Technical Appendix 2019 Abatement Cost Curve Model Local ...... · Eunomia Research & Consulting has taken due care in the preparation of this report to ... V0.4 18/11/19 Ann Ballinger

Local Authority Marginal Abatement Cost Curve Model Technical Appendix 2019

Tanguy TomesOlly JamiesonKathryn Firth

11th December 2019

Report for London Borough of Hounslow

Prepared by Tanguy Tomes

Approved by

………………………………………………….

Alex Massie

(Project Director)

Eunomia Research & Consulting Ltd37 Queen SquareBristolBS1 4QS

United Kingdom

Tel: +44 (0)117 9172250Fax: +44 (0)8717 142942

Web: www.eunomia.co.uk

Disclaimer

Eunomia Research & Consulting has taken due care in the preparation of this report to ensure that all facts and analysis presented are as accurate as possible within the scope of the project. However, no guarantee is provided in respect of the information presented, and Eunomia Research & Consulting is not responsible for decisions or actions taken on the basis of the content of this report.

http://www.eunomia.co.uk/

Version Control Table

Version Date Author Description

V0.1 05/11/19 Tanguy Tomes First draft (internal)

V0.2 15/11/2019 Dominique Sandy

Internal QA

V0.3 16/11/19 Tanguy Tomes Amendments

V0.4 18/11/19 Ann Ballinger Internal QA

V0.5 19/11/19 Tanguy Tomes Amendments

V0.6 19/11/19 Tanguy Tomes Draft final

V0.7 11/12/2019 Kathryn Firth Incorporating client comments

V0.8 16/12/2019 Kathryn Firth Incorporating client comments relating to social housing numbers

Contents

A.1.0 MACC Model .....................................................................................................6

A.1.1Modelling Approach ................................................................................................6

A.1.2Emissions Baselines .................................................................................................9

A.1.3General Assumptions.............................................................................................10

A.1.4Process Assumptions .............................................................................................14

A.1.4.1 Buildings: Current Processes ..........................................................................14

A.1.4.2 Buildings: Future Processes............................................................................17

A.1.4.3 Energy: Current Processes..............................................................................23

A.1.4.4 Energy: Future Processes ...............................................................................26

A.1.4.5 Land Use: Current Processes ..........................................................................29

A.1.4.6 Land Use: Future Processes............................................................................31

A.1.4.7 Transport: Current Processes .........................................................................34

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A.1.4.8 Transport: Future Processes ..........................................................................36

A.1.4.9 Waste: Current Processes ..............................................................................41

A.1.4.10 Waste: Future Processes .........................................................................43

A.1.4.11 Assumption Limitations...........................................................................45

A.1.5Measure Constructions..........................................................................................47

A.2.0 MACC Results ..................................................................................................49

A.3.0 Acronyms and Units.........................................................................................54

MACC TECHNICAL APPENDIX 5

APPENDICES

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A.1.0 MACC ModelThis appendix will describe the workings underpinning the Marginal Abatement Cost Curves (MACCs) which have been generated for the London Borough of Hounslow (Hounslow) in the course of this project.

The appendix is split into five sections:

Appendix A.1.1: describing this project’s modelling approach, including notes on methodology and scoping;

Appendix A.1.2: describing this project’s emissions baselines; Appendix A.1.3: detailing general assumptions including utility impacts and costs; Appendix A.1.4: detailing assumptions for each process; and Appendix A.1.5: detailing how measures have been constructed out of processes.

MACC results are displayed in full in Appendix A.2.0, whilst a list of acronyms and units can be found in Appendix A.3.0.

A.1.1 Modelling ApproachThis section describes the premise of MACC models in general, scoping the decisions specific to this project, and some limitations of the analysis.

General MACC Briefing

The MACC model is a tool which allows organisations to progress towards net-zero in a politically and economically efficient manner. This is achieved by ranking a range of greenhouse gas (GHG)-abating measures in order of cost-effectiveness, thereby providing the basis for the prioritisation of measures.

The metric of cost-effectiveness is called the marginal abatement cost (MAC). This is calculated, for each measure, from two other values: annualised cost and abatement potential (Figure 1). The lower the MAC, the more cost-effective the measure. The MACC itself is a visually intuitive way of displaying this information.

Figure 1: Derivation of Marginal Abatement Cost

Cost(GBP/yr)

Abatement Potential

(tCO2e/yr)

Marginal Abatement Cost

(GBP/tCO2e)

The MACC tool used in this project is termed a bottom-up MACC. This means that results are driven by detailed technical assumptions for each measure rather than top-down macroeconomic models which have a greater focus on rebound and feedback impacts across the economy.


The modelling relies on the principle that each measure seeks to replace one (current) process with another (future) process. Usually, this will involve the phasing out of a carbon-intensive process in favour of a low-carbon process. As such, a measure can be thought of as a combination of two processes – the net difference between the two describing the impact of the measure. Economically, this is described as the opportunity cost; a similar logic applies to the other calculations. For example, if 1 kWh of electricity generated by a combined cycle gas turbine plant (CCGT; a process) emits 400 grams of carbon dioxide equivalent (gCO2e), but 1 kWh of electricity generated by solar photovoltaics (PV; another process) is zero-carbon, then the net benefit of replacing CCGT with PV (a measure) is 400 gCO2e/kWh.

Project-specific Scoping

This section describes this model’s scope with regards to spheres of influence, emissions accounting, and cost accounting.

Firstly, spheres of influence were derived. A sphere of influence reflects a group of emissions sources over which an organisation has the same level of power to effect changes. For this project, two spheres of influence were agreed upon: direct and local authority. The intention here was to separate

1) the emission sources which the Council has an explicit ability or responsibility to control from

2) the emission sources which sit inside the local authority border but over which the Council has a more constrained ability to influence.

The direct sphere considers emissions relating to the operation of council buildings, council and council contractors’ vehicles, council land, and council housing. It does not, however, consider measures which relate to the decisions of residents of council housing. These, and all other emissions sources, are considered in the local authority-wide scope.

Secondly, it is noted that GHGE accounting can either be done according to a production (or territorial) scope, or a consumption scope. A production scope accounts for all GHGs emitted within a given geographical border. Nationally that will be the overall territory plus any offshore areas over which the country has jurisdiction. For a local authority, the convention follows the authority borders plus (i) emissions from electricity consumed in the authority but generated outside the authority, and (ii) emissions from waste collected in the authority but treated outside the authority. This is the scope upon which national inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC) are based. A consumption scope is different, considering instead the emissions from domestic final consumption plus emissions from the production of its imports. In addition, a conventional life cycle assessment approach was taken which excludes biogenic CO2 from the calculations.

The consumption scope better reflects the true emissions footprint of a local authority’s activities as the accounts are not arbitrarily discontinued at its borders. For the UK as a nation, the difference between the quantity of emissions accounted for within the production and consumption scopes is particularly stark; the consumption scope is

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around 80% bigger than the production scope. However, today, production scope accounting is very much the favoured system. It is easier to calculate and, because it has been favoured in policy development over the years, now has well-established methodologies.

For this project, production-scope emissions were calculated in the central case. However, consumption-scope impacts have also been quantified as a sensitivity for cases of ongoing resource consumption. These cases reflect (the embodied emissions in) investments with a lifetime of less than one year. For example, consumption-level impacts of utility consumption, food consumption, and waste production are included. This allows for Hounslow to take a broader view – more representative of its overall impact – within the constraints of the resource available for this project.

It is openly acknowledged that this compromise does not take into account embodied emissions in materials required to implement some measures e.g. electric vehicles or solar panels. These are harder to account for in MACCs; MACCs present annual emissions savings whereas these can be seen as up-front investments of emissions. Upcoming studies, including those from the University of Leeds and Bristol City Council, may make it possible to refine and improve this analysis in future.

Finally, two scopes with relation to transfer costs were used. In economic analyses which aim to quantify the overall costs of specific activities to society, transfer costs (such as taxes and subsidies) tend to be excluded because they cycle back into governmental fiscal budgets for spending elsewhere. A tax results in costs imposed on businesses or householders, but is a source of revenue to the government body that receives the taxation funds. The net impact of the tax to society is, however, zero. Transfers are therefore not a cost to society as the revenue is being used elsewhere for the benefit of society. In line with this convention, the central case of this work presents results excluding transfer costs.

However, this work also presents a sensitivity including transfer costs. This is because local authority budgets are not directly affected by transfers in the same way as national governments. Thus, costs including transfers were deemed to be of interest to better approximate real-world spend at a local level.

MACC Limitations

Although useful, the MACC approach does not provide complete coverage of every relevant consideration. Areas meriting further refinement and or exploration include:

Consumption-basis GHG impacts – including all embodied emissions in all materials affected by measures,

Co-benefits – many could be quantified and integrated into a more detailed economic analysis,

Synergies and concerns relating to other environmental considerations – including restoration of biodiversity and resilience to a heating climate,

Financing and delivery mechanisms for measures – including a review of best practice, barriers, and opportunities specific to Hounslow’s context; and, following on from that,


Priority areas for lobbying of national government.

Limitations relating to process assumptions are discussed in Appendix A.1.4.11.

A.1.2 Emissions BaselinesThe MACC principally aims to prioritise measures based on the potential scale of abatement and cost-effectiveness. Emissions baselines help to contextualise these abatement figures, enabling estimation of the extent to which each measure can contribute to overall decarbonisation. The data is also used to construct the waterfall graphs. Four emissions baselines are used for this project; they are shown in Table 1-1 and reflect the four scope permutations described in Appendix A.1.1, are used for this project.

Table 0-1: Emissions Baselines (ktCO2e/yr)

Scope Direct Local Authority

Production 47 1,036

Consumption 124 2,718

Local authority-wide production emissions were sourced directly from the most recent UK Government data release, accounting for 2017 emissions.1 For context, residents of Hounslow have average emissions of around 3.8 tCO2e per capita, slightly above the Greater London average of 3.4 tCO2e per capita.

Consumption-level emissions for the local authority were estimated based on Bristol City Council’s method:2 an allocation of national estimates on a per capita basis. International transport emissions were from 2017 accounts; emissions embodied in material imports were from 2016 accounts.3,4

1 Department for Business, Energy and Industrial Strategy (2019) UK local authority and regional carbon dioxide emissions national statistics2 Marvin Rees (2019) Climate Emergency - The Mayor’s Response, Report for Full Council, July 2019, https://democracy.bristol.gov.uk/documents/s34127/Climate%20Emergency%20-%20The%20Mayors%20Response.pdf3 Ricardo Energy & Environment (2019) UK Greenhouse Gas Inventory, 1990 to 2017, Report for Department for Business, Energy and Industrial Strategy, April 20194 Department for Environment, Food and Rural Affairs (2019) UK’s Carbon Footprint 1997 – 2016, April 2019, https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/794557/Consumption_emissions_April19.pdf

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Production-level emissions for the council’s own estate and fleet were estimated by combining four sources. Carbon Reduction Commitment (CRC) literature5 provided an estimate for the footprint of council estate energy consumption, including public buildings such as offices and schools.

An estimate of the footprint of energy consumption in Hounslow’s council housing was added on top. This was derived using UK Government data and data provided by the client relating to housing stock (housing type) and utility consumption.6,7,8 Table 1-2 shows the data and assumptions used for these calculations and their sources.

Table 0-2 Table of assumptions- council housing energy consumption

Assumption/data input Value Source

Total Housing 100,740ONS- Live tables on dwelling stock (including

vacants) 9

Council Housing 15,903 Data provided by client

Electricity

3.8 MWh/household based on 382 GWh domestic electricity sales

across 100,740 total households in Hounslow

BEIS Green book supplementary guidance10

Gas

11.8 MWh/household based on 1,188 GWh domestic gas sales

across 100,740 total households in Hounslow

BEIS Green book supplementary guidance 11

5 GEP Environmental (2018) Annual Audit Report 2017/18, Report for London Borough of Hounslow, June 20186 Ministry of Housing, Communities and Local Government (2019) Live tables on dwelling stock (including vacants)7 Department for Business, Energy and Industrial Strategy (2018) Sub-national gas sales and numbers of customers 2005 - 20178 Department for Business, Energy and Industrial Strategy (2018) Sub-national electricity sales and numbers of customers 2005 - 20179 Ministry of Housing, Communities and Local Government (2019) Live tables on dwelling stock (including vacants)10 Department for Business, Energy & Industrial Strategy (2019) Green Book supplementary guidance: valuation of energy use and greenhouse gas emissions for appraisal, accessed 28 November 2019, https://www.gov.uk/government/publications/valuation-of-energy-use-and-greenhouse-gas-emissions-for-appraisal11 Department for Business, Energy & Industrial Strategy (2019) Green Book supplementary guidance: valuation of energy use and greenhouse gas emissions for appraisal, accessed 28 November 2019,


Carbon intensities

Various values. Please see Table 3 below.

BEIS Green book supplementary guidance, Data tables 1 to 19: supporting the toolkit and

the guidance 12

Emissions from council fleet and employee commuting was calculated on the basis of data provided by Hounslow and regional commuting pattern datasets.13 Data on council waste consumption was requested but was incomplete.

Finally, consumption-level emissions for the council’s direct footprint were estimated by multiplying the production-level figure by 2.62 (2,718 divided by 1,036). It should be emphasised that both direct-scope baselines are very much first-order approximations.

A.1.3 General AssumptionsAssumptions relating to specific processes are detailed in Appendix A.1.4. However, there are also a number of general assumptions which underpin the analysis of all processes. These relate to utilities, economics, and financing.

Utilities

The cost and emissions impact of various utilities - electricity, gas, petrol, diesel, and biogas – are summarised in Table 1-3 and Table 1-4 respectively.

Table 0-3: Utility Cost Assumptions

Cost (GBP/Unit)

Utility Excluding Transfers Including Transfers

Electricity (MWh) 101 156

Gas (MWh) 21 36

Petrol (kilolitre) 436 1,318

Diesel (kilolitre) 475 1,369

https://www.gov.uk/government/publications/valuation-of-energy-use-and-greenhouse-gas-emissions-for-appraisal12 Department for Business, Energy & Industrial Strategy (2019) Green Book supplementary guidance: valuation of energy use and greenhouse gas emissions for appraisal, accessed 28 November 2019, https://www.gov.uk/government/publications/valuation-of-energy-use-and-greenhouse-gas-emissions-for-appraisal13 Department for Transport (2018) Table TSGB0109: Usual method of travel to work by region of workplace

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Cost (GBP/Unit)

Utility Excluding Transfers Including Transfers

Biogas (MWh) 32 57

Note: Uses data for 2025, from average or central case where relevant

Source: Department for Business, Energy and Industrial Strategy (2019) Data tables 1 to 19: supporting the toolkit and the guidance

Costs (including transfers) for electricity, gas, petrol, and diesel were taken from Tables 4, 5, and 8 of the UK Government’s Green Book supplementary guidance.14 Where relevant, central or average figures were used. Where time series were published, figures for 2025 were used.

Long run variable costs from the same supplementary guidance (Tables 9, 10, and 13) were used as a readily-available approximations of utility costs excluding transfers. However, it is acknowledged that long run variable costs exclude transfer costs as well as fixed costs of transmission, distribution, and metering that should be accounted for in the cost scope as defined for this project. Biogas costs were also informed by agricultural research from the United States.15

Table 0-4: Utility Impact Assumptions

Emissions Impact (tCO2e/Unit)

Utility Production Consumption

Electricity (MWh, Average) 0.10 0.12

Electricity (MWh, Marginal) 0.22 0.24

Gas (MWh) 0.18 0.21

Petrol (kilolitre) 2.07 2.14

Diesel (kilolitre) 2.42 2.48

Biogas (MWh) 0.00 0.02

14 Department for Business, Energy and Industrial Strategy (2019) Data tables 1 to 19: supporting the toolkit and the guidance15 Krich, K., Augenstein, D., Batmale, J., Benemann, J., Rutledge, B., and Salour, D. (2005) Chapter 8: Financial Analysis of Biomethane Production, Biomethane from Dairy Waste: A Sourcebook for the Production and Use of Renewable Natural Gas in California (July 2005)


Emissions Impact (tCO2e/Unit)

Utility Production Consumption

Notes Uses data for 2025, from average or central case where relevant

Source: Department for Business, Energy and Industrial Strategy (2019) Data tables 1 to 19: supporting the toolkit and the guidance

Production-level impacts for electricity, gas, petrol, and diesel were taken from Tables 1, 2a, and 2b of the UK Government’s Green Book supplementary guidance.16 Where relevant, central or average figures were used. Where time series were published, figures for 2025 were used.

For electricity, the average impact was used to calculate the impact of electricity consumption in houses or offices, for example. The marginal impact was used to calculate the emissions benefit relating to renewable electricity generation (such as solar PV). This difference is because electricity generation which is displaced by renewables in the grid – electricity which sits ‘at the margin’ – is more carbon-intensive than average generation.

Well-to-tank emissions are consumption-scope emissions associated with extracting, processing, and/or transporting utilities such as gas, petrol, and electricity in the lead up to the point of use. For petrol, well-to-tank emissions include emissions from: oil extraction from wells, processing into petrol, and transport to the petrol station. For petrol, the production-scope impact relates to emissions from fuel combustion.

The additional well-to-tank impacts of utility consumption, which is added to the production-level impacts to derive consumption-level impacts, were taken from the most recent GHG Conversion Factors publication.17 This was also the source of production-level impacts for biogas.

Economics

All costs in the model are given in real terms, based in 2019. Costs sourced from different years were aligned to 2019 using deflators based on Table 56 from a recent Consumer Price Inflation release by the UK Office for National Statistics.18 Costs sourced in different currencies were converted to GBP using European Central Bank data as published by Eurostat.19

16 Department for Business, Energy and Industrial Strategy (2019) Data tables 1 to 19: supporting the toolkit and the guidance17 Department for Business, Energy and Industrial Strategy (2019) UK Government GHG Conversion Factors for Company Reporting18 Office for National Statistics (2019) Consumer Price Inflation Reference Tables19 Eurostat (2019) Exchange rates against the euro, 2008-2018, accessed 7 November 2019, https://ec.europa.eu/eurostat/statistics-

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Adjustments relating to transfer costs used value added tax (VAT) rates of 20% and 5% for commercial and domestic contexts, respectively. Transfers for labour were approximated at 20%.

Financing

Capital costs were annualised using a 4% discount rate for public sector investments and a 10% discount rate for private sector investments. Many costs are particularly sensitive to these borrowing rates and finding ways to optimise access to capital in Hounslow merits further exploration.

explained/index.php?title=File:Exchange_rates_against_the_euro,_2008-2018_(1_EUR_%3D_%E2%80%A6_national_currency)_FP19.png


A.1.4 Process AssumptionsThis section will detail the assumptions underpinning current and future processes as researched for this work. Two processes are required for each measure; and the assembly of these processes to form measures is described in Appendix A.1.5.

For each process, the following assumptions are shown:

Consumption and generation of each utility: electricity, gas / biogas, diesel, petrol; Direct emissions: on a consumption and territorial basis; and Costs: including and excluding transfers.

For future processes only, the following inputs are also required:

Technical potential: the extent to which a future (low-carbon) process can displace current (high-carbon) process, given for each sphere of influence; and

Co-benefits and dis-benefits: a qualitative account of other impacts relevant to the process.

All quantitative data is presented on a ‘per unit’ basis with the relevant unit shown next to the process name in each table.

A.1.4.1 Buildings: Current Processes

The current processes for the building sector relate to:

The scale of a typical household’s energy consumption (data given per household), The impact of a typical household’s domestic space and water heating system (data given per MWh heat consumed), The impact of a typical commercial & industrial (C&I) building’s space and water heating system (data given per MWh heat consumed), and The scale of a typical C&I building’s energy consumption (data given per building).

The direct emissions and utility impact inputs for these processes are described in Table 1-5. Direct emissions figures exclude those relating to utilities. Emissions from utility consumption and generation are separately calculated in the model using the utility emissions impacts shown in Table 0-4 in conjunction with the utility consumption/generation figures shown in Table 1-5. The model adds both of these emissions sources to calculate overall emissions for each process.

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Table 0-5: Buildings: Current Processes: Utility Impact and Direct Emissions

Utility Consumption (per Unit) Utility Generation (per Unit) Direct Emissions (tCO2e/Unit)

Process Name Unit Elec (MWh)

Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre) Consumption Territorial

Typical Household Energy Consumption Hhld 3.79 11.79 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Current Domestic Gas Heating MWh 0.00 1.29 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Baseline C&I Space and Water Heating MWh 0.07 1.13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Typical C&I Building Building 59.12 28.73 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

The cost impact inputs for these processes are described in Table 1-6. These costs exclude the costs relating to utilities. Utility consumption and generation costs are separately calculated in the model using the utility cost inputs shown in Table 0-3 in conjunction with the utility consumption/generation figures shown in Table 0-5. The model adds both of these costs together to calculate the overall cost for each process.

No technical potentials are shown in Table 1-6 as the inputs relate only to future processes; the important thing is the extent to which future (low-carbon) processes can displace current (high-carbon) processes.

Table 0-6: Buildings: Current Processes: Cost and Technical Potential

Cost (GBP/Unit) Technical Potential (Unit)

Process Name Unit Including Transfers Excluding Transfers Direct Local Authority

Typical Household Energy Consumption Hhld 0.0 0.00

Current Domestic Gas Heating MWh 49.47 47.11

Baseline C&I Space and Water Heating MWh 63.86 53.22

Typical C&I Building Building 47,548.67 38,038.94


The split of energy sources used to heat space and water in domestic (incl. private and social housing), industrial, office and retail properties was derived from data published by the Department for Business, Energy & Industrial Strategy (BEIS) and the Office of Gas and Electricity Markets (Ofgem). Costs (including capital, installation and maintenance) and efficiencies of boilers - as well as data on other technologies (including heat pumps) that are used to supply heat to domestic properties - were derived from government-published data, technology manufacturers and installers, and cost comparison websites. Hounslow-specific heat and electricity demand per building were derived from local authority-level data published by BEIS, and costs derived from electricity and gas consumption (Appendix A.1.3). Heat and electricity intensity for Commercial and Industrial (C&I) buildings was also calculated for range of building types; this data was also used to estimate the energy consumption of council buildings.

Key data sources used for this part of the model include:

Ofgem’s Typical Domestic Consumption Values; 20

The National Energy Efficiency Data Framework Consumption Data Tables; 21

The English Housing Survey 2016- 2017; 22 The Building Energy Efficiency Survey 2014-2015;23 Sub-national electricity and gas sales;24,25 2015 Real Estate Environmental Benchmarks;26 and

20 Ofgem (2015) Typical Domestic Consumption Values, accessed 3 September 2019, https://www.ofgem.gov.uk/gas/retail-market/monitoring-data-and-statistics/typical-domestic-consumption-values21 National Energy Efficiency Data-Framework (NEED): consumption data tables 2019, accessed 4 September 2019, https://www.gov.uk/government/statistics/national-energy-efficiency-data-framework-need-consumption-data-tables-201922 Ministry of Housing, Communities & Local Government (2018) English Housing Survey 2016 to 2017: headline report, accessed 4 October 2019, https://www.gov.uk/government/statistics/english-housing-survey-2016-to-2017-headline-report23 Department of Business, Energy and Industrial Strategy (2016) Building Energy Efficiency Survey 2014 - 2015: Overarching Report24 Department for Business, Energy and Industrial Strategy (2018) Sub-national electricity sales and numbers of customers 2005 - 201725 Department for Business, Energy and Industrial Strategy (2018) Regional and local authority gas consumption statistics: 2005 to 201726 Better Buildings Partnership (2016) 2015 Real Estate Environmental Benchmarks, accessed 12 November 2019, http://www.betterbuildingspartnership.co.uk/sites/default/files/media/attachment/REEB%20Benchmarks%202015%20-%20Final.pdf

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various cost-comparison sites and consumer guides such as The Heating Hub27 and Energy Savings Trust.28

A.1.4.2 Buildings: Future Processes

The future processes for the building sector relate to:

The scale of a household’s energy consumption following a comprehensive retrofit (data given per household), The scale of a household’s energy consumption following an effective behaviour change campaign (data given per household), The scale of a household’s energy consumption if energy-efficient and repairable domestic appliances are used (data given per household), The scale of a new Passivhaus-standard household’s energy consumption (data given per household), The impact of a household’s domestic space and water heating system if using an air-source heat pump (data given per MWh heat consumed), The impact of a household’s domestic space and water heating system if using a solar system (data given per MWh heat consumed), The impact of a typical C&I building’s space and water heating system if using an air-source heat pump (data given per MWh consumed), The impact of a typical C&I building’s space and water heating system if using a solar system (data given per MWh consumed), and The scale of a new Passivhaus-standard C&I building’s energy consumption (data given per building).


Table 0-7: Buildings: Future Processes: Utility Impact and Direct Emissions



Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


27 The Heating Hub (2019) How much does a new boiler cost to install 2019? | The Heating Hub, accessed 4 September 2019, https://www.theheatinghub.co.uk/guide-to-boiler-installation-costs28 The Energy Savings Trust Renewable Energy, accessed 12 November 2019, https://www.energysavingtrust.org.uk/renewable-energy




Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


Domestic Energy Efficiency Retrofits Hhld 3.79 5.71 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Domestic Energy Behaviour Change Campaign

Hhld3.22 10.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Energy-Efficient and Repairable Domestic Appliances

Hhld2.00 11.79 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

New Zero Carbon Housing Hhld 4.07 1.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Domestic Air Source Heat Pump Heating MWh 0.36 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Solar Heating MWh 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

C&I Air Source Heat Pump MWh 0.36 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

C&I Solar Thermal MWh 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

New Zero Carbon C&I Building Stock Building 22.24 5.56 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

The cost impact inputs for these processes are described in Table 1-8. These costs exclude the costs relating to utilities. Utility consumption and generation costs are separately calculated in the model using the utility cost inputs shown Table 0-3 in conjunction with the utility consumption/generation figures shown in Table 0-7. The model adds both of these costs together to calculate the overall cost for each process.

The extent to which the technical potentials (Table 1-8) are realised depends, at least partly, on the strength of policy which underpins each measure.

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Table 0-8: Buildings: Future Processes: Cost and Technical Potential



Domestic Energy Efficiency Retrofits Hhld 1,746 1,455 15,903 100,740

Domestic Energy Behaviour Change Campaign Hhld 75.1 62.6 0.00 100,740

Energy-Efficient and Repairable Domestic Appliances Hhld 108 103 0.00 100,740

New Zero Carbon Housing Hhld 653 522 2,287 8,537

Domestic Air Source Heat Pump Heating MWh 179 171 144,159 913,199

Solar Heating MWh 248 235 8,561 54,230

C&I Air Source Heat Pump MWh 197 164 9,102 105,623

C&I Solar Thermal MWh 278 232 315 7,337

New Zero Carbon C&I Building Stock Building 52,304 41,843 63.8 2,103

Co-benefits and (where relevant) co-disbenefits relating to these processes are described in Table 0-8. The traffic light label is a qualitative marker summarising these co-benefits. A green light is assigned to a process with a host of co-benefits, an orange light represents a process with very few co-benefits and/or co-disbenefits, and a yellow light is in-between.

Table 0-9: Buildings: Future Processes: Co-benefits and Co-disbenefits

Process Name Co-benefits and Co-disbenefits



Domestic Energy Efficiency Retrofits - Reduces fuel poverty as homes take less fuel to heat (depending, of course, on the retrofit’s financing mechanism)

- Creates installation jobs locally- May stimulate local economy if savings on energy bills are spent locally- All households are better placed to withstand future energy price rises as well as overheating in

heatwaves- Savings to the National Health Service due to reduced cost of treating ill health from cold

homes. The cost to the NHS of ill health from cold homes is estimated at £2.5bn/year- Economic impacts of cold homes including reduced missed work days, plus impacts on

productivity and attainment. It is estimated that minor cold-related illnesses cause 27m lost working days per year in the UK, estimated at a cost of £1.8bn in 2013

- Installation is disruptive to residents


- Using energy more efficiently will reduce household expenditure on energy, freeing income to spend elsewhere

- May stimulate local economy if savings on energy bills are spent locally- Opportunity for community-building through sharing of advice and approaches to saving energy,

potentially good for residents’ awareness


- Using energy more efficiently will reduce household expenditure on energy, freeing income to spend elsewhere

- May stimulate local economy if savings on energy bills are spent locally- Opportunity for community building through sharing of advice and approaches to saving energy,

potentially good for residents’ awareness

22 21/11/2019


New Zero Carbon Housing - Improved user comfort in passively heated and cooled buildings;- Improved control of humidity reducing risk of damp and mould;- Improved indoor air quality through Mechanical Ventilation with Heat Recovery; - Reduces fuel poverty as homes take less fuel to heat;- Creates installation jobs locally;- May stimulate local economy if savings on energy bills are spent locally;- All households are better placed to withstand future energy price rises as well as overheating in

heatwaves;- Savings to the National Health Service due to reduced cost of treating ill health from cold

homes. The cost to the NHS of ill health from cold homes is estimated at £2.5bn/year;- Economic impacts including reduced missed work days, plus impacts on productivity and

attainment. It is estimated that minor cold-related illnesses cause 27m lost working days per year in the UK, estimated at a cost of £1.8bn in 2013

Domestic Air Source Heat Pump Heating - Localised air quality benefits if displacing gas or solid fuel heating

Solar Heating - Improved local air quality if this displaces gas. - Greater local air quality benefits if displacing solid fuel

C&I Air Source Heat Pump - Localised AQ benefits if displacing gas or solid fuel heating

C&I Solar Thermal - Marginally improved local air quality if this displaces gas. - Greater local air quality benefits if displacing solid fuel



New Zero Carbon C&I Building Stock - Improved user comfort in passively heated and cooled buildings;- Improved control of humidity reducing risk of damp and mould;- Improved indoor air quality through Mechanical Ventilation with Heat Recovery;- Reduces fuel poverty as homes take less fuel to heat;- Creates installation jobs locally;- May stimulate local economy if savings on energy bills are spent locally;- All households are better placed to withstand future energy price rises as well as overheating in

heatwaves;- Savings to the National Health Service due to reduced cost of treating ill health from cold

homes. The cost to the NHS of ill health from cold homes is estimated at £2.5bn/year;- Economic impacts including reduced missed work days, plus impacts on productivity and

attainment. It is estimated that minor cold-related illnesses cause 27m lost working days per year in the UK, estimated at a cost of £1.8bn in 2013

These future processes often relate to improved efficiency; switching one technology for another with lower energy consumption or modifications to building fabric that reduce energy demand. For these, a range of data points (efficiencies and capital, installation and maintenance costs) were derived from a range of sources. These include government-published data, technology manufacturers and installers, the National Energy Efficiency Data (NEED) Framework and cost-comparison websites. For behaviour change interventions, the costs and effectiveness were derived from ex-ante impact assessments of a range of historic campaigns.


The NEED Framework Consumption Data Tables; 29

29 National Energy Efficiency Data-Framework (NEED): consumption data tables 2019, accessed 4 September 2019, https://www.gov.uk/government/statistics/national-energy-efficiency-data-framework-need-consumption-data-tables-2019

24 21/11/2019

Papers published by the European Council for an Energy Efficient Economy;30

The Department of Energy and Climate Change’s (DECC) 2012 report ‘What Works in Changing Energy-Using Behaviours in the Home? A Rapid Evidence Assessment; 31 and

various cost-comparison sites and consumer guides such as The Heating Hub,32 Passipedia.org33 and the Energy Savings Trust.34

A.1.4.3 Energy: Current Processes

The current processes for the energy sector relate to:

The impact of a typical household’s domestic space and water heating system (data given per MWh heat consumed), The impact of a typical commercial & industrial (C&I) building’s space and water heating system (data given per MWh consumed), The impact of a typical domestic electricity tariff (data given per MWh consumed), and The impact of electricity as sourced from the grid (data given per MWh provided).


30 Dunbabin, P., Palmer, J., and Terry, N. (2015) Electricity use by domestic appliances in English households, 2015, https://www.eceee.org/library/conference_proceedings/eceee_Summer_Studies/2015/7-appliances-product-policy-and-the-ict-supply-chain/electricity-use-by-domestic-appliances-in-english-households/31 RAND Europe for DECC (2012) What Works in Changing Energy-Using Behaviours in the Home? A Rapid Evidence Assessment, 2012, https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/69797/6921-what-works-in-changing-energyusing-behaviours-in-.pdf32 The Heating Hub (2019) How much does a new boiler cost to install 2019? | The Heating Hub, accessed 4 September 2019, https://www.theheatinghub.co.uk/guide-to-boiler-installation-costs33 Passipedia.org (2019) Passipedia - The Passive House Resource, accessed 12 November 2019, https://passipedia.org/34 The Energy Savings Trust Renewable Energy, accessed 12 November 2019, https://www.energysavingtrust.org.uk/renewable-energy


Table 0-10: Energy: Current Processes: Utility Impact and Direct Emissions



Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


Current Domestic Gas Heating MWh 0.00 1.29 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Baseline C&I Space and Water Heating MWh 0.07 1.13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Normal Energy Tariff MWh 0.00 0.00 0.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00

Current grid electricity MWh 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

The cost impact inputs for these processes are described in Table 1-11 These costs exclude the costs relating to utilities. Utility consumption and generation costs are separately calculated in the model using the utility cost inputs shown in Table 0-3 in conjunction with the utility consumption/generation figures shown in Table 0-10. The model adds both of these costs together to calculate the overall cost for each process.


Table 0-11: Energy: Current Processes: Cost and Technical Potential



Current Domestic Gas Heating MWh 49.47 47.11

Baseline C&I Space and Water Heating MWh 63.86 53.22

Normal Energy Tariff MWh 0.00 0.00

Current grid electricity MWh 0.00 0.00

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The split of energy sources used to heat space and water in domestic (incl. private and social housing), industrial, office and retail properties was derived from data published by BEIS and Ofgem. Costs (including capital, installation and maintenance) and efficiencies of technologies used to supply heat to domestic properties were derived from government-published data, technology manufacturers and installers and cost comparison websites. Hounslow-specific heat and electricity demand per building were derived from local authority-level data published by BEIS, and costs derived from electricity and gas consumption (Appendix A.1.3). The levels of energy consumption for C&I buildings was also calculated for range of building types.


Ofgem’s Typical Domestic Consumption Values; 35

The National Energy Efficiency Data Framework Consumption Data Tables; 36

The English Housing Survey 2016- 2017; 37 The Building Energy Efficiency Survey 2014-2015;38 Sub-national electricity and gas sales;39,40 2015 Real Estate Environmental Benchmarks;41 and various cost comparison sites and consume guides such as The Heating Hub42 and Energy Savings Trust.43

35 Ofgem (2015) Typical Domestic Consumption Values, accessed 3 September 2019, https://www.ofgem.gov.uk/gas/retail-market/monitoring-data-and-statistics/typical-domestic-consumption-values36 National Energy Efficiency Data-Framework (NEED): consumption data tables 2019, accessed 4 September 2019, https://www.gov.uk/government/statistics/national-energy-efficiency-data-framework-need-consumption-data-tables-201937 Ministry of Housing, Communities & Local Government (2018) English Housing Survey 2016 to 2017: headline report, accessed 4 October 2019, https://www.gov.uk/government/statistics/english-housing-survey-2016-to-2017-headline-report38 Department of Business, Energy and Industrial Strategy (2016) Building Energy Efficiency Survey 2014 - 2015: Overarching Report39 Department for Business, Energy and Industrial Strategy (2018) Sub-national electricity sales and numbers of customers 2005 - 201740 Department for Business, Energy and Industrial Strategy (2018) Regional and local authority gas consumption statistics: 2005 to 201741 Better Buildings Partnership (2016) 2015 Real Estate Environmental Benchmarks, accessed 12 November 2019, http://www.betterbuildingspartnership.co.uk/sites/default/files/media/attachment/REEB%20Benchmarks%202015%20-%20Final.pdf42 The Heating Hub (2019) How much does a new boiler cost to install 2019? | The Heating Hub, accessed 4 September 2019, https://www.theheatinghub.co.uk/guide-to-boiler-installation-costs43 The Energy Savings Trust Renewable Energy, accessed 12 November 2019, https://www.energysavingtrust.org.uk/renewable-energy


A.1.4.4 Energy: Future Processes

The future processes for the energy sector relate to:

The impact of providing heating through a natural gas-powered district heating system (data given per MWh heat consumed), The impact of providing heating through a biogas-powered district heating system (data given per MWh heat consumed), The impact of providing heating through a district heating system powered by a residual waste incinerator (data given per MWh heat

consumed), The impact of a green domestic electricity tariff (data given per MWh consumed), and The impact of electricity as generated from solar PV (data given per MWh generated).


Table 0-12: Energy: Future Processes: Utility Impact and Direct Emissions



Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


District Heating (Natural Gas CHP) MWh 0.02 2.93 0.00 0.00 0.72 0.00 0.00 0.00 0.00 0.00

District Heating (Biogas CHP) MWh 0.02 2.93 0.00 0.00 0.72 0.00 0.00 0.00 0.00 0.00

District Heating (Waste CHP) MWh 0.02 0.00 0.00 0.00 0.52 0.00 0.00 0.00 0.20 0.55

Green Energy Tariff MWh 0.00 0.00 0.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00

Solar PV MWh 1.00 0.00 0.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00

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Table 0-13: Energy: Future Processes: Cost and Technical Potential



District Heating (Natural Gas CHP) MWh 184 153 4,892 30,988

District Heating (Biogas CHP) MWh 206 172 4,892 30,988

District Heating (Waste CHP) MWh 242 202 4,892 30,988

Green Energy Tariff MWh 0.00 0.00 116,113 1,764,857

Solar PV MWh 387 322 28,086 198,697


Table 0-14: Energy: Future Processes: Co-benefits and Co-disbenefits


District Heating (Natural Gas CHP) - Potential reduction in energy bills – reduction in fuel poverty- Potential to catalyse local growth if use to drive regeneration and attract new business- Potential stabilising effect on balance of supply and demand through heat storage capacity



District Heating (Biogas CHP) - Biogas production has negative air quality impacts (abatement technology could mitigate some of this)-- Biofuels have indirect GHG emissions associated with them caused by land use change, although this is less

relevant if biogas is sourced from biowaste- Potential stabilising effect on balance of supply and demand through heat storage capacity.

District Heating (Waste CHP) - Incineration has negative air quality impacts (abatement technology could mitigate some of this)- Potential stabilising effect on balance of supply and demand through storage capacity.

Green Energy Tariff - Depending on tariff, may lead to actual additional deployment of renewables- Sends market signals supporting green economy- May be effective in awareness-raising regarding carbon impacts of energy consumption

Solar PV - Greater awareness of energy generation (and consumption) at the domestic level could lead to greater care over use of electricity

- Possible synergies with battery storage to control export or consumption of electricity so as to maximise value (e.g. during peak hours).

- Small benefit from reduced transmission and distribution losses.

Where future processes involve switching one technology for another with lower energy consumption, performance efficiencies as well as capital, installation and maintenance costs were derived from government-published data, cost comparison sites and consumer guides. For district heating, performance data included factors such as distribution losses and parasitic electricity use in the distribution network. Performance of Waste CHP was informed by proprietary Eunomia models. These have been developed, managed, and refined for each waste treatment option over a number of years.

Key sources used for this part of the model include:

30 21/11/2019

DECC’s 2015 ‘Assessment of the Costs, Performance and Characteristics of UK Heat Networks’;44

Ofgem’s ‘The Decarbonisation of Heat’;45

Eunomia’s proprietary waste treatment emissions models; BEIS carbon accounting publications,46 citing Ofgem recommendations;47 and various cost comparison sites and consume guides such as Which48 and EnergySage.49

A.1.4.5 Land Use: Current Processes

The current processes for the land use sector relate to:

The impact of a typical Briton’s diet (data given per capita), and The impact of land cover as it is currently used in Hounslow (data given per hectare)


Table 0-15: Land Use: Current Processes: Utility Impact and Direct Emissions


44 Department of Energy and Climate Change (2015) Assessment of the Costs, Performance and Characteristics of UK Heat Networks, accessed 4 October 2019, https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/424254/heat_networks.pdf45 Ofgem (2019) Ofgem’s Future Insights Series: The Decarbonisation of Heat, 201946 Department for Business, Energy and Industrial Strategy (2019) UK Government GHG Conversion Factors for Company Reporting47 Martin Crouch (2009) Final Green Supply Guidelines48 Which.co.uk (2019) How Much Do Solar Panels Cost?, accessed 12 November 2019, https://www.which.co.uk/reviews/solar-panels/article/solar-panels/solar-panel-costs49 Richardson, L. (2019) How Long Do Solar Panels Last in 2019?



Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


Current Diet capita 0 0 0 0 0 0 0 0 1.91 0.19

Typical Land Use ha 0 0 0 0 0 0 0 0 0 0



Table 0-16: Land Use: Current Processes: Cost and Technical Potential



Current Diet Per capita 2,065 1,966

Typical Land Use ha 0 0

These processes were informed by grey literature, academic journals, and government publications.


Office for National Statistics (ONS) household expenditure data; 50

Natural England’s 2012 report: ‘Carbon storage by habitat’; 51 and

50 NimbleFins (2018) Average UK Household Cost of Food, accessed 12 November 2019, https://www.nimblefins.co.uk/average-uk-household-cost-food#nogo51 Natural England (2012) Carbon storage by habitat: Review of the evidence of the impacts of management decisions and conditions of carbon stores and sources, 2012, http://publications.naturalengland.org.uk/file/1438141

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Academic studies of urban land use.52,53

A.1.4.6 Land Use: Future Processes

The future processes for the land use sector relate to:

The impact of a healthier and more sustainable diet which is richer in plant-based meals (data given per capita), and The impact of greener land cover as would be appropriate for Hounslow (data given per hectare).


Table 0-17: Land Use: Future Processes: Utility Impact and Direct Emissions



Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


Changed Diet capita 0 0 0 0 0 0 0 0 1.17 0.12

Greening Land Use ha 0 0 0 0 0 0 0 0 0 0


52 Kim, G., Miller, P.A., and Nowak, D.J. (2015) Assessing urban vacant land ecosystem services: Urban vacant land as green infrastructure in the City of Roanoke, Virginia, Urban Forestry & Urban Greening, Vol.14, No.3, pp.519–52653 Townsend-Small, A., and Czimczik, C.I. (2010) Carbon sequestration and greenhouse gas emissions in urban turf: GLOBAL WARMING POTENTIAL OF LAWNS, Geophysical Research Letters, Vol.37, No.2, p.n/a-n/a



Table 0-18: Land Use: Future Processes: Cost and Technical Potential



Changed Diet Per capita 1,894 1,804 1,211 181,424

Greening Land Use ha 19,823 16,519 765 5,090


Table 0-19: Land Use: Future Processes: Co-benefits and Co-disbenefits


Changed Diet - Red meats are associated with higher risks of cardiovascular disease, stroke and some cancers, so this measure is likely to lead to a healthier population if it results in a reduction in red meat consumption (providing the population continues to get adequate nutrition from alternative means), leading to potentially lower healthcare costs.

- Complying with the WHO dietary recommendations (similar to the changed diet recommended in this measure) would increase average life expectancy by over 8 months and could help to reduce obesity and type 2 diabetes across the population, thereby reducing strain on the NHS.54

54 Jones, E., Jenkinson, C., and Brammer, S. Climate action co-benefits, https://www.ashden.org/programmes/co-benefits

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Greening Land Use - Productive use of spare land, including road verges, parks, private grasslands and farms. - Reduced management of public land would be needed. - There are also potential benefits of reduced crime, better resilience, better biodiversity, reduced energy use in buildings

due to cooling, better air quality and mental health benefits of green spaces. - Green roofs can help with flood alleviation and can significantly extend the lifetime of a roof, improve biodiversity and

reduce bills.55

These processes were informed by grey literature, academic journals, and government publications. The British Dietary Association (BDA) proposes a sustainable diet which is similar to those recommended by several other reputable sources including the World Health Organisation, the United Nations and the Lancet Report published earlier this year.56,57,58 The diet – which is also the diet modelled in this work – essentially consists of reducing meat and dairy consumption and eating more plant-based meals, though none of the reports suggest a switch to an entirely vegetarian/vegan diet. Academic journals, government publications and a number of other sources are used as sources to approximate land coverage and the carbon sequestration potential of different types of land use.


The British Dietary Association’s ‘Eating patterns for health and environmental sustainability’ report,59 corroborated against publications by the United Nations and the Lancet Report;

Office for National Statistics (ONS) household expenditure data; 60

55 The Green Roof Centre Green Roof FAQ, accessed 13 November 2019, http://www.thegreenroofcentre.co.uk/green_roofs/faq.html56 British Dietary Association (BDA) (2018) Eating patterns for health and environmental sustainability, November 2018, https://www.bda.uk.com/professional/resources/obd_ref_guide.pdf57 The EAT-Lancet Commission (2019) Summary Report of the EAT-Lancet Commission, July 2019, https://eatforum.org/content/uploads/2019/07/EAT-Lancet_Commission_Summary_Report.pdf58 Gallagher, J. (2019) Meat, veg, nuts - a diet designed to feed 10bn, accessed 19 November 2019, https://www.bbc.com/news/health-4686520459 British Dietary Association (BDA) (2018) Eating patterns for health and environmental sustainability, November 2018, https://www.bda.uk.com/professional/resources/obd_ref_guide.pdf60 NimbleFins (2018) Average UK Household Cost of Food, accessed 12 November 2019, https://www.nimblefins.co.uk/average-uk-household-cost-food#nogo


Natural England’s 2012 report: ‘Carbon storage by habitat’; 61 and Academic studies of urban land use.62,63

A.1.4.7 Transport: Current Processes

The current processes for the transport sector relate to:

The impact of commercial vehicles – including lorries and vans – driving (data given per million kilometres driven), The impact of lorries (data given per million kilometres driven), and The impact of cars (data given per million person-kilometres driven)


Table 0-20: Transport: Current Processes: Utility Impact and Direct Emissions



Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


Lorry/Delivery Van Driving Mveh.km 0 0 124 103 0 0 0 0 0 0

61 Natural England (2012) Carbon storage by habitat: Review of the evidence of the impacts of management decisions and conditions of carbon stores and sources, 2012, http://publications.naturalengland.org.uk/file/143814162 Kim, G., Miller, P.A., and Nowak, D.J. (2015) Assessing urban vacant land ecosystem services: Urban vacant land as green infrastructure in the City of Roanoke, Virginia, Urban Forestry & Urban Greening, Vol.14, No.3, pp.519–52663 Townsend-Small, A., and Czimczik, C.I. (2010) Carbon sequestration and greenhouse gas emissions in urban turf: GLOBAL WARMING POTENTIAL OF LAWNS, Geophysical Research Letters, Vol.37, No.2, p.n/a-n/a

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Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


Current Lorry Mveh.km 0 0 310 0 0 0 0 0 0 0

Car Driving Mp.km 0 0 20.6 24.1 0 0 0 0 0 0



Table 0-21: Transport: Current Processes: Cost and Technical Potential



Lorry/Delivery Van Driving Mveh.km 2,750,332 2,291,943

Current Lorry Mveh.km 221,000 191,500

Car Driving Mp.km 148,645 141,018

In the UK, the Department for Transport (DfT) publishes a range of transport statistics on an annual basis. These, in addition to third sector and industry reports, were used to generate performance inputs. Costs including vehicle capital, maintenance, insurance, and any associated infrastructure (such as the costs of new and existing roads), were informed by these sources and supplemented by RAC figures.



DfT statistics on Heavy Goods Vehicle (HGV) fuel consumption;64 Transport Environment’s ‘Analysis of long-haul battery electric trucks in EU’;65

An article on vehicle running costs by the RAC Foundation (2016/17);66 and The 2019 Asphalt Industry Alliance Annual Road Maintenance Survey.67

A.1.4.8 Transport: Future Processes

The future processes for the transport sector relate to:

The impact of prevented commercial transport such as by using urban consolidation centres (data given per million kilometres not driven), The impact of electric lorries (data given per million kilometres driven), The impact of hydrogen lorries (data given per million kilometres driven), The impact of biogas lorries (data given per million kilometres driven), The impact of prevented personal transport (data given per million person-kilometres not driven), The impact of active transport (data given per million person-kilometres), The impact of current public transport in the form of buses and trains (data given per million person-kilometres), and The impact of current public transport in the form of buses and trains (data given per million person-kilometres).


64 Department for Transport (2017) Table TSGB0304 (ENV0104): Average Heavy Goods Vehicle Fuel Consumption, Great Britain, 2003-201665 Earl, T., Mathieu, L., Cornelis, S., Kenny, S., Ambel, C.C., and Nix, J. (2018) Analysis of long haul battery electric trucks in EU, Transport Environment66 Lancefield, N. (2018) Cost of running a car increases by more than a third for poorest families, research finds, accessed 12 November 2019, https://www.independent.co.uk/news/business/news/car-costs-uk-poorest-families-increase-third-year-rac-foundation-disposable-income-average-motoring-a8262931.html67 Asphalt Industry Alliance (2019) Annual Local Authority Road Maintenance Survey, March 2019, https://www.asphaltuk.org/wp-content/uploads/alarm-survey-2019-digital.pdf

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Table 0-22: Transport: Future Processes: Utility Impact and Direct Emissions



Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


Prevented Commercial Transport

Mveh.km 0 0 0 0 0 0 0 0 0 0

Electric Lorry Mveh.km 1,295 0 0 0 0 0 0 0 0 0

Hydrogen Lorry Mveh.km 1,619 0 0 0 0 0 0 0 0 0

Biogas Lorry Mveh.km 69.5 0 0 0 0 0 0 0 0 0

Prevented Personal Transport Mp.km 0 0 0 0 0 0 0 0 0 0

Active Transport Mp.km 0 0 0 0 0 0 0 0 0 0

Current Public Transport Mp.km 36.1 0 10.1 8.9 0 0 0 0 0 0

Electric Vehicles Mp.km 140 0 0 0 0 0 0 0 0 0



Table 0-23: Transport: Future Processes: Cost and Technical Potential






Prevented Commercial Transport Mveh.km 2,750,332 2,291,943 1.64 38

Electric Lorry Mveh.km 368,000 315,500 10.9 254

Hydrogen Lorry Mveh.km 1,859,737 1,558,614 10.9 254

Biogas Lorry Mveh.km 877,982 740,485 10.9 254

Prevented Personal Transport Mp.km 90,695 86,131 10.4 687

Active Transport Mp.km 70,381 62,897 9.87 763

Current Public Transport Mp.km 251,083 209,236 12.5 968

Electric Vehicles Mp.km 201,612 183,926 29.6 2,288


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Table 0-24: Transport: Future Processes: Co-benefits and Co-disbenefits



- Improved town-centre business environment, improved local air quality, additional employment, reduced congestion, reduced noise impacts68

- Improved road safety due to fewer commercial vehicles on the roads69

Electric Lorry - Reduced noise pollution70 - Improved air quality due to reduced pollutants

Hydrogen Lorry - Reduced noise pollution; if it is a hydrogen fuel cell then it will be as quiet as an electric vehicle; if it is hydrogen ICE then there will be a similar noise reduction to biogas lorries71

Biogas Lorry - Reduced noise pollution; gas vehicles are 30-40% quieter than diesel ICE lorries72

68 Department for Environment, Food & Rural Affairs Environmental Noise: Valuing impacts on: sleep disturbance, annoyance, hypertension, productivity and quiet., https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/380852/environmental-noise-valuing-imapcts-PB14227.pdf69 The Royal Society for the Prevention of Accidents HGVs and Vulnerable Road Users, https://www.rospa.com/rospaweb/docs/advice-services/road-safety/cyclists/hgvs-and-vulnerable-road-users.pdf70 Porter, J. (2019) Fake noise will be added to new electric cars starting today in the EU, accessed 13 November 2019, https://www.theverge.com/2019/7/1/20676854/electric-cars-artificial-safety-noise-low-speeds-european-union-rules-2019-202171 California Air Resources Board Hydrogen Fuel Cell, accessed 13 November 2019, https://www.driveclean.ca.gov/Search_and_Explore/Technologies_and_Fuel_Types/Hydrogen_Fuel_Cell.php72 SKM Enviros (2011) ANALYSIS OF CHARACTERISTICS AND GROWTH ASSUMPTIONS REGARDING AD BIOGAS COMBUSTION FOR HEAT, ELECTRICITY AND TRANSPORT AND BIOMETHANE PRODUCTION AND INJECTION TO THE GRID, Report for Department for Energy and Climate Change, May 2011, https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/48166/2711-SKM-enviros-report-rhi.pdf



Prevented Personal Transport

- Reduced air pollution, reduced congestion, reduced noise, reduced land needed for parking, higher productivity, improved journey time reliability due to less traffic. Fewer cars will mean less embodied emissions. Reduced air pollution has health co-benefits and will massively reduce NHS costs, meaning that money saved can be spent on other.73

- Ride sharing benefits: improved well-being through social interaction, money saved on fuel might be spent locally, people can make journeys they otherwise could not, some reduced congestion, reduces isolation and loneliness by bringing people together, potential to address health inequalities as air pollution tends to disproportionately affect those in low-income areas.

Active Transport - Public health benefits, infrastructure benefits, congestion benefits, air quality benefits, noise reduction benefits. Greater opportunities for social interaction and a greater sense of neighbourliness.

- Increased physical activity could save the NHS £17bn within 20 years. It is estimated that there will be approximately 2.5m cases of air pollution-related diseases between 2017 and 2035, costing the NHS/social care £18.75bn.74

Current Public Transport - Reduced congestion (and associated improvements for air pollution, wellbeing, etc.)

Electric Vehicles - Benefit of reduced noise pollution- Opportunities for vehicle-to-grid charging to help to stabilise the grid. - However, switching to EVs does not benefit: congestion, air quality, public health (some reduction in tail pipe

emissions, but there remain air quality issues related to particulate matter from tyre, brake and road wear). EVs do not maximise the reduction in total embodied emissions. May lead to significant additional demands on the grid. No benefits of reduced need for parking.

In the UK, the Department for Transport (DfT) publishes a range of transport statistics on an annual basis. These, in addition to reports from industry and relevant third sector organisations, were used to derive inputs for the transport sector. In some cases, these assumptions are subject to considerable uncertainty, as explored in Appendix A.1.4.11. Key inputs include:

73 Jones, E., Jenkinson, C., and Brammer, S. Climate action co-benefits, https://www.ashden.org/programmes/co-benefits74 Jones, E., Jenkinson, C., and Brammer, S. Climate action co-benefits, https://www.ashden.org/programmes/co-benefits

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A DfT dataset on road traffic per local authority;75

DfT statistics on Heavy Goods Vehicle (HGV) fuel consumption;76 Transport Environment’s ‘Analysis of long-haul battery electric trucks in EU’;77

Biogas Lorries – A report by the Low Carbon Vehicle Partnership modelling the cost of using biomethane in HGV transportation, combined with the Transport Environment report referenced above;78

Hydrogen Lorries – The International Council on Clean Transportation’s White Paper on Zero Emissions Trucks;79 and Transport Environment publication on shared car use.80

A further notable publication used throughout the transport measures is the most recent DfT Great Britain Transport Statistics publication.81 This was used several times to estimate the potential of future processes such as active transport and public transport using modal share statistics.

A.1.4.9 Waste: Current Processes

The current processes for the waste sector relate to:

The impact of current plastic waste treatment including recycling and residual treatment (data given per kilotonne of waste treated), The impact of current food waste treatment including recycling and residual treatment (data given per kilotonne of waste treated), and The impact of current residual waste incineration (data given per kilotonne of waste treated).

75 Department for Transport (2019) Table TRA8905: Car vehicle traffic (vehicle kilometres) by local authority in Great Britain, annual from 199376 Department for Transport (2017) Table TSGB0304 (ENV0104): Average Heavy Goods Vehicle Fuel Consumption, Great Britain, 2003-201677 Earl, T., Mathieu, L., Cornelis, S., Kenny, S., Ambel, C.C., and Nix, J. (2018) Analysis of long haul battery electric trucks in EU, Transport Environment78 Brightman, T., Parker, T., and Matthews, C. (2011) Biomethane for Transport - HGV Cost Modelling79 Hall, D., and Lutsey, N. (2019) Estimating the infrastructure needs and costs for the launch of zero-emission trucks, The International Council on Clean Transport (ICCT) 80 Transport Environment (2017) Does sharing cars really reduce car use?, June 2017, https://www.transportenvironment.org/sites/te/files/publications/Does-sharing-cars-really-reduce-car-use-June%202017.pdf81 Department for Transport (2017) Transport Statistics Great Britain 2017, November 2017, https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/661933/tsgb-2017-report-summaries.pdf


The emissions for these processes are described in Table 1-25. Unlike other sectors, the emissions factors for waste are self-contained in the direct emissions, including the direct emissions as well as those associated with utility consumption and generation. This is because Eunomia’s proprietary waste models – used to generate these factors – already take these impacts into account. In practice, all three processes here are associated with electricity generation, for example, but the impact of this is integrated within the emissions figures (using impact assumptions as shown in Table 0-4).

Table 0-25: Waste: Current Processes: Utility Impact and Direct Emissions



Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


Current Plastic Waste Treatment kilotonne 0 0 0 0 0 0 0 0 1,423 1,564

Food Waste Treatment kilotonne 0 0 0 0 0 0 0 0 -41.8 -41.8

Residual Waste Incineration kilotonne 0 0 0 0 0 0 0 0 213 289

The cost impact inputs for these processes are described in Table 1-26. No technical potentials are shown in Table 1-26 as the inputs relate only to future processes; the important thing is the extent to which future (low-carbon) processes can displace current (high-carbon) processes.

Table 0-26: Waste: Current Processes: Cost and Technical Potential



Current Plastic Waste Treatment kilotonne 66,836 55,696

Food Waste Treatment kilotonne 71,481 59,568

Residual Waste Incineration kilotonne 75,000 62,500

Given Eunomia’s position as a leading waste management consultancy, it was possible to take many assumptions for the Waste sector processes from in-house models. These have been developed and refined over several years and were adapted for the UK context, and mainly inform the direct

44 21/11/2019

process emissions and utility impact inputs. Cost inputs were informed by in-house market research processes. Hounslow’s most recent submission to WasteDataFlow (2018/19) was also used to inform the modelling.

A.1.4.10 Waste: Future Processes

The future processes for the waste sector relate to:

The impact of residual waste disposal by way of mechanical and biological treatment (biostabilisation) preceding landfill (data given per kilotonne of waste treated),

The impact of residual waste incineration with a preceding pre-sorting phase where key materials are removed (data given per kilotonne of waste treated),

The impact of plastic waste prevention (data given per kilotonne of waste prevented), The impact of food waste prevention (data given per kilotonne of waste prevented), and The impact of higher municipal waste recycling (data given per additional kilotonne of waste recycled).

The emissions for these processes are described in Table 1-27. Unlike other sectors, the emissions factors for waste are self-contained in the direct emissions figures, including the direct emissions as well as those associated with utility consumption and generation. This is because Eunomia’s proprietary waste models – used to generate these factors – already take these impacts into account. In practice, many of these processes are associated with electricity consumption, for example, but the impact of this is integrated within the emissions figures (using impact assumptions as shown in Table 0-4).

Table 0-27: Waste: Future Processes: Utility Impact and Direct Emissions



Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


Biostabilisation (MBT) kilotonne 0 0 0 0 0 0 0 0 -90.9 124

Residual Incineration with Pre-Sorting

kilotonne 0 0 0 0 0 0 0 0 -1,703 87.4




Gas (MWh)

Diesel (kilolitre)

Petrol (kilolitre)

Elec (MWh)

Gas (MWh)

Diesel (kilolitre)


Plastic Waste Prevention kilotonne 0 0 0 0 0 0 0 0 -1,190 0

Food Waste Prevention kilotonne 0 0 0 0 0 0 0 0 -2,850 -285

Higher Municipal Recycling kilotonne 0 0 0 0 0 0 0 0 -602 -3.24

The cost impact inputs for these processes are described in Table 1-28. The extent to which the technical potentials (Table 1-28) are realised depends, at least partly, on the strength of policy which underpins each measure.

Table 0-28: Waste: Future Processes: Cost and Technical Potential



Biostabilisation (MBT) kilotonne 137,122 114,268 2.13 49.9

Residual Incineration with Pre-Sorting kilotonne 177,732 148,110 2.13 49.9

Plastic Waste Prevention kilotonne 19,036 15,864 0.06 1.46

Food Waste Prevention kilotonne 12,016 10,014 0.10 2.27

Higher Municipal Recycling kilotonne 19,810 16,508 1.23 28.7


Table 0-29: Waste: Future Processes: Co-benefits and Co-disbenefits


46 21/11/2019


Biostabilisation (MBT) - There will be a slight reduction in overall air pollution associated with the use of biostabilisation followed by landfill where this displaces incineration

- Likely to have relatively small net impact on employment

Residual Incineration with Pre-Sorting - Higher recycling (achieved here through pre-sorting) reduces demand for water/land/deforestation. - Pre-sorting will mean less waste needs to be incinerated, so less local air pollution.

Plastic Waste Prevention - Reduced source of air quality issues (where waste would otherwise be incinerated) and marine plastic pollution risks.

- Would weaken the argument that the use (and anticipated increase in use) of plastic means that continued fossil fuel exploration and extraction is necessary.

Food Waste Prevention - Reduced demand for land/water/resources/deforestation/energy. - Economic benefits for households, as they save money on not buying food that will be wasted. - Reduced source of air pollution from biowaste treatment

Higher Municipal Recycling - Higher recycling reduces demand for water/land/deforestation- generally good for employment opportunities. - Higher recycling means less need for incineration, so less local air pollution.

Given Eunomia’s position as a leading waste management consultancy, it was possible to take many assumptions for the Waste sector processes from in-house models. These have been developed and refined over several years and were adapted for the UK context, and mainly inform the emissions and utility impact inputs. Cost inputs were informed by in-house market research processes. Hounslow’s most recent submission to WasteDataFlow (2018/19) was also used to inform the modelling.

A.1.4.11 Assumption Limitations

The modelling undertaken for this project has been informed by in-depth research of current and future technologies as well as Hounslow’s local context. However, it is unlikely that the outputs would precisely match the costs and impacts of implementing such measures in reality. Key limitations relating to data inputs are described below, with limitations relating to the MACC method and scoping having been described in Appendix A.1.1.


Maturing technologies: uncertainty arises from unknowable future cost-reduction trajectories, competing technologies, competing implementation details, varying delivery mechanisms, and varying local contexts.

Economies of scale: delivery of some measures at a borough- (or multi-borough-) wide scale may allow for some economies of scale in procurement and delivery. This is not accounted for in this work.

Diverse stocks: the complexity of real-life stocks, where diverse technologies are in operation, is not always reflected in the modelling. In particular, this affects housing. Where current technology adoption is dominated by one technology, this is used to represent the whole at the expense of other more marginal technologies. For example, domestic heating is assumed to currently be provided entirely by gas. Clearly, this is an approximation as, in reality, some domestic heating is also supplied by way of oil, electricity, and other fuels. Similarly, some specific installation costs may depend on specific domestic plumbing details, the distribution of which across Hounslow’s building stock is unknown.

Data availability: in some cases, the make-up of current technology stocks – particularly in the commercial and industrial sector – is not known and so expert judgement is used to estimate inputs.

Regional variation: where possible, local authority-specific figures inform the modelling. However, in some cases, national average figures are still used. These may not represent Hounslow’s case precisely.

Scope of costs: the administration costs of delivering measures across the borough have not been estimated in this work.

Disclosure of these limitations is provided to allow for better understanding of the modelling undertaken. These limitations do not devalue the recommendations of the MACC but do lead to potential sources of divergence from the costs and impacts of real-world implementation.

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A.1.5 Measure Constructions32 measures have been modelled in this work; how these are spread across sectors - and how they are constructed out of constituent processes – is summarised in Table 1-30. Given that many measures cut across multiple sectors, it is worth noting that the labels as given below are relatively open to interpretation. Nevertheless, they remain a useful guide to where research has been focused.

Table 0-30: Measure Constructions

Sector Measure Name Current Process Future Process

Buildings Domestic Energy Efficiency Retrofits

Typical Household Energy Consumption

Domestic Energy Efficiency Retrofits

BuildingsDomestic Energy Behaviour Change Campaign



BuildingsEnergy-Efficient and Repairable Domestic Appliances



Buildings New Domestic Buildings Typical Household Energy Consumption

New Zero Carbon Housing

Buildings Domestic ASHP Current Domestic Gas Heating

Domestic Air Source Heat Pump Heating

Buildings Domestic Solar Heating Current Domestic Gas Heating

Solar Heating

Buildings C&I ASHP Baseline C&I Space and Water Heating

C&I Air Source Heat Pump

Buildings C&I Solar Heating Baseline C&I Space and Water Heating

C&I Solar Thermal

Buildings New C&I Buildings Typical C&I Building New Zero Carbon C&I Building Stock

Energy Domestic District Heating (Natural Gas)

Current Domestic Gas Heating

District Heating (Natural Gas CHP)

Energy Domestic District Heating (Biogas)


District Heating (Biogas CHP)

Energy Domestic District Heating (Waste)


District Heating (Waste CHP)

Energy C&I District Heating (Natural Gas)

Baseline C&I Space and Water Heating

District Heating (Natural Gas CHP)

Energy C&I District Heating (Biogas)


District Heating (Biogas CHP)


Sector Measure Name Current Process Future Process

Energy C&I District Heating (Waste)


District Heating (Waste CHP)

Energy Green Energy Tariff Normal Energy Tariff Green Energy Tariff

Energy Solar PV Current Grid Electricity Solar PV

Land Use Dietary Change Current Diet Changed Diet

Land Use Targeted Land Use Typical Land Use Greening Land Use

Transport Reduced Commercial Transport

Lorry/delivery Van Driving


Transport Electric Commercial Transport

Current Lorry Electric Lorry

Transport Hydrogen Commercial Transport

Current Lorry Hydrogen Lorry

Transport Biogas Commercial Transport

Current Lorry Biogas Lorry

Transport Personal Transport Reduction

Car Driving Prevented Personal Transport

Transport Increase Active Transport

Car Driving Active Transport

Transport Increase Public Transport

Car Driving Current Public Transport

Transport Electric Vehicles Car Driving Electric Vehicles

Waste Plastic Waste Prevention

Current Plastic Waste Treatment

Plastic Waste Prevention

Waste Food Waste Prevention Food Waste Treatment Food Waste Prevention

Waste Higher Municipal Recycling

Residual Incineration Higher Municipal Recycling

Waste Incineration with Pre-sorting

Residual Incineration Residual Incineration with Pre-sorting

Waste Residual Biostabilisation

Residual Incineration Biostabilisation (MBT)

50 21/11/2019

A.2.0 MACC ResultsMAC curves and tables are shown below for each of the key sensitivities:

Direct emissions, production scope, excluding transfers (Figure 2 and Table 1-31) Direct emissions, consumption scope, excluding transfers (Figure 3 and Table 1-32) Local authority emissions, production scope, excluding transfers (Figure 4 and Table 1-33) Local authority emissions, consumption scope, excluding transfers (Figure 5 and Table 1-34)

MAC tables are then provided for each sensitivity including transfers:

Direct emissions, production scope, including transfers (Table 1-35) Direct emissions, consumption scope, including transfers (Table 1-36) Indirect emissions, production scope, including transfers (Table 1-37) Indirect emissions, consumption scope, including transfers (Table 1-38) Local authority emissions, production scope, including transfers (Table 1-39) Local authority emissions, consumption scope, including transfers (Table 1-40)


Figure 2: MACC (Direct, Production, Excluding Transfers)

-3,000

-2,000

-1,000

0

1,000

2,000

3,000

0 25 50 75

Mar

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GBP/

tCO

2e)

Cumulative Abatement Potential (ktCO2e/yr)

Dietary Change Increase Active Transport Personal Transport Reduction Food Waste Prevention Reduced Commercial Transport

Higher Municipal Recycling New C&I Buildings Plastic Waste Prevention New Domestic Buildings Electric Commercial Transport

C&I District Heating (Biogas) Domestic District Heating (Biogas) Residual Biostabilisation Incineration with Pre-sorting Electric Vehicles

Biogas Commercial Transport C&I ASHP Domestic ASHP Domestic Solar Heating C&I Solar Heating

Solar PV Increase Public Transport Domestic Energy Efficiency Retrofits Hydrogen Commercial Transport 0

0

52 21/11/2019

Table 0-31: MAC Table (Direct, Production, Excluding Transfers)

Ranking Measure Abatement Potential (tCO2e/yr)

Cost (GBP/yr) Marginal Abatement Cost (GBP/tCO2e)


1 Dietary Change 90 -197,108 -2,182 02 Increase Active Transport 985 -971,332 -986 13 Personal Transport Reduction 1,034 -779,105 -754 24 Food Waste Prevention 24 -4,838 -204 25 Reduced Commercial Transport 841 -170,072 -202 36 Higher Municipal Recycling 360 -56,659 -157 37 New C&I Buildings 514 -25,522 -50 48 Plastic Waste Prevention 98 -2,490 -25 49 New Domestic Buildings 4,468 748,534 168 810 Electric Commercial Transport 6,737 1,171,952 174 1511 C&I District Heating (Biogas) 1,808 552,731 306 1712 Domestic District Heating (Biogas) 1,921 598,841 312 1913 Residual Biostabilisation 351 110,019 314 1914 Incineration with Pre-sorting 429 181,940 425 2015 Electric Vehicles 2,526 1,089,147 431 2216 Biogas Commercial Transport 8,113 4,456,604 549 3017 C&I ASHP 1,621 1,066,795 658 3218 Domestic ASHP 29,007 19,150,331 660 6119 Domestic Solar Heating 2,037 1,380,666 678 6320 C&I Solar Heating 68 46,721 690 6321 Solar PV 6,179 6,220,340 1,007 6922 Increase Public Transport 667 754,669 1,132 7023 Domestic Energy Efficiency Retrofits 17,777 21,139,583 1,189 8824 Hydrogen Commercial Transport 6,373 15,083,751 2,367 94


Figure 3: MACC (Direct, Consumption, Excluding Transfers)

-1,500

-1,000

-500

0

500

1,000

1,500

2,000

2,500

3,000

0 25 50 75 100

Mar

gina

l Aba

tem

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GBP/

tCO

2e)


Increase Active Transport Personal Transport Reduction Dietary Change Reduced Commercial Transport Higher Municipal Recycling

New C&I Buildings Food Waste Prevention Plastic Waste Prevention Incineration with Pre-sorting New Domestic Buildings

Residual Biostabilisation Electric Commercial Transport C&I District Heating (Biogas) Domestic District Heating (Biogas) Domestic District Heating (Waste)

C&I District Heating (Waste) Electric Vehicles Biogas Commercial Transport C&I ASHP Domestic ASHP

Domestic Solar Heating C&I Solar Heating Solar PV Domestic Energy Efficiency Retrofits Increase Public Transport

Hydrogen Commercial Transport

54 21/11/2019

Table 0-32: MAC Table (Direct, Consumption, Excluding Transfers)




1 Increase Active Transport 1,013 -971,332 -959 12 Personal Transport Reduction 1,063 -779,105 -733 23 Dietary Change 903 -197,108 -218 34 Reduced Commercial Transport 865 -170,072 -197 45 Higher Municipal Recycling 1,003 -56,659 -56 56 New C&I Buildings 604 -25,522 -42 57 Food Waste Prevention 274 -4,838 -18 68 Plastic Waste Prevention 163 -2,490 -15 69 Incineration with Pre-sorting 4,071 181,940 45 1010 New Domestic Buildings 5,109 748,534 147 1511 Residual Biostabilisation 645 110,019 171 1612 Electric Commercial Transport 6,640 1,171,952 176 2213 C&I District Heating (Biogas) 1,691 552,731 327 2414 Domestic District Heating (Biogas) 1,819 598,841 329 2615 Domestic District Heating (Waste) 974 378,617 389 2716 C&I District Heating (Waste) 846 332,508 393 2817 Electric Vehicles 2,521 1,089,147 432 3018 Biogas Commercial Transport 8,306 4,456,604 537 3919 C&I ASHP 1,837 1,066,795 581 4020 Domestic ASHP 32,845 19,150,331 583 7321 Domestic Solar Heating 2,332 1,380,666 592 7622 C&I Solar Heating 78 46,721 602 7623 Solar PV 6,788 6,220,340 916 8224 Domestic Energy Efficiency Retrofits 20,345 21,139,583 1,039 10325 Increase Public Transport 678 754,669 1,114 10326 Hydrogen Commercial Transport 6,200 15,083,751 2,433 110


Figure 4: MACC (Local Authority, Production, Excluding Transfers)

-3,000

-2,000

-1,000

0

1,000

2,000

3,000

0 100 200 300 400 500 600 700 800 900 1,000 1,100 1,200 1,300 1,400

Mar

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GBP/

tCO

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Dietary Change Increase Active Transport Personal Transport Reduction Energy-Efficient and Repairable Domestic Appliances

Food Waste Prevention Reduced Commercial Transport Higher Municipal Recycling Domestic Energy Behaviour Change Campaign

New C&I Buildings Plastic Waste Prevention New Domestic Buildings Electric Commercial Transport

C&I District Heating (Biogas) Domestic District Heating (Biogas) Residual Biostabilisation Incineration with Pre-sorting

Electric Vehicles Biogas Commercial Transport C&I ASHP Domestic ASHP

Domestic Solar Heating C&I Solar Heating Solar PV Increase Public Transport

Domestic Energy Efficiency Retrofits Hydrogen Commercial Transport

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Table 0-33: MAC Table (Local Authority, Production, Excluding Transfers)




1 Dietary Change 13,532 -29,526,031 -2,182 142 Increase Active Transport 76,099 -75,070,568 -986 90

3 Personal Transport Reduction 68,489 -51,612,100 -754 158

4 Energy-Efficient and Repairable Domestic Appliances

18,547 -7,837,363 -423 177

5 Food Waste Prevention 553 -112,628 -204 177

6 Reduced Commercial Transport 19,587 -3,959,329 -202 197

7 Higher Municipal Recycling 8,384 -1,319,037 -157 205

8 Domestic Energy Behaviour Change Campaign

38,676 -3,173,754 -82 244

9 New C&I Buildings 16,951 -841,632 -50 26110 Plastic Waste Prevention 2,275 -57,960 -25 26311 New Domestic Buildings 16,676 2,793,899 168 28012 Electric Commercial Transport 156,835 27,283,349 174 43713 C&I District Heating (Biogas) 11,453 3,501,363 306 44814 Domestic District Heating (Biogas) 12,170 3,793,450 312 46015 Residual Biostabilisation 8,161 2,561,268 314 46816 Incineration with Pre-sorting 9,977 4,235,617 425 47817 Electric Vehicles 195,238 84,176,083 431 67418 Biogas Commercial Transport 188,880 103,750,899 549 86219 C&I ASHP 18,807 12,379,836 658 88120 Domestic ASHP 183,749 121,310,718 660 1,06521 Domestic Solar Heating 12,907 8,746,039 678 1,07822 C&I Solar Heating 1,576 1,087,686 690 1,08023 Solar PV 43,713 44,007,031 1,007 1,12324 Increase Public Transport 51,528 58,325,538 1,132 1,17525 Domestic Energy Efficiency Retrofits 112,613 133,911,939 1,189 1,28726 Hydrogen Commercial Transport 148,370 351,153,646 2,367 1,436


Figure 5: MACC (Local Authority, Consumption, Excluding Transfers)

-1,500

-1,000

-500

0

500

1,000

1,500

0 100 200 300 400 500 600 700 800 900 1,000 1,100 1,200 1,300 1,400 1,500 1,600 1,700

Mar

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GBP/

tCO

2e)


Increase Active Transport Personal Transport Reduction Energy-Efficient and Repairable Domestic Appliances Dietary Change

Reduced Commercial Transport Domestic Energy Behaviour Change Campaign Higher Municipal Recycling New C&I Buildings

Food Waste Prevention Plastic Waste Prevention Incineration with Pre-sorting New Domestic Buildings

Residual Biostabilisation Electric Commercial Transport C&I District Heating (Biogas) Domestic District Heating (Biogas)

Domestic District Heating (Waste) C&I District Heating (Waste) Electric Vehicles Biogas Commercial Transport

C&I ASHP Domestic ASHP Domestic Solar Heating C&I Solar Heating

Solar PV Domestic Energy Efficiency Retrofits

58 21/11/2019

Table 0-34: MAC Table (Local Authority, Consumption, Excluding Transfers)




1 Increase Active Transport 78,277 -75,070,568 -959 782 Personal Transport Reduction 70,449 -51,612,100 -733 149


22,455 -7,837,363 -349 171

4 Dietary Change 135,320 -29,526,031 -218 3075 Reduced Commercial Transport 20,137 -3,959,329 -197 327


44,653 -3,173,754 -71 371

7 Higher Municipal Recycling 23,355 -1,319,037 -56 3958 New C&I Buildings 19,929 -841,632 -42 4159 Food Waste Prevention 6,383 -112,628 -18 42110 Plastic Waste Prevention 3,802 -57,960 -15 42511 Incineration with Pre-sorting 94,766 4,235,617 45 52012 New Domestic Buildings 19,068 2,793,899 147 53913 Residual Biostabilisation 15,020 2,561,268 171 55414 Electric Commercial Transport 154,580 27,283,349 176 70815 C&I District Heating (Biogas) 10,713 3,501,363 327 71916 Domestic District Heating (Biogas) 11,520 3,793,450 329 73017 Domestic District Heating (Waste) 6,169 2,398,410 389 73718 C&I District Heating (Waste) 5,362 2,106,323 393 74219 Electric Vehicles 194,806 84,176,083 432 93720 Biogas Commercial Transport 193,375 103,750,899 537 1,13021 C&I ASHP 21,314 12,379,836 581 1,15122 Domestic ASHP 208,063 121,310,718 583 1,36023 Domestic Solar Heating 14,771 8,746,039 592 1,37424 C&I Solar Heating 1,807 1,087,686 602 1,37625 Solar PV 48,025 44,007,031 916 1,42426 Domestic Energy Efficiency Retrofits 128,878 133,911,939 1,039 1,55327 Increase Public Transport 52,365 58,325,538 1,114 1,60528 Hydrogen Commercial Transport 144,332 351,153,646 2,433 1,750


Table 0-35: MAC Table (Direct, Production, Including Transfers)




1 Dietary Change 90 -206,963 -2,291 02 Increase Active Transport 985 -1,364,358 -1,386 13 Personal Transport Reduction 1,034 -1,222,054 -1,182 24 Reduced Commercial Transport 841 -500,655 -595 35 Food Waste Prevention 24 -5,805 -245 36 New C&I Buildings 514 -117,636 -229 37 Higher Municipal Recycling 360 -67,991 -189 48 Electric Commercial Transport 6,737 -825,704 -123 119 Plastic Waste Prevention 98 -2,988 -31 1110 New Domestic Buildings 4,468 694,997 156 1511 Electric Vehicles 2,526 440,875 175 1812 Biogas Commercial Transport 8,113 2,649,683 327 2613 Residual Biostabilisation 351 132,023 377 2614 C&I District Heating (Biogas) 1,808 728,711 403 2815 Domestic District Heating (Biogas) 1,921 820,705 427 3016 Incineration with Pre-sorting 429 218,328 509 3017 Domestic Solar Heating 2,037 1,294,637 635 3218 Domestic ASHP 29,007 19,947,145 688 6119 C&I Solar Heating 68 51,214 756 6120 C&I ASHP 1,621 1,253,450 773 6321 Solar PV 6,179 6,484,628 1,049 6922 Domestic Energy Efficiency Retrofits 17,777 24,249,675 1,364 8723 Increase Public Transport 667 922,442 1,384 8824 Hydrogen Commercial Transport 6,373 15,991,610 2,509 94

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Table 0-36: MAC Table (Direct, Consumption, Including Transfers)




1 Increase Active Transport 1,013 -1,364,358 -1,347 12 Personal Transport Reduction 1,063 -1,222,054 -1,149 23 Reduced Commercial Transport 865 -500,655 -579 34 Dietary Change 903 -206,963 -229 45 New C&I Buildings 604 -117,636 -195 46 Electric Commercial Transport 6,640 -825,704 -124 117 Higher Municipal Recycling 1,003 -67,991 -68 128 Food Waste Prevention 274 -5,805 -21 129 Plastic Waste Prevention 163 -2,988 -18 1310 Incineration with Pre-sorting 4,071 218,328 54 1711 New Domestic Buildings 5,109 694,997 136 2212 Electric Vehicles 2,521 440,875 175 2413 Residual Biostabilisation 645 132,023 205 2514 C&I District Heating (Waste) 846 238,860 282 2615 Biogas Commercial Transport 8,306 2,649,683 319 3416 Domestic District Heating (Waste) 974 330,855 340 3517 C&I District Heating (Biogas) 1,691 728,711 431 3718 Domestic District Heating (Biogas) 1,819 820,705 451 3919 Domestic Solar Heating 2,332 1,294,637 555 4120 Domestic ASHP 32,845 19,947,145 607 7421 C&I Solar Heating 78 51,214 660 7422 C&I ASHP 1,837 1,253,450 682 7623 Solar PV 6,788 6,484,628 955 8224 Domestic Energy Efficiency Retrofits 20,345 24,249,675 1,192 10325 Increase Public Transport 678 922,442 1,361 10326 Hydrogen Commercial Transport 6,200 15,991,610 2,579 110


Table 0-37: MAC Table (Indirect, Production, Including Transfers)




1 Dietary Change 45 -103,043 -2,291 02 Increase Active Transport 163 -226,429 -1,386 0

3 Personal Transport Reduction 172 -202,812 -1,182 0


4,969 -4,618,525 -929 5

5 Reduced Commercial Transport 841 -500,655 -595 6


7 New C&I Buildings 514 -117,636 -229 7


10,362 -2,108,045 -203 17

9 Higher Municipal Recycling 360 -67,991 -189 1710 Electric Commercial Transport 6,737 -825,704 -123 2411 Plastic Waste Prevention 98 -2,988 -31 2412 New Domestic Buildings 4,468 694,997 156 2913 Electric Vehicles 419 73,168 175 2914 Biogas Commercial Transport 8,113 2,649,683 327 3715 Residual Biostabilisation 351 132,023 377 3816 C&I District Heating (Biogas) 3,068 1,236,742 403 4117 Domestic District Heating (Biogas) 3,261 1,392,872 427 4418 Incineration with Pre-sorting 429 218,328 509 4419 Domestic Solar Heating 3,458 2,197,212 635 4820 Domestic ASHP 49,229 33,853,578 688 9721 C&I Solar Heating 68 51,214 756 9722 C&I ASHP 1,621 1,253,450 773 9923 Solar PV 10,429 10,945,173 1,049 10924 Domestic Energy Efficiency Retrofits 30,171 41,155,676 1,364 13925 Increase Public Transport 111 153,088 1,384 13926 Hydrogen Commercial Transport 6,373 15,991,610 2,509 146

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Table 0-38: MAC Table (Indirect, Consumption, Including Transfers)




1 Increase Active Transport 168 -226,429 -1,347 02 Personal Transport Reduction 176 -202,812 -1,149 0


6,016 -4,618,525 -768 6

4 Reduced Commercial Transport 865 -500,655 -579 7

5 Dietary Change 450 -103,043 -229 8

6 New C&I Buildings 604 -117,636 -195 8

7 Domestic Energy Behaviour Change Campaign 11,963 -2,108,045 -176 20

8 Electric Commercial Transport 6,640 -825,704 -124 27

9 Higher Municipal Recycling 1,003 -67,991 -68 2810 Food Waste Prevention 274 -5,805 -21 2811 Plastic Waste Prevention 163 -2,988 -18 2812 Incineration with Pre-sorting 4,071 218,328 54 3213 New Domestic Buildings 5,109 694,997 136 3814 Electric Vehicles 418 73,168 175 3815 Residual Biostabilisation 645 132,023 205 3916 C&I District Heating (Waste) 1,437 405,384 282 4017 Biogas Commercial Transport 8,306 2,649,683 319 4818 Domestic District Heating (Waste) 1,653 561,515 340 5019 C&I District Heating (Biogas) 2,870 1,236,742 431 5320 Domestic District Heating (Biogas) 3,086 1,392,872 451 5621 Domestic Solar Heating 3,957 2,197,212 555 6022 Domestic ASHP 55,744 33,853,578 607 11623 C&I Solar Heating 78 51,214 660 11624 C&I ASHP 1,837 1,253,450 682 11825 Solar PV 11,458 10,945,173 955 12926 Domestic Energy Efficiency Retrofits 34,529 41,155,676 1,192 16427 Increase Public Transport 112 153,088 1,361 16428 Hydrogen Commercial Transport 6,200 15,991,610 2,579 170


Table 0-39: MAC Table (Local Authority, Production, Including Transfers)




1 Dietary Change 13,532 -31,002,332 -2,291 142 Increase Active Transport 76,099 -105,446,129 -1,386 90

3 Personal Transport Reduction 68,489 -80,955,418 -1,182 158


18,547 -17,238,616 -929 177



7 New C&I Buildings 16,951 -3,879,260 -229 214


38,676 -7,868,264 -203 252

9 Higher Municipal Recycling 8,384 -1,582,844 -189 26110 Electric Commercial Transport 156,835 -19,222,597 -123 41811 Plastic Waste Prevention 2,275 -69,552 -31 42012 New Domestic Buildings 16,676 2,594,071 156 43713 Electric Vehicles 195,238 34,073,589 175 63214 Biogas Commercial Transport 188,880 61,685,312 327 82115 Residual Biostabilisation 8,161 3,073,521 377 82916 C&I District Heating (Biogas) 11,453 4,616,130 403 84017 Domestic District Heating (Biogas) 12,170 5,198,885 427 85318 Incineration with Pre-sorting 9,977 5,082,740 509 86219 Domestic Solar Heating 12,907 8,201,079 635 87520 Domestic ASHP 183,749 126,358,260 688 1,05921 C&I Solar Heating 1,576 1,192,279 756 1,06122 C&I ASHP 18,807 14,545,911 773 1,08023 Solar PV 43,713 45,876,790 1,049 1,12324 Domestic Energy Efficiency Retrofits 112,613 153,613,294 1,364 1,23625 Increase Public Transport 51,528 71,292,077 1,384 1,28726 Hydrogen Commercial Transport 148,370 372,288,841 2,509 1,436

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Table 0-40: MAC Table (Local Authority, Consumption, Including Transfers)




1 Increase Active Transport 78,277 -105,446,129 -1,347 782 Personal Transport Reduction 70,449 -80,955,418 -1,149 149


22,455 -17,238,616 -768 171


5 Dietary Change 135,320 -31,002,332 -229 327

6 New C&I Buildings 19,929 -3,879,260 -195 347

7 Domestic Energy Behaviour Change Campaign 44,653 -7,868,264 -176 391

8 Electric Commercial Transport 154,580 -19,222,597 -124 546

9 Higher Municipal Recycling 23,355 -1,582,844 -68 56910 Food Waste Prevention 6,383 -135,153 -21 57611 Plastic Waste Prevention 3,802 -69,552 -18 57912 Incineration with Pre-sorting 94,766 5,082,740 54 67413 New Domestic Buildings 19,068 2,594,071 136 69314 Electric Vehicles 194,806 34,073,589 175 88815 Residual Biostabilisation 15,020 3,073,521 205 90316 C&I District Heating (Waste) 5,362 1,513,095 282 90817 Biogas Commercial Transport 193,375 61,685,312 319 1,10218 Domestic District Heating (Waste) 6,169 2,095,850 340 1,10819 C&I District Heating (Biogas) 10,713 4,616,130 431 1,11920 Domestic District Heating (Biogas) 11,520 5,198,885 451 1,13021 Domestic Solar Heating 14,771 8,201,079 555 1,14522 Domestic ASHP 208,063 126,358,260 607 1,35323 C&I Solar Heating 1,807 1,192,279 660 1,35524 C&I ASHP 21,314 14,545,911 682 1,37625 Solar PV 48,025 45,876,790 955 1,42426 Domestic Energy Efficiency Retrofits 128,878 153,613,294 1,192 1,55327 Increase Public Transport 52,365 71,292,077 1,361 1,60528 Hydrogen Commercial Transport 144,332 372,288,841 2,579 1,750


A.3.0 Acronyms and Units

Term Explanation

BDA British Dietary Association

BEIS (Department of) Business, Energy, and Industrial Strategy

C&I Commercial and industrial

CCGT Combined cycle gas turbine

CHP Combined Heat and Power

CRC Carbon Reduction Commitment

DECC Department of Energy and Climate Change

DfT Department for Transport

GHG Greenhouse Gas

GHGE Greenhouse Gas Emissions

HGV Heavy Goods Vehicle

Hhld Household

ICE Internal Combustion Engine

Kilolitre One thousand litres

Kilotonne One thousand tonnes

Mp.km Mega-person-kilometre

MAC Marginal Abatement Cost

MACC Marginal Abatement Cost Curve

MBT Mechanical and biological treatment

MWh Megawatt-hour

NEED National Energy Efficiency Data

Ofgem Office of Gas and Electricity Markets

ONS Office for National Statistics

PV Photovoltaic

Sphere of Influence A group of emissions sources over which an organisation has the same level of power to effect changes.

tCO2e Tonne of carbon dioxide equivalent

Technical Potential The extent to which a future (low-carbon) process can displace current (high-carbon) process

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Term Explanation

UK United Kingdom

UNFCCC United Nations Framework Convention on Climate Change

Unit (as assigned to each process)

A functional unit upon the basis of which quantitative data for each process is presented

Utility Electricity, gas (or biogas), diesel, or petrol.

WRAP Waste and Resources Action Programme

Documents

Technical Appendix 2019 Abatement Cost Curve Model Local ...... · Eunomia Research & Consulting has taken due care in the preparation of this report to ... V0.4 18/11/19 Ann Ballinger