Features of the Mactool model developed for Ukraine

REUTERS/ Toru Hanai

FEATURES OF THE MACTOOL MODEL DEVELOPED FOR UKRAINE, RESULTS FROM THE ANALYSIS AND IMPLICATIONS OF THESE RESULTS Prepared for The United Nations Development Programme In fulfillment of the requirement to develop a new generation greenhouse gas model that is suitable for sectoral emission modeling in Ukraine and that can be adjusted regularly based on bottom-up information about sectoral and installation-level emissions.

BY THOMSON REUTERS POINT CARBON London, 10 December 2013

ACKNOWLEDGEMENTS This report has been prepared by Thomson Reuters Point Carbon as part of the work under the project “Capacity Building for Low Carbon Growth in Ukraine�.

Thomson Reuters Point Carbon is grateful to the Ukrainian State Environmental Investment Agency for the strong support provided throughout the Project.

The MACTool has been developed in conjunction with Dr. Andreas Maestle and is a modified version of a previously developed version from the World Bank ESMAP team.

The data gathering work for the model has been supported by the Environmental Green Investment Fund (EGIF) and the Institute for Economic Forecasting (IEF) in Ukraine.

This project is kindly supported by the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety of Germany.

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ABOUT POINT CARBON Based on research on environmental, energy and resource management politics at the independent Fridtjof Nansen Institute in Norway, Point Carbon was established in 2000 and has since pioneered in providing services in the carbon and energy markets. The company has grown and matured along with the rapidly developing global environmental markets. Starting with an office in Oslo, Point Carbon now has offices established in Beijing, Kyiv, Malmö, London, Washington D.C and Rio de Janeiro. In May 2010, Point Carbon was acquired outright by Thomson Reuters, the world's leading source of intelligent information for businesses and professionals. This acquisition provides access for Point Carbon to a wide range of data and corporate resources that will enhance our services as well as connect us to a wider client and distribution network for our services.

With over 30 000 clients worldwide, Point Carbon is uniquely positioned as the world’s leading provider of independent news, analysis and consulting services for European and global power, gas and carbon markets. Point Carbon’s in-depth knowledge of power, gas and CO2 emissions market dynamics, positions it as the number one supplier of market intelligence. With clients in over 150 countries, including the world’s major energy companies, financial institutions, international organizations and governments, Point Carbon provides its clients with marketmoving information through monitoring fundamental markets, key market players and business and policy developments. Reports are also translated from English into Japanese, Mandarin, Portuguese, Polish, French, Spanish and Russian. Point Carbon presently employs around 200 specialists, including experts on international and regional climate policy and regulations, mathematical and economic modelling, forecasting methodologies, risk management, technical project knowledge and price discovery. Point Carbon also runs a number of high-level networking events, conferences, workshops and training courses.

POINT CARBON ADVISORY Point Carbon Advisory currently numbers around 15 people based in Oslo, London, Washington D.C, Rio de Janeiro and Kyiv. The department delivers bespoke, fully independent consultancy and multi-client studies to governments and companies in all corners of the world. The department capitalizes on Point Carbon’s world class databases, models, networks and teams of highly skilled analysts covering carbon, energy, corporate strategy, finance and economics. These assets uniquely position Point Carbon Advisory to meet clients’ needs for customized and indepth analysis on a wide range of carbon and energy issues. Advisory Services took off as the major provider of bespoke strategic advice by delivering “multi-client studies” on European and global emissions trading back in 2003. The high quality of the work provided by Point Carbon Advisory has been widely recognized internationally.

At the Energy risk awards 2010 it received the Advisory firm of the year award.

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TABLE OF CONTENTS Acknowledgements ........................................................................................................................... 2 Table of Contents............................................................................................................................... 4 Executive Summary ........................................................................................................................... 6 1

2

3

4

OVERVIEW OF THE MODEL ........................................................................................................ 8 1.1

MACTOOL BASICS .........................................................................................................................................9

1.2

STRUCTURE OF THE TOOL ..........................................................................................................................10

1.3

DATA REQUIREMENTS ................................................................................................................................11

1.4

TESTING CAPABILITIES ................................................................................................................................12

1.5

STRUCTURE OF A CALCULATION SHEET .....................................................................................................13

1.6

SUMMARY SHEETS OVERVIEW...................................................................................................................14

1.7

RESULTS FROM THE TOOL ..........................................................................................................................14

1.8

LIMITATIONS OF THE TOOL ........................................................................................................................16

1.9

ADDITIONAL TOOL FEATURES: BREAK EVEN CARBON PRICES ...................................................................16

SUMMARY OF MITIGATION ACTIONS CONSIDERED ................................................................. 19 2.1

POWER GENERATION MITIGATION ACTIONS ............................................................................................19

2.2

POWER CONSERVATION MITIGATION ACTIONS ........................................................................................20

2.3

FOSSIL FUEL MITIGATION ACTIONS ...........................................................................................................21

2.4

MANUFACTURING/INDUSTRY MITIGATION ACTIONS ...............................................................................21

2.5

WASTE MANAGEMENT MITIGATION ACTIONS ..........................................................................................22

2.6

BUILDINGS MITIGATION ACTIONS .............................................................................................................23

2.7

LAND USE MITIGATION ACTIONS ...............................................................................................................24

2.8

TRANSPORT MITIGATION ACTIONS............................................................................................................25

DATA INPUT AND OUTPUT GENERATION METHODOLOGY ...................................................... 27 3.1

INPUT VARIABLES .......................................................................................................................................27

3.2

DATA ANALYSIS PROCESS FOR MITIGATION ACTIONS ...............................................................................27

ASSUMPTIONS, RESULTS AND DISCUSSION ............................................................................. 32 4

4.1

GLOBAL VARIABLE ASSUMPTIONS .............................................................................................................32

4.2

POWER GENERATION ASSUMPTIONS & RESULTS ......................................................................................32

4.3

POWER CONSERVATION ASSUMPTIONS & RESULTS .................................................................................38

4.4

FOSSIL FUEL ASSUMPTIONS & RESULTS .....................................................................................................40

4.5

MANUFACTURING/INDUSTRY ASSUMPTIONS & RESULTS .........................................................................42

4.6

WASTE MANAGEMENT ASSUMPTIONS & RESULTS ...................................................................................46

4.7

BUILDINGS ASSUMPTIONS & RESULTS.......................................................................................................50

4.8

LAND USE ASSUMPTIONS & RESULTS ........................................................................................................53

4.9

TRANSPORT ASSUMPTIONS & RESULTS .....................................................................................................58

5

LIMITATIONS OF CURRENT ANALYSIS ...................................................................................... 64

6

CONCLUSIONS AND RECOMMENDATIONS ............................................................................... 65

APPENDIX A1: POWER GENERATION ACTIONS RESULTS .................................................................. 68 APPENDIX A2: POWER CONSERVATION ACTIONS RESULTS .............................................................. 70 APPENDIX A3: FOSSIL FUEL ACTIONS RESULTS ................................................................................. 71 APPENDIX A4: MANUFACTURING ACTIONS RESULTS ....................................................................... 72 APPENDIX A5: WASTE MANAGEMENT ACTION RESULTS ................................................................. 73 APPENDIX A6: BUILDINGS ACTION RESULTS .................................................................................... 74 APPENDIX A7: LAND USE ACTION RESULTS ...................................................................................... 75 APPENDIX A8: TRANSPORT ACTION RESULTS .................................................................................. 76

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EXECUTIVE SUMMARY This report summarizes the features and key results from the marginal abatement cost tool (MACTool) developed for Ukraine for the project entitled; ”Capacity Building for Low Carbon Growth in Ukraine”. A similar model had been previously commissioned by the World Bank Energy Sector Management Assistance Program (ESMAP) who worked with independent contractor Dr. Andraes Maestle to develop this for Brazil. TRPC worked with Dr. Maestle to significantly modify the model so that the data analysis for sectors and measures considered in each sector could be conducted independently from the tool itself. With this modification, users of the tool can prepare estimates of capacity deployment, capital costs, operating costs, economic lifetimes and emissions intensity for each sector and measure independent of the tool. These estimates then form the basis of the inputs into the tool to calculate marginal abatement cost curves (MACC) for various stakeholders (e.g. societal or investor) based on different inputs that are most relevant to those stakeholders such as costs, taxes, discount factors etc. The details of the model calculations and its features are described in more detail in Chapter 1 of this report.

TRPC worked with another local Ukranian expert EGIF to gather and finalize a list of 78 mitigation actions (or measures) across eight sector classifications listed below:        

Power Generation (12 actions) Power Conservation (7 actions) Fossil Fuel (3 actions) Manufacturing/Industry (13 actions) Waste Management (10 actions) Buildings (8 actions) Land Use (18 actions) Transport (7 actions)

A description of the individual mitigation actions considered is included in Chapter 2 of this report. EGIF gathered data for these actions from a variety of sources such as the Energy Strategy of Ukraine for the period up to 2030 (current draft version); the National Inventory Report of Anthropogenic Emissions by Sources and Removals by Sinks of Greenhouse Gases in Ukraine for 1990−2010; the Transport and Communication document of Ukraine 2011 (statistical yearbook); project PDDs; and documents from nationally respected organizations such as the National Institute for Strategic Studies (NISS). TRPC then used basic interpolation methods to arrive at 41 year forecasts (2014-2054) for key input parameters that impact MAC values. This interpolation process is described in Chapter 3 of the report.

Based on the inputs MACCs were produced for all eight sectors and the basic data and results from this exercise have been summarized in Chapter 4 of this report. The results in this study indicate that from a societal perspective Ukraine can implement 40 mitigation actions that cost less than $20/ton and can provide cumulative reductions of ~3900 million tons CO2e from 2014-2054. This corresponds to annual reductions of ~96 million tons which is ~25% of the 390 million tons/yr reported by Ukraine for UNFCCC in 2011.

Several of the power generation and power conservation sector actions such as large hydro, pumped storage, geothermal and coal to natural gas conversion, transmission upgrade etc. appear to have favourable, estimated MAC values. As anticipated some of the longer term technology such as carbon capture and sequestration and 6

coal to natural gas conversion (enabled by shale gas development) appeared to have significant emissions benefits in the 100s of millions tons cumulative saved from 2014-2054. Actions in the fossil fuel industry that appear promising deal with the use or clean up of coal mine methane with estimated MAC values of approximately $2/ton and cumulative emissions benefits in the 10s of millions of tons CO2e cumulative from 2014-2054. Similar single digit MAC values were estimated for actions such as iron ore production energy efficiency and continuous steel rolling in the manufacturing industry and these also had similar emissions benefits as the fossil fuel industry actions. In terms of actions for the waste management sector, increased deployment of landfill gas power, upgrading obsolete municipal waste treatment facilities and utilizing segregated colloids were identified as cost effective (<$15/ton). The emissions benefits (savings in the 100s of millions of tons CO2e from 2014-2054) were however largest for some longer term measures such as biodegradable plastics and waste production limits.

Actions targeted towards improving efficiency in the building sector such as draught proofing, energy efficient windows, boiler upgrades etc. also had very good cumulative emissions benefits (in the 10s of millions tons CO2e over a 41 year period) but among these only draught proofing had estimated MAC value of <$10/ton. In the land use category increased deployment of biogas solutions for cattle farming, reducing the number of cows through enhanced milk production and use of organic farming had estimated MAC values of <$20/ton with emissions benefits in the 100s of millions of tons CO2e over a 41 year period. Finally, a majority of the transport sector categories had very large estimated MAC values in the 100s of $/ton and the ones with significant emissions benefits included actions such as vehicle energy efficiency and biofuel deployment which are longer term technologies.

Chapter 5 summarizes some of the limitations of the current analysis and a large part of these limitations has to do with the difficulty of producing 41 year forecasts for deployed capacities, capital costs, operating costs, fuel costs etc. across all of the mitigation actions. It is therefore noted that the analysis presented in this report is simply a snapshot in time and is not meant to be static. TRPC believes that by delivering a flexible tool and the underlying data used in the tool, a transparent framework has been established to improve and update the analysis in the future. Recommendations on how the analysis can be strengthened further have been summarized in Chapter 6.

It will be important that as Ukraine inherits this tool, processes must be established and personnel identified who can conduct regular industry surveys that update the underlying data and results from the tool.

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1 OVERVIEW OF THE MODEL This document provides a summary of the MACTool Model that has been developed by Thomson Reuters Point Carbon for Ukraine for the project, ”Capacity Building for Low Carbon Growth in Ukraine”. Results from the model are also presented along with a discussion on these results, limitations of the current analysis and recommendations for future enhancements of the analysis.

The tool that has been developed for the project is a significantly modified and improved version of the tool developed by the World Bank’s ESMAP office for Brazil. Over 50% of the underlying code has been updated and adapted for this project. Figure 1 provides an illustration of the front page of the MACTool.

Figure 1. MACC Tool Front Page The primary customisations and features introduced into the model for Ukraine by the TRPC team include:  Inclusion of different sector definitions to map more closely with the economic sectors in Ukraine with the ability to include a total of 111 mitigation activities across all sectors. 

Creation of a more generic (less hard coded) set of input variables for key drivers of marginal abatement costs across sectors.



Expansion of the analysis period to 41 years to include the 2014 to 2054 period that can be modified at a future date to reflect future 41 year periods.

This chapter provides a description of the model, underlying methodology for calculating key parameters such as marginal abatement costs and other features of the model.

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1.1 MACTOOL BASICS The MACTool is a Microsoft Excel based model that allows calculating, ranking and visualizing the Marginal Abatement Cost (â&#x20AC;&#x153;MACâ&#x20AC;?) of emissions-reducing measures (or any other measures) that are included in the Tool, and other costs (such as...). Marginal Abatement Cost curves (â&#x20AC;&#x153;MAC curvesâ&#x20AC;? or MACCs) can be used by policy decision makers to assess the emission reduction potential in a country, sector or a region. MAC curves rank the cost associated with emission reduction measures, often called mitigation actions (or measures), and thus allow policy makers to prioritize global and sector specific policy instruments. MAC curves help to answer the questions: By how much can emissions be reduced?

At what cost can emissions be reduced?

What should be done first?

The Marginal Abatement Cost is defined as follows: đ?&#x2018;´đ?&#x2018;¨đ?&#x2018;Ş đ?&#x2018;Şđ?&#x2019;&#x2013;đ?&#x2019;&#x201C;đ?&#x2019;&#x201C;. đ?&#x2019;&#x2013;đ?&#x2019;?đ?&#x2019;&#x160;đ?&#x2019;&#x2022;/đ?&#x2019;&#x2022; đ?&#x2018;Şđ?&#x2018;śđ?&#x;? =

[đ?&#x2018;ˇđ?&#x2018;˝ đ?&#x2018;Źđ?&#x2019;&#x201E;đ?&#x2019;?đ?&#x2019;? đ?&#x2018;Şđ?&#x2019;?đ?&#x2019;&#x201D;đ?&#x2019;&#x2022; đ?&#x2018;łđ?&#x2019;?đ?&#x2019;&#x2DC; đ?&#x2018;Şđ?&#x2019;&#x201A;đ?&#x2019;&#x201C;đ?&#x2019;&#x192;đ?&#x2019;?đ?&#x2019;? đ?&#x2018;Şđ?&#x2019;&#x2013;đ?&#x2019;&#x201C;đ?&#x2019;&#x201C;. â&#x2C6;&#x2019; đ?&#x2018;ˇđ?&#x2018;˝ đ?&#x2018;Źđ?&#x2019;&#x201E;đ?&#x2019;?đ?&#x2019;? đ?&#x2018;Şđ?&#x2019;?đ?&#x2019;&#x201D;đ?&#x2019;&#x2022; đ?&#x2018;Šđ?&#x2019;&#x201A;đ?&#x2019;&#x201D;đ?&#x2019;&#x2020;đ?&#x2019;?đ?&#x2019;&#x160;đ?&#x2019;?đ?&#x2019;&#x2020; đ?&#x2018;Şđ?&#x2019;&#x2013;đ?&#x2019;&#x201C;đ?&#x2019;&#x201C;. đ?&#x2018;źđ?&#x2019;?đ?&#x2019;&#x160;đ?&#x2019;&#x2022;] (đ?&#x2018;Źđ?&#x2019;&#x17D;đ?&#x2019;&#x160;đ?&#x2019;&#x201D;đ?&#x2019;&#x201D;đ?&#x2019;&#x160;đ?&#x2019;?đ?&#x2019;?đ?&#x2019;&#x201D; đ?&#x2018;Šđ?&#x2019;&#x201A;đ?&#x2019;&#x201D;đ?&#x2019;&#x2020;đ?&#x2019;?đ?&#x2019;&#x160;đ?&#x2019;?đ?&#x2019;&#x2020; đ?&#x2019;&#x2022; đ?&#x2018;Şđ?&#x2018;śđ?&#x;?â&#x20AC;&#x201C; đ?&#x2018;Źđ?&#x2019;&#x17D;đ?&#x2019;&#x160;đ?&#x2019;&#x201D;đ?&#x2019;&#x201D;đ?&#x2019;&#x160;đ?&#x2019;?đ?&#x2019;?đ?&#x2019;&#x201D; đ?&#x2018;łđ?&#x2019;?đ?&#x2019;&#x2DC; đ?&#x2018;Şđ?&#x2019;&#x201A;đ?&#x2019;&#x201C;đ?&#x2019;&#x192;đ?&#x2019;?đ?&#x2019;? đ?&#x2019;&#x2022; đ?&#x2018;Şđ?&#x2018;śđ?&#x;?)

where: PV = Present Value in the Base Year Curr. Unit = Currency unit t CO2= tons of Carbon dioxide equivalent If the present value (PV) of the Economic Cost is lower in the Low Carbon case than the PV of the Economic Cost in the Baseline, then the MAC is negative (provided the associated Baseline Emissions are higher than the Low Carbon emissions). In calculating the present value the real social discount rate is used. The social discount rate is usually lower than the discount rate that a private investor would apply as the society will usually take a longer term view when investing. A society is well advised to take the welfare of future generations into account, something that private investors and individuals are notoriously reluctant to do. Private investors require higher and more immediate benefits compared with societies.

Further, it is important to note that real economic costs are used in calculating the Marginal Abatement Cost.

Economic costs are the cost to the society. In deriving the economic cost taxes must be deducted from the market prices and subsidies must be added. In the same manner import duties must be subtracted from the market price.

Prices should take transportation cost to the point of usage into account. If for example coal or natural gas is imported and used as fuel in power plants or feedstock in chemical facilities, the coal or natural gas price should include the cost of transporting gas or coal to the plants In the case of an investor oriented MAC, the core calculation remains the same for emissions but present value calculations will defer because of changes in costs to energy (i.e. retail rates used), discount factors because investor opportunity costs and risk premium requirements are different across technologies and time periods and tax code that ultimately impacts project revenue. Since this project was being conducted for the state, i.e. Ukraine the economic MAC for society has been calculated and reported throughout this report. The tool has calculations that can look at data from an investor perspective and this is discussed at the end of this chapter.

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Marginal Abatement Costs are calculated in real prices of a Base Year. If all prices go up by 5% for example, the same amount of goods and services will nominally cost 5% more but in real terms nothing has changed. If inflated (nominal) prices are used in the calculations the Marginal Abatement Costs shown will be higher than what they really are. This does not mean that relative prices cannot shift along the timeline. For many technologies, for example solar photovolatic, cost reductions are expected and should be taken into account. Relative price changes need to be reflected in relation to the prices of the Base Year.

Implementing a mitigation activity with a negative MAC provides net benefits to society. Lower MAC values are preferred because the larger the number, the greater the effective costs on emissions need to be for that technology to achieve mass adoption. This of course is an over simplification because several other variables such as technology maturation (which reduces costs), policies (e.g. renewable energy standards) and risks for implementing the project (that impact project economics) also play significant roles in identifying the mitigation actions that are likely to have the biggest impact. Nevertheless, a MAC curve provides a first cut estimate of what the prices could be on emissions to enable the implementation of actions that can be subsequently refined through more detailed sectoral and industrial analyses.

To summarize, MAC curves help answer the question of how much and at what cost emissions can be reduced.

They help to find out what the most cost effective mitigation activities are and in what order a society might want to invest in mitigating measures. MAC curves help answer these questions from a societal point of view based on real economic prices and discounting future cost and revenues by the social real discount rate. A detailed description of the formulae used can be found in the annex of the MACCManual Chapter Calculations – Sub Chapter Marginal Abatement Cost Calculations included in the tool.

1.2 STRUCTURE OF THE TOOL Figure 2 provides a schematic for the overall tool structure.

Figure 2. MACTool Structure The MACTool separates Input – Calculation – Output. All data entries are made in the input section. The calculation section contains only formulas. The Output section consists of Sector Summary sheets and a filtering sheet and 10

sorting sheet that feed results into the graphs. When the user creates a new MAC curve the user needs first to set a Base Year and name a unit of account. Data input can be made either using the Graphical User Interface (GUI) as shown in Figure 3 or through copy and paste.

Figure 3. MACTool Data Entry GUI

The MACTool supports a time line of a Base Year plus 41 years (for example Base Year 2013, timeline 2014-2054).

The timeline can be freely set from 11 to 41 years.

1.3 DATA REQUIREMENTS The current version of the MACTool is structured to be generic. All investment cost, operations & maintenance cost, energy cost and revenues associated with Baseline and Low Carbon emissions need to be compiled outside of the model. For this study Excel based data files were prepared that allow the creation of cost and revenue series for the Baseline and the Low Carbon case. Based on these cost and revenue streams, the tool then calculates the Marginal Abatement Cost for the mitigation activities for which the user has entered data.

Baseline and Low Carbon cases and the associated emissions must be generated outside of the tool. These cases are typically designed in consultation with local policy and technical experts to reflect capacity build out, cost trajectories and revenue estimates over the time period of interest. This decoupling assures users that there are no interconnected numbers within the tool that require updating especially when changes are made to the underlying data. Base case and low carbon cases can change with time and the delivered version of the tool allows for independently changing these cases and the underlying numbers before entering these into the tool for the MACC estimation.

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The tool supports the following sectors as outlined in Table 1.

Table 1. MACTool Sectors and Mitigation Activities/Actions Number of mitigation activities supported

Sector

22

Power generation

10

Power conservation

12

Buildings

12

Fossil

15

Manufacturing

10

Transport

10

Waste

20

Land use

111

Total

Each sector has its own TBA (have we said before what TBA is?) sector input sheet. The data input requirements in the Power sector differ somewhat from the other sectors as the user needs to enter the projected levelized investment cost/MWh (MWh = Mega watt hour) (i.e. after discount factor applied to arrive at present values), the operation and maintenance (O&M )cost/MWh, the Fossil fuel cost /MWh and the projected green house gas (GHG) emissions / MWh for conventional electricity generation. For additional details of the power sector calculations we suggest the reader review Manual chapter Calculations – Sub- Chapters Power Generation Calculation sheets and Power Conservation Calculation sheets provided in the tool.

1.4 TESTING CAPABILITIES The MACTool comes with a toolbox of global and time series specific sensitivity test instruments. The tool allows the entry of scenarios and sensitivity test factors that can be combined for up to 5 Cases. The user can for example define a Pessimistic Case (in addition to the baseline case), and set high sensitivity factors for individual cost time series and assigning this to high cost scenarios. An optimistic Case could be defined with sensitivity factors smaller than 100% and low cost scenarios. The user can switch from such defined optimistic to pessimistic cases and study the impact on results. Current results in the tool are based on a “realistic” case which is neither optimistic nor pessimistic. Future calculations can be performed by changing cost estimates, capacity installation estimates etc. to arrive at the optimistic and pessimistic cases. For a detailed description of the testing tools the reader is 12

referred to the chapter Data Entry Sub-chapter Cases, Scenarios and Sensitivities in the MACC Manual provided with the tool.

1.5 STRUCTURE OF A CALCULATION SHEET To simplify the MAC calculations investment cost are levelized (on the Level sheet, for details see MACCManual chapter Calculations). The MACTool gives the user the choice to automatically reinvest and thus “lock in” a certain capital stock. This is an important feature especially when considering what occurs to an existing fleet of equipment at the end of its life time (especially if this is less than the 41 year period used in the current analysis).

The current default assumption is that the stock is reinvested at the capital costs for the technology the year after its useful life. In many cases this reinvestment feature might not be desirable as technologies change. The user can take direct control of reinvestments by turning off this automatic reinvestment feature.

Data from the TBA sector sheets (populated through the GUI) are fed into the corresponding Calculation sheets.

These sheets have all the same structure:     

Common - Discount rate from Assumptions sheet Baseline - Data from TBA Sector sheet Low Carbon - Data from TBA Sector sheet Results - MAC and Break Even Carbon Prices Output - for Sector Summary sheet

Figure 4 presents an illustrative TBA Sector sheet for the buildings sector. Data can be directly entered into the relevant rows of the baseline and low carbon scenarios in this sheet and this can be more efficient for experienced users compared to data entry via the GUI.

Figure 4. Illustrative Calculation Sheet for Buildings Sector

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1.6 SUMMARY SHEETS OVERVIEW The Sector Summary sheets collect the results from the individual mitigation activity calculation sheets and provide a sector overview. From the Sector Summary sheet data flows into the Summary Filter sheet. The purpose of the Summary Filter sheet is to allow the user to include or exclude mitigation activities. Working with a subset of mitigation activities greatly improves the readability of graphs. The MACTool allows including/excluding (Filter out) individual mitigation activities and/or whole sectors. The calculation results for the mitigation activities that the user has included are fed into the Summary sheet and sorted there according to the needs of the graphs at hand.

For example, the MAC curve needs the Marginal Abatement Cost ranked from the lowest to the highest. The investment Cost graph needs the (Low Carbon case) investment cost to be sorted from the lowest to the highest.

Table 2. Summary Sheets and Purpose Purpose

Summary sheet type

Collects results for sector

TBA Sector sheet

Allows to include/exclude activities and/or sectors

Summary Filter sheet

Sort filtered results

Summary sheet

1.7 RESULTS FROM THE TOOL

Figure 5 is an example of a MAC curve generated by the tool. Cumulative emissions reductions are shown on the xaxis. The Y-axis shows the Marginal Abatement Cost/t CO2. The mitigation activities are ranked according to their Marginal Abatement Cost starting with the lowest. The implementation of mitigation activities with negative Marginal Abatement Cost provides net benefits to society (blue rectangles). As you move along the x-axis to the right the Marginal Abatement Costs increase.

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Figure 5. Illustrative MAC Curve generated as an output from the tool The MACtool generates wedge graphs for all sectors combined and detailed wedge graphs illustrating the contributions that specific mitigation activities make as illustrated in Figure 6. In the graph above the Low Carbon emissions are shaded light green. The wedges above the Low Carbon emissions show the avoided emissions for different sectors with the Power Sector contributing most.

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Figure 6. Illustrative Wedge Graph The avoided emissions are calculated as the difference between the baseline emissions and low carbon emissions.

In the case of the current analysis conducted for this paper, several of the sectors did not have data on both the baseline and low carbon emissions. Instead, the available data had avoided emissions (i.e. emissions savings). As such the wedge graphs are currently only operational for the power generation sector. Future enhancements will require population of baseline and low carbon emissions for each mitigation action so that the visualization across all wedge graphs is complete.

1.8 LIMITATIONS OF THE TOOL The MACTool in its current embodiment is an aggregation and visualization template. As such, it requires substantial calculation and data preparation conducted outside the tool. This feature is therefore both a limitation and strength. The limitation primarily stems from the fact that users must independently calculate several of the key inputs such as capital costs, operating costs, emissions inventory etc. for each action outside the tool. The strength of this approach is that it gives the experienced user the flexibility to define mitigation activities which may especially be important as specific actions are achieved and new actions emerge. This flexibility is also important in cases where there is significant technology and cost improvements especially over a 41 year period.

The delivered MACTool for Ukraine provides this freedom. Our team as part of the deliverable for this study has also delivered preliminary data analysis sheets based on raw data inputs gathered by EGIF that can be modified in the future to generate more robust numbers for entry into the tool.

It is the vision of our team that future use and enhancement of the results from the tool will follow the process described below.

1) Sector experts (i.e. for power, manufacturing etc.) are assigned as responsible parties for periodically updating the key inputs into the tool. This will include year to year capacity installed for specific actions, associated costs and emissions contributions.

2) An independent group of tool operators can populate the data provided by the sector experts and run various scenarios to arrive at results such as MAC values and emissions benefits that ultimately inform policy decisions.

1.9 ADDITIONAL TOOL FEATURES: BREAK EVEN CARBON PRICES This study generates a MAC curve for Ukraine and as the results presented later in this study indicate, there are quite a number of mitigation activities that provide net benefits for Ukraine. That does however not imply that the necessary investments take place spontaneously i.e., MAC curves do not tell us how private investors faced with market prices react. To help answer that question, the MACtool allows to calculate Break Even Carbon prices. The need for calculating these prices arises from the fact that in calculating the MAC curve economic prices (net of taxes and subsidies) are used (i.e. a societal perspective is taken). A private investor must however pay taxes and might benefit from subsidies. The prices an investor is confronted with are therefore distorted by several externalities such as tax codes, exchange rates, other investment opportunities, associated risks and returns etc. In general, a private investor will only invest if they expect a higher return (from their benchmark internal rate of return or IRR) to compensate for the risks taken. This return varies not only across sectors but also across regions 16

and mitigation actions. The key parameter required for the investor in this instance is therefore a Break Even Carbon Price so that the investment can go forward.

The Internal Rate of Return (IRR) is defined as the discount rate that ensures that the Present value of the project cash flow is equal to zero. đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ?&#x2018;&#x201A;&đ?&#x2018;&#x20AC; đ??śđ?&#x2018;&#x153;đ?&#x2018; đ?&#x2018;Ą + đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ??¸đ?&#x2018;&#x203A;đ?&#x2018;&#x2019;đ?&#x2018;&#x;đ?&#x2018;&#x201D;đ?&#x2018;Ś đ??śđ?&#x2018;&#x153;đ?&#x2018; đ?&#x2018;Ą + đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ??żđ?&#x2018;&#x2019;đ?&#x2018;Łđ?&#x2018;&#x2019;đ?&#x2018;&#x2122;đ?&#x2018;&#x2013;đ?&#x2018;§đ?&#x2018;&#x2019;đ?&#x2018;&#x2018; đ??źđ?&#x2018;&#x203A;đ?&#x2018;Łđ?&#x2018;&#x2019;đ?&#x2018; đ?&#x2018;Ą. đ??śđ?&#x2018;&#x153;đ?&#x2018; đ?&#x2018;Ą â&#x20AC;&#x201C; đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ?&#x2018;&#x2026;đ?&#x2018;&#x2019;đ?&#x2018;Łđ?&#x2018;&#x2019;đ?&#x2018;&#x203A;đ?&#x2018;˘đ?&#x2018;&#x2019;đ?&#x2018; = 0 The

IRR

that

ensures

the

above

result

will

normally

differ

from

the

benchmark

IRR.

We can however introduce a Break Even Carbon Price to ensure that the above equation is true for the investorâ&#x20AC;&#x2122;s benchmark IRR through the following equations: đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ??śđ?&#x2018;&#x153;đ?&#x2018; đ?&#x2018;Ą = đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ?&#x2018;&#x201A;&đ?&#x2018;&#x20AC; đ??śđ?&#x2018;&#x153;đ?&#x2018; đ?&#x2018;Ą + đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ??¸đ?&#x2018;&#x203A;đ?&#x2018;&#x2019;đ?&#x2018;&#x;đ?&#x2018;&#x201D;đ?&#x2018;Ś đ??śđ?&#x2018;&#x153;đ?&#x2018; đ?&#x2018;Ą + đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ??żđ?&#x2018;&#x2019;đ?&#x2018;Łđ?&#x2018;&#x2019;đ?&#x2018;&#x2122;đ?&#x2018;&#x2013;đ?&#x2018;§đ?&#x2018;&#x2019;đ?&#x2018;&#x2018; đ??źđ?&#x2018;&#x203A;đ?&#x2018;Łđ?&#x2018;&#x2019;đ?&#x2018; đ?&#x2018;Ąđ?&#x2018;&#x161;đ?&#x2018;&#x2019;đ?&#x2018;&#x203A;đ?&#x2018;Ą đ??śđ?&#x2018;&#x153;đ?&#x2018; đ?&#x2018;Ą đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ??śđ?&#x2018;&#x153;đ?&#x2018; đ?&#x2018;Ą â&#x20AC;&#x201C; đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ?&#x2018;&#x2026;đ?&#x2018;&#x2019;đ?&#x2018;Łđ?&#x2018;&#x2019;đ?&#x2018;&#x203A;đ?&#x2018;˘đ?&#x2018;&#x2019;đ?&#x2018; â&#x20AC;&#x201C; đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ??´đ?&#x2018;Łđ?&#x2018;&#x153;đ?&#x2018;&#x2013;đ?&#x2018;&#x2018;đ?&#x2018;&#x2019;đ?&#x2018;&#x2018; đ??¸đ?&#x2018;&#x161;đ?&#x2018;&#x2013;đ?&#x2018; đ?&#x2018; đ?&#x2018;&#x2013;đ?&#x2018;&#x153;đ?&#x2018;&#x203A;đ?&#x2018; â&#x2C6;&#x2014; đ??ľđ?&#x2018;&#x;đ?&#x2018;&#x2019;đ?&#x2018;&#x17D;đ?&#x2018;&#x2DC; đ??¸đ?&#x2018;Łđ?&#x2018;&#x2019;đ?&#x2018;&#x203A; đ??śđ?&#x2018;&#x17D;đ?&#x2018;&#x;đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018;&#x203A; đ?&#x2018;&#x192;đ?&#x2018;&#x;đ?&#x2018;&#x2013;đ?&#x2018;?đ?&#x2018;&#x2019; = 0 đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ??śđ?&#x2018;&#x153;đ?&#x2018; đ?&#x2018;Ą â&#x20AC;&#x201C; đ?&#x2018;&#x192;đ?&#x2018;&#x2030; đ?&#x2018;&#x2026;đ?&#x2018;&#x2019;đ?&#x2018;Łđ?&#x2018;&#x2019;đ?&#x2018;&#x203A;đ?&#x2018;˘đ?&#x2018;&#x2019;đ?&#x2018; = đ?&#x2018;&#x192;đ?&#x2018;&#x2030; (đ??´đ?&#x2018;Łđ?&#x2018;&#x153;đ?&#x2018;&#x2013;đ?&#x2018;&#x2018;đ?&#x2018;&#x2019;đ?&#x2018;&#x2018; đ??¸đ?&#x2018;&#x161;đ?&#x2018;&#x2013;đ?&#x2018; đ?&#x2018; đ?&#x2018;&#x2013;đ?&#x2018;&#x153;đ?&#x2018;&#x203A;đ?&#x2018; ) â&#x2C6;&#x2014; đ??ľđ?&#x2018;&#x;đ?&#x2018;&#x2019;đ?&#x2018;&#x17D;đ?&#x2018;&#x2DC; đ??¸đ?&#x2018;Łđ?&#x2018;&#x2019;đ?&#x2018;&#x203A; đ??śđ?&#x2018;&#x17D;đ?&#x2018;&#x;đ?&#x2018;?đ?&#x2018;&#x153;đ?&#x2018;&#x203A; đ?&#x2018;&#x192;đ?&#x2018;&#x;đ?&#x2018;&#x2013;đ?&#x2018;?đ?&#x2018;&#x2019; which implies: đ?&#x2018;Šđ?&#x2019;&#x201C;đ?&#x2019;&#x2020;đ?&#x2019;&#x201A;đ?&#x2019;&#x152; đ?&#x2018;Źđ?&#x2019;&#x2014;đ?&#x2019;&#x2020;đ?&#x2019;? đ?&#x2018;Şđ?&#x2019;&#x201A;đ?&#x2019;&#x201C;đ?&#x2019;&#x192;đ?&#x2019;?đ?&#x2019;? đ?&#x2018;ˇđ?&#x2019;&#x201C;đ?&#x2019;&#x160;đ?&#x2019;&#x201E;đ?&#x2019;&#x2020; / đ?&#x2019;&#x2022; đ?&#x2018;Şđ?&#x2018;śđ?&#x;? =

(đ?&#x2018;ˇđ?&#x2018;˝ đ?&#x2018;Şđ?&#x2019;?đ?&#x2019;&#x201D;đ?&#x2019;&#x2022; â&#x20AC;&#x201C; đ?&#x2018;ˇđ?&#x2018;˝ đ?&#x2018;šđ?&#x2019;&#x2020;đ?&#x2019;&#x2014;đ?&#x2019;&#x2020;đ?&#x2019;?đ?&#x2019;&#x2013;đ?&#x2019;&#x2020;đ?&#x2019;&#x201D;) đ?&#x2018;ˇđ?&#x2018;˝ đ?&#x2018;¨đ?&#x2019;&#x2014;đ?&#x2019;?đ?&#x2019;&#x160;đ?&#x2019;&#x2026;đ?&#x2019;&#x2020;đ?&#x2019;&#x2026; đ?&#x2018;Źđ?&#x2019;&#x17D;đ?&#x2019;&#x160;đ?&#x2019;&#x201D;đ?&#x2019;&#x201D;đ?&#x2019;&#x160;đ?&#x2019;?đ?&#x2019;?đ?&#x2019;&#x201D; đ?&#x2019;&#x2022; đ?&#x2018;Şđ?&#x2018;śđ?&#x;?

In this case, the benchmark IRR is used to calculate the present values. A negative Break Even Carbon Price shows that the investment is attractive for the private sector i.e. no subsidy is required.

However, if the Break Even Carbon Price is positive, a society might be interested to learn what subsidy is required for investments in mitigation activities with a negative MAC to take place, given by the equation: đ?&#x2018;şđ?&#x2019;&#x2013;đ?&#x2019;&#x192;đ?&#x2019;&#x201D;đ?&#x2019;&#x160;đ?&#x2019;&#x2026;đ?&#x2019;&#x161; = đ?&#x2018;Šđ?&#x2019;&#x201C;đ?&#x2019;&#x2020;đ?&#x2019;&#x201A;đ?&#x2019;&#x152; đ?&#x2018;Źđ?&#x2019;&#x2014;đ?&#x2019;&#x2020;đ?&#x2019;? đ?&#x2018;Şđ?&#x2019;&#x201A;đ?&#x2019;&#x201C;đ?&#x2019;&#x192;đ?&#x2019;?đ?&#x2019;? đ?&#x2018;ˇđ?&#x2019;&#x201C;đ?&#x2019;&#x160;đ?&#x2019;&#x201E;đ?&#x2019;&#x2020; /đ?&#x2019;&#x2022; đ?&#x2018;Şđ?&#x2018;śđ?&#x;? â&#x2C6;&#x2014; đ?&#x2018;¨đ?&#x2019;&#x2014;đ?&#x2019;?đ?&#x2019;&#x160;đ?&#x2019;&#x2026;đ?&#x2019;&#x2020;đ?&#x2019;&#x2026; đ?&#x2018;Źđ?&#x2019;&#x17D;đ?&#x2019;&#x160;đ?&#x2019;&#x201D;đ?&#x2019;&#x201D;đ?&#x2019;&#x160;đ?&#x2019;?đ?&#x2019;?đ?&#x2019;&#x201D; đ?&#x2019;&#x2022; đ?&#x2018;Şđ?&#x2018;śđ?&#x;?

The MACtool calculates three Carbon Prices: the Break Even Carbon Price, the Break Even Carbon Price Local Energy Market Prices and the Break Even Carbon Price Incremental. For a numeric example the reader can refer to the MACCManual, chapter Calculations â&#x20AC;&#x201C; Sub-chapter Break Even Carbon Price Calculations provided with the tool.

A summary of the characteristics and limitations of the three carbon price types are provided below.

Table 3. Summary of Break Even Carbon Prices Characteristics

Limitations

Break Even Carbon Price

Only Low Carbon cost and revenues taken into account

Economic prices, investment cost levelized, no financial model

Break Even Carbon Price Local Energy Market Prices

Energy market prices, only Low Carbon cost and revenues taken into account

Economic prices except energy market prices, investment cost

Carbon Price Type

17

levelized, no financial model Break Even Carbon Price Incremental

Incremental cost

Economic prices, investment cost levelized, no financial model

The current study has not focused extensively on reporting these break even prices and this is by design. It is our opinion that more rigorous data needs to be collected prior to updating the break even prices reported in the tool in its current form. This rigorous data includes: ď&#x201A;ˇ

A comprehensive inventory based view on installation capacities, market penetration rates etc. for each mitigation action of interest across each sector. This can only be prepared by engaging the relevant sector participants in more detailed industry wide surveys and studies.

ď&#x201A;ˇ

A pro forma level economic model for each mitigation action that estimates capital costs, operating costs and revenues from the perspective of an individual investor incorporating the best financial data (e.g. preferred rates of return for debt and equity) and engineering data (e.g. year to year performance of the action based on data in the field).

18

2 SUMMARY OF MITIGATION ACTIONS CONSIDERED This chapter provides a summary of the sectors and mitigation actions considered in this study. A total list of 78 mitigation actions were considered split into 8 sector categories. Namely:        

Power Generation (12 actions) Power Conservation (7 actions) Fossil Fuel (3 actions) Manufacturing/Industry (13 actions) Waste Management (10 actions) Buildings (8 actions) Land Use (18 actions) Transport (7 actions)

As mentioned earlier, the MACTool is set up to provide flexibility in terms of considering additional actions and revising the data for actions considered within the study independent of the tool itself. In this regard, the tool in its current version includes the capability of considering up to 111 mitigation actions. A brief description of the mitigation actions considered for each sector follows.

2.1 POWER GENERATION MITIGATION ACTIONS The power generation mitigation actions consider the deployment of renewable energy for utility and distributed scale power generation to meet the electricity demands in Ukraine. Cleaner conventional methods that reduce the GHG footprint of fossil fuel based power generation are also considered. Table 4 provides a description for the 11 power generation mitigation actions considered for this study.

Table 4 : Description of Mitigation Actions in Power Generation Action

Description

Large Solar PV

Solar photovoltaic technology installations for commercial (100s and 10s of kW) and utility scale (in MWs) power generation.

Residential Solar PV

Solar photovoltaic technology installations for residential (single digit kWs) power generation.

Wind

Large scale wind turbines (in MWs) for utility scale power generation.

Large Hydro

Large scale hydropower turbines (in MWs) for utility scale power generation installed at dams.

Small Hydro

Small scale hydropower turbines (in 10s kW) for commercial scale power generation installed at small dams or in rivers (as run of river).

Biomass Power

Large scale boiler and turbine based equipment (in MWs) that uses wood and other biomass sources as fuel for utility scale power generation.

Geothermal Power

Steam turbine and organic rankine cycle solutions (in MWs) that use hot water or steam from underground, drilled sources for utility scale power generation.

19

Pumped Storage Hydro

Hydropower solution coupled with fossil fuel (or renewable sources) where a large reservoir (typically uphill) is created and filled with fossil power during off peak hours and used during peak hours for utility scale power generation.

Coal Fired Ultra Super Critical Plants

Utility scale coal power plants modified to operate at supercritical conditions to improve

(USPC)

efficiencies and reduce emissions.

Natural Gas Combined Cycle Plants

Utility scale power plants that run off natural gas operating at high efficiencies by recovering

(NGCC)

waste heat to generate incremental power via a steam generator.

Carbon Capture and Sequestration with

Capturing carbon dioxide from high efficiency coal plants and feeding it deep underground as a

USPC Plants

means of reducing emissions.

Nuclear

Utility scale power plants that operate off nuclear fuel.

There may be additional variations of the actions identified above that are considered in the future. For example, wind power could be considered in the distributed scale if technology improves and adequate sources are considered. Electrical and thermal storage techniques could also be included once more economically viable options are identified for these actions.

2.2 POWER CONSERVATION MITIGATION ACTIONS The power conservation mitigation actions focus on reductions of grid electricity consumption on the demand side.

Table 5 summarizes the key assumptions for the 7 power conservation actions considered for this study.

Table 5 : Description of Mitigation Actions in Power Conservation Action

Description

Energy Efficient Lighting

Lighting energy efficiency focuses on replacing incandescent lamps with compact fluorescent lighting. LED lighting will in all likelihood need be considered in the near future.

Energy Efficient Refrigerators

Refrigerator energy efficiency typically focuses on improving the underlying equipment such as compressors, heat exchangers and controls to provide more cooling for less electricity.

Energy Efficient Washer/Dryers

Washer/dryer energy efficiency focuses on improving the mechanical equipment (e.g. fans) and the controls to deliver more cleaning and drying for less electricity.

Energy Efficient Microwaves

Microwave energy efficiency focuses on the design and controls of the underlying equipment in these devices to help heat food with less electricity.

Energy Efficient Televisions

Television energy efficiency focuses on replacing cathode ray tubes with more efficient LCD and LED versions.

Power Transmission Upgrade

Power transmission upgrade focuses on replacing underperforming, aging transmission lines with modern lines and controls to prevent line losses from the generation source to the demand source.

Smart Grid

Smart grid is a combination of technologies such as smart meters, controls, electrical storage

20

that are installed both on the supply and demand side to reduce electricity consumption and losses due to unwanted use, and to better integrate distributed generation.

The actions identified for the power conservation sector could be further analyzed by splitting out the specific technologies identified for each action. For example, lighting could be classified into street lighting, residential, commercial and industrial users because the underlying equipment in these sectors (i.e. the inventory) would be different. This in turn leads to different adoption rates. Similarly, a category such as smart grid is fairly broad and can be split into individual measures such as smart meters, controls, storage etc. once these technologies mature and the economics in the field are better understood.

2.3 FOSSIL FUEL MITIGATION ACTIONS The fossil fuel mitigation actions focus on improving the efficiency of fossil fuel production and using untapped resources that are currently being flared and/or emitted into the atmosphere. Table 6 summarizes the key assumptions for the 3 fossil fuel actions considered for this study.

Table 6 : Description of Mitigation Actions in Fossil Fuel Action

Description

Coal Mine Methane â&#x20AC;&#x201C; Ventilation Air

Oxidizing the methane emitted from coal mines to lower GHG content carbon dioxide before

Machine (VAM)

emitting it into the atmosphere.

Coal Mine Methane â&#x20AC;&#x201C; Combined Heat

The methane from coal mines can be captured and converted to produce electrical power and

and Power (CHP)

thermal energy in this action.

Coal Mining Energy Efficiency

Improving the electrical efficiency in coal mining processes by replacing outdated equipment, preventing onsite line losses etc.

Several actions exist for both oil and gas production that may be considered in the future under this category. For example, increase deployment of shale gas will bring with it opportunities for water management, energy efficiency in drilling and collection etc. that can be considered.

2.4 MANUFACTURING/INDUSTRY MITIGATION ACTIONS The manufacturing/industry mitigation actions focus on improving the process efficiency of various commodity manufacturing processes such as cement, steel, aluminium etc. Table 7 summarizes the key assumptions for the 13 manufacturing/industry actions considered for this study.

Table 7 : Description of Mitigation Actions in Manufacturing/Industry Action

Description

Aluminium Scrap Recycling

Improving the recycling rates of aluminium.

Ammonia Energy Efficiency

Reducing the amount of natural gas used in ammonia production.

Ammonia Electrolysis

Generating the hydrogen required for ammonia production via an electrolysis process using

21

water (as compared to steam reforming of methane).

Dry Cement Process

Replacing wet manufacturing processes with the dry process that is less energy intensive.

Wet Cement Process (Slag)

Using raw material in the form of slag (typically a byproduct of iron production) and ash (from power production) as a replacement to conventional feedstock (i.e. limestone). This is coupled with wood biomass as a substitute for the fuel to reduce the GHG footprint from traditional wet manufacturing processes.

Shale Gas in Cement

Replacing the coal fuel in cement manufacturing with shale gas.

Direct Reduction Iron

Replacing conventional blast and oxygen furnaces with direct iron reduction and electric arc furnaces to reduce the energy consumption in the overall process.

Iron Ore Production Energy Efficiency

Improving the process efficiency of iron ore concentrate production through improved thermal integration.

Steel Rolling/Casting Energy Efficiency

Introducing processes that directly form molten steel into desired rolled shapes thereby improving process efficiency and reducing material wastage compared to multistep processes.

Steel Continuous Rolling

Improving the efficiency of continuous rolling process for steel.

Steel Electric Arc Furnace (EAF)

Introducing electric arc furnaces that offer the possibility of using scrap metals and improved scalability of production thereby improving process efficiency of the steel manufacturing process.

Lime Production Energy Efficiency

Replacing less efficient production kilns for lime with more efficient equipment.

Paper Production Energy Efficiency

Replacing outdated boilers used in the paper production industry with more efficient

(Boiler Replacement)

equipment that improves overall process efficiency.

Beyond the actions considered for this study additional energy intensive industries such as glass, petrochemical industries and associated actions for these industries could be considered in the future. Furthermore, several of the industries considered for the study may have additional mitigation actions that could be considered. A popular action that is receiving more attention across industries is the implementation of large on site CHP solutions to meet electric and thermal demands. The use of these onsite energy solutions enables the reduction of transmission and distribution losses from the grid while also improving the overall efficiency (i.e. fuel to useful energy).

2.5 WASTE MANAGEMENT MITIGATION ACTIONS The waste management mitigation actions focus on improving the efficiency of recycling processes, reducing waste and finding alternative uses for waste. Table 8 summarizes the key assumptions for the 10 waste management actions considered for this study.

Table 8 : Description of Mitigation Actions in Waste Management Action

Description

22

Landfill Gas Power (LFG)

Collecting fugitive methane emissions from landfills and generating power from the methane.

Clean Municipal Solid Waste Power

Combusting or incinerating municipal solid waste to produce heat that drives a power

(MSW)

generation cycle.

Waste Water Utilization for Power

Converting the organic solids in waste water via anaerobic digestion into methane that is used for power generation.

Segregate Colloids Utilization for Power

Similar to waste water utilization with the feedstock being food waste.

(Food Waste Biogas) Replace Obsolete Municipal Waste

Upgrading pumping and other electromechanical equipment at municipal waste facilities with

Facilities (Pumping Systems)

more energy efficient equipment.

Composting

Combusting municipal solid waste and using the heat if possible.

Biodegradable Plastics

Using advanced plastic materials that are made from biological sources (rather than petrochemical) that degrade more quickly when placed in the environment.

Increased Recycling

Increasing the rate of recycling for several materials such as metals, glass, cardboard, paper, plastics etc.

Modern Materials Recycling

Enhancing conventional recycling processes through the deployment of segregated recycling at the residential and municipal level.

Waste Production Limits

Enhancing consumer awareness to reduce the amount of waste generated.

There might be additional actions that can be taken at waste processing and recycling facilities (e.g. CHP implementation) but in general, the above list appears to be fairly comprehensive.

2.6 BUILDINGS MITIGATION ACTIONS The buildings mitigation actions focus on improving the energy performance of buildings in terms of reducing electricity and thermal energy usage. Table 9 summarizes the key assumptions for the 8 building actions considered for this study.

Table 9 : Description of Mitigation Actions in Buildings Action

Description

Draught Proofing

Adding seals and insulation around windows, doors etc. to prevent thermal losses.

Wall Insulation

Improving the insulation materials used between walls to minimize thermal losses.

Windows Energy Efficiency

Using various window types such as double pane, triple pane etc. to prevent thermal ingress during summer months and losses during winter months.

Boiler Upgrades

Upgrading boiler equipment used to provide space heating in buildings.

Heat Pumps

Replacing existing electrically driven heating equipment with mechanical heat pumps.

23

Heat Network Optimization

Implemented primarily for district heat systems whereby natural gas and steam lines used in the system are upgraded to minimize line losses.

Heat Network Boiler Upgrade

Upgrading the boiler units used in district heat systems.

Water Energy Efficiency

Minimizing the amount of water consumed per capita and also reducing the energy required for cleaning, delivering and heating the water that is supplied.

There are several other systems in large buildings such as security, fire suppression, elevators etc. that could all be made more efficient. Furthermore, advanced controls that adjust energy usage based on occupancy can be an action considered in the future. Even some of the existing measures identified above can be refined further. For example, the windows category can be further categorized by building types (i.e. commercial, residential, industrial etc.) and a variety of technologies such as electrochromic windows, low e-glass etc. could be studied for those building types.

2.7 LAND USE MITIGATION ACTIONS Land use mitigation actions focus on improving agricultural and farming operations. Actions that enhance forest cover and protect various land types are also considered. Table 10 summarizes the key assumptions for the 18 land use actions considered for this study.

Table 10 : Description of Mitigation Actions in Land Use Action

Description

Biogas Plants – Cattle

Capturing the biogas (through anaerobic digestion) released in cattle farms and converting it into power.

Biogas Plants – Swine

Capturing the biogas (through anaerobic digestion) released in swine farms and converting it into power.

Concentrated Fodder – Cattle

Concentrating the fodder to reduce the roughage fed to cattle.

Reduction of Cows – Increased Milk

Reducing the number of cows in dairy farms by increasing the milk production per cow.

Production Ionophores in Cattle Ration

Reducing the amount of feed required per cattle by adding an ionophore supplement.

Zeolites in Cattle Ration

Improving feed efficiency for cattle by adding zeolites as a supplement.

Sunflower Seeds in Cattle Ration

Reducing the need for conventional cattle feed by supplementing it with sunflower seeds.

Crop Rotation

Reducing the amount of fertilizers used by planting alternate crops that improve the nitrogen content in soil (e.g. legumes).

Extensive to Intensive Agriculture

Consolidating farming operations from multiple small farms to larger farmers offering

Processes

efficiencies in terms of labor, materials and energy consumption.

Nitrification Inhibitors in Corn

Adding inhibitors that preven the nitrification process (that results in nitrous oxide emissions)

24

Production

from soil.

Erosion Prevention Measures

Changing the landscape (e.g. using barriers) to minimize soil loss due to weather events.

Preservation of Degraded Lands

Preventing over use of lands where soil is being gradually depleted.

Wetlands Renewal

Renewing wetlands to its previous condition by planting vegetation and preventing use of the land for other purposes.

Straw Combustion

Recovering straw from farmland and burning it to generate heat and/or power.

Organic Farming

Using a variety of techniques including crop rotation, biological pest control, green manure etc. that minimizes the use of petrochemicals used in current farming operations.

LULUCF – Organic Fertilizer Use

Using organic fertilizers are a replacement for traditional petrochemical based fertilizers.

LULUCF – No Till Techniques

Growing crop without disturbing the soil (which occurs in a tilling process).

LULUCF – Afforestation

Replanting trees in forests that have been depleted for other use (e.g. for wood used in construction and paper industry)

The list of actions for this sector appears to be fairly comprehensive. One opportunity for further refinement might be qualifying the farmlands into types and making the measures more specific to specific farm types.

2.8 TRANSPORT MITIGATION ACTIONS The mitigation actions considered for this sector fall under two broad categories, fuel transport and vehicular transport. Table 11 summarizes the key assumptions for the 7 transport actions considered for this study.

Table 11 : Description of Mitigation Actions in Transport Action

Description

Gas Pipeline Modernization

Replacing the pipelines that are currently used to transport natural gas within the country.

Gas Transport Modernization

Implementing pipeline modernization and modernization of the compressor stations in the system.

NG Pressure Reduction

Recovering some of the energy lost at pressure reduction stations into useful electrical energy.

Vehicle Energy Efficiency

Converting the road fleet of buses, high density vehicles (i.e. vans) and low density vehicles (i.e. cars) into more energy efficient vehicles that consume less gasoline, diesel or LPG as applicable.

Biofuels

Replacing part of the gasoline used in fuels with bioethanol and diesel with biodiesel. The biofuels are generated from sustainable sources such as wood waste, high oil content seeds etc.

City Transport Electrification

Converting the existing fleet of diesel buses used to transport several passengers to electrically driven trolleys and trams.

Railway Electrification

Upgrading existing fossil fuel driven railways to more efficient electric equipment.

25

There are several other actions that could be considered within this sector in the future. Electric vehicles could be considered for road transport (i.e. in the vehicle energy efficiency category). Airlines and shipping actions could also be considered in the future.

26

3 DATA INPUT AND OUTPUT GENERATION METHODOLOGY This chapter describes the key input variables required for operating the MACTool and how these were generated based on the data gathered by EGIF to produce the desired output from the tool.

3.1 INPUT VARIABLES The key input variables, such as, capital costs, operating costs, efficiencies etc. for each measure is calculated outside the tool and then entered into the tool to calculate marginal abatement costs. For example, in the case of Solar PV, users would independently calculate the efficiency changes, capital and operating cost changes etc. for a 41 year period in separate data files and these estimates are then populated into the tool to estimate marginal abatement costs. This approach provides flexibility in revising numbers in the future without impacting underlying numbers in the tool. While there are several input variables that can be set within the tool, there is a minimum set of variables that must be entered to calculate marginal abatement costs for each measure. A majority of these input variables must be calculated year over year for the 41 year period for each measure and they include:  Capital costs 

Operation and maintenance costs (O&M)



Unsubsidized energy costs (for electricity, natural gas, liquid fuels, coal)



Revenues or savings (specific to each measure if applicable)



Electricity generated/consumed (for Power Sector)



Emissions factors or emissions reductions as applicable (average over a 41 year period)

Additional data that must be assumed or acquired to complete the analysis include:  Exchange rates (where applicable if data is not available consistently in one currency) 

Discount factor (as a single input variable for the 41 year period)



Economic lifetime (as a single input variable for the 41 year period)

3.2 DATA ANALYSIS PROCESS FOR MITIGATION ACTIONS The TRPC team has been working with EGIF, the subcontractor selected to provide the key input data for the measures to arrive at estimates of the marginal abatement costs. The first step in the process was finalizing a list of measures that were both applicable within the Ukrainian context and for which preliminary data could be

27

gathered through a combination of primary and secondary research. As discussed in the previous chapter a list of 78 mitigation actions were finalized across 8 sectors.

EGIF produced excel sheets for each measure that included basic values for the input variables, gathering this from a variety of prior studies conducted in Ukraine and elsewhere. The output from this effort for Large Solar PV has been illustrated in Table 12.

Table 12. Illustrative Basic Data for Large Solar PV Mitigation option: Solar power Existing Power Plants 0.3178 (0.494) 25 25 3840

Installed capacity, GW Energy input Technical lifetime, years Economic lifetime, years Capital cost per project, $/kW Annual O&M costs per project (fixed and variable), $/kW Load (capacity) factor, %

15

Capital cost per output, $/MWh Annual other costs per project, $/kW CO2 and other GHG emissions, g CO2-eq./kWh Annual emissions per SO2, g/kWh project NOx, g/kWh Time line 2012 2030

Installed capacity, GW 0.3178 (0.494 at 01/07/2013) 1.5-2.5

Referenses PV solar power plants [3], [4] 1.5-2.5 [1] 25 25 [5] 1700-2100 17-21** [2] 9-16

— -

100-150 — -

References [3], ([4]) [2]

References 1 E11 Photovoltaic solar power http://iea-etsap.org/web/Supply.asp 2 Оновленна Енергетична стратегія України на період до 2030 р 3 http://www.ukrenergo.energy.gov.ua/ukrenergo/control/uk/publish/article?art_id=117896&cat_id=35061 4 http://vidomosti-ua.com/economics/71127 5 http://consumers.unian.net/ukr/detail/7318 * Occurring during manufacturing only ** 1% of project cost

This data was then transformed by TRPC into the year to year data required for the MACTool. In order to do this, we had to make several simplifying assumptions that must be continuously revised as better data becomes available. These simplifying assumptions for Large Solar (and unique at times for each measure) include: 

Annual installations (in MW) for a base case and low carbon case



Annual capital, O&M and capacity factors that account for any learning curve changes that might result over a 41 year period (e.g. capital costs decrease due to technology improvement)



Market penetration rates (applicable for many energy efficiency measures)



Fuel costs and exchange rates

Table 13 illustrates the output of the data analysis for Large Solar PV where current available data for Ukraine extends only until 2030.

28

Table 13. Illustrative Data Analysis for Large Solar PV MW Installed Capacity % MWh acc New Capacity $/kW $ Base Case Low Carbon Capacity Factors Generation CAPEX Decrease CAPEX Actuals 2013 494 494 Base Case Low Carbon Base Case Low Carbon Base Case Low Carbon Base Case Low Carbon 2014 494 494 15% 15% 649,116 649,116 3840 3840 $0 $0 2015 556.875 619.375 15% 15% 731,734 813,859 3718.75 3706.25 $233,816,406 $464,671,094 2016 619.75 744.75 15% 15% 814,352 978,602 3597.5 3572.5 $226,192,813 $447,902,188 2017 682.625 870.125 15% 15% 896,969 1,143,344 3476.25 3438.75 $218,569,219 $431,133,281 2018 745.5 995.5 15% 15% 979,587 1,308,087 3355 3305 $210,945,625 $414,364,375 2019 808.375 1120.875 15% 15% 1,062,205 1,472,830 3233.75 3171.25 $203,322,031 $397,595,469 2020 871.25 1246.25 15% 16% 1,144,823 1,746,744 3112.5 3037.5 $195,698,438 $380,826,563 2021 934.125 1371.625 15% 16% 1,227,440 1,922,470 2991.25 2903.75 $188,074,844 $364,057,656 2022 997 1497 15% 16% 1,310,058 2,098,195 2870 2770 $180,451,250 $347,288,750 2023 1059.875 1622.375 15% 16% 1,392,676 2,273,921 2748.75 2636.25 $172,827,656 $330,519,844 2024 1122.75 1747.75 15% 16% 1,475,294 2,449,646 2627.5 2502.5 $165,204,063 $313,750,938 2025 1185.625 1873.125 15% 16% 1,557,911 2,625,372 2506.25 2368.75 $157,580,469 $296,982,031 2026 1248.5 1998.5 15% 16% 1,640,529 2,801,098 2385 2235 $149,956,875 $280,213,125 2027 1311.375 2123.875 15% 16% 1,723,147 2,976,823 2263.75 2101.25 $142,333,281 $263,444,219 2028 1374.25 2249.25 15% 16% 1,805,765 3,152,549 2142.5 1967.5 $134,709,688 $246,675,313 2029 1437.125 2374.625 15% 16% 1,888,382 3,328,274 2021.25 1833.75 $127,086,094 $229,906,406 2030 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $119,462,500 $213,137,500 2031 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2032 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2033 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2034 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2035 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2036 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2037 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2038 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2039 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2040 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2041 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2042 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2043 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2044 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2045 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2046 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2047 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2048 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2049 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2050 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2051 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2052 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2053 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0 2054 1500 2500 15% 16% 1,971,000 3,504,000 1900 1700 $0 $0

It is important to note that our team has performed this initial analysis with the best available data to date. Each data sheet will be provided to the UNDP and Ukrainian stakeholders as part of our delivery so that these can be modified in the future based on the latest data available as more detailed engineering and economic studies on each measure are undertaken within the Ukrainian context. Once the annual data is synthesized for each measure, the data is then input into the tool as illustrated in Figure 7.

29

Figure 7. Illustration of Data Entry into Tool from Data Analysis Performed The resulting output can then be analyzed by sector as illustrated in Figure 8.

Figure 8. Illustrative MAC Curve for Power Generation

30

This process is then repeated for each sector to produce the MAC and emissions reduction value estimates for each of the 78 mitigation actions considered for this data. As stated before the quality of the estimates are highly dependent on the input data gathered to date and underlying assumptions that have been forecast over a 41 year period. It is the expectation of the team that the results presented in this study represent a snapshot in time and will likely be revised in the future as better data becomes available and the analysis is refined further.

31

4 ASSUMPTIONS, RESULTS AND DISCUSSION This chapter provides a summary of key assumptions that have been made for global variables and each mitigation action, the resulting marginal abatement costs estimated from the tool along with a discussion on drivers that are impacting the cost estimates.

4.1 GLOBAL VARIABLE ASSUMPTIONS Table 14 summarizes the global variables and associated assumptions used across the analysis presented in this study. These values were assumed to be the same for both the base case and low carbon case calculations. Future iterations might consider different trends for some variables in the base case and low carbon case.

Table 14 : Key Assumptions for General Variables Variable

Assumption

Wholesale electricity price

0.056823 $/kWh (2013), growing at annual rate of 2% out to 2054, developed in

(unsubsidized)

consultation with EGIF

Grid emissions factor

0.42 tons CO2e/MWh assumed flat 2013-2054, developed in consultation with EGIF

Natural gas prices

411.22 $/1000 cubic meter (2013), growing at an annual rate of 2% out to 2054

Coal prices

101.18 – 277.87 $/ton (2013-2054), provided by EGIF

Blended liquid fuel prices

1627.6 $/ton (2013), growing at an annual rate of 2% out to 2054 (applied for gasoline, diesel, LPG), developed in consultation with EGIF

EUR per $ exchange rate

0.774 – 0.693 (2013-2054), provided by EGIF

UAH per $ exchange rate

8.199 – 13.660 (2013-2054), provided by EGIF

Population

45.25 M – 38.86 M (2013-2054), provided by EGIF from Ukraine State Statistics Service

Note: Exchange rates and population estimates were needed because some of the measures contained data that were normalized for these variables (e.g. water energy efficiency).

4.2 POWER GENERATION ASSUMPTIONS & RESULTS Table 15 summarizes the key assumptions for the eleven power generation mitigation actions identified earlier.

Table 15 : Key Assumptions for Mitigation Actions in Power Generation Action

Key Assumptions (Base Case)

Key Assumptions (Low Carbon Case)

Large Solar PV

Installed in MW: 600 – 1500 (2013-2030) and

Installed in MW: 600 – 2500 (2013-2030) and

flat after 2030

flat after 2030

Capacity Factor : 15% across all years

Capacity Factor : 15% till 2019, 16% after 2020

32

Action

Residential Solar PV

Wind

Key Assumptions (Base Case)

Key Assumptions (Low Carbon Case)

Capital Costs in $/kW: 3840 – 1900 (2013-2030)

Capital Costs in $/kW: 3840 – 1700 (2013-2030)

and flat after 2030

and flat after 2030

O&M Costs in $/MWh: 10 across all years

O&M Costs in $/MWh: 10 till 2019, 5 after 2020

Emissions in tons/MWh: 0

Emissions in tons/MWh: 0

Lifetime: 25 years

Lifetime: 25 years

Installed in MW: 0 – 1000 (2013-2050) and flat

Installed in MW: 0 – 2000 (2013-2050) and flat

after 2050

after 2050

Capacity Factor : 15% across all years

Capacity Factor : 15% across all years

Capital Costs in $/kW: 5000 – 1500 (2013-2038)

Capital Costs in $/kW: 5000 – 1500 (2013-2038)

and flat after 2038

and flat after 2038

O&M Costs in $/MWh: 10 across all years

O&M Costs in $/MWh: 10 till 2019, 5 after 2020

Emissions in tons/MWh: 0

Emissions in tons/MWh: 0

Lifetime: 25 years

Lifetime: 25 years

Installed in MW: 262.8 – 1000 (2013-2030) and

Installed in MW: 0 – 2000 (2013-2050) and flat

flat after 2030

after 2050

Capacity Factor : 26% across all years

Capacity Factor : 26% - 36% (2013-2030) and flat

Capital Costs in $/kW: 2920.50 – 2100 (20132030) and flat after 2030

after 2030 Capital Costs in $/kW: 2920.50 – 1850 (2013-

O&M Costs in $/kW: 71 across all years Emissions in tons/MWh: 0

2030) and flat after 2030 O&M Costs in $/kW: 71-35 (2013-2030) and flat after 2030

Lifetime: 25 years Emissions in tons/MWh: 0 Lifetime: 25 years Large Hydro

Installed in MW: 4500 – 5800 (2013-2030) and

Installed in MW: 4500 – 5800 (2013-2025) and

flat after 2030

flat after 2025

Capacity Factor : 31% - 45% (2013-2030) and flat

Capacity Factor : 31% - 56% (2013-2030) and flat

after 2030

after 2030

Capital Costs in $/kW: 6250 – 4000 (2013-2030)

Capital Costs in $/kW: 6250 – 1750 (2013-2030)

and flat after 2030

and flat after 2030

O&M Costs in $/kW: 85-60 (2013-2030) and flat

O&M Costs in $/kW: 85-35 (2013-2030) and flat

after 2030

after 2030

33

Action

Small Hydro

Biomass Power

Geothermal Power

Key Assumptions (Base Case)

Key Assumptions (Low Carbon Case)

Emissions in tons/MWh: 0

Emissions in tons/MWh: 0

Lifetime: 30 years

Lifetime: 30 years

Installed in MW: 90 – 600 (2013-2030) and flat

Installed in MW: 90 – 800 (2013-2030) and flat

after 2030

after 2030

Capacity Factor : 55% across all years

Capacity Factor : 55% across all years

Capital Costs in $/kW: 5000 – 3000 (2013-2030)

Capital Costs in $/kW: 5000 – 2000 (2013-2030)

and flat after 2030

and flat after 2030

O&M Costs in $/kW: 56-45 (2013-2030) and flat

O&M Costs in $/kW: 56-34 (2013-2030) and flat

after 2030

after 2030

Emissions in tons/MWh: 0

Emissions in tons/MWh: 0

Lifetime: 30 years

Lifetime: 30 years

Installed in MW: 6.2 – 500 (2013-2030) and flat

Installed in MW: 6.2 – 1000 (2013-2030) and flat

after 2030

after 2030

Capacity Factor : 76% - 83% (2013-2030) and flat

Capacity Factor : 76% - 91% (2013-2030) and flat

after 2030

after 2030

Capital Costs in $/kW: 6000 – 4500 (2013-2030)

Capital Costs in $/kW: 6000 – 3000 (2013-2030)

and flat after 2030

and flat after 2030

O&M Costs in $/MWh: 50-40 (2013-2030) and

O&M Costs in $/MWh: 50-30 (2013-2030) and

flat after 2030

flat after 2030

Emissions in tons/MWh: 0

Emissions in tons/MWh: 0

Lifetime: 20 years

Lifetime: 20 years

Installed in MW: 1.36 – 1000 (2013-2030) and

Installed in MW: 1.36 – 2500 (2013-2030) and

flat after 2030

flat after 2030

Capacity Factor : 55% - 68% (2013-2030) and flat

Capacity Factor : 55% - 80% (2013-2030) and flat

after 2030

after 2030

Capital Costs in $/kW: 3000 – 2000 (2013-2030)

Capital Costs in $/kW: 3000 – 1000 (2013-2030)

and flat after 2030

and flat after 2030

O&M Costs in $/MWh: 75-50 (2013-2030) and

O&M Costs in $/MWh: 75-25 (2013-2030) and

flat after 2030

flat after 2030

Emissions in tons/MWh: 0

Emissions in tons/MWh: 0

Lifetime: 20 years

Lifetime: 20 years

34

Action

Key Assumptions (Base Case)

Key Assumptions (Low Carbon Case)

Pumped Storage Hydro

Installed in MW: 900 – 4700 (2013-2025) and

Installed in MW: 90 – 4700 (2013-2020) and flat

flat after 2025

after 2020

Capacity Factor : 76% across all years

Capacity Factor : 76% across all years

Capital Costs in Euro/kW: 1200 across all years

Capital Costs in Euro/kW: 1200 across all years

O&M Costs in Euro/kW: 4 across all years

O&M Costs in Euro/kW: 4 across all years

Emissions in tons/MWh: 0.04 (savings)

Emissions in tons/MWh: 0.04 (savings)

Lifetime: 40 years

Lifetime: 40 years

Installed in MW: 0 across all years

Installed in MW: 500 MW installed in 2020 and

Coal Fired Ultra Super Critical Plants (USPC)

Capacity Factor : 80% across all years Capital Costs in $/kW: 2250 across all years O&M Costs in $/kW: 88 across all years Revenues/Savings in g/kWh (coal): 144 across all years

2030 Capacity Factor : 80% across all years Capital Costs in $/kW: 2250 across all years O&M Costs in $/kW: 88 across all years Revenues/Savings in g/kWh (coal): 144 across all

Emissions in tons/MWh: 0.26 (savings over coal at 1)

years Emissions in tons/MWh: 0.26 (savings over coal at 1)

Lifetime: 40 years

Lifetime: 40 years Natural Gas Combined Cycle Plants

Installed in MW: 450 – 6755 (2016-2030) and

Installed in MW: 900 – 13508 (2016-2030) and

(NGCC)

flat after 2030

flat after 2030

Capacity Factor : 60% across all years

Capacity Factor : 60% across all years

Capital Costs in $/kW: 1100 across all years

Capital Costs in $/kW: 1100 across all years

O&M Costs in $/kW: 72.5 across all years

O&M Costs in $/kW: 72.5 across all years

Emissions in tons/MWh: 0.66 (savings over coal

Emissions in tons/MWh: 0.66 (savings over coal

at 1)

at 1)

Lifetime: 25 years

Lifetime: 25 years

Installed in MW: 0 across all years

Installed in MW: 500 MW installed in 2020 and

Carbon Capture and Sequestration with USPC Plants

Capacity Factor : 80% across all years Capital Costs in $/kW: 3538 across all years O&M Costs in $/kW: 191 across all years Revenues/Savings in g/kWh (coal): 144 across all

35

2030 Capacity Factor : 80% across all years Capital Costs in $/kW: 3538 across all years O&M Costs in $/kW: 191 across all years

Action

Key Assumptions (Base Case) years

Key Assumptions (Low Carbon Case) Revenues/Savings in g/kWh (coal): 144 across all

Emissions in tons/MWh: 0.90 (savings over coal at 1)

years Emissions in tons/MWh: 0.90 (savings over coal

Lifetime: 40 years

at 1) Lifetime: 40 years

Nuclear

Installed in MW: 13835 â&#x20AC;&#x201C; 18000 (2013-2030)

Installed in MW: 13835 â&#x20AC;&#x201C; 18000 (2013-2030)

and flat after 2030

and flat after 2030

Capacity Factor : 74% - 77% (2013-2030) and flat

Capacity Factor : 74% - 77% (2013-2030) and flat

after 2030

after 2030

Capital Costs in $/kW: 4000 across all years

Capital Costs in $/kW: 4000 across all years

O&M Costs in $/MW: 13 across all years

O&M Costs in $/MW: 13 across all years

Emissions in tons/MWh: 0

Emissions in tons/MWh: 0

Lifetime: 50 years

Lifetime: 50 years

Based on these inputs into the MACTool, the generation Marginal Abatement Cost Curve (MACC) for the sector has been illustrated in

36

Figure 9. Since the data for the power generation sector was available only until 2030, the MACC has also been calculated out to 2030 in the figure. The tool does have an output for MACC out to 2054 but this has assumed installation capacities remain flat for several technologies beyond the 2030 period. Once better data is available for these technologies (e.g. solar PV) beyond 2030, the MACC curve can be recalculated.

Figure 9. MACC for Power Generation Mitigation Actions The MAC values and associated emissions reduction estimates for the sector have been summarized in Appendix A1 (for 2030) and A2 (for the full 41 year period). The highest MAC values were estimated for residential and large and these have estimated MAC values of >$100/ton in the period out to 2030. These reduce $37/ton and $48/ton respectively for residential and large Solar PV in the 41 year period calculation primarily because no additional capacity installations have been estimated for the period beyond 2030 for this technology. These results in general are consistent with what might be expected for an expensive technology that is still undergoing significant 37

changes in costs and installed capacity around the world. The largest emissions reduction potential was observed for natural gas combined cycle plants largely driven by the fact that these replace existing, dirtier coal plants that have a large current installed based (~13 GW). NGCC plants were estimated to have a MAC value of -$7/ton (for a 41 year period) which is driven by lower capital and operating costs compared to other alternatives. The lowest MAC value of -$47/ton (for a 41 year period) was obtained for pumped storage because this had a combination of low capital and operating costs along with large lifetimes which implies minimum reinvestment is required to keep the capacity operational over a 41 year period. It is important to note that changes to grid emission factors, capital and operating costs (due to learning curve effects) and grid electric prices (unsubsidized) can have significant impacts on future estimates of MAC values especially in the out years (i.e. beyond 2020).

4.3 POWER CONSERVATION ASSUMPTIONS & RESULTS Table 16 summarizes the key assumptions for the seven power conservation mitigation actions identified earlier.

Table 16 : Key Assumptions for Mitigation Actions in Power Conservation Action

Key Assumptions (Base Case)

Key Assumptions (Low Carbon Case)

Energy Efficient Lighting

Total units installed: 254 M to 383 M (2013-

Total units installed: 254 M to 383 M (2013-

2054)

2054)

Market Penetration EE: 20% - 100% (2013-2050)

Market Penetration EE: 20% - 100% (2013-2040)

Capital Costs in UAH/unit: 35 for all years

Capital Costs in UAH/unit: 35 for all years

Energy Savings in kWh/unit: 12.24 for all years

Energy Savings in kWh/unit: 12.24 for all years

Emissions Savings in tons/MWh: 0.42 (grid avg)

Emissions Savings in tons/MWh: 0.42 (grid avg)

Lifetime: 5 years

Lifetime: 5 years

Total units installed: 19 M to 56 M (2013-2054)

Total units installed: 19 M to 56 M (2013-2054)

Market Penetration EE: 20% - 54% (2013-2054)

Market Penetration EE: 20% - 100% (2013-2054)

Capital Costs in Euro/unit: 168.5 for all years

Capital Costs in Euro/unit: 168.5 for all years

Energy Savings in kWh/unit: 76.83 for all years

Energy Savings in kWh/unit: 76.83 for all years

Emissions Savings in tons/MWh: 0.42 (grid avg)

Emissions Savings in tons/MWh: 0.42 (grid avg)

Lifetime: 20 years

Lifetime: 20 years

Total units installed: 14 M to 19 M (2013-2054)

Total units installed: 14 M to 19 M (2013-2054)

Market Penetration EE: 20% - 54% (2013-2054)

Market Penetration EE: 20% - 100% (2013-2054)

Capital Costs in Euro/unit: 305 for all years

Capital Costs in Euro/unit: 305 for all years

Energy Savings in kWh/unit: 61.58 for all years

Energy Savings in kWh/unit: 61.58 for all years

Emissions Savings in tons/MWh: 0.42 (grid avg)

Emissions Savings in tons/MWh: 0.42 (grid avg)

Energy Efficient Refrigerators

Energy Efficient Washer/Dryers

38

Energy Efficient Microwaves

Energy Efficient Televisions

Power Transmission Upgrade

Smart Grid

Lifetime: 20 years

Lifetime: 20 years

Total units installed: 7 M to 32 M (2013-2054)

Total units installed: 7 M to 32 M (2013-2054)

Market Penetration EE: 20% - 54% (2013-2054)

Market Penetration EE: 20% - 100% (2013-2054)

Capital Costs in Euro/unit: 117 for all years

Capital Costs in Euro/unit: 117 for all years

Energy Savings in kWh/unit: 3.44 for all years

Energy Savings in kWh/unit: 3.44 for all years

Emissions Savings in tons/MWh: 0.42 (grid avg)

Emissions Savings in tons/MWh: 0.42 (grid avg)

Lifetime: 10 years

Lifetime: 10 years

Total units installed: 20 M to 28 M (2013-2054)

Total units installed: 20 M to 28 M (2013-2054)

Market Penetration EE: 77% - 100% (2013-2030)

Market Penetration EE: 77% - 100% (2013-2022)

Capital Costs in Euro/unit: 1938.5 for all years

Capital Costs in Euro/unit: 1938.5 for all years

Energy Savings in kWh/unit: 18.2 for all years

Energy Savings in kWh/unit: 18.2 for all years

Emissions Savings in tons/MWh: 0.42 (grid avg)

Emissions Savings in tons/MWh: 0.42 (grid avg)

Lifetime: 10 years

Lifetime: 10 years

Total TWh: 204 to 456 (2013-2054)

Total TWh: 204 to 456 (2013-2054)

% Upgraded: 10% - 100% (2013-2050)

% Upgraded: 20% - 100% (2013-2040)

Capital Costs in UAH/TWh: 2.15 for all years

Capital Costs in UAH/TWh: 2.15 for all years

Energy Savings %: 11%

Energy Savings %: 11%

Emissions Savings in tons/MWh: 0.42 (grid avg)

Emissions Savings in tons/MWh: 0.42 (grid avg)

Lifetime: 50 years

Lifetime: 50 years

Total TWh: 40 to 102 (2013-2054)

Total TWh: 40 to 102 (2013-2054)

% Upgraded: 0% - 20% (2013-2050) and flat

% Upgraded: 0% - 40% (2013-2050) and flat

after 2050

after 2050

Capital Costs in $/kWh: 0.095 for all years

Capital Costs in $/kWh: 0.095 for all years

Energy Savings %: 5.9%

Energy Savings %: 5.9%

Emissions Savings in tons/MWh: 0.42 (grid avg)

Emissions Savings in tons/MWh: 0.42 (grid avg)

Lifetime: 50 years

Lifetime: 50 years

39

Based on these inputs into the MACTool, the MACC for the sector has been illustrated in Figure 10. The values for microwaves and TVs are very large (in the 1000s $/ton) and not presented in the graphic.

Figure 10. MACC for Power Conservation Mitigation Actions The MAC values and associated emissions reduction estimates for the sector have been summarized in Appendix A3. Energy efficient lighting was estimated to have a MAC of -$38/ton and an emission benefit of over 4 million tons saved over a 41 year period. This result is consistent with findings in several other regions where lighting programs have been prioritized because it is both cost effective and has positive impacts on emissions through energy savings. Energy efficient televisions were estimated to have a very large MAC of > $20,000/ton as a result of price and relatively low energy savings delivered with new technology. The low total emissions benefit in the case of televisions is also driven by the fact that new technologies continue to replace older ones independent of policies. In terms of appliances energy efficient refrigerators appeared to be the most promising but even there the estimated MAC Value is $50/ton. Transmission upgrades and deployment of a smart grid also had negative MAC values with emission benefits in the double and single digit range respectively. In the case of transmission upgrades and smart grid it is quite likely that costs have been underestimated which is part of what is driving low MAC values. It should be noted that assumed market penetrations for all power conservation technologies have a significant impact on the costs and assumed energy savings per unit (or TWh as applicable) will also drive the emission benefits and calculated MAC values.

4.4 FOSSIL FUEL ASSUMPTIONS & RESULTS Table 17 summarizes the key assumptions for the three mitigation actions identified for the fossil fuel sector earlier.

Table 17 : Key Assumptions for Mitigation Actions in Fossil Fuel Action

Key Assumptions (Base Case)

Key Assumptions (Low Carbon Case)

Coal Mine Methane â&#x20AC;&#x201C; Ventilation Air

Total mines serviced: 0 to 120 (2013-2054)

Total mines serviced: 0 to 145 (2013-2030) and

40

Machine (VAM)

Capital Costs in $/mine: 1,000,000 for all years O&M Costs in $/mine: 96,000 for all years Emissions Savings in tons/mine: 28561

flat after 2030 Capital Costs in $/mine: 1,000,000 for all years O&M Costs in $/mine: 96,000 for all years Emissions Savings in tons/mine: 28561

Lifetime: 15 years

Lifetime: 15 years Coal Mine Methane â&#x20AC;&#x201C; Combined Heat and Power (CHP)

Total mines serviced: 0 to 120 (2013-2054)

Total mines serviced: 0 to 145 (2013-2030) and flat after 2030

MW/mine: 2 for all years Capital Costs in $/kW: 1500 for all years O&M Costs in $/kWh: 0.025 for all years Emissions Savings in tons/mine: 33462

MW/mine: 2 for all years Capital Costs in $/kW: 1500 for all years O&M Costs in $/kWh: 0.025 for all years Emissions Savings in tons/mine: 33462

Lifetime: 15 years

Lifetime: 15 years Coal Mining Energy Efficiency

Total millions tons/yr: 83.5 M to 425 M (2013-

Total millions tons/yr: 83.5 M to 425 M (2013-

2054)

2054)

Market Penetration: 3% - 100% (2013-2050) and

Market Penetration: 3% - 100% (2013-2030) and

flat after 2050

flat after 2030

Capital Costs in million UAH/million ton: 9950

Capital Costs in million UAH/million ton: 9950

for all years

for all years

Electricity Consumption in kWh/ton: 52 to 15.4

Electricity Consumption in kWh/ton: 52 to 15.4

(2013-2054)

(2013-2054)

Emissions Savings in tons/MWh: 1 (coal avg)

Emissions Savings in tons/MWh: 1 (coal avg)

Lifetime: 40 years

Lifetime: 40 years

Based on these inputs into the MACTool, the generation Marginal Abatement Cost Curve (MACC) for the sector has been illustrated in Figure 11. The value for coal mine methane is very large (in the $100s/ton) and not presented in the graphic.

41

Figure 11. MACC for Fossil Fuel Mitigation Actions The MAC values and associated emissions reduction estimates for the sector have been summarized in Appendix A4. The utilization of coal mine methane through CHP or oxidization of methane to CO2 via VAM are estimated to have MAC values of $2/ton with emissions benefits at 61 and 52 million tons cumulative respectively from 20142054. The small difference in emissions benefits is driven primarily by the higher savings realized through deployment of CHP solutions for coal mine methane. Deployment of energy efficiency at coal mines is estimated to have a MAC value over $700/ton and this large value is primarily driven by capital costs and low electricity savings (and associated rates).

4.5 MANUFACTURING/INDUSTRY ASSUMPTIONS & RESULTS Table 18 summarizes the key assumptions for the thirteen mitigation actions considered for the manufacturing sector identified earlier.

Table 18 : Key Assumptions for Mitigation Actions in Manufacturing/Industry Action

Key Assumptions (Base Case)

Key Assumptions (Low Carbon Case)

Aluminum Scrap Recycling

Total tons/yr: 110 for all years

Total tons/yr: 110 (2013-2019), 170 (2020-

Capital Costs in $/ton: 5050 for all years O&M Costs in $/ton: 2082 for all years Emissions Savings in tons/ton of material: 10.2

2029), 230 (2030-2054) Capital Costs in $/ton: 5050 for all years O&M Costs in $/ton: 2082 for all years Emissions Savings in tons/ton of material: 10.2

Lifetime: 20 years

Lifetime: 20 years Ammonia Energy Efficiency

Ammonia Electrolysis

Total ktons/yr: 4156 (2013-2019), 4500 (2020-

Total ktons/yr: 4156 (2013-2019), 4500 (2020-

2054)

2054)

Market Penetration %: 15% - 100% (2014-2050)

Market Penetration %: 25% - 100% (2014-2040)

and flat after 2050

and flat after 2040

Capital Costs in $/ton: 76.4 for all years

Capital Costs in $/ton: 76.4 for all years

Energy Savings in MMBTU/ton: 8 (as natural

Energy Savings in MMBTU/ton: 8 (as natural

gas)

gas)

Emissions Savings in tons/ton of material: 0.48

Emissions Savings in tons/ton of material: 0.48

Lifetime: 30 years

Lifetime: 30 years

Total ktons/yr: 4156 (2013-2019), 4500 (2020-

Total ktons/yr: 4156 (2013-2019), 4500 (2020-

2054)

2054)

Market Penetration %: 3% - 58% (2014-2054)

Market Penetration %: 5% - 92% (2014-2054)

Capital Costs in $/ton: 1429.5 for all years

Capital Costs in $/ton: 1429.5 for all years

42

Dry Cement Process

Wet Cement Process (Slag)

Shale Gas in Cement

Direct Reduction Iron

Iron Ore Production Energy Efficiency

O&M Costs in $/ton: 645 for all years

O&M Costs in $/ton: 645 for all years

Emissions Savings in tons/ton of material: 2.14

Emissions Savings in tons/ton of material: 2.14

Lifetime: 30 years

Lifetime: 30 years

Total ktons/yr: 5000 (2013-2029), 7500 (2020-

Total ktons/yr: 5000 (2013-2019), 7500 (2020-

2049), 10000 (2050-2054)

2029), 10000 (2030-2050), 12500 (2050-2054)

Capital Costs in Euro/ton: 56 for all years

Capital Costs in Euro/ton: 56 for all years

Emissions Savings in tons/ton of material: 0.27

Emissions Savings in tons/ton of material: 0.27

Lifetime: 40 years

Lifetime: 40 years

Total ktons/yr: 0 (2013-2019), 2000 (2020-

Total ktons/yr: 0 (2013-2019), 4000 (2020-

2029), 3000 (2030-2039), 3500 (2040-2049),

2029), 6000 (2030-2039), 7000 (2040-2049),

4000 (2050-2054)

8000 (2050-2054)

Capital Costs in Euro/ton: 4.8 for all years

Capital Costs in Euro/ton: 4.8 for all years

O&M Costs in Euro/ton: 565 for all years

O&M Costs in Euro/ton: 565 for all years

Emissions Savings in tons/ton of material: 0.89

Emissions Savings in tons/ton of material: 0.89

Lifetime: 40 years

Lifetime: 40 years

Total ktons/yr: 0 (2013-2019), 5000 (2020-

Total ktons/yr: 0 (2013-2019), 8500 (2020-

2029), 7500 (2030-2049), 10000 (2050-2054)

2029), 11000 (2030-2039), 12500 (2040-2054)

Capital Costs in Euro/ton: 61.6 for all years

Capital Costs in Euro/ton: 61.6 for all years

O&M Costs in MMBTU/ton: 3.41 for all years (as

O&M Costs in MMBTU/ton: 3.41 for all years (as

natural gas)

natural gas)

Emissions Savings in tons/ton of material: 0.15

Emissions Savings in tons/ton of material: 0.15

Lifetime: 40 years

Lifetime: 40 years

Total ktons/yr: 0 (2013-2019), 1900 (2020-

Total ktons/yr: 0 (2013-2019), 3800 (2020-

2029), 6500 (2030-2039), 7500 (2040-2049),

2029), 13000 (2030-2039), 15000 (2040-2049),

8500 (2050-2054)

17000 (2050-2054)

Capital Costs in $/ton: 320 for all years

Capital Costs in $/ton: 320 for all years

O&M Costs in $/ton: 214 for all years

O&M Costs in $/ton: 214 for all years

Emissions Savings in tons/ton of material: 1.53

Emissions Savings in tons/ton of material: 1.53

Lifetime: 20 years

Lifetime: 20 years

Total ktons/yr: 63758 (2013-2019), 65000

Total ktons/yr: 63758 (2013-2019), 65000

(2020-2054)

(2020-2054)

43

Steel Rolling/Casting Energy Efficiency

Steel Continuous Rolling

Steel Electric Arc Furnace (EAF)

Lime Production Energy Efficiency

Market Penetration %: 15% - 100% (2014-2050)

Market Penetration %: 25% - 100% (2014-2040)

and flat after 2050

and flat after 2040

Capital Costs in $/ton: 5.34 for all years

Capital Costs in $/ton: 5.34 for all years

Energy Savings in MMBTU/ton: 0.18 (as natural

Energy Savings in MMBTU/ton: 0.18 (as natural

gas)

gas)

Emissions Savings in tons/ton of material: 0.09

Emissions Savings in tons/ton of material: 0.09

Lifetime: 30 years

Lifetime: 30 years

Total ktons/yr: 8725 (2013-2019), 10240 (2020-

Total ktons/yr: 8725 (2013-2019), 10240 (2020-

2029), 11840 (2030-2039), 12800 (2040-2049),

2029), 11840 (2030-2039), 12800 (2040-2049),

13440 (2050-2054)

13440 (2050-2054)

Market Penetration %: 4% - 44% (2014-2054)

Market Penetration %: 8% - 88% (2014-2054)

Capital Costs in $/ton: 170 for all years

Capital Costs in $/ton: 170 for all years

Energy Savings in MMBTU/ton: 0.05 (as natural

Energy Savings in MMBTU/ton: 0.05 (as natural

gas)

gas)

Emissions Savings in tons/ton of material: 0.09

Emissions Savings in tons/ton of material: 0.09

Lifetime: 30 years

Lifetime: 30 years

Total ktons/yr: 14905 (2013-2019), 17647

Total ktons/yr: 29782 (2013-2019), 34586

(2020-2029), 20404 (2030-2039), 22058 (2040-

(2020-2029), 38869 (2030-2039), 40808 (2040-

2049), 23161 (2050-2054)

2049), 42848 (2050-2054)

Capital Costs in $/ton: 175 for all years

Capital Costs in $/ton: 175 for all years

Emissions Savings in tons/ton of material: 0.22

Emissions Savings in tons/ton of material: 0.22

Lifetime: 30 years

Lifetime: 30 years

Total ktons/yr: 1746 (2013-2019), 3123 (2020-

Total ktons/yr: 1746 (2013-2019), 4500 (2020-

2029), 3623 (2030-2039), 4173 (2040-2049),

2029), 5500 (2030-2039), 6600 (2040-2049),

4723 (2050-2054)

7700 (2050-2054)

Capital Costs in $/ton: 80 for all years

Capital Costs in $/ton: 80 for all years

O&M Costs in $/ton: 32 for all years

O&M Costs in $/ton: 32 for all years

Emissions Savings in tons/ton of material: 1.59

Emissions Savings in tons/ton of material: 1.59

Lifetime: 30 years

Lifetime: 30 years

Total ktons/yr: 4250 (2013-2019), 5125 (2020-

Total ktons/yr: 4250 (2013-2019), 6000 (2020-

2029), 5625 (2030-2039), 5875 (2040-2054)

2029), 7000 (2030-2039), 7500 (2040-2054)

Capital Costs in Euro/ton: 97 for all years

Capital Costs in Euro/ton: 97 for all years

44

O&M Costs in Euro/ton: 47 for all years

O&M Costs in Euro/ton: 47 for all years

Emissions Savings in tons/ton of material: 0.11

Emissions Savings in tons/ton of material: 0.11

Lifetime: 40 years

Lifetime: 40 years

Paper Production Energy Efficiency

Total units installed: 2 â&#x20AC;&#x201C; 12 (2014-2030), flat

Total units installed: 4 â&#x20AC;&#x201C; 21 (2014-2030), flat

(Boiler Replacement)

after 2030

after 2030

Capital Costs in Euro/unit: 450,000 for all years

Capital Costs in Euro/unit: 450,000 for all years

O&M Costs in Euro/unit: 15,750 for all years

O&M Costs in Euro/unit: 15,750 for all years

Energy Savings in MMBTU/unit: 35,727 for all

Energy Savings in MMBTU/unit: 35,727 for all

years (as natural gas)

years (as natural gas)

Emissions Savings in tons/unit: 1688

Emissions Savings in tons/unit: 1688

Lifetime: 40 years

Lifetime: 40 years

Based on these inputs into the MACTool, the MACC for the sector has been illustrated in Figure 12.

Figure 12. MACC for Manufacturing Mitigation Actions The MAC values and associated emissions reduction estimates for the sector have been summarized in Appendix A5. Several of the energy efficiency technologies were estimated to have low MAC values with the lowest being deployment of this measure for iron ore production (at $1/ton). The largest MAC values were estimated for wet cement process and lime production energy efficiency at $153/ton and $122/ton respectively. These large values were driven by the fact that both actions had high capital and operating costs with no estimated revenues. The data gathered to date for many of the measures that ended up with large MAC value estimates did not have associated revenues/savings. As an illustration, aluminium scrap recycling ($40/ton) did not have a revenue estimate in the form of sales of recovered tons which would reduce the estimated MAC value. It is possible that 45

the operation and maintenance costs often reported in literature include the benefit of such savings. It will therefore be important to confirm or estimate savings/revenues (if any) to further improve MAC value estimates for this sector. In terms of total emissions benefits steel and iron ore related actions appeared to have the biggest impact (>100 million tons saved from 2014-2054) which is as expected because these are often the most energy intensive manufacturing processes. Each of the industries (i.e. cement, steel etc.) warrants further study to validate the costs and benefits of the actions that have been identified for this sector. A survey of experts for each industry would be an appropriate way to validate and correct numbers that have been used to arrive at the MAC and emissions value estimates that have been estimated in this report.

4.6 WASTE MANAGEMENT ASSUMPTIONS & RESULTS Table 19 summarizes the key assumptions for the ten mitigation actions considered for the waste sector identified earlier.

Table 19 : Key Assumptions for Mitigation Actions in Waste Action

Key Assumptions (Base Case)

Key Assumptions (Low Carbon Case)

Landfill Gas Power (LFG)

Installed in MW: 1.25 – 40 (2013-2030) and flat

Installed in MW: 1.25 – 80 (2013-2030) and flat

after 2030

after 2030

Capacity Factor : 80% across all years

Capacity Factor : 80% across all years

Capital Costs in $/kW: 3200 across all years

Capital Costs in $/kW: 3200 across all years

O&M Costs in $/kW: 200 across all years

O&M Costs in $/kW: 200 across all years

Revenues Costs in $/kWh: Assumed grid electric

Revenues Costs in $/kWh: Assumed grid electric

rates (wholesale, unsubsidized)

rates (wholesale, unsubsidized)

Emissions Savings in tons/MW: 32,000

Emissions Savings in tons/MW: 32,000

Lifetime: 25 years

Lifetime: 25 years

Clean Municipal Solid Waste Power

Installed in MW: 0 (2013-2025), 3.5 (2025-

Installed in MW: 0 (2013-2019), 3.5 (2020-

(MSW)

2029), 7 (2030-2039), 10.5 (2040-2049), 14

2024), 7 (2025-2029), 10.5 (2030-2039), 14

(2050-2054)

(2040-2049), 17.5 (2050-2054)

Capacity Factor : 76% across all years

Capacity Factor : 76% across all years

Capital Costs in $/kW: 71,429 across all years

Capital Costs in $/kW: 71,429 across all years

O&M Costs in $/kW: 4000 across all years

O&M Costs in $/kW: 4000 across all years

Revenues Costs in $/kWh: Assumed grid electric

Revenues Costs in $/kWh: Assumed grid electric

rates (wholesale, unsubsidized)

rates (wholesale, unsubsidized)

Emissions Savings in tons/MW: 49,789

Emissions Savings in tons/MW: 49,789

Lifetime: 25 years

Lifetime: 25 years

Installed in MW: 1.25 – 66.25 (2013-2050) and

Installed in MW: 1.25 – 132.5 (2013-2050) and

Waste Water Utilization for Power

46

flat after 2050

flat after 2050

Capacity Factor : 80% across all years

Capacity Factor : 80% across all years

Capital Costs in $/kW: 5440 across all years

Capital Costs in $/kW: 5440 across all years

O&M Costs in $/kW: 1088 across all years

O&M Costs in $/kW: 1088 across all years

Revenues Costs in $/kWh: Assumed grid electric

Revenues Costs in $/kWh: Assumed grid electric

rates (wholesale, unsubsidized)

rates (wholesale, unsubsidized)

Emissions Savings in tons/MW: 9760

Emissions Savings in tons/MW: 9760

Lifetime: 25 years

Lifetime: 25 years

Segregate Colloids Utilization for Power

Installed in MW: 1.25 – 50 (2013-2050) and flat

Installed in MW: 1.25 – 100 (2013-2050) and flat

(Food Waste Biogas)

after 2050

after 2050

Capacity Factor : 80% across all years

Capacity Factor : 80% across all years

Capital Costs in $/kW: 8160 across all years

Capital Costs in $/kW: 8160 across all years

O&M Costs in $/kW: 1632 across all years

O&M Costs in $/kW: 1632 across all years

Revenues Costs in $/kWh: Assumed grid electric

Revenues Costs in $/kWh: Assumed grid electric

rates (wholesale, unsubsidized)

rates (wholesale, unsubsidized)

Emissions Savings in tons/MW: 40,500

Emissions Savings in tons/MW: 40,500

Lifetime: 25 years

Lifetime: 25 years

Replace Obsolete Municipal Waste

Upgraded kW: 0 – 37782 (2013-2050) and flat

Upgraded kW: 0 – 75563 (2013-2050) and flat

Facilities (Pumping Systems)

after 2050

after 2050

Energy Savings: 25% across all years (energy

Energy Savings: 25% across all years (energy

reduction over installed base)

reduction over installed base)

Capital Costs in $/kW: 1000 across all years

Capital Costs in $/kW: 1000 across all years

O&M Costs in $/kW: 200 across all years

O&M Costs in $/kW: 200 across all years

Revenues Costs in $/kWh: Assumed grid electric

Revenues Costs in $/kWh: Assumed grid electric

rates (wholesale, unsubsidized)

rates (wholesale, unsubsidized)

Emissions Savings in tons/kW: 5

Emissions Savings in tons/kW: 5

Lifetime: 25 years

Lifetime: 25 years

Total Projects: 0 (2013-2015), 1 (2016-2019), 2

Total Projects: 0 (2013-2015), 2 (2016-2019), 5

(2020-2021), 3 (2022-2025), 4 (2026-2029), 5

(2020-2021), 6 (2022-2023), 7 (2024-2025), 8

(2030-2033), 6 (2034-2039), 7 (2040-2049), 8

(2026-2027), 9 (2028-2029), 10 (2030-2033), 11

(2050-2054)

(2034-2037), 12 (2038-2039), 13 (2040-2044),

Composting

Capital Costs in $/project: 250,000 across all

47

14 (2044-2049), 15 (2050-2054)

years

Capital Costs in $/project: 250,000 across all

O&M Costs in $/project: 60,000 across all years

years

Emissions Savings in tons/project: 17,700

O&M Costs in $/project: 60,000 across all years

Lifetime: 10 years

Emissions Savings in tons/project: 17,700 Lifetime: 10 years

Biodegradable Plastics

Increased Recycling

Modern Materials Recycling

Waste Production Limits

Total Projects: 0 – 12500 (2013-2050) and flat

Total Projects: 0 – 25000 (2013-2050) and flat

after 2050

after 2050

O&M Costs in $/project: 10,000 across all years

O&M Costs in $/project: 10,000 across all years

Emissions Savings in tons/project: 600

Emissions Savings in tons/project: 600

Lifetime: 10 years

Lifetime: 10 years

Total ktons: 0 – 2676 (2013-2050) and flat after

Total ktons: 0 – 5351 (2013-2050) and flat after

2050

2050

O&M Costs in $/ton: 83.55 across all years

O&M Costs in $/ton: 83.55 across all years

Emissions Savings in tons/ton of material: 0.267

Emissions Savings in tons/ton of material: 0.267

Lifetime: 10 years

Lifetime: 10 years

Total Projects: 0 before 2020, 0 – 5 (2020-2050)

Total Projects: 0 before 2020, 0 – 10 (2020-

and flat after 2050

2050) and flat after 2050

CAPEX Costs in $/project: 5,000,000 across all

CAPEX Costs in $/project: 5,000,000 across all

years

years

O&M Costs in $/project: 2,000,000 across all

O&M Costs in $/project: 2,000,000 across all

years

years

Emissions Savings in tons/project: 0.404

Emissions Savings in tons/project: 0.404

Lifetime: 10 years

Lifetime: 10 years

Total billion tons: 0.5 – 0.76 (2013-2054)

Total billion tons: 0.5 – 0.76 (2013-2054)

Market Penetration: 0.04% - 2.5% (2013-2050)

Market Penetration: 0.08% - 5.0% (2013-2050)

O&M Costs in $/ton: 1200 across all years

O&M Costs in $/ton: 1200 across all years

Emissions Savings in tons/ton of material: 687

Emissions Savings in tons/ton of material: 687

Lifetime: 10 years

Lifetime: 10 years

Based on these inputs into the MACTool, the MACC for the sector has been illustrated in Figure 13.

48

Figure 13. MACC for Waste Mitigation Actions The MAC values and associated emissions reduction estimates for the sector have been summarized in Appendix A6. Waste production limits had the largest estimated MAC value at $215/ton but also had the largest emissions impact of 215 M tons CO2e estimated savings from 2014-2054. The large MAC is driven by the fact that there are no realized savings currently factored in to the calculations. If the reduced waste results in reductions in energy consumed, lower commodity costs etc. up stream, there could be savings that can positively impact results.

However, it is understandable why such savings would be difficult to quantify because in effect that requires a thorough analysis of waste types and the underlying economics from source to sink for those waste types. The power generation solutions such as LFG and segregated colloids (i.e. food waste biogas plants) are estimated to have MAC values under $15/ton which appear favourable. The economics for these solutions could be made even more favourable if the electric prices for power generated for these facilities are higher while costs are decreased due to technology learning curve effects. Increased use of biodegradable plastics appears to be most favourable

49

among the list of actions in terms of a low estimated MAC value of ($2/ton) and high emissions reduction potential (165 M CO2e savings from 2014-2054). Careful, bottom-up quantification for emissions, installed capacities and costs across the various mitigation actions for the waste sector is required to further refine the analysis and strengthen the estimates. For example, the landfill gas estimates could be refined by landfill type (based on how much methane is produced), that can in turn reveal what equipment might be placed (if any) and the associated emissions before and after action. A similar methodology can be applied for all other power generation actions identified for this sector. In the case of waste management techniques such as recycling, composting etc.; a bottom- up inventory (from source to sink) will be critical in understanding growth drivers for emissions and the true costs for mitigation actions.

4.7 BUILDINGS ASSUMPTIONS & RESULTS Table 20 summarizes the key assumptions for the 8 building mitigation actions identified earlier.

Table 20 : Key Assumptions for Mitigation Actions in Buildings Action

Key Assumptions (Base Case)

Key Assumptions (Low Carbon Case)

Draught Proofing

Total building m2 for install: ~1.1 B for all years

Total building m2 for install: ~1.1 B for all years

Market Penetration EE: 0.5% - 50.5% (2013-

Market Penetration EE: 0.5% - 80.5% (2013-

2050) and flat after 2050

2050) and flat after 2050

Capital Costs in Eur/m2: 4.6 for all years

Capital Costs in Eur/m2: 4.6 for all years

Energy Savings in thermal MWh/m2: 0.0535 for

Energy Savings in thermal MWh/m2: 0.0535 for

all years

all years

Emissions Savings in tons/m2: 0.0134

Emissions Savings in tons/m2: 0.0134

Lifetime: 40 years

Lifetime: 40 years

Total building m2 for install: ~1.1 B for all years

Total building m2 for install: ~1.1 B for all years

Market Penetration EE: 0.5% - 60.5% (2013-

Market Penetration EE: 0.5% - 80.5% (2013-

2050) and flat after 2050

2050) and flat after 2050

Capital Costs in Eur/m2: 12.43 for all years

Capital Costs in Eur/m2: 12.43 for all years

Energy Savings in thermal MWh/m2: 0.0439 for

Energy Savings in thermal MWh/m2: 0.0439 for

all years

all years

Emissions Savings in tons/m2: 0.0110

Emissions Savings in tons/m2: 0.0110

Lifetime: 40 years

Lifetime: 40 years

Total building m2 for install: ~1.1 B for all years

Total building m2 for install: ~1.1 B for all years

Market Penetration EE: 0.5% - 60.5% (2013-

Market Penetration EE: 0.5% - 80.5% (2013-

2050) and flat after 2050

2050) and flat after 2050

Wall Insulation

Windows Energy Efficiency

50

Boiler Upgrades

Heat Pumps

Heat Network Optimization

Capital Costs in Eur/m2: 14.09 for all years

Capital Costs in Eur/m2: 14.09 for all years

Energy Savings in thermal MWh/m2: 0.024 for

Energy Savings in thermal MWh/m2: 0.024 for

all years

all years

Emissions Savings in tons/m2: 0.006

Emissions Savings in tons/m2: 0.006

Lifetime: 40 years

Lifetime: 40 years

Total units installed: 0.1 M – 2.5 M (2013-2050)

Total units installed: 0.1 M – 4.95 M (2013-

and flat after 2050

2050) and flat after 2050

Capital Costs in $/unit: 1461 for all years

Capital Costs in $/unit: 1461 for all years

O&M Costs in $/unit: 100 for all years

O&M Costs in $/unit: 100 for all years

Energy Savings in 1000 m3 NG/unit: 2.37 for all

Energy Savings in 1000 m3 NG/unit: 2.37 for all

years

years

Emissions Savings in tons/unit: 2.58

Emissions Savings in tons/unit: 2.58

Lifetime: 40 years

Lifetime: 40 years

Total units installed: 0 M – 0.7 M (2013-2050)

Total units installed: 0 M – 1.41 M (2013-2050)

and flat after 2050

and flat after 2050

Capital Costs in $/unit: 19,800 for all years

Capital Costs in $/unit: 19,800 for all years

O&M Costs in $/unit: 100 for all years

O&M Costs in $/unit: 100 for all years

Heating Load in kW/unit: 15

Heating Load in kW/unit: 15

Electricity Savings %: 65% - 70% (2013-2050)

Electricity Savings %: 65% - 70% (2013-2050)

and flat after 2050

and flat after 2050

Emissions Savings in tons/unit: 1.48

Emissions Savings in tons/unit: 1.48

Lifetime: 10 years

Lifetime: 10 years

Total pipeline upgraded in km: 0 – 37,300

Total pipeline upgraded in km: 0 – 37,300

(2013-2050) and flat after 2050

(2013-2030) and flat after 2030

Capital Costs in million UAH/km: 2.25 for all

Capital Costs in million UAH/km: 2.25 for all

years

years

O&M Costs in UAH/km: 1000 for all years

O&M Costs in UAH/km: 1000 for all years

Energy Savings in MMBTU/km: 7369 (as natural

Energy Savings in MMBTU/km: 7369 (as natural

gas) for all years

gas) for all years

Emissions Savings in tons/km: 183.50

Emissions Savings in tons/km: 183.50

Lifetime: 50 years

Lifetime: 50 years

51

Heat Network Boiler Upgrade

Water Energy Efficiency

Installed in MW: 0 – 147701 (2013-2050) and

Installed in MW: 0 – 147701 (2013-2030) and

flat after 2050

flat after 2030

Capital Costs in Euro/MW: 90,000 across all

Capital Costs in Euro/MW: 90,000 across all

years

years

O&M Costs in Euro/MW: 3150 across all years

O&M Costs in Euro/MW: 3150 across all years

Energy Savings in MMBTU/MW: 172 across all

Energy Savings in MMBTU/MW: 172 across all

years (as natural gas)

years (as natural gas)

Emissions Savings in tons/MW: 10.13

Emissions Savings in tons/MW: 10.13

Lifetime: 50 years

Lifetime: 50 years

Population forecast: 45.35 M – 38.86 M (2013-

Population forecast: 45.35 M – 38.86 M (2013-

2054)

2054)

Market Penetration of Improvements: 2.7% -

Market Penetration of Improvements: 5.88% -

100% (2013-2050) and flat after 2050

100% (2013-2030) and flat after 2030

Capital Costs in Euro/capita: 83.33 across all

Capital Costs in Euro/capita: 83.33 across all

years

years

Water consumed in liter/capita: 142 - 72 (2013

Water consumed in liter/capita: 142 - 72 (2013

– 2050) and flat after 2050

– 2030) and flat after 2030

Thermal energy savings kWh/liter: 4.65 E-2 for

Thermal energy savings kWh/liter: 4.65 E-2 for

all years

all years

Electric energy savings kWh/liter: 0.12 E-2 for all

Electric energy savings kWh/liter: 0.12 E-2 for all

years

years

Emissions Savings in tons/ton of material: 0.15

Emissions Savings in tons/ton of material: 0.15

tons/capita

tons/capita

Lifetime: 50 years

Lifetime: 50 years

Based on these inputs into the MACTool, the MACC for the sector has been illustrated in Figure 14.

52

Figure 14. MACC for Mitigation Actions in Buildings The MAC values and associated emissions reduction estimates for the sector have been summarized in Appendix A7. Draught proofing was estimated to have the lowest MAC value ($2/ton) with the highest cumulative emissions benefit (91 million tons CO2e from 2014-2054). The MAC value estimates for heat pump and heat network boiler upgrades were the highest primarily driven by large capital costs for both these measures. The data for draught proofing, insulation and windows replacement used building stock information from 2010. It will be important to further refine this data in the future to not only account for growth in building stock but also distinguishing different building types within the stock and identifying the most applicable actions for different types of buildings to achieve energy reduction objectives. Similar arguments can be made for the applicability of boiler upgrades and heat pumps in building stock where more accurate numbers could be arrived at by producing bottoms up inventory for this type of equipment across building types. The same logic can also be applied to develop a more thorough analysis of the district heating networks and their development that can yield more accurate estimates to be populated in heat network optimization actions.

4.8 LAND USE ASSUMPTIONS & RESULTS Table 20 summarizes the key assumptions for the eighteen land use mitigation actions identified earlier.

Table 21 : Key Assumptions for Mitigation Actions in Land Use Action

Key Assumptions (Base Case)

Key Assumptions (Low Carbon Case)

Biogas Plants – Cattle

Installed in MW: 1 – 387 (2013-2050) and flat

Installed in MW: 1 – 774 (2013-2050) and flat

after 2050

after 2050

Capacity Factor : 72% across all years

Capacity Factor : 72% across all years

Capital Costs in $/kW: 3000 across all years

Capital Costs in $/kW: 3000 across all years

53

O&M Costs in $/kW: 183 across all years

O&M Costs in $/kW: 183 across all years

Revenues Costs in $/kWh: Assumed grid electric

Revenues Costs in $/kWh: Assumed grid electric

rates (wholesale, unsubsidized)

rates (wholesale, unsubsidized)

Emissions Savings in tons/MW: ~6500

Emissions Savings in tons/MW: ~6500

Lifetime: 15 years

Lifetime: 15 years

Installed in MW: 3 – 61 (2013-2050) and flat

Installed in MW: 3 – 122 (2013-2050) and flat

after 2050

after 2050

Capacity Factor : 72% across all years

Capacity Factor : 72% across all years

Capital Costs in $/kW: 4607 across all years

Capital Costs in $/kW: 4607 across all years

O&M Costs in $/kW: 576500 across all years

O&M Costs in $/kW: 576500 across all years

Revenues Costs in $/kWh: Assumed grid electric

Revenues Costs in $/kWh: Assumed grid electric

rates (wholesale, unsubsidized)

rates (wholesale, unsubsidized)

Emissions Savings in tons/MW: ~9500

Emissions Savings in tons/MW: ~9500

Lifetime: 15 years

Lifetime: 15 years

Total Mtons/yr: 0 – 1.95 (2040-2050) and flat

Total Mtons/yr: 0 – 3.90 (2040-2050) and flat

after 2050

after 2050

O&M Costs in $/ton: 400 for all years

O&M Costs in $/ton: 400 for all years

Revenues in $/ton: 51.2 for all years

Revenues in $/ton: 51.2 for all years

Emissions Savings in tons/ton of material: 0.16

Emissions Savings in tons/ton of material: 0.16

Lifetime: 10 years

Lifetime: 10 years

Reduction of Cows – Increased Milk

Total Heads/yr: 0 – 294702 (2039-2050) and flat

Total Heads/yr: 0 – 589404 (2039-2050) and flat

Production

after 2050

after 2050

CAPEX Costs in $/head: 1524 for all years

CAPEX Costs in $/head: 1524 for all years

O&M Costs in $/head: 1005 for all years

O&M Costs in $/head: 1005 for all years

Revenues in $/head: 6330 for all years

Revenues in $/head: 6330 for all years

Emissions Savings in tons/head: 4.55

Emissions Savings in tons/head: 4.55

Lifetime: 5 years

Lifetime: 5 years

Total tons/yr: 0 – 218 (2019-2050) and flat after

Total tons/yr: 0 – 436 (2019-2050) and flat after

2050

2050

O&M Costs in $/ton: 5000 for all years

O&M Costs in $/ton: 5000 for all years

Revenues in $/ton: 12,250 for all years

Revenues in $/ton: 12,250 for all years

Biogas Plants – Swine

Concentrated Fodder – Cattle

Ionophores in Cattle Ration

54

Emissions Savings in tons/ton of material: 2879

Emissions Savings in tons/ton of material: 2879

Lifetime: 30 years

Lifetime: 30 years

Total Mtons/yr: 0 – 0.51 (2019-2050) and flat

Total Mtons/yr: 0 – 1 (2019-2050) and flat after

after 2050

2050

CAPEX Costs in $/ton: 15.3 for all years

CAPEX Costs in $/ton: 15.3 for all years

O&M Costs in $/ton: 231.25 for all years

O&M Costs in $/ton: 231.25 for all years

Revenues in $/ton: 956.24 for all years

Revenues in $/ton: 956.24 for all years

Emissions Savings in tons/ton of material: 1.68

Emissions Savings in tons/ton of material: 1.68

Lifetime: 30 year

Lifetime: 30 year

Total Mtons/yr: 0 – 225,343 (2019-2050) and

Total Mtons/yr: 0 – 450,686 (2019-2050) and

flat after 2050

flat after 2050

O&M Costs in $/ton: 500 for all years

O&M Costs in $/ton: 500 for all years

Emissions Savings in tons/ton of material: 2.26

Emissions Savings in tons/ton of material: 2.26

Lifetime: 1 year

Lifetime: 1 year

Total Projects: 221 - 355 (2013-2050) and flat

Total Projects: 221 - 710 (2013-2050) and flat

after 2050

after 2050

O&M Costs in $/project: 3.2 M for all years

O&M Costs in $/project: 3.2 M for all years

Revenues in $/project: 5.3 M for all years

Revenues in $/project: 5.3 M for all years

Emissions Savings in tons/project: 1908

Emissions Savings in tons/project: 1908

Lifetime: 10 years

Lifetime: 10 years

Extensive to Intensive Agriculture

Total hectares (ha): 0 – 4.67 M (2013-2050) and

Total hectares (ha): 0 – 9.34 M (2013-2050) and

Processes

flat after 2050

flat after 2050

CAPEX Costs in $/ha: 45.83 for all years

CAPEX Costs in $/ha: 45.83 for all years

O&M Costs in $/ha: 6.88 for all years

O&M Costs in $/ha: 6.88 for all years

Revenues in $/ha: 33.89 for all years

Revenues in $/ha: 33.89 for all years

Emissions Savings in tons/ha: 0.25

Emissions Savings in tons/ha: 0.25

Lifetime: 10 years

Lifetime: 10 years

Nitrification Inhibitors in Corn

Total tons/yr: 0 – 5020 (2019-2050) and flat

Total tons/yr: 0 – 10040 (2019-2050) and flat

Production

after 2050

after 2050

O&M Costs in $/ton: 21,375 for all years

O&M Costs in $/ton: 21,375 for all years

Zeolites in Cattle Ration

Sunflower Seeds in Cattle Ration

Crop Rotation

55

Erosion Prevention Measures

Preservation of Degraded Lands

Wetlands Renewal

Straw Combustion

Organic Farming

Revenues in $/ton: 141,052 for all years

Revenues in $/ton: 141,052 for all years

Emissions Savings in tons/ton of material: 115

Emissions Savings in tons/ton of material: 115

Lifetime: 30 year

Lifetime: 30 year

Total hectares (ha): 0 – 2.69 M (2013-2050) and

Total hectares (ha): 0 – 5.37 M (2013-2050) and

flat after 2050

flat after 2050

CAPEX Costs in $/ha: 1000 for all years

CAPEX Costs in $/ha: 1000 for all years

Revenues in $/ha: 285.95 for all years

Revenues in $/ha: 285.95 for all years

Emissions Savings in tons/ha: 0.13

Emissions Savings in tons/ha: 0.13

Lifetime: 15 years

Lifetime: 15 years

Total hectares (ha): 0 – 275,000 (2013-2050)

Total hectares (ha): 0 – 550,000 (2013-2050)

and flat after 2050

and flat after 2050

CAPEX Costs in $/ha: 1000 for all years

CAPEX Costs in $/ha: 1000 for all years

Revenues in $/ha: 26.76 for all years

Revenues in $/ha: 26.76 for all years

Emissions Savings in tons/ha: 0.50

Emissions Savings in tons/ha: 0.50

Lifetime: 20 years

Lifetime: 20 years

Total hectares (ha): 0 – 148,730 (2013-2050)

Total hectares (ha): 0 – 297,460 (2013-2050)

and flat after 2050

and flat after 2050

CAPEX Costs in $/ha: 100 for all years

CAPEX Costs in $/ha: 100 for all years

Emissions Savings in tons/ha: 3.9

Emissions Savings in tons/ha: 3.9

Lifetime: 37 years

Lifetime: 37 years

Installed in MW: 0 – 4425 (2020-2050) and flat

Installed in MW: 0 – 8850 (2020-2050) and flat

after 2050

after 2050

Capacity Factor : 72% electric, 90% thermal

Capacity Factor : 72% electric, 90% thermal

across all years

across all years

Capital Costs in $/kW: 3625 across all years

Capital Costs in $/kW: 3625 across all years

O&M Costs in $/kW: 540 across all years

O&M Costs in $/kW: 540 across all years

Revenues Costs in $/kWh: Assumed grid electric

Revenues Costs in $/kWh: Assumed grid electric

and natural gas rates (wholesale, unsubsidized)

and natural gas rates (wholesale, unsubsidized)

Emissions Savings in tons/MW: 0.073

Emissions Savings in tons/MW: 0.073

Lifetime: 20 years

Lifetime: 20 years

Total Projects: 19.9 - 160 (2013-2050) and flat

Total Projects: 40 - 320 (2013-2050) and flat

56

LULUCF – Organic Fertilizer Use

LULUCF – No Till Techniques

LULUCF – Afforestation

after 2050

after 2050

Capital Costs in $/project: 109,375 for all years

Capital Costs in $/project: 109,375 for all years

O&M Costs in $/project: 1.35 M for all years

O&M Costs in $/project: 1.35 M for all years

Revenues in $/project: 5.04 M for all years

Revenues in $/project: 5.04 M for all years

Emissions Savings in tons/project: 3144

Emissions Savings in tons/project: 3144

Lifetime: 10 years

Lifetime: 10 years

Total hectares (ha): 0 – 15.2 M (2013-2050) and

Total hectares (ha): 0 – 15.2 M (2013-2020) and

flat after 2050

flat after 2020

Capital Costs in $/ha: 6 for all years

Capital Costs in $/ha: 6 for all years

O&M Costs in $/ha: 87 for all years

O&M Costs in $/ha: 87 for all years

Emissions Savings in tons/ha: 2.1

Emissions Savings in tons/ha: 2.1

Lifetime: 10 years

Lifetime: 10 years

Total hectares (ha): 0 – 160,000 (2013-2050)

Total hectares (ha): 0 – 320,000 (2013-2050)

and flat after 2050

and flat after 2050

Capital Costs in $/ha: 600 for all years

Capital Costs in $/ha: 600 for all years

O&M Costs in $/ha: 375 for all years

O&M Costs in $/ha: 375 for all years

Emissions Savings in tons/ha: 71.4

Emissions Savings in tons/ha: 71.4

Lifetime: 10 years

Lifetime: 10 years

Total hectares (ha): 0 – 329,000 (2013-2050)

Total hectares (ha): 0 – 658,000 (2013-2050)

and flat after 2050

and flat after 2050

Capital Costs in $/ha: 658 for all years

Capital Costs in $/ha: 658 for all years

O&M Costs in $/ha: 156 for all years

O&M Costs in $/ha: 156 for all years

Emissions Savings in tons/ha: 1.56

Emissions Savings in tons/ha: 1.56

Lifetime: 10 years

Lifetime: 10 years

Based on these inputs into the MACTool, the MACC for the sector has been illustrated in Figure 15.

57

Figure 15. MACC for Mitigation Actions in Land Use The MAC values and associated emissions reduction estimates for the sector have been summarized in Appendix A8. In the case of animal farming both cattle and swine waste driven biogas plant were estimated to have MAC Values under $15/ton. Among cattle feed improvement solutions supplementing with ionophores was estimated at a MAC value of $0/ton with zeolites estimated at $19/ton. Cattle reduction in this category is estimated to have the greatest emission reduction potential of 100 M tons cumulative from 2014-2054 with a MAC value estimate of $5/ton. Concentrated fodder and sunflower seed supplementing appear expensive with estimated MAC values >$100/ton.

In terms of farming techniques for crop production no till techniques and organic fertilizers appear most promising with estimated MAC values at $1/ton and $15/ton. These techniques also have some of the highest emission reduction potentials reported at cumulative values of 239 M tons and 301 M tons for no till and organic fertilizers respectively from 2014-2054. The numbers estimated for MAC values and emissions reductions in this study can be strengthened further by conducting a thorough investigation of animal farming and crop production inventory whereby a farm by farm assessment is made to understand which techniques might be truly applicable and which may have been already deployed. This exercise will also help in strengthening the estimates of costs, revenues and emissions benefits.

4.9 TRANSPORT ASSUMPTIONS & RESULTS Table 1 summarizes the key assumptions for the transport mitigation actions identified earlier.

Table 22 : Key Assumptions for Mitigation Actions in Power Conservation Action

Key Assumptions (Base Case)

Key Assumptions (Low Carbon Case)

Gas Pipeline Modernization

Total pipeline upgraded in km: 0 â&#x20AC;&#x201C; 38,550

Total pipeline upgraded in km: 0 â&#x20AC;&#x201C; 38,550

(2013-2050) and flat after 2050

(2013-2030) and flat after 2050

58

Capital Costs in million UAH/km: 25.99 for all

Capital Costs in million UAH/km: 25.99 for all

years

years

Energy Savings in million cubic meter/km: 4.9E-

Energy Savings in million cubic meter/km: 4.9E-

3 (as natural gas)

3

Emissions Savings in tons/km: 68.7

Emissions Savings in tons/km: 68.7

Lifetime: 50 years

Lifetime: 50 years

Gas Transport Modernization –

Total upgraded MW: 0 – 675 (2013-2050) and

Total upgraded MW: 0 – 675 (2013-2030) and

Compressor Stations Upgrade + Pipeline

flat after 2050

flat after 2050

Capacity Factor : 100% across all years (backup

Capacity Factor : 100% across all years (backup

always exists)

always exists)

Capital Costs in $/kW: 1484 across all years

Capital Costs in $/kW: 1484 across all years

Electricity Savings %: 20% across all years

Electricity Savings %: 20% across all years

Revenues Costs in $/kWh: Assumed grid electric

Revenues Costs in $/kWh: Assumed grid electric

rates (wholesale, unsubsidized)

rates (wholesale, unsubsidized)

Emissions Savings in tons/MW: ~115

Emissions Savings in tons/MW: ~115

Lifetime: 50 years

Lifetime: 50 years

Total installed MW: 0 – 470 (2013-2050) and

Total installed MW: 0 – 470 (2013-2030) and

flat after 2050

flat after 2030

Capacity Factor : 40% across all years (backup

Capacity Factor : 40% across all years (backup

always exists)

always exists)

Capital Costs in $/kW: 1450 across all years

Capital Costs in $/kW: 1450 across all years

Operating Costs in $/kWh: 0.003 across all years

Operating Costs in $/kWh: 0.003 across all years

Revenues Costs in $/kWh: Assumed grid electric

Revenues Costs in $/kWh: Assumed grid electric

rates (wholesale, unsubsidized)

rates (wholesale, unsubsidized)

Emissions Savings in tons/MWh: 0.42 (grid

Emissions Savings in tons/MWh: 0.42 (grid

average)

average)

Lifetime: 20 years

Lifetime: 20 years

Vehicle Energy Efficiency – Buses, High

Total mileage km buses: 2.21 B – 4.97 B (2013-

Total mileage km buses: 2.21 B – 4.97 B (2013-

Density Vehicles (HDV, e.g. vans) and

2054)

2054)

Total mileage km HDV: 6.01 B – 1.35 B (2013-

Total mileage km HDV: 6.01 B – 1.35 B (2013-

2054)

2054)

Total mileage km LDV: 115 B – 260 B (2013-

Total mileage km LDV: 115 B – 260 B (2013-

(added from above)

NG Pressure Reduction

Low Density Vehicles (LDV, e.g. cars)

59

Biofuels

2054)

2054)

Vehciles per km: 1.13E-4 (buses), 2.08E-4 (HDV),

Vehciles per km: 1.13E-4 (buses), 2.08E-4 (HDV),

5.99 E-5 (LDV) across all years

5.99 E-5 (LDV) across all years

Fuel Mix buses: 18.5% Gasoline, 81.5% Diesel,

Fuel Mix buses: 18.5% Gasoline, 81.5% Diesel,

0% LPG all years

0% LPG all years

Fuel Mix HDV: 28% Gasoline, 72% Diesel, 0%

Fuel Mix HDV: 28% Gasoline, 72% Diesel, 0%

LPG all years

LPG all years

Fuel Mix LDV: 58.7% Gasoline, 31.8% Diesel,

Fuel Mix LDV: 58.7% Gasoline, 31.8% Diesel,

9.5% LPG all years

9.5% LPG all years

Market Penetration High Efficiency Vehicles:

Market Penetration High Efficiency Vehicles:

2.7% - 100% (2013-2050) and flat after 2050

5.88% - 100% (2013-2030) and flat after 2030

(across all fleets and fuel types)

(across all fleets and fuel types)

Capital Costs in $/vehicle: 120,000 (buses),

Capital Costs in $/vehicle: 120,000 (buses),

60,000 (HDV), 30,000 (LDV) across all years

60,000 (HDV), 30,000 (LDV) across all years

Fuel Savings %: 0.41% - 15% (2013-2050) and

Fuel Savings %: 0.81% - 30% (2013-2050) and

flat after 2050 (across all fleets and fuel types)

flat after 2050 (across all fleets and fuel types)

Revenues in $/ton: Used general liquid fuel

Revenues in $/ton: Used general liquid fuel

prices (blended average)

prices (blended average)

Emissions Footprint in g CO2/Litre fuel: 2249

Emissions Footprint in g CO2/Litre fuel: 2249

(gasoline), 2606 (diesel), 1551 (LPG)

(gasoline), 2606 (diesel), 1551 (LPG)

Lifetime: 10 years (for all vehicles and fuel

Lifetime: 10 years (for all vehicles and fuel

types)

types)

Gasoline Demand in million tons: 4 – 16.05

Gasoline Demand in million tons: 4 – 16.05

(2013-2050) and flat after 2050

(2013-2050) and flat after 2050

Diesel Demand in million tons: 5.3 – 27.95

Diesel Demand in million tons: 5.3 – 27.95

(2013-2050) and flat after 2050

(2013-2050) and flat after 2050

Market Penetration Bioethanol : 5% - 10%

Market Penetration Bioethanol : 5% - 20%

(2013-2050) and flat after 2050 (replaces

(2013-2050) and flat after 2050 (replaces

gasoline)

gasoline)

Market Penetration Biodiesel : 0% - 10% (2013-

Market Penetration Biodiesel : 0% - 20% (2013-

2050) and flat after 2050 (replaces diesel)

2050) and flat after 2050 (replaces diesel)

Capital Costs in UAH/mln tons: 7 across all years

Capital Costs in UAH/mln tons: 7 across all years

for both fuels

for both fuels

Revenues in $/ton: Used general liquid fuel

Revenues Costs in $/ton: Used general liquid

60

City Transport Electrification

Railway Electrification

prices (blended average)

fuel prices (blended average)

Emissions Savings in tons/million ton fuel: 1.99

Emissions Savings in tons/million ton fuel: 1.99

M

M

Lifetime: 25 years

Lifetime: 25 years

Total Passenger billion km: 61.2 â&#x20AC;&#x201C; 92 (2013-

Total Passenger billion km: 61.2 â&#x20AC;&#x201C; 92 (2013-

2050) and flat after 2050

2050) and flat after 2050

Market Penetration Trolley Buses : 13% - 21%

Market Penetration Trolley Buses : 13% - 30%

(2013-2050) and flat after 2050 (replaces diesel

(2013-2050) and flat after 2050 (replaces diesel

buses)

buses)

Market Penetration Trams : 8% - 12% (2013-

Market Penetration Trams : 8% - 15% (2013-

2050) and flat after 2050 (replaces diesel buses)

2050) and flat after 2050 (replaces diesel buses)

Capital Costs in Trolleys million UAH/passenger

Capital Costs in Trolleys million UAH/passenger

km: 12.89 across all years

km: 12.89 across all years

Capital Costs in Trolleys million UAH/passenger

Capital Costs in Trolleys million UAH/passenger

km: 15.56 across all years

km: 15.56 across all years

Electricity Consumed in Trolleys kWh/passenger

Electricity Consumed in Trolleys kWh/passenger

km: 0.048 across all years (for OPEX)

km: 0.048 across all years (for OPEX)

Electricity Consumed in Trams kWh/passenger

Electricity Consumed in Trams kWh/passenger

km: 0.053 across all years (for OPEX)

km: 0.053 across all years (for OPEX)

Diesel Consumed in kg/passenger km: 0.085 (for

Diesel Consumed in kg/passenger km: 0.085 (for

savings calculation)

savings calculation)

O&M Costs in $/kWh: Assumed grid electric

O&M Costs in $/kWh: Assumed grid electric

rates (wholesale, unsubsidized)

rates (wholesale, unsubsidized)

Revenues in $/ton: Used general liquid fuel

Revenues in $/ton: Used general liquid fuel

prices (blended average)

prices (blended average)

Emissions Savings in tons/MWh: 0.0032

Emissions Savings in tons/MWh: 0.0032

Lifetime: 30 years

Lifetime: 30 years

Total line to be upgraded in km: 21619 all years

Total line to be upgraded in km: 21619 all years

Market Penetration Bioethanol : 47% - 60%

Market Penetration Bioethanol : 47% - 60%

(2013-2050) and flat after 2050

(2013-2050) and flat after 2050

Capital Costs in million UAH/km: 1.39 for all

Capital Costs in million UAH/km: 1.39 for all

years

years

O&M Costs in MWh/km: 58.67 for all years

O&M Costs in MWh/km: 58.67 for all years

61

Energy Savings in tons/km: 29.30 (as diesel fuel)

Energy Savings in tons/km: 29.30 (as diesel fuel)

O&M Costs in $/kWh: Assumed grid electric

O&M Costs in $/kWh: Assumed grid electric

rates (wholesale, unsubsidized)

rates (wholesale, unsubsidized)

Revenues in $/ton: Used general liquid fuel

Revenues in $/ton: Used general liquid fuel

prices (blended average)

prices (blended average)

Emissions Savings in tons/km: 67.63

Emissions Savings in tons/km: 67.63

Lifetime: 40 years

Lifetime: 40 years

Based on these inputs into the MACTool, the MACC for the sector has been illustrated in Figure 16.

62

Figure 16. MACC for Mitigation Actions in Transport

The MAC values and associated emissions reduction estimates for the sector have been summarized in Appendix A9. Other than natural gas energy recovery In general, none of the actions considered under the transport sector appears to have viable economics. Even this measure has a fairly low emissions reduction potential of 6 M tons cumulative from 2014-2054. In terms of vehicular transport, the lowest MAC value was estimated for railway electrification at $30/ton but it also had an estimated emissions reduction potential of 6 M tons cumulative from 2014-2054. Biofuels and vehicle energy efficiency appear to have the greatest estimated reductions potential at 133 M tons and 188 M tons cumulative respectively from 2014-2054 but the MAC values for these are in the triple digits (in the $100s/ton range). This is somewhat expected because the technologies in both these action areas are still maturing, offering considerable room for cost reduction and efficiency improvements (that should improve the overall economics). Furthermore, both these actions will benefit if forecasted liquid fuel prices rise higher than expect. Based on the data gathered to date for many of the vehicular actions considered in this study, it would be prudent to conduct more detailed studies for these actions to strengthen the estimates and deploy actions as technologies become more viable.

63

5 LIMITATIONS OF CURRENT ANALYSIS There are some discrepancies in absolute MAC numbers and trends with previously conducted work by NERA and BNEF and it is likely that these are driven by differences in assumptions in terms of energy prices, capital and operating costs, discount factors etc. that often distinguish MACC from an economic and investor perspective.

There are several barriers that proved challenging for completing this analysis. Most of these barriers relate to the availability of Ukraine specific data across the 78 measures, especially over a 41 year period where forecasting is complex. Wherever possible, the TRPC team and local experts have identified the best possible local data and used accepted and up-to-date materials â&#x20AC;&#x201C; such as the Energy Strategy of Ukraine for the period up to 2030 (current draft version); the National Inventory Report of Anthropogenic Emissions by Sources and Removals by Sinks of Greenhouse Gases in Ukraine for 1990â&#x2C6;&#x2019;2010; the Transport and Communication document of Ukraine 2011 (statistical yearbook); project PDDs; and documents from nationally respected organizations such as the National Institute for Strategic Studies (NISS). However, in many cases there is a shortage of detailed engineering studies that can be directly referenced for each measure that actually includes the drivers around the various assumptions. Another major barrier in the project was the fact that a majority of the data when available was spread across multiple sources and as such assuring consistency across various sources was challenging.

As is to be expected, the analysis that can be performed at this time is dependent on the accuracy of several additional general variables such as the 41 year forecasts for energy costs, emissions factors, exchange rates and discount factors that all are highly dependent on Ukrainian and global macroeconomic performance over that time period. Additionally restrictions arise from the broader assumptions made on how technical parameters such as system efficiencies, lifetimes etc. and economic parameters such as capital and operating costs vary for each measure. This is because many of these factors can vary significantly over a 41 year period due to changes in technology and the underlying resources utilized in development and deployment (e.g. labour, commodities, research and development spend etc.). A limitation in a lot of the data gathered for this study is the lack of good information on projected learning curves for each action. These learning curves can impact costs and improve performance which ultimately makes the economics more favourable. Similarly, the emissions benefits for several technologies have been qualified in a generic form (e.g. tons CO2 per ton of iron). Improved numbers must be collected through a facility level build up to allow for better population of the emissions data within the tool and to produce meaningful wedge graphs across sectors. Several of the measures (especially energy efficiency related) require estimation of market penetration of new measures, accounting and retirement of older inventory etc.

These have been addressed to the extent possible at this stage and the data can be continually improved, based on further study, in order to refine the associated marginal abatement costs. Finally, costs and other parameters that impact these underlying costs are impacted by inflation and often times, labour and material inflation indices vary across industries. These will need to be adequately estimated in future iterations to further strengthen MAC estimates across sectors.

We provide recommendations in the next chapter on how some the limitations in the data and analysis can be addressed in the future.

64

6 CONCLUSIONS AND RECOMMENDATIONS 6.1 CONCLUSIONS The results from the analysis conducted in the MACTool indicates that there are 40 actions with marginal cost values of $20/ton or under that can provide cumulative reductions of ~3900 million tons CO2e from 2014-2054.

This corresponds to annual reductions of ~98 million tons which is ~25% of the 390 million tons/yr reported by Ukraine for UNFCCC in 2011. A summary of these actions by sector have been summarized in Table 23.

Table 23. List of Promising Mitigation Actions by Sector Sector

Actions

MAC Value ($/ton)

Emissions

Reduction

Cumulative 2014-2054 years (millions tons CO2e) Power Generation

Power Conservation

Fossil Fuel

Manufacturing/Industry

PumpedStorage

-47

46

LargeHydro

-41

79

GeothermalPower

-13

154

SmallHydro

-9

13

NaturalGasCCGT

-7

1227

CoalUSPC

-5

143

BiomassPower

-1

56

WindPower

0

137

Nuclear

0

0

CoalUSPC+CCS

1

278

PowerTransmission

-29

80

SmartGrid

-11

9

EELamps

7

4

CoalVAM

2

52

Coalmine Methane

2

61

IronOreEE

1

46

ContinuousSteelRoll

2

158

AmmoniaEE

3

17

EAFSteel

4

114

65

Waste Management

Buildings

Land Use

Transport

CementDry

5

24

PaperEE

8

1

Composting

1

3

BiodegradablePack

2

160

LFGPower

3

38

SegrCollUtil

11

57

ModernMatlRecyc

12

2

ReplaceObsFacilities

12

4

DraughtProofing

6

91

WallInsulation

16

57

WaterEE

18

64

AgrIonophores

0

13

WetlandsRenew

0

13

LULUCF-noTill

1

239

AgriBiomassCattle

5

100

ExtensiveIntensiveAgr

9

27

AgriBiomassSwine

13

24

LULUCF-Organic

15

301

AgrZeolites

19

18

ReductionCows

19

8

NGLinePresReduc

-366

6

It is possible that the viability of these actions or others that did not meet the <$20/ton threshold can change based on a variety of factors such as technology improvements and cost reductions.

66

6.2 RECOMMENDATIONS The recommendations for future work as it relates to this study focuses primarily on how to improve the underlying data used to develop 41 year forecasts across sectors. These include: ď&#x201A;ˇ

ď&#x201A;ˇ

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Developing industry wide surveys across sectors that provide further granularity on installed capacities, costs, technology trends etc. These surveys can also information on the practicality of implementing actions in that industry. For example, in the case of energy efficiency in the iron ore industry, a detailed studied of each facility in Ukraine should provide data on current emissions, mitigation actions that have been implemented and what could be implemented. This will in turn enable the creation of facility level cost estimates for implementable actions as well as timelines for implementation. In the case of equipment replacement such as boilers, this survey should collect data on existing inventory and capital/operating costs for the inventory and its replacement rates. Effective surveys also reveal actions that have not been considered and it is this type of information that is also required to look at specific actions and their viability from an investor perspective. Consequently, the importance of establishing more rigor in collecting and analyzing the underlying data that forms the basis of MAC value estimates cannot be understated.

Forecasts for global variables such as electric prices, fossil fuel prices etc. must be developed for a 41 year period through related macroeconomic models. There needs to be an established interconnectivity between the macroeconomic models and scenarios developed for the MACTool i.e. the base case and low carbon case must be accurately reflected because inputs and outputs are independent. For example, increased deployment of clean energy solutions will reduce grid emission factors but depending on how expensive these solutions are, they can increase the cost of electricity delivered. Increasingly computable general equilibrium (CGE) models are being used to be used in conjunction with a MACTool to properly map the macroeconomic impacts of implementing specific actions. Ukraine might explore how these toolsets could be better connected.

The Ukranian team that inherits the tool and the underlying data should periodically visit underlying assumptions and update the data in the tool on an ongoing basis. It is recommended that sector teams be established to ensure that data is kept up to date. The workshop training that TRPC is providing should therefore be seen as the first step in establishing the critical human capital required to keep the tool operational.

67

APPENDIX A1: POWER GENERATION ACTIONS RESULTS (2014-2030) Action

MAC Value in $/ton

Emissions Reduction (2014-2054) in millions tons CO2e

Large Solar PV

48

21

Residential Solar PV

37

10

Wind

0

137

Large Hydro

-41

79

Small Hydro

-9

13

Biomass Power

-1

56

Geothermal Power

-13

154

Pumped Storage Hydro

-47

46

Coal Fired Ultra Super Critical Plants

-5

143

-7

1227

1

278

N/A

N/A

(USPC) Natural Gas Combined Cycle Plants (NGCC) Carbon Capture and Sequestration with USPC Plants Nuclear

Note: Nuclear is not available because there is no difference anticipated between base case and low carbon case (i.e. projects in plan will be executed in either case)

68

APPENDIX A2: POWER GENERATION ACTIONS RESULTS (2014-2054) Action

MAC Value in $/ton

Emissions Reduction (2014-2054) in millions tons CO2e

Large Solar PV

48

21

Residential Solar PV

37

10

Wind

0

137

Large Hydro

-41

79

Small Hydro

-9

13

Biomass Power

-1

56

Geothermal Power

-13

154

Pumped Storage Hydro

-47

46

Coal Fired Ultra Super Critical Plants

-5

143

-7

1227

1

278

N/A

N/A

(USPC) Natural Gas Combined Cycle Plants (NGCC) Carbon Capture and Sequestration with USPC Plants Nuclear

Note: Nuclear is not available because there is no difference anticipated between base case and low carbon case (i.e. projects in plan will be executed in either case)

69

APPENDIX A3: POWER CONSERVATION ACTIONS RESULTS (2014-2054) Action

MAC Value in $/ton

Emissions Reduction (2014-2054) in millions tons CO2e

Energy Efficient Lighting

-38

4

Energy Efficient Refrigerators

50

15

Energy Efficient Washer/Dryers

210

5

Energy Efficient Microwaves

2065

0

Energy Efficient Televisions

27276

0

Power Transmission Upgrade

-29

80

Smart Grid

-11

9

70

APPENDIX A4: FOSSIL FUEL ACTIONS RESULTS (2014-2054) Action

MAC Value in $/ton

Emissions Reduction (2014-2054) in millions tons CO2e

Coal Mine Methane – Ventilation Air

2

52

2

61

740

32

Machine (VAM) Coal Mine Methane – Combined Heat and Power (CHP) Coal Mining Energy Efficiency

71

APPENDIX A5: MANUFACTURING ACTIONS RESULTS (20142054) Action

MAC Value in $/ton

Emissions Reduction (2014-2054) in millions tons CO2e

Aluminum Scrap Recycling

40

37

Ammonia Energy Efficiency

3

17

Ammonia Electrolysis

58

76

Dry Cement Process

5

24

Wet Cement Process (Slag)

153

93

Shale Gas in Cement

65

19

Direct Reduction Iron

24

309

Iron Ore Production Energy Efficiency

1

46

Steel Rolling/Casting Energy Efficiency

26

10

Steel Continuous Rolling

2

158

Steel Electric Arc Furnace (EAF)

4

114

Lime Production Energy Efficiency

122

5

Paper Production Energy Efficiency

8

1

(Boiler Replacement)

72

APPENDIX A6: WASTE MANAGEMENT ACTION RESULTS (2014-2054) Action

MAC Value in $/ton

Emissions Reduction (2014-2054) in millions tons CO2e

Landfill Gas Power (LFG)

3

38

Clean Municipal Solid Waste Power

45

6

Waste Water Utilization for Power

29

18

Segregate Colloids Utilization for Power

11

57

12

4

Composting

1

3

Biodegradable Plastics

2

160

Increased Recycling

68

24

Modern Materials Recycling

12

2

Waste Production Limits

215

215

(MSW)

(Food Waste Biogas) Replace Obsolete Municipal Waste Facilities (Pumping Systems)

73

APPENDIX A7: BUILDINGS ACTION RESULTS (2014-2054) Action

MAC Value in $/ton

Emissions Reduction (2014-2054) in millions tons CO2e

Draught Proofing

6

91

Wall Insulation

16

57

Windows Energy Efficiency

33

31

Boiler Upgrades

11

84

Heat Pumps

294

24

Heat Network Optimization

35

66

Heat Network Boiler Upgrade

420

14

Water Energy Efficiency

18

64

74

APPENDIX A8: LAND USE ACTION RESULTS (2014-2054) Action

MAC Value in $/ton

Emissions Reduction (2014-2054) in millions tons CO2e

Biogas Plants - Cattle

5

100

Biogas Plants - Swine

13

24

Concentrated Fodder - Cattle

143

2

Reduction of Cows – Increased Milk

19

8

Ionophores in Cattle Ration

0

13

Zeolites in Cattle Ration

19

18

Sunflower Seeds in Cattle Ration

304

31

Crop Rotation

271

16

9

27

25

12

Erosion Prevention Measures

156

9

Preservation of Degraded Lands

36

3

Wetlands Renewal

0

13

Straw Combustion

304

31

Organic Farming

81

14

LULUCF – Organic Fertilizer Use

15

301

LULUCF – No Till Techniques

1

239

LULUCF - Afforestation

35

15

Production

Extensive to Intensive Agriculture Processes Nitrification Inhibitors in Corn Production

75

APPENDIX A8: TRANSPORT ACTION RESULTS (2014-2054) Action

MAC Value in $/ton

Emissions Reduction (2014-2054) in millions tons CO2e

Gas Pipeline Modernization

1078

25

Gas Transport Modernization

687

43

NG Pressure Reduction

-366

6

Vehicle Energy Efficiency

921

188

Biofuels

199

133

City Transport Electrification

8230

0

34

6

Railway Electrification

76