EMIGMA Carbon Report by SJC82

Draft Report for

Manchester City Council

EMIGMA Review

Prepared for Bryan Cosgrove By Wood Holmes Ref: 4396

March 2012

82 King Street | Manchester | M2 4WQ | UK +44 (0) 161 870 2441 | www.woodholmes.com

Client:

Manchester City Council

Project Title:

EMIGMA Review

Reference Number:

4396

Version:

Confidentiality, copyright and reproduction:

This report is submitted by Wood Holmes to Manchester City Council as part of ongoing work on the GM Carbon Metrics Programme. It may not be used for any other purposes, reproduced in whole or in part, nor passed to any organisation or person without the specific permission in writing of Wood Holmes.

PREPARED BY Name:

Position:

Senior Consultant

Signature:

Date:

March 2012

AUTHORISED FOR ISSUE Name:

Stuart Smith

Position:

CEO

Signature: Date:

March 2012

Manchester City Council EMIGMA Review

Contents 1

Summary

Introduction and Background

Methodological Comparison

Outcomes and Implications

Key Questions

Recommended Model

Appendix 1 – Overview of EMIGMA Data Inputs

Appendix 2 – EMIGMA Presentation Geographies

Summary This document outlines findings and recommendations concerning the potential application of the Emissions Inventory for Greater Manchester (EMIGMA) dataset within the performance management framework underpinning carbon reduction in Greater Manchester.

Objectives This study seeks to explore the feasibility and implications of replacing the DECC Local and Regional CO2 dataset with the EMIGMA CO2 alternative as the core metrics within the Performance Management Framework.

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Methodologies A methodological comparison of the two datasets is summarised as follows: CO2 OUTPUT CATEGORY

ASSOCIATED MODULES DECC

EMIGMA

SCOPE AND BOUNDARY CORRELATION

Road Transport (A roads) K. Road Transport (Motorways)

Road Traffic

L. Road Transport (Minor roads)

CALCULATION METHODOLOGY CORRELATION

Motorways

Different

Other Major Roads

Key difference: EMIGMA use of GM SATURN traffic flow modelling as opposed to DfTderived alternative

Minor Roads

EMIGMA appears to present an advantage in the form of locally constructed data

M. Road Transport Other

None

N/A

Potential addition to EMIGMA at reporting stage

None

Bus Stations

N/A

Additional EMIGMA insight to Road Traffic CO2 emissions

Different Rail

COMMENTARY

F. Diesel Railways

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Rail

Key difference: EMIGMA use of local constructed rail traffic estimates

EMIGMA appears to present an advantage in the form of locally constructed data

Industrial Combustion

B. Industry and Commercial Gas

Commercial Gas Combustion

C. Large Industrial Installations

Point Source (Part A)

D. Industrial and Commercial Other Fuels E. Agricultural Combustion

Domestic Combustion

H. Domestic Gas I. Domestic 'Other Fuels'

Different Close

Point Source (Part B)

Key difference: EMIGMA use of Part A, Part B, and Boiler emission data collected by Local Authorities

EMIGMA appears to present an advantage in the form of locally constructed data

Point Source (Boilers) None

N/A

Potential addition to EMIGMA at reporting stage

Domestic Combustion

DECC and EMIGMA present close parallel

Electricity Consumption

A. Industry and Commercial Electricity

Electricity

DECC and EMIGMA present close parallel

LULUCF

N. LULUCF Net Emissions

None

N/A

Potential addition to EMIGMA at reporting stage

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Data Record The Data Record presented by EMIGMA and DECC is summarised as follows: Area

Activity AEA Modules

A. Industry and Commercial Electricity B. Industry and Commercial Gas Bolton C. Large Industrial Installations Bury D. Industrial and Commercial Other Manchester Fuels Oldham E. Agricultural Combustion X Rochdale F. Diesel Railways Salford G. Domestic Electricity Stockport H. Domestic Gas Tameside I. Domestic 'Other Fuels' Trafford J. Road Transport (A roads) Wigan K. Road Transport (Motorways) L. Road Transport (Minor roads) M. Road Transport Other N. LULUCF Net Emissions

EMIGMA Modules

Commercial Gas Combustion Point Source (Part A) Point Source (Part B) Point Source (Boilers) Domestic Combustion Motorways Other Major Roads Minor Roads Rail Electricity Bus Stations

Annual reports are prepared for each, as of March 2012, the following datasets are available (represented by their headline CO2 Total): 2005 2006 2007 2008 2009 2010 2011 EMIGMA (ktCO2/year) 19,827 18,166 18,904 DECC (ktCO2/year) 18389 18397 17836 17603 15902 -

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Highlight Differences The 2020 CO2 reduction target is 40.23% of the 2005 figure. Therefore, the higher 2005 baseline presented by EMIGMA requires more CO2 to be removed from the annual account in order to meet the target: 2005

2020

Dataset

Published Figure (ktCO2)

40.23% of 2005 (ktCO2)

DECC EMIGMA

18388.53 19,826.80

10990.82 11850.48

Required Annual Reduction by 2020 from 2005 (ktCO2) 7397.71 7976.32

A simple comparison of trend shows EMIGMA to demonstrate a higher degree of volatility in over reported years:

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In March 2012, DECC presents the steeper reduction trend. However, the DECC trend is dependent on the 2009 value for which an EMIGMA perspective is not yet available. The most significant divergence between EMIGMA and DECC is the treatment of Commercial/Industrial Combustion. EMIGMA appears to record significantly more CO2 emissions associated with Commercial/Industrial Combustion than DECC. This addition to the Commercial/Industrial CO2 perspective brought by EMIGMA appears to account for a substantial portion of the disparity between DECC and EMIGMA GM CO2 Totals. Furthermore, through its construction, the EMIGMA Commercial/Industrial Combustion estimate appears sensitive to change to an extent that the DECC alternative is not. This sensitivity carries for most AGMA areas, but is at its height for Trafford, followed by Rochdale, Manchester, and Bolton. The 2005-2007 trend exhibited by Transport emission categories reveals a further focus of fundamental difference between the DECC and EMIGMA datasets. In all, a switch from DECC to EMIGMA brings an asymmetric impact on AGMA areas and emission sector that must be considered in subsequent reduction strategies.

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Key Questions Overview answers to key questions are: In what ways are the DECC and EMIGMA datasets different and in what ways are the DECC and EMIGMA datasets the same? Key differences focus on: 

The additional treatment of E. Agricultural Combustion, M. Road Transport Other (Combustion of waste lubricants and emissions from LPG vehicles, and N. LULUCF Net Emissions by DECC



The additional treatment of Bus Stations by EMIGMA



The GM-based construction of Road Traffic CO2 account, integrating data compiled and developed at GM-level employing the GM SATURN traffic model and supplemental counts



The GM based construction of Industrial Point Source CO2 account, integrating data compiled and developed at GM level, employing data reports from Local Authority teams regarding field assessments of named facilities (Part A, Part B, and Boilers)

What are the positive implications of switching from DECC to EMIGMA within the Performance Management Framework? In the treatment of CO2 output from Road Traffic and Industrial Point Sources, the EMIGMA dataset integrates data components bearing closer connectivity to the respective emitting activities than the DECC alternative. This closer connectivity does not necessarily indicate ‘accuracy’ nor can an objective judgement be made between the two datasets. The primary interest for the carbon metrics programme is the potential benefits to ‘responsiveness’ in the data platform applied to judge performance. In drawing the EMIGMA treatment of Road Traffic and Industrial Point Sources into the performance management framework, high-level models for these components within the DECC dataset are replaced by local-level alternatives. In terms of monitoring impact associated with low carbon interventions, the local level alternatives may be considered more able to register impact or change and thus the EMIGMA dataset may provide more robust service to the decarbonisation drive.

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What are the negative implications of switching from DECC to EMIGMA within the Performance Management Framework? 

The EMIGMA dataset estimates a higher 2005 baseline value than the DECC alternative. By extension, the EMIGMA dataset implicates a higher tCO2 reduction challenge than the DECC dataset; as the 2020 CO2 reduction target is 40.23% of the 2005 figure. The EMIGMA dataset adds ~578ktCO2 to the reduction challenge relative to the DECC dataset.



Significant portions of the EMIGMA dataset are compiled by GM stakeholders employing GM resources. In contrast, the DECC dataset is compiled by DECC employing centralised resources. Specifically, the EMIGMA Point Source components (Part A, Part B, and Boilers) demand a level of resource from Local Authorities in collecting and reporting raw data.

Can the EMIGMA dataset be tuned to comply with the scope and boundary applied by DECC? The EMIGMA and DECC datasets already demonstrate a strong degree of overlay in their approach to defining the scope and bounds of the annual GM CO2 account. Principal differences are: DECC components EMIGMA

not

featured

in EMIGMA components not featured in DECC

E. Agricultural Combustion M. Road Transport Other (Combustion of waste lubricants and emissions from LPG Bus Stations vehicles N. LULUCF Net Emissions Through discussion with key EMIGMA representatives, it is clear that DECC modules can be added to the EMIGMA tCO2 report. The spatial resolution of each DECC module within the EMIGMA report is dependent on the nature of the associated raw data supplied to the EMIGMA team. Addition of identified DECC modules to EMIGMA Local Authority accounts is simply achieved through summing modules at the stage of reporting. Integrating identified DECC modules within the EMIGMA 1km2 report demands raw data and transformation resources drawing more resource.

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What actions are required to establish an up-to-date, annual EMIGMA report cycle? At the time of writing, March 2012, the EMIGMA dataset is reported for 2005, 2006, and 2007. Historic versions of EMIGMA predate 2005; however methodological evolution and the anchor-role of 2005 in the carbon metrics landscape limit their applicability. The next planned EMIGMA update will be for 2009. A principal factor considered to explain the delay in reporting post 2007 is principally the lack of a timely, full report on Part A, Part B, and Boiler emissions from each of the AGMA Authorities. Other features of the EMIGMA cycle such as data processing by the EMIGMA team are considered to take time and resource, albeit within the bounds of an annual reporting cycle. A key point of action focusses on the need to establish a stable, repeatable reporting of Part A, Part B, and Boiler emissions by Local Authorities. Actions implicated in the start-up of a modified EMIGMA report are considered in later sections.

What actions are required to establish the EMIGMA dataset as the core metrics within the Performance Management Framework? The Performance Management Framework has been designed with flexibility to transfer to the EMIGMA dataset as the principal metrics platform. Principal actions focus on the Performance Tracker tool which requires modification to the modular structure of CO2 reports, together with adjustment of associated ktCO2 Totals and Sub-Totals. Subsequent ktCO2 Totals and Sub Totals must be traced through the Decarbonisation Programme toolset.

What potential future developments in the field of metrics are relevant to the continued development of the Performance Management Framework? 

The conversion factors facilitating calculation of CO2 accounts are under constant review and modification. The DECC dataset reflects this

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development through retrospective updates to previous years at the point of publication of each new year in the sequence. This process of retrospective update does not currently feature in the EMIGMA report. 

The library of metrics underpinning the DECC Local and Regional CO2 reports are under development. A key example is the new energy consumption reports at LSOA. It is apparent that such data releases may modify EMIGMA processes for some modules.



Novel reporting elements such as the UK CRC Energy Efficiency Scheme league table, and the building Smart Meter programme potentially present novel perspectives of relevance to CO2 metrics. However, the accuracy and utility of such data may be queried.

Options The following options are presented to AGMA: IMPLICATION OPTION PRO

CON 

Potential lack of responsiveness to local interventions derived from high level modelling



Exposure to risk of discontinuation or modification of the dataset



Does not achieve a complete match with the DECC scope and boundary convention



Requires GM stakeholder resource to be committed to annual data collection and reporting cycle (specifically the collection of Part A, Part B, and Boiler data by each Local Authority)



Requires limited additional data

No Change

 Keep DECC 1 dataset as the  principal metrics platform

 Adoption of 2 EMIGMA in the 2005-2007 format

3 Adoption



CO2 Report compliant with national convention Low/no data production costs to GM stakeholders

Adopts potential benefits to responsiveness to impact and change brought by locally generated data components (specifically the CO2 estimates of Road Traffic and Industrial Point Sources)

Draws EMIGMA closer to compliance with national

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EMIGMA in 20052007 format with addition of DECC  modules at the resolution of Local Authority Area



Adoption of  EMIGMA in 20052007 format with 4 addition of DECC modules at the  resolution of 1km2

area CO2 reporting convention Adopts potential benefits to responsiveness to impact and change brought by locally generated data components (specifically the CO2 estimates of Road Traffic and Industrial Point Sources) Extends insight into spatial profile of CO2 across GM to the level of the 1km2 grid; supporting targeting of interventions Draws EMIGMA closer to compliance with national area CO2 reporting convention Adopts potential benefits to responsiveness to impact and change brought by locally generated data components (specifically the CO2 estimates of Road Traffic and Industrial Point Sources)

processing by EMIGMA team at the stage of reporting 

Requires GM stakeholder resource to be committed to annual data collection and reporting cycle (specifically the collection of Part A, Part B, and Boiler data by each Local Authority)



Requires additional data collection and processing effort from the EMIGMA team1



Requires GM stakeholder resource to be committed to annual data collection and reporting cycle (specifically the collection of Part A, Part B, and Boiler data by each Local Authority)

Recommendation Based on the need to balance cost and benefit, Option 3 emerges as a candidate for initial adoption; bringing the key benefits of the EMIGMA methodology at the spatial resolution of the performance management framework: In essence, Option 3 is continuation of the EMIGMA format evidenced in the 2005-07 reports with adjustment to the reporting at Local Authority Area level. Two key Key actions required in execution of the Option include: 

Establishment of a sufficiently resourced annual update cycle for the

The nature of this additional effort is indicated within the discussion of the review of presentation geographies in Appendix 2.

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EMIGMA report 

Establishment of a commitment to the Part A, Part B, and Boiler data reporting processes from each Local Authority



Development of a tailored EMIGMA CO2 report at Local Authority Area level; integrating the specified additional DECC modules



Resolution of resourcing and timing of EMIGMA reports for the 2007-2011 period



Feasibility review of retrospective update process for 2005 and 2006 EMIGMA reports



Reconfiguration of the Performance Management Framework to the EMIGMA data platform

The formulation of a schedule for execution depends on initial signals regarding preferred option and resource. The fundamental similarities between DECC and EMIGMA datasets facilitates transfer of the proposed adapted EMIGMA ‘Option 3’ report into the Performance Management Framework. The EMIGMA dataset presents a potential path to presentation of the adapted CO2 report at the resolution of 1km2. The technical and resource feasibility of this ‘Option 4’ development requires further exploration. In conjunction, the extent to which a 1km2 perspective adds value to the GM decarbonisation programme must be considered. Further future issues include: 

The conversion factors facilitating calculation of CO2 accounts are under constant review and modification. The DECC dataset reflects this development through retrospective updates to previous years at the point of publication of each new year in the sequence. This process of retrospective update does not currently feature in the EMIGMA report.



Novel reporting elements such as the UK CRC Energy Efficiency Scheme league table and the building Smart Meter programme potentially present

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novel perspectives of relevance to CO2 metrics. However, the accuracy and utility of such data may be queried.

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Introduction and Background

2.1

This document outlines findings and recommendations concerning the potential application of the Emissions Inventory for Greater Manchester (EMIGMA) dataset within the performance management framework underpinning carbon reduction in Greater Manchester.

Background 2.2

This work stems directly from the Greater Manchester (GM) Carbon Metrics Project2.

2.3

The Greater Manchester (GM) Carbon Metrics Project sought to establish an Inventory of Carbon Metrics and a Performance Management Framework serving Climate Change Strategy in the city region3.

2.4

A fundamental component of the resulting Performance Management Framework is a dataset providing a sector-segmented ‘end user’ account of carbon dioxide emissions (CO2) at Local Authority level.

2.5

Two datasets have been assessed and found to be credible options for this ‘account’:

2.6



The Department of Energy and Climate Change (DECC): Local Authority Carbon Dioxide Figures4



Highways Forecasting and Analytical Services, Transport for Greater Manchester: Emissions Inventory for Greater Manchester (EMIGMA)5

Currently, the Performance Management Framework utilises the DECC dataset6. This selection primarily derives from the fact that the DECC dataset presents the more recent update; the last annual account from DECC concerning 2009, the last annual account from EMIGMA concerning 2007.

Please contact Bryan Cosgrove, Manchester City Council with reference to the GM Carbon Metrics Programme. 3 GMCA. 2011. Greater Manchester Climate Change Strategy: Report of Chief Executive, Oldham th MBC’. 29 July 2011. www.agma.gov.uk/cms_media/files/9_g_m_climate_change_strategy.pdf 4 DECC. 2011. ‘Local Authority Carbon Dioxide Figures’. www.decc.gov.uk/en/content/cms/statistics/climate_stats/gg_emissions/uk_emissions/2009_laco2/2009 _laco2.aspx 5 Highways Forecasting and Analytical Services, TfGM. 2011. ‘EMIGMA Reports’. www.gmtu.gov.uk/reports/emigma.htm 6 Wood Holmes. 2011. ‘GM Carbon Metrics Project: Lot 1c Report and Tools’. Please contact Bryan Cosgrove, Manchester City Council.

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2.7

However, during discussions of data ‘quality’, the EMIGMA dataset, when up to date, appears to present significant advantages for tracking of CO2 performance in Greater Manchester.

2.8

A deeper comparison of the DECC and EMIGMA datasets is provided in Section 3 of this report.

2.9

This study seeks to further explore the potential application and advantage of the EMIGMA dataset as a foundation for the decarbonisation strategies of GM stakeholders.

2.10

Specifically, the study seeks to clarify the strategic implications and map an action plan for effective implementation of the EMIGMA dataset as the principal measure of Carbon performance across GM.

Objectives 2.11

Fundamentally, this study seeks to explore the feasibility and implications of replacing the DECC Local and Regional CO2 dataset with the EMIGMA CO2 alternative as the core metrics within the Performance Management Framework.

2.12

In so doing, this study seeks to answer the following questions: 

In what ways are the DECC and EMIGMA datasets different?



In what ways are the DECC and EMIGMA datasets the same?



What are the positive implications of switching from DECC to EMIGMA within the Performance Management Framework?



What are the negative implications of switching from DECC to EMIGMA within the Performance Management Framework?



Can the EMIGMA dataset be tuned to comply with the scope and boundary applied by DECC?



What actions are required to establish an up-to-date, annual EMIGMA report cycle?



What actions are required to establish the EMIGMA dataset as the core metrics within the Performance Management Framework?



What potential future developments in the field of metrics are relevant to the continued development of the Performance Management Framework?

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2.13

Findings and a potential action plan are outlined below.

Approach 2.14

2.15

Work has been lead by Wood Holmes with close support from: 

Bryan Cosgrove – Manchester City Council



Barry Weston – Highways Forecasting and Analytical Services, Transport for Greater Manchester



Ian Hull – Highways Forecasting and Analytical Services, Transport for Greater Manchester

In addition, the work closely references the Methodology statements outlined in key texts: 

DECC. 2011. 'Local Authority CO2 emissions estimates 2009: Methodology Summary'. www.decc.gov.uk/assets/decc/11/stats/climate-change/2755-localand-regional-co2-emissions-ests.pdf



Highways Forecasting and Analytical Services, TfGM. 2011. ‘EMIGMA Reports’. www.gmtu.gov.uk/reports/emigma.htm

Overview: EMIGMA 2.16

The Emissions Inventory for Greater Manchester (EMIGMA)7 presents a central record of information concerning the emission of pollutants identified in the UK Air Quality Strategy8.

2.17

Pollutants included within the EMIGMA data record include: VOCs, CO, NOx, SO2, Benzene, 1,3 Butadiene, PM10. Of principal interest to the application of EMIGMA within GM decarbonisation strategy is the ‘CO2 as C’ record.

7 8

EMIGMA: www.gmtu.gov.uk/reports/emigma.htm UK Air Quality Strategy: www.defra.gov.uk/environment/quality/air/air-quality/approach/

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2.18

A broad mission statement is presented in the 2006 report9: The database allows the magnitude and spatial distribution of emissions across Greater Manchester to be investigated and enables the relative importance of different sources of air pollution to be examined. The emissions data has a further role in providing the basis for dispersion modelling exercises and air quality management planning. In conjunction with transport models it also provides the basis for forecasting air quality and determining the effects of changes in land use planning and transportation policies on mass emissions.

2.19

It is important to note that the primary function of EMIGMA is not the reporting of Carbon; however a valuable account of Carbon output for GM is provided in its broader treatment of Air Quality.

2.20

EMIGMA groups emission sources into three broad categories:

2.21



Stationary Point Sources – emissions predominantly from industrial processes



Mobile Line Sources – emissions from road, rail, and air transportation



Area Sources – emissions from activities such as domestic energy usage that are not practically tackled at the resolution of Stationary Point or Mobile Line10

This grouping results in a modular structure for the CO2 as C record. The following is the reporting structure adopted in the 2006 published report: Table 1 – EMIGMA Modular Structure: MAJOR GROUP

MINOR GROUP SUB-GROUP Part A

Stationary Point Sources Point Sources

Part B Boilers Motorways

Roads Mobile Line Sources

Other Major Roads Minor Roads

Rail

Stations

GMTU. 2009. ‘EMIGMA Update 2006’. www.gmtu.gov.uk/reports/emigma/GMTUReport1530.pdf For example, emissions associated with Industrial Grid Gas, Industrial Grid Electricity, Domestic Grid Gas, Domestic Grid Electricity usage is potentially resolved at the area of individual postcode. Aggregation is applied as a practical data handling strategy. 10

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Track Domestic Gas Combustion Combustion

Domestic Non-Gas Combustion Commercial Gas Combustion

Area Sources Electricity

Domestic Electricity Commercial Electricity

2.22

A degree of flexibility surrounds the modular structure of the EMIGMA record; component datasets are readily recombined, input data evolves, and required reporting formats change.

2.23

A diverse array of datasets input into EMIGMA; a schematic is provided in Appendix 1. Both measured and modelled datasets are blended within EMIGMA; components include: 

Outputs from the GM Saturn Traffic Model



Reports from Part A and B Environmental Permit Audits



National energy data publications such as DECC Sub-National Energy Consumption Statistics11 and Digest of United Kingdom Energy Statistics (DUKES)12



Data from the National Atmospheric Emissions Inventory (NAEI)

2.24

An outline of data inputs is provided within Appendix 1.

2.25

Ultimately, emission components are aggregated to a 1km2 grid covering GM; reports at the NUTS3, Local Authority area are provided in annual reports.

2.26

Focussing on 2005, the year at which the Performance Management Framework is anchored, EMIGMA presents the following published dataset13:

Sub-National Energy Consumption Statistics: www.decc.gov.uk/en/content/cms/statistics/energy_stats/regional/regional.aspx 12 Digest Of United Kingdom Energy Statistics (DUKES): www.decc.gov.uk/en/content/cms/statistics/publications/dukes/dukes.aspx 13 GMTU. 2007. ‘EMIGMA Update 2005’. www.gmtu.gov.uk/reports/emigma/GMTUReport1331.pdf

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Table 2 – EMIGMA Published 2005-2012 Data Record – Totals: EMIGMA 2005 2006 2007 2008 2009 2010 2011 GM Total: ‘CO2 as C’ (t/year) 5,402,397 4,949,756 5,150,913- GM Total: CO2 (kt/year) 19,826.80 18,165.60 18,903.90 Note: conversion of 'CO2 as C' to 'CO2' requires multiplication of figure by 3.67 due to ratio of molecular weight for C and CO2 (12:44)

Roads

Rail

Part A

Part B

Boilers

Combustion

Bus Stations

Electricity

Total

Conversion to ktCO2 (kt/year)

Table 3 – EMIGMA 2005 – Segmented Dataset:

1,078,626 115,729 100,683 153,767 61,939 118,170 145,134 104,161 74,936 80,638 123,470

70,027 5,319 1,062 13,540 3,986 3,293 6,728 14,433 5,650 2,280 13,736

425,335 43,785 7,562 5,562 11,400 99,600 14,036 0 2,080 203,651 37,659

9,860 76 4,671 1,422 1,371 274 708 292 0 0 1,047

336,789 75,728 4,376 33,676 11,304 20,151 43,002 13,378 4,440 100,316 30,416

1,866,722 175,876 203,308 324,269 139,496 137,644 148,387 181,008 134,570 236,486 185,677

1,302 115 105 299 90 149 93 95 155 64 137

1613736 139424 95066 351351 113688 112440 149377 157365 119160 222782 153082

5,402,397 556,052 416,833 883,886 343,274 491,721 507,465 470,732 340,991 846,217 545,224

19,826.80 2,040.71 1,529.78 3,243.86 1,259.82 1,804.62 1,862.40 1,727.59 1,251.44 3,105.62 2,000.97

EMIGMA 2005 – ‘CO2 as C’ (t/year)

GM Bolton Bury Manchester Oldham Rochdale Salford Stockport Tameside Trafford Wigan

Note: conversion of 'CO2 as C' to 'CO2' requires multiplication of figure by 3.67 due to ratio of molecular weight for C and CO2 (12:44)

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Overview: DECC Local and Regional Carbon Dioxide 2.27

National Statistics of carbon dioxide emissions for local authority areas for 2009, and revised figures for the years 2005-2008, have been produced on behalf of DECC by AEA14.

2.28

To date, this DECC data has been updated on an annual cycle with a 21 month lag derived from the reporting conventions of the utilities sector (from which a substantial portion of input data is derived).

2.29

The principal output metric is ktCO2; emissions on an end-user basis have been assigned to all 406 local authorities in the UK. An outline of the nature and purpose of the dataset is provided15: Wherever possible, estimates are based on ‘real’ local data such as electricity and gas consumption, and emissions from sites where pollution is regulated. All emissions from energy production (e.g. from electricity generation or refineries) are allocated according to where energy is actually consumed by householders and businesses, rather than where the source of the energy produced is located. The remaining emissions are assigned to local areas on the basis of other local information such as traffic, population, employment and data on household fuel types. The main data sources are the UK National Atmospheric Emissions Inventory, maintained on behalf of DECC and the Devolved Administrations by our contractors, AEA, and DECC’s National Statistics of energy consumption for local authority areas. The work to produce the estimates was carried out by AEA. All emissions included in the national inventory are covered, except aviation, shipping and military transport, for which there is no obvious basis for allocation to local areas. These estimates are intended as a resource to help those working on local or regional indicators and inventories as part of their efforts to reduce carbon dioxide emissions. On their own, however, they cannot give all the information necessary to plan and monitor the progress of all

DECC. 2009. ‘Local Authority Carbon Dioxide Figures’. www.decc.gov.uk/en/content/cms/statistics/climate_stats/gg_emissions/uk_emissions/2009_laco2/2009 _laco2.aspx 15 DECC/ONS. 2009. ‘Statistical Release: 2009 Carbon Dioxide Emissions At Local Authority And Regional Level’. www.decc.gov.uk/assets/decc/11/stats/climate-change/2749-statis-2009-uk-carbondioxide-la-emissons.pdf

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local emissions reduction initiatives - this may require additional monitoring at the local level. 2.30

As such, unlike EMIGMA, the DECC dataset is solely concerned with the production of a Carbon report.

2.31

For each Local Authority, estimates are produced for each of the following components: A. Industry and Commercial Electricity

H. Domestic Gas

B. Industry and Commercial Gas

I. Domestic 'Other Fuels'

C. Large Industrial Installations

J. Road Transport (A roads)

D. Industrial and Commercial Other Fuels K. Road Transport (Motorways)

2.32

E. Agricultural Combustion

L. Road Transport (Minor roads)

F. Diesel Railways

M. Road Transport Other

G. Domestic Electricity

N. LULUCF Net Emissions

As with EMIGMA, the DECC dataset blends measured and modelled data; an overview of the inputs and transformations is provided below16: Table 4 – DECC Local and Regional CO2 Modular Structure: MODULE TITLE

DATA SOURCE

Industrial, Commercial and Agriculture Electricity

DECC regional energy statistics

Industrial, Commercial and Agriculture Gas

DECC regional energy statistics

Large Industrial Installations

Point source emissions for large industrial installations.

Industrial and

Remaining industrial emissions distributed using

DECC. 2011. ‘Local Authority CO2 emissions estimates 2009: Methodology Summary’. www.decc.gov.uk/assets/decc/11/stats/climate-change/2755-local-and-regional-co2-emissions-ests.pdf

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2.33

Commercial Other Fuels

high resolution (1km) emissions distribution of fuel use based in employment distributions and fuel intensity by sector.

Agricultural Combustion

High resolution (1km) emissions distribution maps developed under the NAEI programme

Diesel Railways

High resolution (1km) emissions distribution maps developed under the NAEI programme

Domestic Electricity

DECC regional energy statistics

Domestic Gas

DECC regional energy statistics

Domestic 'Other Fuels'

High resolution emissions distribution maps developed under the NAEI programme

Road Transport (A roads)

Road Transport (Motorways)

Road Transport (Minor roads)

Road Transport Other

LULUCF Net Emissions

Based on the NAEI data used by AEA to compile the DECC road transport fuel estimates. Emissions from fuel combustion in the road transport sector based on detailed DfT traffic census data and NAEI emissions factors.

LULUCF regional data supplied by Centre for Ecology and Hydrology17

Focussing on 2005, the year at which the Performance Management Framework is anchored, DECC presents the following published dataset (2011 update)18:

CEH – http://ecosystemghg.ceh.ac.uk/ DECC. 2011. ‘Local and regional CO2 emissions estimates for 2005-2009 – full dataset’. www.decc.gov.uk/publications/basket.aspx?FilePath=11%2fstats%2fclimate-change%2f2751-local-andregional-co2-emissions-estimates.xls&filetype=4&minwidth=true#basket 18

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Table 5 – DECC Published 2005-2012 Data Record – Totals: DECC 2005 2006 2007 2008 2009 2010 2011 GM Total (ktCO2) 18388.53 18397.21 17835.9 17602.88 15901.9 Table 6 – DECC 2005 – Segmented Dataset:

B. Industry and Commercial Gas

C. Large Industrial Installations

D. Industrial and Commercial Other Fuels

E. Agricultural Combustion

F. Diesel Railways

G. Domestic Electricity

H. Domestic Gas

I. Domestic 'Other Fuels'

J. Road Transport (A roads)

K. Road Transport (Motorways)

L. Road Transport (Minor roads)

M. Road Transport Other

Total

GM Bolton Bury Manchester Oldham Rochdale Salford Stockport Tameside Trafford Wigan

A. Industry and Commercial Electricity

DECC 2005

4264.28 335.31 217.51 974.4 272.6 285.31 392.54 385.97 301.78 722.57 376.29

2007.83 146.64 143.04 419.17 119.9 135.31 159.88 167.28 144.95 360.5 211.16

61.61 11.67 0 29.05 4.58 0 6 0.39 0.14 3.12 6.66

740.18 105.64 60.39 90.94 79.52 74.1 43.18 56.52 92.73 50.22 86.94

11.13 1.6 1.29 0.38 0.97 1.6 0.41 1.62 0.84 0.69 1.73

60.92 6.02 0 13.04 4.76 3.15 8.36 8.54 6.31 2.77 7.97

2469.49 261.26 177.59 425.05 194.06 191.15 224.7 287.33 203.59 221.02 283.74

3795.76 399.56 290.75 584.77 326.04 305.9 308.47 463.35 323.21 354.9 438.81

105.06 11 7.01 13.5 8.58 8.59 7.79 10.19 8.66 7.46 22.28

1469.27 180.5 97.04 244.2 117.07 106.4 177.69 160.34 92.99 109.87 183.17

1592.14 130.9 220.55 161.23 47.8 265.45 282.83 122.08 98.17 99.71 163.42

1723.14 228.67 132.91 314.22 110.07 114.82 152.43 195.17 107.61 188.23 179.01

21.63 2.48 1.91 3.49 1.33 1.88 2.69 2.29 1.35 1.9 2.31

66.18 1.22 1.52 3.21 2.02 3.31 34.49 3.38 2.42 7.84 6.77

Note: this data is from the 2011 update

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Methodological Comparison

3.1

An understanding of differences in the calculation, compilation, and reporting of DECC and EMIGMA datasets is crucial to informing a choice between the two.

3.2

It should be noted that this discussion does not seek to conclude with the identification of a ‘correct’ dataset, rather identify advantages presented by each dataset in supporting targeted decarbonisation in GM.

3.3

A preceding comparison of EMIGMA and DECC has been made by AEA in which the closeness of the EMIGMA and DECC boundary and scope was established (reference). This discussion builds on that foundation.

3.4

The following exploration of methodologies focusses on issues central to the ambitions of the Greater Manchester (GM) Carbon Metrics Project: 

The extent to which EMIGMA can be introduced as an alternative to the DECC dataset without drawing significant revision of the scope and boundary of CO2 reporting



The extent to which EMIGMA enhances perspective or utility within the performance management framework as an alternative to DECC

3.5

Put simply, the focus is to ascertain whether the EMIGMA dataset does, or can, comply with the national convention for scope and boundary encoded within the DECC dataset, whilst offering GM stakeholders an enhanced capability to identify and monitor emissions and interventions.

3.6

These issues are explored in the following sections.

Calculation 3.7

In order to facilitate a switch to the EMIGMA dataset as the principal performance tracking resource, EMIGMA must present a credible analogue to the scope and bounds of the DECC dataset. In other words, the EMIGMA dataset must not appear as a reduced scope and bounds of the GM footprint and thereby reduced responsibility and ambition for the decarbonisation strategy.

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3.8

The following sections contrast calculation methodologies for each module in overview. Full statements are available in respective methodology reports19,20.

Road Traffic 3.9

The DECC and EMIGMA datasets present close alignment in terms of scope and boundary applied in the estimation of CO2 output from Road Traffic: ► direct emission of CO2 through combustion of vehicle fuels during the movement of road vehicles on the road network within the GM geographic boundary.

3.10

The principal differences in the definition of scope and boundary are: 

An additional ‘Road Transport Other (Combustion of waste lubricants and emissions from LPG vehicles)’ module in the DECC report: accounting for 21.63ktCO2 in 2005 (0.12% of the Annual Total)



An additional ‘Bus Stations’ module in the EMIGMA report: accounting for 4.78ktCO2 (0.02% of the Annual Total)

3.11

The minor role played by these additional components does not greatly impact the overlay of DECC and EMIGMA for the purposes of tracking CO2 emissions from Road Traffic.

3.12

In terms of the calculation of CO2 estimates, DECC and EMIGMA approaches may be summarised as follows: Table 7 – Road Traffic CO2 Modules and Methods Overview: DATASET MODULES Road Transport (A roads) Road Transport (Motorways) DECC

OUTLINE Variables: Activity data derived from DfT traffic movement models and counts data

Road Transport (Minor roads)

Fleet composition data derived from Road Transport Other NAEI regional fleet projections (Combustion of waste Spatial Distribution: lubricants and emissions from

AEA. 2011. 'Local and Regional Carbon Dioxide Emissions Estimates for 2005-2009 for the UK: Technical Report'. www.decc.gov.uk/assets/decc/11/stats/climate-change/2753-local-and-regional-co2emissions-estimates.pdf 20 Highways Forecasting and Analytical Services, TfGM. 2011. ‘EMIGMA Reports’. www.gmtu.gov.uk/reports/emigma.htm

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LPG vehicles)

Mapped through OS road network maps Conversion Factors: NAEI

Motorways Other Major Roads

Variables: Activity data derived from GM SATURN traffic flows model and counts data Fleet composition data derived from NAEI regional fleet projections and DfT GMTU/TfGM transport statistics resources

Minor Roads Spatial Distribution: GM road network maps Conversion Factors:

EMIGMA

NAEI Variables: Activity and fleet composition data derived from GMPTE bus station usage reports Bus Stations

Spatial Distribution: Bus station address Conversion Factors: NAEI

3.13

3.14

With specific regard for the GM Metrics programme, the principal difference of note between the DECC and EMIGMA treatment of Road Traffic is the different sources of Activity Data: 

The DECC dataset utilises a centralised DfT-driven traffic modelling resource



The EMIGMA dataset utilises the GM SATURN Model attenuated with traffic counts to estimate traffic movements

Despite the capacity of the DfT model to reflect regional patterns of activity and fleet profile, the EMIGMA dataset appears to bear a closer relationship to the GM road network and may be considered more able to respond to interventions.

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Rail Traffic 3.15

The DECC and EMIGMA datasets present close alignment in terms of the scope and boundary of CO2 output associated with rail movements on the GM rail network: ► direct emission of CO2 through the combustion of diesel fuel during the movement of rail stock on the rail network within the GM geographic boundary.

3.16

In terms of the calculation of CO2 estimates, DECC and EMIGMA approaches may be summarised as follows: Table 8 – Diesel Rail CO2 Modules and Methods Overview: DATASET MODULES

OUTLINE Variables: Activity data derived from DfT statistics for vehicle kilometer (v.km) of freight, intercity, and regional journey types for each rail link

DECC

Diesel Railways

Fleet composition data based on estimation of journey type mix for each rail link Spatial Distribution: Mapping of GB rail link maps by Local Authority Area Conversion Factors: NAEI Variables: Activity data in the form of rail movement data is calculated by the EMIGMA team through reference to Passenger and Freight Rail timetables

EMIGMA

Rail

Fleet Composition data is accessed through operators or estimated via NAEI derived proxy

rail

Spatial Distribution: GM network map (72 track sections) Conversion Factors: NAEI

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3.17

The key difference between DECC and EMIGMA treatments of Rail Emissions appears to be compilation of the Activity Data in terms of how rail movement on the network is estimated.

3.18

Compiled by the EMIGMA team with direct reference to timetables and network maps for GM, the EMIGMA estimate appears to bear a higher degree of specificity to the GM context. The additional insights provided by a metric compiled at GM level appear to favour the pursuit of decarbonisation in terms of targeting and tracking impact.

3.19

Reference to the EMIGMA Rail CO2 record for 2005 and 2006 reveals a copy of data derived from the 2003 Rail Timetable has been used for the two years; undermining EMIGMA’s capability to act as a dynamic, responsive tracking device for Rail interventions. However, the 2007 update presents a refreshed calculation.

Industrial Combustion 3.20

A major component of the GM CO2 Total, the CO2 output of Commercial and Industrial facilities is complex.

3.21

The DECC and EMIGMA datasets both seek to account for three primary components: 

CO2 from consumption of Grid-derived Gas by Commercial and Industrial facilities



CO2 from combustion of fuels by stationary Commercial and Industrial facilities



CO2 from combustion and processes by large Industrial facilities

3.22

For these three components in aggregate, the DECC and EMIGMA datasets demonstrate a degree of correlation; however, disaggregated, the scope and bounds of modules is not necessarily matched.

3.23

Strongest correlation is apparent with the scope and boundary of emissions associated with Commercial and Industrial Gas Combustion: ► direct emission of CO2 through the combustion of Natural Gas in stationary, domestic facilities within the GM geographic boundary

3.24

The DECC data library has evolved since the 2006 EMIGMA report; potentially presenting new resources for the EMIGMA calculation that draw the two approaches closer still.

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3.25

Overlay in the modelling and estimation of the remaining components is less clean, despite their eventual closer alignment in terms of scope and boundary once summed. The common scope and boundary for these components is: ► direct emission of CO2 through the combustion of non-gas fuels in stationary, domestic facilities within the GM geographic boundary ► direct emission of CO2 through fuels combustion and processes at selected ‘large’ stationary, domestic facilities within the GM geographic boundary

3.26

CO2 output associated with the stationary combustion of fuel in industrial facilities is tackled in the following manner: Table 9 – Industrial Combustion Emissions Modules and Methods Overview: DATASET MODULES

OUTLINE Variables: Activity data derived from consumption reporting by DECC, derived from utilities

Industry Commercial Gas

Industry and Commercial designation is applied to all meters recording over and 73,200kWh Spatial Distribution: Meter-point mapped using National Statistics Postcode Directory Conversion Factors: NAEI

DECC

Variables: Activity data is based on NAEI database of point sources (including input from Environment Agency Pollution Inventory, the EU Emissions Trading Scheme Installations Large Industrial (which reported emissions to the Environment Installations Agency for the period 2005-2009) and other information obtained from AEA’s industry contacts) Implicated facilities include: Power stations, refineries, coke ovens; Other plant regulated as combustion processes under Integrated

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Pollution Control (IPC); Integrated steelworks; Cement clinker manufacture; Lime manufacture; Other plant regulated under IPC; Other sites for which EU ETS annual emissions data were available Spatial Distribution: Mapped to Point Source and 1m2 distribution Conversion Factors: NAEI Variables: Industrial and Commercial Other Fuels (all fuels – excluding electricity and gas and large industrial installations)

Activity data based on emissions distribution of fuel use based on employment distributions, point source data, and fuel intensity by sector Spatial Distribution: 1km2 distribution reported at NUTS3 Conversion Factors: NAEI Variables: Activity data for agriculture stationary combustion is mapped using the IDBR employment data. Off-road machinery emissions estimated through land use profiling. Emissions from the breakdown in the atmosphere of pesticides applied to crops estimated through arable land use mapping.

Agricultural Combustion

Spatial Distribution: Mapped according to land use profiling Conversion Factors: NAEI Variables: EMIGMA

Commercial Industrial Gas

and Activity data based on consumption reporting by DECC at MSOA Industry and Commercial designation is applied to all meters recording over

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73,200kWh Spatial Distribution: Domestic MSOA disaggregated by working population. Reported at 1km2 and NUTS3 Conversion Factors: NAEI Variables: Activity data based on data entry by GM Local Authorities for identified Part A, Part B, and Boiler point sources Implicated facilities logged in the Royal Point Source (Part A, Haskoning review and translated in the Part B, and Boiler) EMIGMA online data entry portal Spatial Distribution: Point Source coordinate Conversion Factors: NAEI 3.27

The common approach to establishing a threshold of 73,2000kWh indicates characterisation of CO2 from Gas Consumption by many GM SMEs as Domestic in both the EMIGMA and DECC datasets.

3.28

The approach to estimation of CO2 emissions from Large Industrial sites presents significant divergence between DECC and EMIGMA methodologies:

3.29



DECC seeks to integrate reporting from regulated facilities reporting to the Environment Agency Pollution Inventory (principally Part A) and EU ETS, together with estimates of fuel use in facility types and blending of emission estimates across geographic areas



EMIGMA demonstrates a more direct connection to reporting from specified industrial Part A, Part B, and Boiler facilities facilitated by data collection by AGMA Authorities

Overall, a case is made for EMIGMA to be considered to craft a more direct representation of large industrial facilities in the GM area which is potentially more responsive to intervention providing an annual cycle of data collection by Local Authorities is maintained.

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3.30

The DECC dataset presents additional components not fully accounted for by the EMIGMA dataset; specifically treatment of Non-Gas Industrial Combustion and Agricultural Combustion.

3.31

EMIGMA is considered to account for at least some Non-Gas Industrial Combustion within the treatment of Boiler point source sites. However Agricultural Combustion, a minor emissions component for the DECC GM estimate, appears to remain untreated in EMIGMA.

Domestic Combustion 3.32

The DECC and EMIGMA datasets present close alignment in terms of the scope and boundary of emissions associated with Domestic Combustion: ► direct emission of CO2 through the combustion of fuels (Gas, Oil, and Solid Fuel) in stationary, domestic facilities within the GM geographic boundary.

3.33

Emissions associated with the stationary combustion of fuel in domestic facilities are tackled in the following manner: Table 10 – Domestic Combustion Modules and Methods Overview: DATASET MODULES

OUTLINE Variables: Activity data based on consumption reporting by DECC, derived from utilities

Domestic Gas

Domestic designation is applied to all meters recording under 73,200kWh (potentially including SME gas usage) Spatial Distribution: Mapped using National Statistics Postcode Directory

DECC

Conversion Factors: NAEI Variables: Domestic Other Fuels Activity data based on averaged fuel profiles for (Oil and Solid Fuels) housing types (BRE) applied in combination with housing profiles

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Regional housing stock profiles informed by census, together with isolation of off-grid, low gas usage residential areas (DECC energy mapping) Spatial Distribution: OS Code-Point Conversion Factors: NAEI Variables: Activity data based on consumption reporting by DECC at MSOA Adopts DECC Domestic filter Domestic Combustion

Gas

Spatial Distribution: Domestic MSOA disaggregated by residential population. Reported at 1km2 and NUTS3 Conversion Factors: NAEI

EMIGMA

Variables: Activity data based on consumption reporting by DECC Adopts DECC Domestic filter Domestic Non-Gas Spatial Distribution: Combustion (Oil and Data presented at Local Authority Area level, Solid Fuel) disaggregated equally amongst GM MSOAs and ultimately reported at 1km2 Conversion Factors: NAEI

3.34

No substantial differences are apparent in the reporting of Domestic Gas Combustion at the level of Local Authority Area. Beyond this level of disaggregation, methodologies diverge; EMIGMA breaking down by population and DECC by house address facilitated by access to meter-point data.

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3.35

As is noted for Commercial and Industrial Gas Consumption, it is likely both DECC and EMIGMA incorporate CO2 derived from Gas consumption by SMEs and service sector businesses due to the common 73,200kWh threshold.

3.36

Differences are clear in the treatment of Domestic Non-Gas Combustion (Oil and Solid Fuel). Two approaches to modelling this component are presented; reflecting the difficulty posed by this element of fuel use.

3.37

The DECC dataset adopts a modelling process that is not readily influenced by change in the local area. EMIGMA does appear to integrate consumption data and is thus arguably more able to record change that is not dependent on revision of modelled proxies.

3.38

The DECC data library has evolved since the 2006 EMIGMA report; potentially presenting new resources for the EMIGMA calculation that draw the two approaches closer still.

Electricity Consumption 3.39

The DECC and EMIGMA datasets present close alignment in terms of the scope and boundary of emissions associated with consumption of electricity: ► indirect emission of CO2 by power generation facilities following consumption of electricity from the grid by the end user at powered facilities within the GM geographic boundary.

3.40

Emissions associated with the consumption of Electricity from the National Grid are tackled in the following manner: Table 11 – Electricity Modules and Methods Overview: DATASET MODULES

OUTLINE Variables: Activity data based on consumption reporting by DECC, derived from utilities

DECC

Industry and All meters recording over 100,000kWh, together with Commercial those meters located in an Industrial area logging Electricity between 50,000-100,000kWh Spatial Distribution: Meter addresses (MPAN – Meter Point Administration Number). Accurate to the level of a

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metered address, reported in part at LSOA and in full at NUTS3 Conversion Factors: NAEI Variables: Activity data based on consumption reporting by DECC, derived from utilities All meters recording under 50,000kWh, together with those meters located in a domestic area logging between 50,000-100,000kWh Domestic Electricity

Spatial Distribution: Meter addresses (MPAN – Meter Point Administration Number). Accurate to the level of a metered address, reported in part at LSOA and in full at NUTS3 Conversion Factors: NAEI Variables: Activity data based on consumption reporting by DECC at MSOA Adopts DECC Commercial/Domestic filter

EMIGMA

Electricity

Spatial Distribution: Domestic MSOA disaggregated by residential population, Commercial MSOA disaggregated by working population. Reported at 1km2 and NUTS3 Conversion Factors: NAEI

3.41

No substantial differences are apparent in the reporting of Electricity consumption at the level of Local Authority Area. Beyond this level of disaggregation, methodologies diverge; EMIGMA breaking down by population and DECC by MPAN address.

3.42

A question remains regarding the root of the difference between reported Electricity components at Local Authority Level for the 2005, 2006, and 2007 reports; methodology statements not immediately explaining the difference.

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3.43

The DECC data library has evolved since the 2006 EMIGMA report; potentially presenting new resources for the EMIGMA calculation that draw the two outcomes closer.

LULUCF 3.44

Land Use, Land Use Change and Forestry (LULUCF) activities are both a source and sink for atmospheric CO2. Generally emissions are produced from soils and liming of soils and are removed through forest growth.

3.45

LULUCF is only within the scope and boundary of the DECC dataset.

3.46

The Centre for Ecology and Hydrology (CEH) in Edinburgh annually prepares estimates of the uptake (removal from atmosphere) of CO2 by afforestation and net loss or gain of carbon dioxide from soils (emissions to or removals from the atmosphere) for inclusion in the UK GHG Inventory. Activity data is based on mapping of LULUCF categories to Local Authority boundaries21.

3.47

The LULUCF CO2 component appears to be entirely isolated from the EMIGMA report; presenting an opportunity to add the LULUCF component as an adjunct at the reporting stage.

Per Capita Emissions 3.48

The DECC Local and Regional CO2 dataset ultimately calculates a Local Authority Area tCO2 figure together with an associated per capita figure.

3.49

Currently, EMIGMA reports a CO2 as C figure that requires simple conversion to a tCO2 figure22. Per capita figures are not yet calculated under the EMIGMA reporting format (2005-07), but are readily incorporated at the reporting stage.

DECC. 2009. ‘Mapping Carbon Emissions & Removals for the Land Use, Land Use Change & Forestry Sector’. www.decc.gov.uk/en/content/cms/statistics/climate_stats/gg_emissions/uk_emissions/2009_laco2/2009 _laco2.aspx 22 Conversion of 'CO2 as C' to 'CO2' requires multiplication of figure by 3.67 due to ratio of molecular weight for C and CO2 (12:44)

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Retrospective Updates 3.50

The DECC dataset is currently subject to a process of retrospective update through which CO2 estimates for past years are revised in accordance with developments to elements such as the conversion factors used to translate activity measures to a tCO2 figure.

3.51

The effect is apparent in a comparison of 2009 and 2010 publications of the DECC dataset: Table 12 – Comparison of 2009 and 2010 DECC Regional and Local CO2 Publications: ktCO2 2005 2006 2007 2008 2009 DECC Local and Regional CO2 – 2009 18,197 18,208 17,670 17,491 n/a Edition DECC Local and Regional CO2 – 2010 18,389 18,397 17,836 17,603 15,902 Edition

3.52

A parallel process of updating for the EMIGMA dataset does not yet exist. The practicality and value of developing an update process for some EMIGMA modules appears as a point for further discussion. However, with updates to DECC having a relatively limited impact on the quoted tCO2 total, in the order of ~1% of the CO2 Total, the need for an update process appears to be secondary to other adjustments.

Reporting 3.53

The following sections review reporting formats for DECC and EMIGMA:

Modules 3.54

A key aspect of a dataset’s value to performance management of a decarbonisation programme is its capability to disaggregate components of the total and isolate key areas.

3.55

The extent to which the CO2 account can be disaggregated directly impacts the extent to which low carbon interventions can be targeted and their impact tracked.

3.56

Both DECC and EMIGMA datasets show a broadly aligned modular structure:

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Table 13 – Outline of Modules within DECC and EMIGMA Reports: Activity AEA Modules A. Industry and Commercial Electricity B. Industry and Commercial Gas Bolton C. Large Industrial Installations Bury D. Industrial and Commercial Other Manchester Fuels Oldham E. Agricultural Combustion X Rochdale F. Diesel Railways Salford G. Domestic Electricity Stockport H. Domestic Gas Tameside I. Domestic 'Other Fuels' Trafford J. Road Transport (A roads) Wigan K. Road Transport (Motorways) L. Road Transport (Minor roads) M. Road Transport Other N. LULUCF Net Emissions Area

EMIGMA Modules

Commercial Gas Combustion Point Source (Part A) Point Source (Part B) Point Source (Boilers) Domestic Combustion Motorways Other Major Roads Minor Roads Rail Electricity Bus Stations

3.57

In terms of the level of disaggregation presented by the reporting format, the EMIGMA report (2005/07 format) presents a key advantage with the capability to break down to Part A, Part B, and Boiler point source emissions.

3.58

However, the EMIGMA 2005 reporting framework does not readily support discrimination of impact on CO2 output associated with Commercial/Industrial and Domestic Electricity use. In addition, CO2 accounts for Domestic Gas and Domestic Non Gas are aggregated.

3.59

The following adjustments to the reporting format of EMIGMA have been discussed with the EMIGMA team: 

Disaggregation of the Electricity into Commercial/Industrial and Domestic components



Disaggregation of the Domestic Combustion into Gas and Non-Gas components

3.60

Achievable in theory, the practical dimensions of each adjustment will be considered in later sections.

3.61

The overlap is incomplete; LULUCF, Agricultural Combustion, and Road Transport Other are not fully represented in the EMIGMA account. However, these components

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summed account for ~0.5% of the GM Total in 2009 (DECC dataset) and thus represent minor components. 3.62

With regard to match the DECC scope and boundary, the addition of DECC modules ‘LULUCF’, ‘Agricultural Combustion’, and ‘Road Transport Other’ to the EMIGMA account at the stage of reporting is considered in later sections.

Reporting Schedule 3.63

Currently the DECC dataset is published on an annual cycle every September, 21 months after the end of the year in question. This 21 month lag is derived from data processing by utilities, NAEI, AEA, and DECC23: The full UK Inventory of Greenhouse Gas Emissions by which the UK reports to the UN Framework Convention on Climate Change (UNFCCC), is the top priority for the UK reflecting the need to meet international reporting obligations. This is completed at a 13 month lag. After this, the reallocation of emissions from source to end-user sector is carried out. Once this is complete, the Local Authority data can be produced. This is a complex mapping process, involving the data sources used in the preparation of the full UK inventory, as well as additional sources, including end-user inventories, road transport data and local energy data. It takes four months to undertake the modelling process, quality assurance the data and to prepare the results for publication.

3.64

Therefore, at the time of writing (December 2011) the most recent annual update is for 2009, published September 201124.

3.65

The EMIGMA dataset does not present an established reporting cycle; 2005 report was published in July 2007 and the 2006 report was published in July 2009. No further complete EMIGMA updates are yet published.

3.66

Factors determining the update cycle for EMIGMA are: 

Publication of EMIGMA input data by DECC



Processing of EMIGMA input data by TfGM

DECC. 2011. ‘UK Emissions Statistics: Frequently Asked Questions’. www.decc.gov.uk/assets/decc/statistics/climate_change/407-uk-emissions-stats-faq.pdf 24 DECC. 2011. ‘Local and regional CO2 emissions estimates for 2005-2009 – full dataset’. www.decc.gov.uk/publications/basket.aspx?FilePath=11%2fstats%2fclimate-change%2f2751-local-andregional-co2-emissions-estimates.xls&filetype=4&minwidth=true#basket

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

Reporting of input data by Local Authorities



Processing and compilation of the EMIGMA report

3.67

The timing of reporting of Part A, Part B, and Boiler estimates by Local Authority teams emerges as the principal factor impeding EMIGMA publication on the same annual schedule with 21 month lag demonstrated by DECC.

3.68

Potential for EMIGMA to reduce the 21 month lag presented by DECC requires further consideration; only being a possibility once regular Part A, Part B, and Boiler reporting is established.

3.69

Reference to DECC’s timetable of statistical releases25 indicates annual reporting for sub-regional energy consumption on an annual cycle with a ~6 month lag26. As such data represents one element of the EMIGMA input data resource; the potential to shorten the 21 month lag may be presented. However, further stakeholder discussion regarding the potential and practicality of shortening the 21 month lag period is required before firm conclusions can be made.

Spatial Resolution 3.70

The DECC Local and Regional CO2 dataset reports at Local Authority Level; using Local Authority Population estimates to calculate a tCO2 per capita figure for each Local Authority.

3.71

Data concerning energy consumption is available at higher levels of granularity for the DECC dataset; including breakdown of electricity and gas consumption to Lower and Middle Super Output level. However, this break-down is incomplete across the modules of the DECC Local and Regional CO2 dataset.

3.72

In publication, EMIGMA presents reports for each Local Authority area together with a computation of a 1km2 grid for GM. Conversations with EMIGMA representatives indicate flexibility with regard to spatial granularity, albeit within the bounds of available resource.

3.73

A commentary on spatial granularity has been provided by the EMIGMA team and is included in Appendix 2.

DECC. 2011. ‘DECC’s timetable of statistical releases for twelve months ahead’. www.decc.gov.uk/assets/decc/Statistics/publications/37-decc12monthstatscalendar.pdf 26 st th Annual reports are published in March for the preceding Gas-year (1 Oct to 30 Sept)

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The current structure of the GM Carbon Metrics performance management framework currently adopts a resolution to Local Authority Area. This decision derives from the structure of the ‘incumbent’ DECC dataset, currently used as the data foundation, together with consideration of the strategic application of the framework. This issue will be picked up in subsequent ‘Recommendations’.

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Summary 3.74

Key outcomes from the preceding overview are summarised below: Table 14 – Summary of DECC and EMIGMA Dataset Methodology Comparison:

CO2 OUTPUT CATEGORY

ASSOCIATED MODULES DECC

EMIGMA

SCOPE AND BOUNDARY CORRELATION

CALCULATION METHODOLOGY CORRELATION

COMMENTARY

Road Transport (A roads) K. Road Transport (Motorways) Road Traffic

L. Road Transport (Minor roads)

Motorways

Different

Other Major Roads

Key difference: EMIGMA use of GM SATURN traffic flow modelling as opposed to DfTderived alternative

Minor Roads

EMIGMA appears to present an advantage in the form of locally constructed data

M. Road Transport Other

None

N/A

Potential addition to EMIGMA at reporting stage

None

Bus Stations

N/A

Additional EMIGMA insight to Road Traffic CO2

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emissions Different Rail

Industrial Combustion

F. Diesel Railways

Rail

B. Industry and Commercial Gas

Commercial Gas Combustion

C. Large Industrial Installations D. Industrial and Commercial Other Fuels

E. Agricultural Combustion

Point Source (Part A)

Key difference: EMIGMA use of local constructed rail traffic estimates

EMIGMA appears to present an advantage in the form of locally constructed data

Different Close

Point Source (Part B)

Key difference: EMIGMA use of Part A, Part B, and Boiler emission data collected by Local Authorities

EMIGMA appears to present an advantage in the form of locally constructed data

Point Source (Boilers) None

N/A

Potential addition to EMIGMA at reporting stage

Domestic Combustion

DECC and EMIGMA present close parallel

H. Domestic Gas Domestic Combustion

I. Domestic 'Other Fuels'

4396 – MCC – 13/03/2012 © Wood Holmes

3.75

Electricity Consumption

A. Industry and Commercial Electricity

Electricity

DECC and EMIGMA present close parallel

LULUCF

N. LULUCF Net Emissions

None

N/A

Potential addition to EMIGMA at reporting stage

The outcomes and implications of this comparison will be considered in following sections.

4396 – MCC – 13/03/2012 © Wood Holmes

Outcomes and Implications

4.1

Methodological differences in the production and reporting of DECC and EMIGMA datasets carry implications for a decarbonisation strategy due to alternative starting points and sensitivity to change.

4.2

An awareness and understanding of the different outcomes of the DECC and EMIGMA calculation methodologies, together with the implications for the decarbonisation strategy, is crucial prior to any choice between the two.

4.3

The following sections explore differences in: 

The CO2 Annual Totals for GM



The CO2 Annual Totals for Local Authority Areas



The CO2 Annual Totals for Total Components

4.4

Throughout, the discussion uses 2005 as an anchor point due to its status as a key milestone year in the plotting of National and Regional carbon reduction strategies.

4.5

Primary outcomes of the discussion will be summarised in the proceeding reflection on the questions posed to this study.

Annual GM CO2 Totals 4.6

The starting point for comparison of the DECC and EMIGMA datasets is the headline annual CO2 tonnage totals for GM.

4.7

An overview comparison of available data for each of the DECC and EMIGMA datasets reveals a near 1.5MtCO2 difference in 2005, converging in 2006 at the 18.2-18.4MtCO2 mark, and diverging in 2007 to a ~738ktCO2 difference. Graph 1 – Comparison of DECC and EMIGMA Headline GM CO2 Totals:

4396 – MCC – 13/03/2012 © Wood Holmes

4.8

With regard to the performance management framework, the disparity at 2005 is of particular importance.

4.9

The 2020 CO2 reduction target is 40.23% of the 2005 figure. Therefore, the higher 2005 baseline presented by EMIGMA requires more CO2 to be removed from the annual account in order to meet the target: Table 15 – Comparison of DECC and EMIGMA Headline GM CO2 Totals: 2005

2020

Dataset

Published Figure (ktCO2)

40.23% of 2005 (ktCO2)

DECC EMIGMA

18388.53 19,826.80

10990.82 11850.48

Required Annual Reduction by 2020 from 2005 (ktCO2) 7397.71 7976.32

4.10

Selection of EMIGMA, and the EMIGMA 2005 baseline by extension, adds an additional 500ktCO2 to the CO2 reduction challenge.

4.11

Due to the importance of the 2005 figure, selection of EMIGMA appears to require clarification of the 2005 data-point; ensuring retrospective revisions to methodology and conversion factors are integrated.

4.12

In addition to the 2005 data-point, trend is of key importance to the comparison of DECC and EMIGMA datasets.

4.13

A simple trendline comparison reveals the following:

4396 – MCC – 13/03/2012 © Wood Holmes

Graph 1b - Comparison of DECC and EMIGMA Headline GM CO2 Totals Trends:

4.14

A degree of caution is necessary in the interpretation of a 3-number trend such as that presented by EMIGMA; a need heightened by the clear fluctuation across 20052007 pattern.

4.15

A key observation is that the EMIGMA gradient of decarbonisation, judged by simple trendline, is flatter than that presented by DECC. However, the DECC trendline is substantially deflected by the 2009 value; an impact not yet reflected in the EMIGMA dataset.

4.16

Data for 2007-2009 is required from EMIGMA to investigate trend further and establish whether GM has decarbonised at a steeper rate than that estimated by DECC. Qualitative assessment at this stage suggests a degree of alignment.

4.17

Overall, through comparison of headline CO2 a total alone, it is apparent that EMIGMA makes a higher estimate for 2005, when compared with DECC, and is sensitive to reductions in the 2005-2007 period that DECC is not.

Area Sub-Totals 4.18

The annual CO2 Totals for each GM Local Authority Area may be compared for DECC and EMIGMA:

Graph 2 – Comparison of DECC and EMIGMA Area CO2 Totals – 2005:

4.19

In 2005, EMIGMA presents the highest estimate in 6 of the 10 Area accounts. Overall, EMIGMA and DECC estimates show close correlation for the majority of Local Authority Areas.

4.20

The 2005 figures indicate the basis for disparity between GM CO2 Totals is principally the estimate for Trafford; the EMIGMA estimate featuring an additional ~1MtCO2 when compared with DECC.

4.21

This pattern is repeated to a lesser degree for the CO2 accounts of Bolton and Rochdale.

4.22

Therefore, choice of EMIGMA as the lead dataset, and the 2005 baseline by extension, over the DECC alternative is more significant for Trafford than other Areas. In switching from DECC to EMIGMA in the performance management framework, Trafford gains substantial additional CO2 reduction requirement.

4.23

Prior analysis of the passage between 2005-2007 indicates EMIGMA brings sensitivity to CO2 reductions that the DECC dataset does not register. Broken down to Local Authority Area, this sensitivity is not equally distributed:

Graph 3 – Comparison of DECC and EMIGMA 2005-2007 CO2 Reduction:

4.24

Overall, as is suggested by the pattern presented by EMIGMA and DECC CO2 Totals across 2005-2007, the EMIGMA dataset is sensitive to substantial CO2 reductions not recorded by the DECC methodology.

4.25

This sensitivity carries for most AGMA areas, but is at its height for Trafford, followed by Rochdale, Manchester, and Bolton.

4.26

Over the 2005-2007 period, no single AGMA area records a net increase in tCO2 emissions under the DECC methodology; a high degree of alignment in the reduction path is demonstrated across all areas.

4.27

Over the same period under the EMIGMA methodology, Trafford records a large ~800ktCO2 rise in emissions and Bolton, Bury, and Manchester record above distinct reductions of ~300-400ktCO2.

4.28

Therefore, the choice between DECC and EMIGMA impacts Areas differently.

4.29

In the case of a switch from DECC to EMIGMA, significant additions are made to the Trafford baseline (2005), and Trafford, Rochdale, Manchester, and Bolton gain sensitivity to increases and reductions not recorded under the DECC methodology.

Sector Sub-Totals 4.30

The Annual CO2 Totals for each component of the DECC and EMIGMA CO2 Totals may be compared in order to further probe the issue of sensitivity.

4.31

Due to the incomplete read across between the DECC and EMIGMA modular structures direct comparison of sector modules is not possible. Equivalent groupings may be developed in order to inform broad comparisons: Table 16 – Grouping of DECC and EMIGMA Modules: DECC Industrial, Commercial Agriculture Gas

EMIGMA and Commercial Combustion

Industrial/Commercial Large Industrial Installations

Gas

Point Source (Part A)

Point Source (Part B) Industrial and Commercial Other Point Source (Boilers) Fuels Domestic Gas Domestic

Domestic Combustion Domestic 'Other Fuels' Road Transport (A roads)

Other Major Roads

Road Transport (Motorways)

Motorways

Road Transport (Minor roads)

Minor Roads

Diesel Railways

Rail

Transport

Domestic Electricity Electricity

Industrial, Commercial Agriculture Electricity

and

Electricity

4.32

This manner of grouping modules is considered a close, but not perfect, match.

4.33

Comparison between DECC and EMIGMA for the 2005 record reveals Commercial/Industrial Combustion appears to account for a substantial portion of the disparity between the two datasets:

Graph 4 –DECC and EMIGMA 2005 Sector Group Comparison:

4.34

The difference between DECC and EMIGMA estimates for the Commercial/Industrial Combustion grouping is considered beyond the bounds of error for the approach to grouping modules for comparison:

4.35

Difference is not restricted to the Commercial/Industrial Combustion grouping; Transport and Electricity estimates each presenting a significant 750-1000ktCO2 difference.

4.36

Transport presents a particularly interesting result; essentially contrasting the use of GM-specific traffic modelling with that of the National traffic modelling to suggest DECC overestimates the CO2 account for transport in GM.

4.37

Different estimates for the Electricity and Domestic Combustion groupings are more difficult to explain in the sense that a comparison of DECC and EMIGMA methodologies for these groupings does not immediately explain a disparity of this magnitude.

4.38

The result flags a need for further investigation of the EMIGMA 2005 estimate for Electricity and Domestic Combustion. Potential explanations include; differences in the modelling of combustion of non-gas Domestic fuels, selection of conversion factor (and its retrospective update), application of geographic filter, or slight disparity in the DECC source publications.

4.39

The prominence of differences between the Commercial/Industrial Combustion grouping carries to comparison of reduction over the 2005-2006 period: Graph 5 –CO2 Reduction 2005-2006 DECC and EMIGMA Sector Group Comparison:

4.40

EMIGMA estimates a ~1.4MtCO2 reduction for the Commercial/Industrial Combustion grouping in 1 year; contrasting with a 0.2MtCO2 estimate from DECC. A similar, albeit lesser, relationship is apparent with the Domestic Combustion grouping. In addition, an equal, but opposite Transport trend is presented; EMIGMA suggesting emissions growth and DECC suggesting emissions reduction.

4.41

Again, the impact of retrospective updates on the DECC dataset must be acknowledged.

4.42

However, the 2005-2006 pattern presented by EMIGMA appears to broadly illustrate the impact of the ‘bottom up’ estimation of Commercial/Industrial Combustion emissions in the EMIGMA methodology and the novel Transport perspective.

4.43

The analysis may be extended to include the newly published EMIGMA 2007 update:

Graph 5b –CO2 Reduction 2005-2007 DECC and EMIGMA Sector Group Comparison:

4.44

The graph continues to support the observations that EMIGMA and DECC bring different sensitivities to emissions flux in each sector; particular divergence appearing focussed on Commercial/Industrial and Transport categories.

4.45

EMIGMA estimates a ~700ktCO2 reduction for the Commercial/Industrial Combustion grouping in 2 years; contrasting with a ~300ktCO2 estimate from DECC.

4.46

A similar relationship is apparent with the Domestic Combustion grouping; as discussed, the methodological basis for this is unclear but is suspected to reflect the different approach to modelling non-gas Domestic emissions, slight differences in the DECC source publications, and the process of retrospective update of the DECC dataset (the 2005 being updated in 2011).

4.47

Again, opposing Transport trends are presented; EMIGMA suggesting emissions growth and DECC suggesting emissions reduction.

4.48

The steep reduction in the EMIGMA record for Commercial and Industrial Combustion group over 2005-2006 is further resolved by the 2005-2006 trend in Part A, Part B, and Boiler CO2 totals for each Area:

Graph 6 –CO2 Reduction 2005-2006 EMIGMA Commercial and Industrial Group:

4.49

A level of volatility is apparent for the year that, if verified by subsequent updates, poses problems for any decarbonisation strategy in terms of attributing impact. A need to account for changes in the Part A, Part B, and Boiler record appears necessary if the impact of low carbon interventions is to be dissected.

4.50

Extending to the newly available EMIGMA 2007 dataset, the pattern of volatility is developed:

Graph 6b –CO2 Reduction 2005-2007 EMIGMA Commercial and Industrial Group:

4.51

The update confirms Trafford Industrial and Commercial point source emissions to represent a dominant component of the EMIGMA emissions record; bringing ~1.2MtCO2 to the CO2 Total in 2 years.

4.52

Overall, the sector analysis illustrates the methodological differences between DECC and EMIGMA.

4.53

Although similar in magnitude, estimates for Transport differ in trend between DECC and EMIGMA over the 2005-2006 period.

4.54

The most significant divergence between EMIGMA and DECC is the treatment of Commercial/Industrial Combustion. EMIGMA appears to record significantly more CO2 emissions associated with Commercial/Industrial Combustion than DECC. This addition to the Commercial/Industrial CO2 perspective brought by EMIGMA appears to account for a substantial portion of the disparity between DECC and EMIGMA GM CO2 Totals.

4.55

Through its construction, the EMIGMA Commercial/Industrial Combustion estimate appears sensitive to change to an extent that the DECC alternative is not. However, the dramatic changes recorded by the Part A, Part B, and Boiler categories of

EMIGMA over 2005-2007 appear to demand further scrutiny in order to allow the impact of low carbon strategy to be resolved against a backdrop of ‘noise’. 4.56

Further complexity is added to the comparison if we query whether EMIGMA responds differently to DECC under certain macroeconomic conditions due to its enhanced sensitivity.

Key Questions

5.1

In tandem with a simple comparison of datasets, their origins, architecture, and outputs, the study has discussed the practicality of developing EMIGMA for use in place of the DECC dataset.

5.2

The following sections summarise these conversations under the headings of each question posed to this study at the outset.

In what ways are the DECC and EMIGMA datasets different and in what ways are the DECC and EMIGMA datasets the same? 5.3

The two datasets are summarised in Table 14 – Summary of DECC and EMIGMA Dataset Methodology Comparison.

5.4

Key differences focus on: 

The additional treatment of E. Agricultural Combustion, M. Road Transport Other (Combustion of waste lubricants and emissions from LPG vehicles, and N. LULUCF Net Emissions by DECC



The additional treatment of Bus Stations by EMIGMA



The GM-based construction of Road Traffic CO2 account, integrating data compiled and developed at GM-level employing the GM SATURN traffic model and supplemental counts



What are the positive implications of switching from DECC to EMIGMA within the Performance Management Framework? 5.5

In the treatment of CO2 output from Road Traffic and Industrial Point Sources, the EMIGMA dataset integrates data components bearing closer connectivity to the respective emitting activities than the DECC alternative.

5.6

This closer connectivity does not necessarily indicate ‘accuracy’ nor can an objective judgement be made between the two datasets.

5.7

The primary interest for the carbon metrics programme is the potential benefits to ‘responsiveness’ in the data platform applied to judge performance.

5.8

In drawing the EMIGMA treatment of Road Traffic and Industrial Point Sources into the performance management framework, high-level models for these components within the DECC dataset are replaced by local-level alternatives.

5.9

In terms of monitoring impact associated with low carbon interventions, the local level alternatives may be considered more able to register impact or change and thus the EMIGMA dataset may provide more robust service to the decarbonisation drive.

What are the negative implications of switching from DECC to EMIGMA within the Performance Management Framework? 



Can the EMIGMA dataset be tuned to comply with the scope and boundary applied by DECC? 5.10

The EMIGMA and DECC datasets already demonstrate a strong degree of overlay in their approach to defining the scope and bounds of the annual GM CO2 account. Principal differences are: Table 17 – Overlaps in DECC and EMIGMA Components: DECC components EMIGMA

not

featured

in EMIGMA components not featured in DECC

E. Agricultural Combustion M. Road Transport Other (Combustion of waste lubricants and emissions from LPG

Bus Stations

vehicles N. LULUCF Net Emissions 5.11

Through discussion with key EMIGMA representatives, it is clear that DECC modules can be added to the EMIGMA tCO2 report.

5.12

The spatial resolution of each DECC module within the EMIGMA report is dependent on the nature of the associated raw data supplied to the EMIGMA team.

5.13

Addition of identified DECC modules to EMIGMA Local Authority accounts is simply achieved through summing modules at the stage of reporting. Integrating identified DECC modules within the EMIGMA 1km2 report demands raw data and transformation resources drawing more resource.

What actions are required to establish an up-to-date, annual EMIGMA report cycle? 5.14

At the time of writing, December 2011, the EMIGMA dataset is reported for 2005, 2006, and 2007.

5.15

Historic versions of EMIGMA predate 2005; however methodological evolution and the anchor-role of 2005 in the carbon metrics landscape limit their applicability.

5.16

The next planned EMIGMA update will be for 2009.

5.17

A principal factor considered to explain the delay in reporting post 2007 is principally the lack of a timely, full report on Part A, Part B, and Boiler emissions from each of the AGMA Authorities.

5.18

Other features of the EMIGMA cycle such as data processing by the EMIGMA team are considered to take time and resource, albeit within the bounds of an annual reporting cycle.

5.19

A key point of action focusses on the need to establish a stable, repeatable reporting of Part A, Part B, and Boiler emissions by Local Authorities.

5.20

Actions implicated in the start-up of a modified EMIGMA report are considered in later sections.

What actions are required to establish the EMIGMA dataset as the core metrics within the Performance Management Framework?

5.21

The Performance Management Framework has been designed with flexibility to transfer to the EMIGMA dataset as the principal metrics platform.

5.22

Principal actions focus on the Performance Tracker tool which requires modification to the modular structure of CO2 reports, together with adjustment of associated ktCO2 Totals and Sub-Totals.

5.23

Subsequent ktCO2 Totals and Sub Totals must be traced through the Decarbonisation Programme toolset.

What potential future developments in the field of metrics are relevant to the continued development of the Performance Management Framework? 



2020

Dataset

Published Figure (ktCO2)

40.23% of 2005 (ktCO2)

DECC EMIGMA

18388.53 19,826.80

10990.82 11850.48

Required Annual Reduction by 2020 from 2005 (ktCO2) 7397.71 7976.32

A simple comparison of trend shows EMIGMA to demonstrate a higher degree of volatility in over reported years:

Recommended Model

6.1

Following review of the EMIGMA and DECC datasets; the following options are presented with regard to use of the datasets within the Performance Management Framework developed in the preceding GM Carbon Metrics Programme: Table 18 – Options for the use of DECC and EMIGMA datasets within the GM Performance Management Framework: IMPLICATION OPTION PRO

CON 

Potential lack of responsiveness to local interventions derived from high level modelling



Exposure to risk of discontinuation or modification of the dataset



Does not achieve a complete match with the DECC scope and boundary convention



Requires GM stakeholder resource to be committed to annual data collection and reporting cycle (specifically the collection of Part A, Part B, and Boiler data by each Local Authority)



Requires limited additional data processing by EMIGMA team at the stage of reporting



Requires GM stakeholder resource to be committed to annual data collection and reporting cycle (specifically the collection of Part A, Part B, and Boiler data by each Local

No Change

 Keep DECC 1 dataset as the  principal metrics platform

 Adoption of 2 EMIGMA in the 2005-2007 format

 Adoption of EMIGMA in 20052007 format with  addition of DECC 3 modules at the resolution of Local Authority Area

CO2 Report compliant with national convention Low/no data production costs to GM stakeholders

Adopts potential benefits to responsiveness to impact and change brought by locally generated data components (specifically the CO2 estimates of Road Traffic and Industrial Point Sources)

Draws EMIGMA closer to compliance with national area CO2 reporting convention Adopts potential benefits to responsiveness to impact and change brought by locally generated data components (specifically the CO2 estimates of Road Traffic and Industrial Point Sources)

Authority) 

Adoption of  EMIGMA in 20052007 format with 4 addition of DECC modules at the  resolution of 1km2

6.2

Extends insight into spatial profile of CO2 across GM to the level of the 1km2 grid; supporting targeting of interventions Draws EMIGMA closer to compliance with national area CO2 reporting convention



Requires additional data collection and processing effort from the EMIGMA team27



Requires GM stakeholder resource to be committed to annual data collection and reporting cycle (specifically the collection of Part A, Part B, and Boiler data by each Local Authority)

Adopts potential benefits to responsiveness to impact and change brought by locally generated data components (specifically the CO2 estimates of Road Traffic and Industrial Point Sources)

Based on the need to balance cost and benefit, Option 3 emerges as a candidate for initial adoption; bringing the key benefits of the EMIGMA methodology at the spatial resolution of the performance management framework: Table 19 – Outline of Modules within the proposed ‘Option 3’ EMIGMA Report: AREA REPORTS

CO2 MODULES

Commercial Gas Combustion

Bolton

Point Source (Part A)

Bury

Point Source (Part B)

Manchester

Point Source (Boilers)

Oldham

Domestic Gas Combustion EMIGMA

Rochdale

Domestic Non-Gas Combustion

Salford

Motorways

Stockport

Other Major Roads

Tameside

Minor Roads

Trafford

Rail

The nature of this additional effort is indicated within the discussion of the review of presentation geographies in Appendix 2.

Wigan

Electricity Bus Stations E. Agricultural Combustion DECC

M. Road Transport Other N. LULUCF Net Emissions

6.3

In essence, Option 3 is continuation of the EMIGMA format evidenced in the 2005-07 reports with adjustment to the reporting at Local Authority Area level. Two key

6.4

Key actions required in execution of the Option include:

6.5



Establishment of a sufficiently resourced annual update cycle for the EMIGMA report



Establishment of a commitment to the Part A, Part B, and Boiler data reporting processes from each Local Authority



Development of a tailored EMIGMA CO2 report at Local Authority Area level; integrating the specified additional DECC modules



Resolution of resourcing and timing of EMIGMA reports for the 2007-2011 period



Feasibility review of retrospective update process for 2005 and 2006 EMIGMA reports



Reconfiguration of the Performance Management Framework to the EMIGMA data platform

The formulation of a schedule for execution depends on initial signals regarding preferred option and resource.

Implications Performance Management Framework 6.6

The fundamental similarities between DECC and EMIGMA datasets facilitates transfer of the proposed adapted EMIGMA ‘Option 3’ report into the Performance Management Framework.

6.7

Principal actions focus on the Performance Tracker tool which requires modification to the modular structure of CO2 reports, together with adjustment of associated ktCO2 Totals and Sub-Totals.

6.8

Subsequent ktCO2 Totals and Sub Totals must be traced through the Decarbonisation Programme toolset.

Future Considerations 6.9

The EMIGMA dataset presents a potential path to presentation of the adapted CO2 report at the resolution of 1km2.

6.10

The technical and resource feasibility of this ‘Option 4’ development requires further exploration.

6.11

In conjunction, the extent to which a 1km2 perspective adds value to the GM decarbonisation programme must be considered.

6.12

Currently, the GM decarbonisation strategy appears to function at the level of sector and Local Authority Area resolution.

6.13

Further future issues include: 



Novel reporting elements such as the UK CRC Energy Efficiency Scheme league table and the building Smart Meter programme potentially present novel perspectives of relevance to CO2 metrics. However, the accuracy and utility of such data may be queried.

Appendix 1 – Overview of EMIGMA Data Inputs

Reference: Highways Forecasting Analytical Services

and

Note 514 A Guide To HFAS Systems And Software Barry Weston September 2011 Fig 1, pg13

Appendix 2 Geographies

–

EMIGMA

Presentation

Review provided by Barry Weston: 8.1

8.2

The EMIGMA report uses a 1 km2 grid as its presentation geography. It is used for historical reasons and no doubt stems from a desire to be consistent with national datasets that use a similar geography. However, the datasets that EMIGMA is built from use a variety of geographies: 

Points for large industrial and commercial sources



Points for bus stations



Points for hot soak emissions (here the points are the centroids of the 864 transportation zones within GM)



Polylines for the links of the road network



Polylines for the links of the rail network



Polylines (at varying elevations) for the LTO paths at the airport



Polygons (MLSOA) for industrial/commercial and domestic gas and electricity deliveries



Polygons (LA boundaries) for non-gas domestic and commercial combustion



Grid square (5 km) for livestock emissions



Grid square (1 km) for non-LTO airport emissions

These different geographies are brought to the presentation geography using a number of methods, mostly implemented within a GIS: 

Points are allocated to their containing grid square.



Polyline objects are cut by the grid square boundaries and the attributes of each polyline are then distributed to the grid pro rata to the length of the polyline within each grid square.



Polygons are treated in a more complex manner depending on the nature of the commodity. For example, domestic gas consumption is split from MLSOA to LLSOA pro rata to the LLOSA populations. The LLSOA boundaries are then cut by the grid square boundaries and the LLSOA emissions are then

distributed to the grid pro rata to the area of the LLSOA within each grid square. 

8.3

5 km grid squares (giving livestock numbers) were first cut to remove all builtup areas. These are derived from the Ordnance Survey’s Meridian product which represents built-up areas as polygons. The areas remaining within each 5 km grid square were cut by the 1 km grid boundaries and the livestock numbers were then distributed pro rata to the (remaining after the removal of the built-up areas) area of each 5 km grid square within each 1 km grid square.

The same techniques can be applied to give any required presentation geography, for example wards, Parliamentary constituencies or LA boundaries. In the case of LA boundaries, which are relatively large compared to the 1 km grid, there are two options: 

Repeat the steps used to bring the data to the 1 km grid geography but using LA boundaries



Cut the 1km grid by the LA boundaries and then distribute the emissions pro rata to the area of each grid square in each LA.

8.4

The second option is quicker but will tend to smear emissions across LA boundaries. For example, consider a large industrial process which is within District A and also within a grid square that is split 50/50 by the boundary with District B. In this case the emissions from the process will be split equally between Districts A and B.

8.5

HFAS is able to undertake either option. Costs will be slightly higher for the second, more accurate, option. The additional work required by the second option will take approximately two days at a cost of £660.