilise the smart city to adress areas from the SCI report, such as high pollution levels, unaffordable rents, while also seeking to improve the cities offering of public spaces. From the example of the superblock in Barcelona, Manchester can learn from thatas they also have very real issues with congestion, public transport and generally very low urban mobility.

Smart System H/Safety -Overview-

Pollution

Categorising city systems which affect citizens health, or ability to feel more comfortable.

Mobility -Overview-

Transport

Categorising city systems which help citizens move around the city, be it for work or pleasure.

Activities -Overview-

GreenSpaces

MIN

avv score

Car-sharing Apps/ lower congestion Apps for an available parking space Bicycle hiring Online scheduling and ticket sales information on traffic congestion

Traffic congestion is not a problem

Online purchasing of tickets to shows and museums has made it easier to attend

Green spaces are satisfactory

Categorising city systems which affect citizens ability to enjoy the city.

Opportunities -Overview-

Employment Categorising city systems which affect citizens ability to acquire skills, education and employement.

Governance -Overview-

Transparency Categorising city systems which affect citizens ability to engage with democratic decision making.

Structures

Public transport is satisfactory

CITY

MAX

avv score

Rent not affordable +pollution 53 100

Traffic Problem 43 100

Cultural activities (shows, bars, and museums)

Improve green spaces 68 100

Online job listings IT skills are taught well in schools Online services better public transport internet speed and reliability meet -connectivity needs

Employment finding services children have access to a good school Lifelong learning opportunities Businesses are creating new jobs Minorities feel welcome

Online public access to city finances Online voting has increased participation online platform where residents can -propose ideas Processing Identification Documents online

Information on local government decisions Corruption of city officials not a problem Residents contribute to decision making Residents provide feedback

Poor school access 63 100

High Gov corruption 57 100

REFERENCES: https://ilovemanchester.com/manchester-plan-smart-city

708

709

2021 CPU[AI]

Top down Bottom up

Within both approaches there are those that tend to associate smart cities with terms such as healthy, vibrant, pleasant, clean and friendly. Duckenfield T (2014)

Smart city initiative approaches:

Generally when looking at smart city initiatives, they can be broadly classified under either a top down or a bottom up approach. They shall be covered here:

BOTTOM UP

Characteristics

TOP DOWN Top down or technology centric approaches are associated with pre-defined offerings. Cities adopting this approach become smart by integrating data gathered from different kinds of censors (smart meters and CCTV cameras amongst others) into a single virtual platform in order to manage city operations more efficiently, often working with technology companies to take advantage of already developed products or software. Examples of this include Glasgow’s planned Integrated Operation Centre. New cities such as Songdo in South Korea and Masdar in the United Arab Emirates have been developed using a ‘top down’ approach; they are being designed from scratch and built using technology-enabled infrastructures. However, while interesting, these types of large-scale, top down projects are not relevant or applicable for many old and wellestablished UK cities as they depend on a blank canvas. In most cases, wide-scale top down approaches to smart cities stretch far beyond UK cities’ financial and technical capabilities and many of these projects do not respond to their needs. (Nohrová, 2014)

The bottom up approach emphasises the use of new technologies (for example, social media, websites, mobile applications or censoring technologies) and new data (becoming available mainly through open data platforms or censors) as a means to enable citizens to devise solutions, acquire new skills through online learning and improve their interaction with public authorities. Such initiatives include open data platforms that allow the development of new mobile applications or online crowdfunding platforms to fund innovative projects. By making citizens more engaged in civic life through online platforms, it is also argued that bottom up initiatives can encourage a “more direct form of local democracy” as David Willets, the Minister of State for Universities and Science recently stated. Within both approaches there are those that tend to associate smart cities with terms such as healthy, vibrant, pleasant, clean and friendly. Cycling, car-free town centres and improved public transport are examples of this tendency. More literally, others focus on citizens’ skills and qualifications-levels to describe how smart a city is. (Nohrová, 2014)

The general approach in the UK: So far UK cities, along with community organisations and social entrepreneurs, have tended to favour the bottom up technologies approach to smart cities. This is reflected in the rapidly increasing number of such projects being established across the country. These range from open data platforms in cities such as London, Bristol and Leeds to interactive websites in London and online platforms that match skills with business needs, such as Peterborough’s Visual Career Pathways project. They also include citizens using censors such as smart meters to become more aware of their energy consumption and save money (such as in Bristol). In recognition of this confusion, the British Standards Institute (BSI) recently released the Smart Cities Framework (commissioned by the Government) which aims to provide cities with some guidance on how to implement smart strategies. Without being sector specific, the framework sets out a wide set of principles and recommendations related to leadership and governance, procurement, and digital inclusion, among others. Whilst this represents a positive step in creating a common framework for all the different players and interests to organise around, it is still too soon to evaluate its effectiveness in providing direction to UK cities on this agenda.(Nohrová, 2014)

710

Smart City Approaches

711

2021 CPU[AI]

The Connected City “Before a city can be smart, it has to be connected.”

Layers of smartness

- McKinsey Global Institute, 2018

The three layers of ‘smartness’ which together make the Smart City

Source: McKinsey Global Institute, 2018

TRADITIONAL PHYSICAL: roads, bridges, canals, water supply, power grid, housing, people etc. SOCIAL: education, healthcare, entertainment etc.

TECHNOLOGY BASE/ DIGITAL LAYER

APPLICATIONS &

Networks of connected devices and sensors (IoT) include: high-speed communication networks a critical mass of smartphones open data portals sensors

Smart applications (smart meters, traffic management, GPS routing, smart parking etc.) Data analysis capabilities (IoT and Big Data)

INTERNET OF THINGS generate data applications require the transmission and reception of data on the go >> facilitate the use of beacons people as dynamic sensors - enable real-time monitoring and adjustments

712

Layers of smartness

fast expansion resulted in millions of ‘dumb’ objects becoming ‘smart’ (fitted with sensors + actuators + Internet connection) and connected to the cloud e.g.: smart thermostats, RFID tags, GPS systems apps

USER ADOPTION & Leads to: users making better decisions behaviour change

OPEN DATA fast expansion resulted in millions of ‘dumb’ objects becoming ‘smart’ (fitted with sensors + actuators + Internet connection) and connected to the cloud e.g.: smart thermostats, RFID tags, GPS systems apps

713

2021 CPU[AI]

“Digital technology is vital to unlocking net-zero

Digital Infrastructure

transition.” - The Royal Society, 2020

Supporting the Smart City

Digital infrastructure enables the existence of the Smart City through the sensing, network and processing components. The connection of technologies is made through high-speed fibre optics networks. The global emissions from digital technologies (smart meters, supercomputers, weather modelling and AI) account for an estimated 1.4% - 5.9% (The Royal Society, 2020). However, it could deliver close to 1/3 of the carbon emissions reductions by 2030.

PROCESSING COMPONENTS

APIs, Databases, Security, Applications

Data centres, could computing, control centres, embedded cybersecurity & mitigation strategies, open data platforms

Data Analytics & Decision Making

Optimisation, AI, big data, machine learning, deep learning, feedback

Provide users with services Data anonymisation Processing and storage of data Extraction of patterns and inferences to guide decision making; develop strategies and policies to manage systems

ACHIEVABLE EMISSION REDUCTIONS FORECAST FOR INFORMATION WORLD / APPLICATION

0.06 kgCO2 / 200 ft cable reduction in manufacturing emissions though the use of fibre optic cabling. For the same length, the extraction of 2kg of copper ore would produce 1000 kgCO2 (CityFibre, 2018).

7.3m tCo2

NETWORK COMPONENTS

equates to 15% reduction in carbon emission through the use of digital technologies. This is half of the required reduction to meet the Paris Agreement (TriplePoint, 2021).

Network Technologies

Home Area Networks Neighbourhood Area Networks Wide Area Networks

Wi-Fi, Zigbee, Bluetooth, Li-Fi etc. Wi-SUN Cellular, SigFox, NB-IoT etc.

Network Typologies

Point to point Star Mesh (preferred for IoT systems)

Linear system, low resiliency Centralised system No central connection point, high on fault resiliency

COMMUNICATION WORLD / NETWORK

£1.2b UK annual energy savings / up to 50% reduction in the average emissions of large companies through the use of cloud-based operations & shared data centres (CityFibre, 2018).

1.6 GtCO2 or up to 30% emissions reduction through the use of Buildings Energy Management Systems (BEMS) (CityFibre, 2018).

Wearable Devices

Health monitoring devices, smart skins, smartwatches etc.

Sensors

Temperature, air quality, noise, traffic congestion etc.

SENSING & CONTROL COMPONENTS Smart Sensing Devices

Smartphones, smart meters, video surveillance cameras etc.

Measure information from the physical world Sensing and control - twoway flow of the smart city Monitor, optimise and manage all devices

PHYSICAL WORLD / PERCEPTION

714

Supporting the Smart City

715

2021 CPU[AI]

Enabling Technologies Significance & Challenges

“Existing and new technologies are integrated to support the development of a connected network of devices of a smart city” - Ahad et al., 2020 :online

Efficient data storage and processing via the Internet

Analysis of big data to generate predictions, prevention and cost-effective solutions, holistic insights on systems functioning

Challenge: Manage large volumes of data in a centralised manner COULD / EDGE COMPUTING

AI, ML, DL

Management of large volume of real time data from the IoT devices of the smart city

BIG

Challenge: Unstructured and incomplete data

INTERNET OF

CYBER-PHYSICAL SYSTEM

716

Significance & Challenges

Challenge: Infrastructural requirements

Challenge: Implementation costs

SECURITY PROTOCOLS

Challenge: Implementation costs

ICT

Challenge: Security

Source: Ahad et al., 2020

Challenge: Security and trust

Accurate location services for smart navigation, tracking, transportation and other smart city processes GEOSPATIAL TECHNOLOGIES

Facilitates an intelligent control system and real time data collection through different types of sensors WIRELESS SENSOR NETWORK

Challenge: Environmental impacts - manufacturing, disaster

Provides all the services required to create a connection between devices, communities and governments

A collection of networks, devices, processing, management, computations and related physical processes.

Distributed data management and autonomous peer-topeer connectivity between devices >> trusted transactions and agreements BLOCKCHAIN

A collection of networks, devices, processing, management, computations and related physical processes.

Enables a network of communicating devices Challenge: Security and privacy (encryption, network attacks, data leakage, access control)

Challenge: Complex processes

Provides strong connection to enable efficiency of devices. Needs high fibre optic counts

Challenge: Implementation

The core of smart cities Collection & transmission of data to the network gateways for further processing SENSORY DEVICES

Challenge: Memory, power, interoperability, reliability

717

2021 CPU[AI]

The Internet of Things Bridging the gap

The Internet of Things (IoT) network architecture provides the means to be present everywhere by incorporating transparently and seamlessly a large number of heterogeneous end systems and sensors with the purpose to supply services that involve highly complex tasks (Kim et al., 2017). IoT is the driving technology of the digital age, enabling the creation of services and systems such as smart grids, connected health and smart home applications. The reduction in cost of sensors and the cities administrations move towards real-time management of smart systems such as water, energy, waste, transportation etc. led to a wide application of IoT. The UN predicts that by 2030, 60 per cent of the world population will live in cities. The challenges

Objects equipped with sensors, actuators, processors

Its architecture has 3 layers: Physical Network Application

Smart spaces & self-aware interconnected things for health, mobility etc.

resulted are population growth, increased need of resources and efficient services. Therefore, techniques need to be developed to reduce resource consumption at the urban level. Here, IoT plays a crucial role as it enables the remote monitoring, management and control of devices as well as the creation of new insights and actionable information from massive streams of real-time data. Park et al. (2018:online) define IoT as “a set of technologies for accessing the data collected by various devices through wireless and wired Internet networks”. However, the interconnectivity of the network poses a number of challenges which limit its seamlessness.

SCALABILITY

IoT is not one technology but a combination of various connected ones 42 billion devices will be connected to the Internet by 2025

Example: Temperature sensor detects heat

SECURITY & PRIVACY

Sensor

The Internet of Things (IoT)

Systems interact with the environment and optimize processes via learning through interactions

Hyperconnected society. Devices become intelligent and context aware

80 zettabytes of data will be generated by 2025

Sends this detect signal to the control centre. Control Centre

Bridging the gap between the real and the digital world

Bridging the gap

SELFORGANISATION

Control centre sends command to sprinkler. Control Centre Sprinkler turns on and puts out flame. Actuator

718

CHALLENGES IN IoT:

Source: Sensor flow [adapted from] Bridgera, 2017:online)

ENERGY EFFICIENCY

• It is a concern due to the high number of devices requiring simultaneous connectivity • Scalability issues can be divided in two categories: vertical –addition or removal of computing resources from an IoT node– and horizontal – addition or removal of an IoT node–. • Cloud computing and cloud-based architecture have been proposed as solutions. However, the challenge remains due to the increased number of services needed to be provided (fault tolerance, data storage, access control, privacy, security etc.) (Imran et al., 2020) • It is a concern due to the lack of privacy standards and end-to-end security solutions • RFID and newer releases of 5G and other local network protocols aim to solve privacy and security issues at hardware level • Key Management System with zero-trust network feature and blockchain aim to address privacy and trust issues • The challenge remains the interdependency of security, privacy, and trust for IoT ecosystems (Imran et al., 2020) • Its purpose is to enable the IoT systems to continuously respond to the changing environments in an automated and coordinated way using control loops to reconfigure the system behaviour • Important to ensure the robustness and survival of the network • The challenges that remain are the heterogeneous interoperability of the system, optimal self-organising protocols and routing strategies for large-scale distributed heterogeneous IoT networks, and cross-platform behaviour optimisation. (Imran et al., 2020)

Approaches used to design energy efficient IoT networks: • Developing energy efficient routing protocols • Incorporate renewable energy devices in the network & adopting loadbalancing strategies • Utilising wireless charging mechanism to address the fundamental problem of power management for large-scale heterogeneous IoT networks • Hardware issue: the need to develop net zero energy sensors as the current trend focuses more on functionality. (Imran et al., 2020)

719

2021 CPU[AI]

Sensing the City “The first step in improving quality of life and

Sensor purposes

efficiency in a city is understanding it.”- Sidewalk Labs, 2017 Sensors are the technology that sits at the core of the smart city. They collect data about the physical environment in order to enable a deeper understanding of the urban environment. The fast development of sensor technologies led to an increase in the construction rate of smart cities and smart infrastructures and data processing strategies. The future smart city infrastructure will use Wireless Sensor Networks for monitoring as it allows for fast deployment and practicality due to the lack of cabling (CCSIC, no date). Together with low power Micro Electro Mechanical Systems sensors, will lead to significant monitoring cost savings. The development of energy harvesting solutions will potentially increase battery lifetime or it might eliminate them entirely. Therefore, sensing technology can be used to understand and improve the multiple purposes of the smart city. SENSING

Footfall, flow of vehicles & cyclists, state of the urban environment, energy usage, information on business types

Human presence, audio and visual signal, distance between objects, position of objects, signs of smoke, fire hydrants location etc.

Security cameras, air quality sensor/ smoke detector monitor/ carbon monoxide detector, proximity sensor, passive infrared sensor, laser rangefinding

Weight, volume of waste in chutes, amount of landfill, recycling, and organics

Volume sensor, weight sensor, id verification (RFID tags), computer vision camera (for sorting)

GPS location, presence of vehicles and bicycles, changes in street use, car parking location & payment data, pedestrian volume count, availability of pick-up and drop-off zones

Autonomous navigation sensor, vehicle detection sensor , camera, pedestrian detection sensor, push button

Payments data, data exchange information (e.g. keyless entry system)

Identification sensors ( RFID tags and Near Field Communication (NFC) devices)

Pedestrian and vehicle detection, adaptive traffic lights data, presence, changes in street use, outdoor conditions

Navigation beacons for navigational assistance, weather sensors, inpavement LED lighting for signal changes, pedestrian detection sensor, speaker, push button

WASTE MANAGEMENT

Motion, temperature, moisture, payment data, usage, ambient light levels, streetlight usage, heat recovery data, occupancy, energy storage performance

Data monitoring of air quality, noise levels, structural integrity, odour etc. to detect unsafe conditions ENFORCEMENT

Water quality, flow rate, inflow & outflow of stormwater, valve and gate status, proximity data WATER EFFICIENCY

720

SAFETY & SECURITY

Lidar, laser rangefinding, thermal sensor, passive infrared sensor (PIR), computer vision (cameras), voltage sensor

PLANNING & DECISION-MAKING

ENERGY EFFICIENCY

SENSING

Sensor purposes

Lidar, thermometer, passive infrared sensor (PIR), road surface sensor, light sensor, thermal energy meter, optical sensor, BEMS (Building Energy Management Systems)

Air quality sensors (carbon monoxide, particulate matter, sulfur dioxide), noise level sensors (generated by vehicles, construction, human activity), load and vibration sensors

Liquid level sensors, liquid flow sensors, leak detection sensors, ph level sensor, water quality sensor, proximity sensor (e.g. faucet switches)

MOBILITY

INFORMATION, ACCESS ETC.

ACCESSIBILITY

Source: Sidewalk Labs, 2019b

721

2021 CPU[AI]

Sensing the City “Sensors provide the knowledge and data from

Sensor types

which smart city innovations are created.”- Syed et al., 2021 The sensing technology used in the Internet of Things (IoT) can be divided into several categories: ambient, electrical, chemical, biosensors, identification, presence, hydraulic, motion and others (Syed at al., 2021). Sensors are the essential elements in the IoT systems which facilitate the interaction between the smart city systems and the city’s inhabitants as well as the development of new solutions. The sensors application can be found across all smart city components (smart homes, smart energy, smart health, smart transport, smart infrastructure, smart city services, ecology and smart industry).

SENSOR

USED

Liquid measurements (level, flow, leak detection)

Security cameras, air quality sensor/ smoke detector monitor/ carbon monoxide detector, proximity sensor, passive infrared sensor, laser rangefinding

Motion data (activity tracking, vibration sensing etc.)

Smart Energy, Smart Home, Smart Industry, Smart Infrastructure, Smart Transportation

Human motion (passive infrared sensor), vehicle presence (loop sensor), distance of objects (ultrasonic sensor), position of objects (capacitive sensor)

Smart City Services, Smart Home, Smart Transportation

Payments data, data exchange information using RFID tags and Near Field Communication (NFC) devices

Smart Health, Smart Home, Smart Industry, Smart Transportation

Audio & visual information, signal strength (Bluetooth, Wi-Fi etc.)

Ecology, Smart City Services, Smart Health, Smart Home, Smart Industry, Smart Infrastructure, Smart Transportation

HYDRAULIC SENSOR

USED Environmental conditions data (temperature, humidity, light intensity and pressure)

AMBIENT

CHEMICAL

Air quality data (carbon monoxide, carbon dioxide, particulate matter, sulfur dioxide etc), signs of smoke, ph water level, water quality data

Ecology, Smart City Services, Smart Energy, Smart Home, Smart Transportation, Smart Infrastructure, Smart Industry

Ecology, Smart City Services, Smart Home, Smart Transportation PRESENCE

Health parameters (heart beat, breath, blood pressure, ECG, oxigen level, skin resistance etc.)

Smart Health, Smart Industry

IDENTIFICATION

BIOSENSORS

Electrical power usage of consumers / appliances, voltage, transformers data ELECTRIC SENSORS

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Sensor types

MOTION SENSORS

Smart Energy, Smart Home, Smart Industry, Smart Infrastructure OTHER SENSORS

Source: Syed et al., 2021

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Sensing the City

“When we design sensor network monitoring systems

Challenges

for smart cities, we have two essential problems: node deployment and sensing management.”- Du et al., 2018

SENSOR NETWORK CHALLENGES: NODE DEPLOYMENT // It can be done in a deterministic or random way depending on the area covered. It affects the monitoring performance of the system. Dense deployment leads to data redundancy, while sparsified deployment results in insufficient information. Sensors have limited memory due to small size and limited operations if battery powered (Du et al., 2018). SELF-MANAGEMENT // The sensor network must be capable to adapt, configure (deployment of additional nodes), repair and maintain itself as its topology is continuously changing (due to node failure). Essential for random deployment. HETEROGENEITY // Nodes with different sensing, computation and processing capacity can create communication and configuration issues. Needs new routing protocols for the sensible use of nodes to increase the network lifetime (Du et al., 2018). NETWORK LIFETIME // It is the time interval in which the sensor network can provide the information of a specific area continuously. The energy of a sensor node is mostly consumed by the wireless communication. Therefore, the issues are centred upon deployment of sensor, relay and sink nodes (Du et al., 2018).

COVERAGE // A problem due to the larger areas that need to be monitored. The two essential aspects are: the minimum number of sensor nodes needed for an area to be fully covered and the distribution of sensors so that the covered area is as large as possible. The use of algorithmic models to address it (Du et al., 2018).

SENSOR LIFESPAN // Solid state batteries used for powering wireless sensors have a lifespan of up to 10 years. Harsh environmental conditions can lead to sensor malfunctioning and inaccurate data (Ilika, 2019). SENSING MANAGEMENT // studies what type of devices, when should they make measurements and transmissions and how much power should they spend to sense (Du et al., 2018). STATIC SENSOR NETWORKS // Sensor selection problem. Minimisation of energy consumption while sensing a set of targets by testing the optimal sensing range and going into sleep mode when not needed to sense (Du et al., 2018). MOBILE SENSOR // Networks Sensing scheduling problem. Efficiency is achieved by taking turns to monitor an area mainly when energy consumption is high.

SECURITY // Nodes should support access control to limit unauthorised access. Data privacy and integrity should be preserved. Left: Sidewalk Labs information banner on data collection purposes in a public area (park).Citizens should be given an option to optin and opt-out in case of personal information collection.

Source: Sidewalk Labs, 2019b: 125

CROWD ASSISTED SENSOR NETWORKS // Rewarding and unceratin mobility of participants problem. Choosing the most cost-effective participant, the optimum price for sensing tasks as well as predicting their next call as measurements are transmitted via a 3G call as well as their mobility based on historical traces (Du et al., 2018). SENSOR INSTALLATION: Top Right: Sidewalk Labs illustration showing the current sensor installation process. Without a standardised digital infrastructure, sensor placement / replacement takes hours to mount, connect and test. Bottom Right: Sidewalk Labs illustration proposing a new mounting system called Koala. Koala mounts allow for quick installation, repair and upgrade of sensors.

Source: Sidewalk Labs, 2019b: 126

Source: Sidewalk Labs, 2019a:online

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Challenges

725

“Info-scapes (virtual landscapes of information)

2021 CPU[AI]

provide citizens with an increased awareness of

Real-time Sensing Infoscapes

their environment and allow them to make informed decisions. The city of future becomes ‘smart’ through the collaborative activity of sentient, self-reporting agents, i.e. its citizens.”- Nabian and Ratti., 2017

Source: Transportation correlated with noise (Xiaoji Chen, 2009:online) MIT SENSEABLE CITY LAB: COPENHAGEN WHEEL The “Copenhagen Wheel” transforms ordinary bicycles into hybrid e-bikes that also function as mobile sensing units. The system captures the energy dissipated while cycling and braking and saves it for when the biker needs a bit of a boost. It also maps pollution levels, traffic congestion, and road conditions in real-time. The bikers can also share their collected data with friends, or with the city – anonymously if they wish – thereby contributing to a fine-grained database of environmental information from which all city inhabitants can benefit. In short, the neo-cyborg user of a “smart” solution such as “Copenhagen Wheel”, merges humanity with real-time information (Nabian and Ratti, 2017).

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Infoscapes

Source: Aggregated concert data (Nabian and Ratti, 2017:21) REAL-TIME

ROME

INFO-

Aggregate picture of data transferred through the Telecom Italia cellphone network during a Madonna Concert. The project looks at how positions and activities of mobile phones can be used to “sense” people’s presences. When aggregated at the highest possible level, mobile location data does not impinge on the privacy of individuals but can return important information on the concentration and relative weights of human activities in the urban environment, as well as flows and patterns of city use. Visualisations and analyses of such data can be obtained in as close as real-time as possible. They allow for answering questions regarding the dynamics of the city: people, traffic, climate etc. (Nabian and Ratti, 2017).

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Sensor Node Deployment Framework

CONTEXT

The ever-reducing cost of wireless sensor networks (WSNs) enables their implantation everywhere. This results in smart spaces with the ability to monitor and control the processes within as well as the creation of the Internet of Things. Therefore, WSNs must be well planned for smart city sensing considering: • Type of node • Location of deployment • Networking management for a cost-effective monitoring

PROBABILISTIC

FORMULAS

A probabilistic disk model considers that the probability for a sensor to detect a target decreases with the distance between the sensor and the target. It is more realistic than the binary model, but it can make coverage problems more difficult to solve due to overlap in sensing area (Chen and Chen, 2018).

BINARY DISK MODEL probability

COVERAGE

TWO ESSENTIAL The minimum number of sensor nodes to allow for full coverage of the monitored area. The optimal deployment location of a given number of sensor nodes so that the covered area is as large as possible.

BINARY

DISK MODEL

A binary disk model assumes that sensors can accurately detect targets within their sensing ranges (Chen and Chen, 2018). A sensor node is assumed to cover a disk area with a radius r centred at the node itself. The deployment of sensors is based on a pattern called r-strip where a string of nodes are placed along a line and the distance between two adjacent nodes is r. The use of a number of strips to cover a whole area together with the assumption that the sensing and transmission range of sensor nodes are the same, guarantee the connectivity of the network (Du et al., 2018) A model with a stronger requirement on network connectivity considers a minimum of two node-disjoint paths (maximum number of paths connecting each pair) among every pair of the sensor nodes. The nodes are deployed in a strip-based pattern, where the distance between two horizontal adjacent nodes is (the minimum value of the sensing range * √3 )* the communication range. It is considered the optimal deployment regardless of the ration between sensing and communication range (Du et al., 2018).

728

Framework

si = sensor

rs 0 rs

PROBABILISTIC r+re

SENSING MODEL

{

1 if d(s , p) ≤ r ρ(si, p) = 0 if d(si, p) > rs i s

d(si, p)

rc= communication range p= target point d= distance

DISK

{

probability

r-re

rs= sensing range

1 ρ(si, p) = 0 e - (d( , p)-(r-

0 r-re

))

if d(si, p) ≤ r-re if d(si, p) ≥ r+re otherwise

r+re d(si, p)

Source: Diagrams [adapted from] Chen and Chen, 2018:35) If r - re < d(si, p) < r + re then the probability for a target point p to be detected by sensor is e - (d( , p)-(r- )) This means that target p will neither definitely be detected nor definitely not be detected by si . SIMPLIFIED

PROBABILISTIC

Chen and Chen (2018) show that even under such a simplified probabilistic sensing model, at least half of sensors can be saved.

DISK

{

e - d( ρ(si, p) = 0 , =1

r = re

,p)

if d(si, p) ≤ rs otherwise rs = r + re

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Sensor Node Deployment Framework

FORMULAS (CONTINUED)

If the location of nodes is known, then the optimal deployment problem can be formulated as an linear programming problem or a binary linear programming problem using a divide-and-conquer approach. Due to integer variables, an optimal solution is difficult to achieve at large scale. To address this issue, approximate / greedy algorithms have been proposed (Du et al., 2018).

Overlap of sensing areas. When a target at point p in the given region of interest is within the sensing range of two sensors ( si and sj), the probability for the target to be detected by at least one of si and sj is: 1-(1- (si, p))(1- (sj, p)) Suppose a region of interest has n sensors s1, s2 ,..., sn . Then, when a target is at point p in the region of interest, the probability for the target to be detected by at least one sensor is a function m(p) defined as:

Greedy algorithms are used to address the minimum set cover problem (minimum number of sensor nodes to cover all interested points). The algorithm, in this case, works on the idea that during each iteration a sensor node is deployed to the location from which it can cover most of the uncovered points, until all are covered (Du et al., 2018).

m(p) = 1 -∏(1- (si, p)) i=1

Heuristic algorithms have also been proposed, such as genetic algorithms. Looking at the deployment of two different nodes for the monitoring of water distribution networks (cheaper node with smaller coverage and transmission range vs expensive node with larger coverage and transmission range) . The genetic algorithm solves the deployment of these types of nodes with a given budget to maximise coverage of the network (Du et al., 2018).

In general, the sensing range and the communication range satisfy the relation rc ≥ 2rs . The simplified probabilistic disk model proposed by Chen and Chen (2018) considers the rc = √3rs , as when this relation is met optimal deployment can be achieved and the connectivity of the wireless sensor network can be ensured.

√3rs

Optimal deployment Optimal deployment – the general case of three neighbouring sensors Source: Diagrams [adapted from] Chen and Chen, 2018:35) SENSING MODEL

DISCRETE POINTS MODEL

In a discrete points sensor field the location of points is known as well as the network structure of the monitoring field. This model of coverage is better suited for smart cities. Greedy and heuristic algorithms can be used together to compare the results and choose the best outcome. Heuristic > Greedy as it gives better results (Du et al., 2018).

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Framework

MAX COVERAGE

The problem of maximum coverage is generally solved by observing that the coverage improvement of adding a sensor node to a sensor network is less than adding a sensor node to a subset of the sensor network. A greedy algorithm is used to address the issue of maximum coverage. Supposing that there are n sensors to be deployed, the algorithm first deploys √n sensor nodes and then the rest n - √n to make the nodes connected. The solution achieved is O(√n) - an approximation to the optimal solution (Du et al., 2018).

CONCLUSION

Equal distance deployment of sensor nodes is not optimal. An equal power deployment strategy needs to be applied. Maximising lifetime per unit cost is essential using a greedy algorithm to determine deployment and then test the number of nodes. Apart from sensor node deployment, the relay and sink node deployments has to be determined precisely. It is generally solved using a heuristic algorithm based on particle swarm optimisation. An artificial bee colony algorithm is used to find a solution for deployment.

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Sensor Node Deployment Framework

Continuation of the simplified probabilistic disk model proposed by Chen and Chen (2018) which result in a reduction in the number of sensors used for deployment.

EXPERIMENTAL RESULTS Suppose the given region of interest is of size 1000m x 1000m, rs = 25m, and (  = 0.0446,  = 1, r = 12.5m, re = 12.5m). If pth = 80% then the standard probabilistic model uses 15544 sensors, while the method proposed by Chen and Chen(2018) uses 2064 saving therefore 86% sensors.

r2 r1

pth

Pseudo sensing ranges r1 and r2 where r2 = √3r1 Source: Diagrams [adapted from] Chen and Chen, 2018:35-36)

The region defined by the green circles outline has the property that each point is within radius r1 of at least one sensor and within radius r2 of at least two other sensors.

Chen and Chen (2018) take into consideration the benefit of neighbouring sensors and consider each sensor to have two pseudo rensing ranges. Here r2 denotes the distance between two neighbouring sensors. The desired threshold probability pth is defined by the relation 0 < pth < 1. A point p within the region of interest is considered covered if (si, p) < pth. The probability for a target at point p in the area defined by the green circle outline to be detected is calculated using the previously defined m(p) formula: pmin = 1-(1-e

)(1-e

)(1-e )

If pmin ≥ pth the coverage deployment is guaranteed under the probabilistic sensing model. pr1 = e pr2 = e

732

= sensing probability (*) = sensing probability(*)

Framework

80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99

pr1

pr2

1-pr1

1-pr2

34.20 54.74 56.66 57.66 58.70 60.89 62.06

36.28 37.38 38.53 41.02 42.35 43.77

44.31 42.34 41.30 40.22

36.71 64.57 67.39 70.66 72.54 74.66 80.20 84.46

46.88 48.61 50.48 52.52 54.80 57.35 60.28 63.79 68.24 74.64

The sensing probability % required to satisfy (*) Source: Chen and Chen, 2018:36)

34.06 32.61 31.05

64.78 63.72 62.62 61.47 60.26 57.65 56.23 54.72 51.39

pmin 80.00 81.00 82.00 84.00 86.00 87.00 88.00 90.00 91.00 92.00

47.48 94.00

27.46 22.86

42.65 36.21 31.76

96.00 97.00 98.00

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Sensor Network Application Examples

smart city monitoring node deployment node type

objectives

sensing management network type

applications

design variable

structural health

sensor

coverage

wireless sensor network

energy

relay

connectivity

crowd assisted sensor network

location

camera sensor network

sensing time

urban traffic

...

smart grid

sink

lifetime ...

pipeline network

street light Node deployment and sensing management with their applications. Source: Diagram [adapted from] Du et al., 2018:4)

...

PIPELINE NETWORK MONITORING Monitoring pipeline networks is essential to ensure environmental protection and public health. Examples include leakages, contaminations and accidents. Sensors mean accountability, thus sewage would not be dumped into rivers. Sensing performance and its metrics (coverage area & population, detecting time etc.) depend on sensor node deployment. Mobile sensors could achieve better performance than static. Systems currently in use are WaterWise@SG (detect leakage and predict bursts), PipeNet (leakages via three tier node monitoring of pressure and PH levels), Steamflood & Waterfloor Tracking System (leakages & blockages).

URBAN TRAFFIC MONITORING Traffic monitoring systems in use are loop detectors (vehicle presence) and traffic cameras. The cost of deployment and maintenance of sensors is high. Therefore only major roads are monitored. To reduce system cost and provide wider coverage, vehicles can be used as sensor nodes to estimate traffic density and flow. To preserve privacy, only taxis and buses are used. Due to their non-uniform distribution and predetermined routes generate biased results. Crowd sensing via smartphones has a potential to be sensor nodes for traffic monitoring but energy consumption is a limiting issue. A heterogeneous systems is needed for improved performance.

The solution to the node deployment is formulated with respect to SHM metrics, WSN lifetime and connectivity.

STRUCTURAL HEALTH SHM systems - detect anomalies and signs of damage of infrastructure at early stages to for citizens security Sensing system is the most important as it collects in-situ data and environmental parameters. Sensing and sampling rates are higher than the sensor nodes for monitoring applications in the other systems, thus more expensive. Deployment of sensor nodes due to sites at different positions is an integer optimisation problem, solved via greedy and heuristic algorithms (Du et al., 2018).

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Examples

Greedy algorithm: Used to monitor the Lee Shao Kee tower in Hong Kong PolyU Campus. The deployment of high-end, lowend and relay nodes are determined in each phase. Redundant nodes are also deployed to ensure resilience to node failures (Du et al., 2018). Heuristic algorithm (easier to apply but it is not time efficient for optimal solution): Adaptive monkey algorithm developed for SHM of high-rise structure. Used to monitor Dalian World Trade Building and Dalian International Trade Mansion. In the climbing process it searches for the optimum location, while in the watch-jump process it looks for better positions than the current one to reach a global optimum deployment (Du et al., 2018). Heuristic algorithms should be applied to small scale SHM systems and greedy algorithms for large scale.

CAMERA SENSOR NETWORK CSN have a cone based monitoring systems, different from the conventional disc based monitoring models, meaning that they can turn to different directions to monitor different area. The deployment problems are: maximizing coverage with given a number or total price of nodes, optimizing camera poses given fixed locations, and minimizing total cost given a requirement of monitoring percentages. The deployment and sensing management (best subset selection to perform task) of CSNs are suboptimal due to the freedom of orientation and field of view which also have cost implications (Du et al., 2018).

STREETLIGHT MONITORING Streetlight monitoring has two purposes: to reduce energy consumption and to provide enough illumination for safety reasons. Each lamp is deployed with a sensor node which collects environmental and functional data. It uses power line communication for local data sharing and wireless communication for long-range data communication (Du et al., 2018). Location dependent sensing management can save energy consumption. In densely populated areas the nodes should measure real-time data for illumination control, while in sparsely inhabited areas motion sensors can be used to detect movement and trigger illumination (Du et al., 2018).

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2021 CPU[AI] Do you feel safe with the permanent hard shoulder removal?

Smart motorways how smart are they?

Should the government scrap the scheme, but keep the tech?

DO NOT USE CLOSED LANES

60 60 60

What are smart motorways in the UK? Smart motorways implemented in the UK, are esentially an upgraded road network which incorporates sensors and road cameras to actively and dynamically adjust the policies governing the system. Agencies can use this data to inform the network on factors such as, speed limits, lane use while also warning road users of any debry or collisions. This ‘smartness’ is hoped to provide the network an increased ability to reduce deaths by dangerous MC driving, increase the capacity of the existing road infrastructure, and some have suggested they can help reduce pollution by keeping the entire system and the correct speed when needed. Smart motorways use embedded copper loops beneith the road BH surface every 100m or so. The loops can then sense when a large metalic object passes over them, how quickly they are travelling, and also, the network can senses which class of vehicle are most using the system. This technology is most often seen in conventional traffic lights, to ‘sense’ when there may be vehicles waiting. This typeBRof sensing is largely LN being phased, due to the loops making the road more susceptible to pot holes, in favour of a more robust ‘sidefire-radar’ which can do the same thing with a beam of light.

The Future of smart motorways in the UK? The current plan for smart roads is based on the upgrading of existing ‘dumb’ systems. This is in contrast to the building of completely ‘new’ and ‘smart’ road networks based on different modes of travel, be it smart electric charging of vehicles as they drive - Electric roads. However, the proposals do intend to improve the overal network by enabling more real-time data to users, to help give alternative routes in adance of travelling. They network is also said to look into drone technology and Ai to spot anomalies, such as pot holes, to gain a better insight of the network, to then actuate improvements.

Smart City Systems

24%

CONTROLLED Variable speed limits without the hardshoulder, used mainly as a mechanism to manage speeding on dangerous stretch.

Smart travel decisions: Real-time Data

ALL LANE RUNNING The Hardshoulder always in use, sensors detect incidents to close live lanes, to ‘protect’ road users. To increase road capacity. THROUGH JUNCTION Old system to allow hardshoulder use on approach to junction exit. Not used much now. Aim was for reduced congestion.

Number of people killed*

Benefits of smart motorways 1. Monitor Traffic levels

2. changed speed to releive congestion 3. Helps ease the £2bn cost to the economy ................. from congestion and travel times TECHNOLOGIES The future of smart motorways highly depends on the progress of technology. Already we are approaching the quantum limitiation of silicon transistor technology. With millions of vehicles on the roads everyday, tracking and optimising the system needs miles and miles of fibre optics and high speed data streams. Some of this capacity is in the form of 5G and some in undergrond cables. These basic technologies working together in a network allows the system to become more intelligent. This new intelligence automates the actuation of responses, and allows for the anticipation of future problems.

Figure 01 - Author

5G Networks

Number of fines 2018

*from 2014 to 2018 (Panorama 2020 investigation)

System diagrams

There is potentiall however, with the use of real time data to provide road users with advanced advice on where the congestion is, where it might be (using historic data to look for patterns in road user behaviour) and how might user be re-directed to avoid heavy delays. Google already attempts this.

72,348 30 mins

60 60 60

CLOSED LANES

Using DATA

DYNAMIC HARD SHOULDER In addition to controlled, dynamic roads also semi-utilise the hardshoulder to further manage congestion. Sensors close Lanes.

DO NOT USE REFERENCES: https://www.rac.co.uk/drive/features/smart-motorways-and-driver-safety-2021/

TYPES

Average response time

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62%

YES

Although installed in order to add road capacity and reduce congestion on the motorway network in the UK, all further works have stopped. Smart motorways have been deemed to overlook fundemental safety concerns, with an investigation by Panorama revealing nearly 40 extra people have died because of them. In a push for efficiency gains, there are a number of unknowns.

15%

YES

Death by design

63%

ANPR Governance

Radar Figure 02: Highways England

Fibre Optics

Drones

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Machine Learning

Smart Cities

Big Data

AI +

Sensors

Urban Sprawl

Automation

Digital Infrastructure +

Smart Systems

IoT

Alternative Fuel

Data

Healthcare Infrastructure

+ Transportation + -

Waste

+ +

Parking

Energy[Generation] + + +

Infrastructure DecentralUrban + Improvements ised(Uber) Development Spatial Connectivity + Personal Freedom of + Inequalities + + + Vehicles Movement + Air Quality + -

Waste Heat

Albedo

Urban Ecology +

+ +

UHI Effect

Policy

Public Transport +

Sustainability

Electric Vehicles [EVs]

Embodied Carbon

+ + +

Health Impacts

Water Quality

Trees

Air Pollution Walk-

Temperature

Material Choice -

Urban Farming

+ +

Air Handling -

Performance

Buildings

Energy [consumption] -

Manufacturing

Efficient Design +

Digital Twin

BIM

Systems Dynamics The system dynamics diagram helped us to understand the complexities of city systems. Smart cities situate themselves in optimising and driving efficiencies of, and between systems. This diagram identified key areas which have possitive feedback on other systems, and few which have negative relations. We have further identified that tranportation has a direct effect on air quality, UHI, energy consumption, and more. With these contributing to the increase in carbon with the atmosphere, we can make decisions on how to mitigate towards carbon zero futures.

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Smart City Systems

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Can Smart city Initiatives help Manchester keep on top of their 2038 target? Manchester approach to creating a thriving, healthy and zero carbon city is outlined in the Draft Manchester Zero Carbon Framework 2020-2038. The city has set an ambitious target to reach carbon neutrality by 2038, 12 years ahead of the national target. The commitment has greater local significance as it was drove by citizens participation in the development of targets for Our Manchester Strategy 2016-2025. Manchester’s aim within the proposed Zero Carbon Framework is to limit the impacts of climate change both locally and globally in agreement with climate science, the Paris Agreement and the views of residents and businesses. The current targets based on analysis by the Tyndall Centre at University of Manchester and which were adopted in 2018 are:15 million tonne carbon budget for 2018-2100, urgent and deep carbon reduction; 50% reduction by 2022 from 2018 levels (1.97 MtCO2) and zero carbon by 2038 (Manchester Climate Change Agency et al., 2019). The objectives focus on improving citizens quality of life as we as creating jobs and attracting investments. They are to be achieved via the implementation of smart solutions to improve the energy performance of the housing sector, the transition to zero emission vehicles and the use of zero emission public transport, walking and cycling as preferred means of mobility. Apart from the reduction in emissions, efficient

740

Smart Cities and Manchester

energy performance will result in household savings between £49m - £141m / year while the use of zero emission transport will result in improved air quality taking a leap from the worst city in the country with the related 1,000 deaths/year. The need to provided more efficiency and better monitoring of energy and transportation while ensuring that citizens get the information they need to better manage their lives is acquired through the implementation of the Internet of Things(IoT). The connectivity of the city to IoT is sustained by digital infrastructure policies such as the implementation of a full fibre network. The newest initiative will deliver 2,700 km of fibre optic broadband infrastructure across the region. The target in terms of digital infrastructure is to deliver high speed digital connectivity over full fibre and 4G & 5G mobile across the whole city region by 2025 in order to remove the bandwidth barrier on reform objectives (GMCA, no date). A fully connected city, will enable the deployment of sensors across systems which coupled with data analysis tools will generate insights into the quality of performance, policies and inform future decion-making in an evidence based manner.

USERS

APPS DIGITAL TWINS

ECOLOGICAL ENVIRONMENT

INFORMATION LIVEABLE NETWORK

WELLBEING

SUSTAINABILITY

OPTIMISE SYSYEMS

CONSUMPTION

CONNECTED STREETS

POLLUTION

CITY INFRASTRUCTURE

PARKING

WATER SYSTEMS STREET LIGHTING

SENSORS

ACTUATION

WASTE DISPOSAL

ROAD SIGNS

TRAFFIC SYSTEMS

FAULT DETECTION

FLOOD DEFENSE MANEGEMENT

62mbs

Average broadband speed

Opportunities

5G 59% ownded by EE

Speed 7% lower than Average across the UK

2700km of new fibre optic broadband

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Smart City Metrics Assessing 'smartness'

KEY PERFORMANCE INDICATORS Cities must be able to measure how smart they are, whether they are becoming smarter and to what extent. Measurement provides a basis to track progress, to make decisions and to compare cities. A Key Performance Indicator (KPI) is a quantifiable measure that an organisation uses to assess performance on objectives (The Open Univeristy, no date). However, measuring the extent to which a city is becoming smarter is not a straightforward task. Cities use KPIs to measure the progress of their smart city projects (e.g. tonnes of CO2 emissions per capita, number of Wi-Fi hotspots installed etc.), but they are not comparable across all cities. However, United For Smart Sustainable Cities (U4SSC) proposes a consistent and standardised method to measure performance and progress. They propose three dimensions of smartness and sustainability in a city: Environment, Society & Culture and Economy and their sub-dimensions to provide a comprehensive view of a smart sustainable city. These are used as a benchmark for performance to reach strategic goals, to track progress, perform long term trend analysis (U4SSC, 2021). Higher Education Degrees

Air Pollution GHG Emissions

Life Expectancy

Wastewater Treatment

ECONOMY

Local Food Production

Green Areas

Gini Coefficient

Green Area Accessibility

Informal Settlements

Electricity Consumption

Availability of Wi-Fi in Public Areas Used to measure ‘smartness’ and to what extent it is happening

Resilience Plans

Recreational Facilities

Traffic Fatalities Violent Crime Rate Emergency Services Response Time

Smart Water Meters Drainage / Storm Water System ICT Monitoring

KPIs are not comparable across all cities, however the U4SSC created a standardised method through which it compares and ranks ‘smartness’.

Gender Income Equity

Residential Thermal Energy Consumption

Household Internet Access Wireless Broadband Coverage

Poverty

Noise Exposure

EMF Exposure

SOCIETY & CULTURE

Adult Literacy

Water Consumption

~ 91 KPI Subcategories

Data collected from sensors facilitates real-time feedback on performance

Student ICT Access

Drinking Water Quality

Solid Waste Treatment

3 KPI Categories for Smart Cities

Smart Electricity Meters Access to Electricity Traffic Monitoring Intersection Control

KPIs measure performance but not how it improves city outcomes e.g.: Does increased broadband connectivity create more jobs for citizens?

Open Data Unemployment Rate Water Supply Loss Solid Waste Collection Public Transport Network Low-Carbon Emission Passenger Vehicles

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Assessing 'smartness'

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DATA MARKET

DATABASES

DASHBOARD BUILDER DATA SOURCES

DATA COLLECTION OR AS METRIC ENGINES

IOT BROKER

PRIVATE COMPANIES

DEFINITION

GUI

HISTORIC VALUES

WIDGETS DASHBOARDS

DASHBOARDS WIDGET INSTANCES

IOT APPLICATIONS

MAPS AND ANALYTICS

Smart city data dashboards

POLLUTION LEVELS HIGH CARBON ZERO PROJECTION 2076 YOU HAVE REACHED YOUR CARBON LIMIT

SMS,EMAIL

SETTINGS USER INFO

NOTIFICATOR

API

CITY PARKING FULL

What are they?

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and participation, by enabling a feedback loop to citizens For cities, they enable monitoring and analysis for faster and more accurate decision-making. (Johanna Walker, 2020)

BIG DATA and Dashboards

Dashboard Potential for USERS

Water Usage Weather Patterns Air quality data Traffic data Waste Manegement

2. Consider audiences 3. Present Information meaningfully 4. Use best visualisation practices

Dashboards often visualise datasets in the domain of energy and mobility including transportation data, electricity consumption, cargo e-bikes, parking vacancies, and energy produced from the new renewable plant. These can give users more control over how they can use the city by making better informed decisions.

SOLAR GAS

5. Use timelines

energy

6. Make them intuitive 7. Make sure your data makes sense 8. Reduce risk of identifiable data 9. Guide your user what to do after 10. Offer long term value

REFERENCES: Johanna Walker- UOS, UK

Energy Demands Crime Levels Congestion Pollution Levels Network Capacity

For a city to be smarter, the use of emerging appropriate I n t e r n e t - o f - T h i n g s ( I oT ) technologies is needed, not only to gather city data but also to provide services to the public for analytics and other applications in a remarkably efficient manner (Martins, P, 2020) Designing and integrating systems that can make analysis for generating meaningful information for citizens is an influential prerequisite.

1. Pick meaninfgul indicators

Best Practice

In the context of smart cities, the most used visualisation tools are dashboards. “Dashboards visualize a consolidated set data for a certain purpose which enables users to see what is happening and to initiate actions”. They are instruments to reduce information asymmetry, whether between citizens and council, or field operatives and central departments, or departments and the central council. Through dashboards, important information scattered across open data portals and feeds around the web, gather into a cohesive and understandable location. For the public, they serve as a way to increase accountability, transparency, and even citizen engagement

STORED

54 100

SMART CITY RANKING

Dashboard Potential for PLANNERS Smart dashboards can be considered as a tool that is supposed to display the summary information of a city in a single view to help citizen tracking and analyzing what is happening to the city. All this information not only gives a general picture of the current state of all systems that make up the city but also allows analysing and discovering trends and behaviors that are repeated over time, which can predict future incidents and formulate solutions before that they arise. (Mina Farnambar, Chun Ming Rong, 2020)

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Big Data The real-time city

Cities have become a focus area for targeting climate change due to their contributions toward emissions which account for 70% of the global carbon emissions. Fleming (2017) argue that the carbon emissions per capita from consumption and the outsource of resources for cities, have an enormous impact and exceed direct emissions. Therefore, it is essential to have data about all sectors and their innerworkings to reach net zero.

Provision of information on emissions from homes, modes of transport etc. City Dashboard - city wide emissions

Machine to machine communication control & operation of systems

Real-time feedback on carbon emissions to inform decisonmaking Guidance to decision - makers for further investments

Data needed to reach net zero: • Energy use, land use, construction phases, supply chains, transport and other industries. These data will be used to monitor, control, enable carbon accounting and the study of trends(Royal Society, 2020).

City-wide carbon management systems measure and control performance

• Inner-workings of sectors from mapping of physical assets to business processes. These data will be used to develop digital technologies to reduce, optimise and control emissions (ibid.).

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The real-time city

Data quality, availability, privacy, long-term storage and ethics remain issues of the use of big data

Continuous monitoring of the schemes

Big Data

A comprehensive interdisciplinary approach is needed at city scale. Information and communication technologies have enabled the collection and analysis of large amounts of infrastructure and citizens data. The challenge now is to visualise big data so that cities can share and compare performance of systems and consumption to decrease GHG emissions and evaluate the public response to this evidencebased policy. Data collection and sharing poses ethical, security and privacy issues which need to be addressed alongside digital divide. The current available data on infrastructure – homes, businesses and transport – and citizens – living, working and studying – make it possible to estimate the annual carbon emissions at city level. However, this cannot yet be done in real-time or with regards to comprehending people’s attitudes and behaviours. The challenge here is that the quality and quantity needed to obtain a true city-wide overview is not available yet (Fleming, 2017). Data are not available uniformly but in concentrations (e.g. high on transport but low on food procurement and waste).

Move beyond monitoring to control, management, public engagement, public feedback

Net zero carbon programmes Data needed to achieve net zero via the development and use of digital technologies IoT - seamless communication between systems

Air quality action zones

Reuse projects community & non-domestic Zero-emission vehicle programme

People , Businesses & Smart Systems

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Block Chain, and Decentral Systems

Decentral Systems

CENTRALISED

DECENTRALISED CONSENSUS

COMMAND CENTRE

Arguments for

Trustless The blockchain is immutable and automates trusted transactions between counterparties who do not need to know each other. Transactions are only executed when programmed conditions are met by both parties.

Transparent Public blockchains are open-source software, so anyone can access them to view transactions and their source code. Suggestions are accepted or rejected via consensus.

0 1

SENSOR DATA

1 1

DATA

1 1

Agents have to communicate through the central server

LEDGERS P2P

4 S2

DATA

2 0

DATA

SENSOR DATA

S2 S1

SENSORS

Securing accountability Although centralization is in vogue, several trends foretell a shift toward greater decentralization. For example, millennials now represent the largest generation in the workforce. Millennials, in particular, seek flexibility and autonomy in their work, which are characteristics more compatible with decentralized structures. Keeping that growing segment of the workforce engaged may necessitate spreading decision making more broadly across the enterprise. Bililies, Ph.D. (2016)

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BIG DATA and Dashboards

With many of the cities on the SCI report showing signs that they have a lot to do to become more transparent and less corrupt, some economies are now moving to decentralised systems. Although these decentral systems offer a lot of benefits, the largest concern is energy use. If we look at Bitcoin, and other decentral currencies, the data mining farms can consume as much as a european city, often powered on cheap coal. If we are to make our cities more open, the technology cannot make excess carbon contributions.

Arguments against

Environmental Impacts

Application

Supply Chains

Blockchain networks like Bitcoin use a lot of electricity to validate transactions, leading to environmental concerns. Bitcoin consumes as much power as a small european country. Made worse when powered by coal.

Scalability Decentralisation comes at the cost of scalability. In turn, is the root cause of speed inefficiencies. It’s why, as we saw, Bitcoin and Ethereum can only process a maximum of seven and 30 transactions, respectively, compared to Visa’s 24,000.

Blockchain is being used to track precious metals’ origins and foods. Many of our materials and supplies come from questionable sources. Many metals used in electric cars come from child labour camps in the DRC. Blockchain may deter industries from buying and selling without a traceable ledger/history.

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Digital Twins More than mimicking reality

Digital twins are virtual realistic replicas of cities that aid decision- making. They have a technology-driven perspective with a focus on real-time sensory data, big data analytics, 3D visualisation and automation aimed at achieving urban sustainability goals by providing insights for an effective and efficient city planning and management (Nochta et al., 2020). The current model of digital twins lacks interdisciplinary insights and participative processes that involve users (citizens and administrations) alongside researchers and technology suppliers (Nochta et al.). The resulted insights would ensure meaningful contribution to policy and practice and facilitate a successful implementation. This approach, informed by a socio-technical perspective can help move beyond the hype of the digital twin concept. Technological advancements do Insights generated by big data, ML, AI, etc.

not guarantee a more successful usage of model outputs as evidence in decision-making. The way the outputs and the policy recommendations based on them are created and used in a complex decision-making process depends on the actors involved as they have different backgrounds, perspectives and interests. This issue remains unknown to modellers. Another problem of digital twins is their definition as digital replicas or mirror images of physical systems which is simplistic. Tomko and Winter (2019) define the digital twin as cyber-physical-social ecosystems, analogous to organisms with a brain. This perspective highlights the difficulties of digital twins application due to bi-directional connection between digital, physical and social areas. Security – not all information should be public Optimise use of resources e.g. energy and water

Demonstrate benefits of data sharing

Offers insights on the impact of decisions

DIGITAL TWIN

Boost quality of life

Unifies separate systems

What does a digital twin do?

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Reduce disruption and delay for transport

Realtime data forecasting to an aging infrastructure

More than mimicking reality

Improve responsiveness in natural disasters

PURPOSE

Public good

Value creation

Insight

Must have clear purpose

Must be used to deliver genuine public benefit in perpetuity

Must enable value creation and performance improvement

Must provide determinable insight into the built environment

TRUST

Security

Openness

Quality

Must be trustworthy

Must enable security and be secure itself

Must be as open as possible

Must be built on data of an appropriate quality

FUNCTION

Federation

Curation

Evolution

Must function effectively

Must be based on a standard connected environment

Must have clear ownership, governance and regulation

Must be able to adapt as technology and society evolve

The Gemini Principles for a national digital twin Source: Bolton et al., 2018:16) NATIONAL DIGITAL TWIN

VIRTUAL SINGAPORE

The Government has set an agenda to transform the way it delivers, operates, and uses the built assets through digital technology, data collection, sharing and analytic. This would enable effective information management which will aid the decision making process and lead to financial savings. Their aim is to build a national digital twin, not as a singular model but as an ecosystem of digital twins connected via securely shared data. Greater data sharing could release £7bn / year of benefits across the UK infrastructure sectors ~25% of total spend (Bolton et al., 2018). The Gemini Principles represent a framework for the realisation of the digital twin. This approach lacks interdisciplinary.

Virtual Singapore is a platform-based digital twin developed using geospatial and geometrical data sourced from public agencies and infrastructure sensors. It’s main purpose is to aid the best planning decisions and communicate information to citizens visually (NRF, 2018). The realisation of Singapore’s digital twin by integrating city-scale data from a range of sources to simulate and inform planning and management is mostly made possible due to its unique city-state status.

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What are the barriers to cities becoming smart?

Key Barriers CONSTRAINED DEMAND

UNDEVELOPED BUSINESS MODELS

An overview + Executive Summary:

Smart city Summary

Most smart initiatives involve the use of new and disruptive technologies that allow things to be done that were not possible before. As a result, smart technologies require the creation of new markets with new ways of working and new financial and governance models. These markets also need the right conditions to emerge: new innovation and entrepreneurial ecosystem where stakeholders interact effectively and where new business models and ways of working can be created so that new technologies can be adapted. Without this ecosystem, the smart technologies industry is unlikely to

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grow and mature. (Nohrova, 2014) As shown in the diagram on the right, there are a few aspects where there are barriers for cities to overcome in order to reap the full benefits that they can bring. One of the primary problems is the lack of technology related skills. Cities need to first add provision to accelerate the education system, teaching students how tech based qualifications can lead to better futures. Smart cities do not come without their share of controversy, especially with the public perception of how users data is used, and for what purpose.

Overall, smart cities seek to improve the performance of the city through technologies and data evaluation. The city has a better understanding by first sensing, monitoring, evaluating and finally actuating change. A better understanding of how the city is used will lead to:

LACK TECHNOLOGY SKILL + CAPACITY

DIFFICULT TO WORK ACROSS DEPARTMENTS AND CITY BOUNDARIES

CITIES HAVE LIMITED INFLUENCE OVER SOME BASIC SERVICES

CONCERNS FOR DATA PRIVACY, SECURITY AND VALUE

1. Reduced Energy demand, with optimised energy grids 2. Increased data analytics to better organise city services, driving better performance

DIFFICULT TO ENCOURAGE USER PARTICIPATION

3. More democratic governance through data sharing + digital twins. 4. Use big data so that cities can share and compare performance of systems and consumption to decrease GHG emissions and lead to zero carbon cities.

A Summary and barriers

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Conclusion The design of Zero Carbon Cities are at a critical juncture. As cities are the often primary sources of economic growth and innovation, it is imperative that cities lead the globe in achieving net-zero energy. It will be difficult to control global warming if cities are slow to implement agendas such as Zero Carbon. Carbon consumption and emissions is a problem shared by city dwellers, businesses, communities, and governments. For cities to get to or close to net-zero carbon, it requires a systemic transformation by each person, business, group, or agency. Each party faces its limitations, but these elements work together, the scale of improvements are

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amplified. For this reason each chapter in this research document sought to cover important aspects and initiatives for achieving net-zero carbon futures. Many companies are still using the same carbon-intensive growth model they’ve been using while contributing to the challenge of global warming. However, they should and can shift to a new, carbon-free route that ensures future security, wealth and good health. In actuality, it will be difficult to achieve carbon neutrality. For this to happen, the way cities handle real estate, construction, water, and waste and the plans for all of these will need to be completely overhauled.

There are global climate benefits which include improved prospects and living conditions for city dwellers, a higher standard of living and of public services. On top of that, more jobs are generated, higher productivity in general, as well as improved population health. However, shifting to a zero-carbon economy has its own set of challenges. Cities must act fast if the global temperature rise is to be capped to below 1.5°C. If significant strides in the right direction are not made by 2030, it may be too late to reverse some of the damage. If the worst climate predictions come true, many cities may not have a future at all.

There are numerous approaches to bring about change, as this paper has demonstrated. Even for authorities without access to capital markets, the financial industry can provide a variety of options for cities to obtain funds for change. Green transition projects, ranging from electric buses to increased recycling, have already shown to be a success in many communities. There is a lot of room for cities, investors, and other organisations to work together to get additional projects online. Achieving the design of zerocarbon city is within grasp. It’s a goal that cities all across the world can achieve if the correct steps are taken quickly.

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