2024 Government Gas Conversion Factors for company reporting Methodology Paper for Conversion factors Final Report June 2024 * * * OGL © Crown copyright 2024 This publication is licensed under the terms of the Open Government Licence v3.0 except where otherwise stated. To view this licence, visit [www.nationalarchives.gov.uk/doc/open-government-licence/](http://www.nationalarchives.gov.uk/doc/open-government-licence/) or write to the Information Policy Team, The National Archives, Kew, London TW9 4DU, or email: [psi@nationalarchives.gsi.gov.uk](mailto:psi@nationalarchives.gsi.gov.uk). Any enquiries regarding this publication should be sent to [GreenhouseGas.Statistics@energysecurity.gov.uk](mailto:GreenhouseGas.Statistics@energysecurity.gov.uk). This document has been produced by Rebekah Bramwell, Dom Ingledew, Eirini Karagianni, Joe London, Joanna MacCarthy, Peter Brown, Paddy Mullen, Charles Walker, Judith Bates, Nik Hill, Dan Willis, Jason Wong (Ricardo) and Billy Harris (WRAP) for the Department for Energy Security and Net Zero (DESNZ). * * * Contents Glossary.....10 1. General Introduction.....13 Overview of major changes since the previous update.....15 Conversion factors update frequency.....16 2. Fuel Emission Factors.....19 Section summary.....19 Summary of changes since the previous update.....19 Direct Emissions.....19 Indirect/WTT Emissions from Fuels.....20 3. UK Electricity, Heat and Steam Emission Factors.....25 Section summary.....25 Summary of changes since the previous update.....25 Direct Emissions from UK Grid Electricity.....26 Indirect/WTT Emissions from UK Grid Electricity.....35 Conversion factors for the Supply of Purchased Heat or Steam.....35 Summary of Method 1: 1/3: 2/3 Method (DUKES).....36 Calculation of CO₂ Emissions Factor for CHP Fuel Input, FuelMixCO₂factor.....36 Calculation of Non-CO₂ and Indirect/WTT Emissions Factor for Heat and Steam * * * Direct Emissions from Taxis ..... 66 Direct Emissions from Vans/Light Goods Vehicles (LGVs) ..... 66 Plug-in Hybrid Electric and Battery Electric Vans (xEVs) ..... 69 Direct Emissions from Buses ..... 70 Direct Emissions from Motorcycles ..... 72 Direct Emissions from Passenger Rail ..... 74 International Rail (Eurostar) ..... 74 National Rail ..... 75 Light Rail ..... 75 London Underground ..... 76 Indirect/WTT Emissions from Passenger Land Transport ..... 77 Cars, Vans, Motorcycles, Taxis, Buses and Ferries ..... 77 Rail ..... 77 6. Freight Land Transport Emission Factors ..... 78 Section summary ..... 78 Summary of changes since the previous update ..... 78 Direct Emissions from Heavy Goods Vehicles (HGVs) ..... 78 Direct Emissions from Vans/Light Goods Vehicles * * * Taking Account of Seating Class Factors ..... 95 Freight Air Transport Direct CO₂ Emission Factors ..... 96 Conversion factors for Dedicated Air Cargo Services ..... 97 Conversion factors for Freight on Passenger Services ..... 99 Average Conversion factors for All Air Freight Services ..... 100 Air Transport Direct Conversion factors for CH₄ and N₂O ..... 100 Emissions of CH₄ ..... 100 Emissions of N₂O ..... 101 Indirect/WTT Conversion factors from Air Transport ..... 102 Other Factors for the Calculation of GHG Emissions ..... 102 Great Circle Flight Distances ..... 102 Non-CO₂ impacts and Radiative Forcing ..... 103 9\. Bioenergy and Water ..... 107 Section summary ..... 107 Summary of changes since the previous update ..... 107 General Methodology ..... 108 Water ..... 108 B $$ \\mathrm {C O} \_ {2} $$ * * * 13. Fuel Properties ..... 123 Section summary ..... 123 Summary of changes since the previous update ..... 123 General Methodology ..... 123 14. SECR kWh Conversion factors ..... 125 Section summary ..... 125 Summary of changes since the previous update ..... 126 General Methodology ..... 126 15. Homeworking ..... 127 Section summary ..... 127 General Methodology ..... 127 References ..... 129 Appendix 1. Additional Methodological Information on the Material Consumption/Use and Waste Disposal Factors ..... 136 1.1 Data Quality Requirements ..... 136 1.2 Data Sources ..... 137 1.3 Use of data below the set quality standard ..... 137 1.4 Wood and Paper data ..... 138 1.5 Excluded Materials and Products ..... 138 * * * Tables Table 1: summary of conversion factors that are in AR4 or/and AR5 basis GWPs ........................17 Table 2: Related worksheets to the fuel conversion factors...........................................................19 Table 3: Liquid biofuels for transport consumption.........................................................................21 Table 4: Imports of LNG into the UK as a share of imports and net total natural gas supply..........22 Table 5: Basis of the indirect/WTT emissions factors for different fuels.........................................23 Table 6: Related worksheets to UK electricity and heat & steam emission factors.........................25 Table 7: Base electricity generation emissions data......................................................................28 Table 8: Base electricity generation conversion factors (excluding imported electricity).................30 Table 9: Base electricity generation emissions factors (including imported electricity)...................32 Table 10: Fuel types and associated emissions factors used in the determination of FuelMixCO2factor ......................................................................................................................................37 Table 11: Heat/Steam CO2 emission factor for DUKES 1/3 2/3 method.........................................39 Table 12: Related worksheets to passenger land transport emission factors................................. 44 Table 13: DfT's Table BUS03a\_km - Passenger kilometres on local bus services by metropolitan area status and country: Great Britain ...................................................................................45 Table 14: DfT's Table BUS03b - Average bus occupancy on local bus services by metropolitan area status and country: Great Britain ...................................................................................46 Table 15: Average CO2 conversion factors and total registrations by engine size for 2005 to 2022 (based on data sourced from SMMT)........................................................................................47 Table 16: Average ‘real-world’ uplift for the UK applied to gCO2/km data ......................................48 Table 17: Summary of emissions reporting and tables for electric vehicle emission factors...........53 Table 18: xEV car models and their allocation to different market segments................................. 54 Table 19: Summary of key data elements, sources and key assumptions used in the calculation of GHG conversion factors for electric cars and vans................................................................. 61 Table 20: Average car CO2 conversion factors and total registrations by market segment for 2006 to 2022 (based on data sourced from SMMT)....................................................................64 Table 21: New conversion factors for vans for the 2024 GHG Conversion factors.........................68 Table 22: xEV van models and their allocation to different size categories....................................69 Table 23: Key assumptions used in the calculation of CO2 emissions from Urea (aka ‘AdBlue’) use71 Table 24: Conversion factors for buses for the 2024 GHG Conversion factors..............................72 Table 25: Summary dataset on CO2 emissions from motorcycles based on detailed data provided by Clear (2008)..................................................................................................................73 Table 26: GHG emission factors, electricity consumption and passenger km for different tram and light rail services...................................................................................................................76 Table 27 Related worksheets to freight land transport emission factors ........................................78 Table 28: Change in CO2 emissions caused by +/- 50% change in load from the average loading factor of 50%...........................................................................................................................79 $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ * * * Table 29: Typical van freight capacities and estimated average payload.......................................82 Table 30: Utilisation of vehicle capacity by company-owned LGVs: annual average 2003 – 2005 (proportion of total vehicle kilometres travelled).............................................................82 Table 31: Related worksheets to sea transport emission factors...................................................85 Table 32: Assumptions used in the calculation of ferry emission factors........................................86 Table 33: Related worksheets to air transport emission factors.....................................................88 Table 34: Assumptions used in the calculation of revised average CO2 conversion factors for passenger flights for 2024...............................................................................................................89 Table 35: Illustrative short- and long- haul flight distances from the UK.........................................92 Table 36: CO2 conversion factors for alternative freight allocation options for passenger flights based on 2024 GHG Conversion factors.......................................................................................94 Table 37: Final average CO2 conversion factors for passenger flights for 2024 GHG Conversion factors (excluding distance and RF uplifts)................................................................................95 Table 38: CO2 conversion factors by seating class for passenger flights for 2024 GHG Conversion factors (excluding distance and RF uplifts)....................................................................96 Table 39: Revised average CO2 conversion factors for dedicated cargo flights for 2024 GHG Conversion factors (excluding distance and RF uplifts)....................................................................97 Table 40: Assumptions used in the calculation of average CO2 conversion factors for dedicated cargo flights for the 2024 GHG Conversion factors..................................................................98 Table 41: Air freight CO2 conversion factors for alternative freight allocation options for passenger flights for 2024 GHG Conversion factors (excluding distance and RF uplifts)...........................99 Table 42: Final average CO2 conversion factors for all air freight for 2024 GHG Conversion factors (excluding distance and RF uplifts)..............................................................................100 Table 43: Total emissions of CO2, CH4 and N2O for domestic and international aircraft from the UK GHG inventory for 2021........................................................................................................101 Table 44: Final average CO2, CH4 and N2O conversion factors for all air passenger transport for 2024 GHG Conversion factors (excluding distance and RF uplifts) ......................................101 Table 45: Final average CO2, CH4 and N2O conversion factors for air freight transport for 2024 GHG Conversion factors (excluding distance and RF uplifts)................................................102 Table 46: Impacts of radiative forcing according to Lee et al., (2021)..........................................104 Table 47: Aviation non-CO2 emissions equivalence metrics for GWP, GTP and GWP\* taken from Lee et al. (2021).....................................................................................................................105 Table 48: Related worksheets for bioenergy and water emission factors.....................................107 Table 49: Fuel lifecycle GHG Conversion factors for biofuels......................................................109 Table 50: Fuel sources and properties used in the calculation of biomass and biogas emission factors ....................................................................................................................................111 Table 51: Distances and transportation types used in EF calculations.........................................120 Table 52: Distances used in the calculation of emission factors ..................................................122 Table 53: Related worksheets to SECR kWh emissions factors..................................................125 $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C O} \_ {2}, \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ * * * Figures Figure 1: Time series of the mix of UK electricity generation by type.............................................26 Figure 2: Updated GCF 'Real world' uplift values for the UK based on (ICCT, 2017).....................50 Figure 3: Comparison of 'Real world' uplift values from various sources (ICCT, 2017)..................51 Figure 4: Illustration of the relationship of electric range to average electric share of total km for PHEVs assumed in the calculations...........................................................................................63 Figure 5: Boundary of material consumption data sets................................................................119 * * * Glossary | Abbreviation | Definition | | --- | --- | | ANPR | Automatic Number Plate Recognition | | BEV | Battery electric vehicle | | CAA | Civil Aviation Authority | | CBS | National Bureau for Statistics in the Netherlands | | CEF | Carbon emission factor | | CH4 | Methane | | CHP | Combined Heat and Power | | CHPQA | Combined Heat and Power Quality Assurance | | CNG | Compressed natural gas | | CO2 | Carbon dioxide | | DfT | Department for Transport | | DUKES | Digest of UK Energy Statistics | | EEA | European Environment Agency | | EF | Emission factor | | ETS | Emissions Trading System | | FAME | Fatty Acid Methyl Ester | | GCV | Gross calorific value | | GHG | Greenhouse gas | | GVW | Gross vehicle weight | | GWP | Global Warming Potential | | HGVs | Heavy goods vehicles | | HVO | Hydrotreated vegetable oil | | IPCC | Intergovernmental Panel on Climate Change | | LCA | Life cycle assessment | | LGVs | Light goods vehicles | | LNG | Liquefied natural gas | | LPG | Liquefied petroleum gas | | ME | Methyl-ester | | MTBE | Methyl tert-butyl ether | | NAEI | National Atmospheric Emissions Inventory | | NCV | Net calorific value | | NEDC | New European Driving Cycle | | NOx | Nitrogen oxides | | N2O | Nitrous oxide | | ORR | Office of Rail and Road | | PHEV | Plug-in hybrid electric vehicle | | RF | Radiative forcing | | RoPax | Roll on/roll off a passenger | | RTE | French transmission system operator | | RTFO | Renewable Transport Fuel Obligation | | RW | Real-world | | SEAI | Sustainable Energy Authority of Ireland | | SECR | Streamlined Energy and Carbon Reporting | | SMMT | Society of Motor Manufacturers and Traders | | T&D | Transmission & Distribution | | TfL | Transport for London | | TTW | Tank-To-Wheel (i.e. direct emissions at the point of use) | | UK GHGI | UK's Greenhouse Gas Inventory | | UNFCCC | United Nations Framework Convention on Climate Change | | WLTP | Worldwide Harmonised Light Vehicle Test Procedure | | WTT | Well-To-Tank(i.e.upstream emissions from the production of fuel or electricity) | | WTW | Well-To-Wheel(=Well-To-Tank+Tank-To-Wheel) | | xEV | Generic term for battery electric vehicles(BEV), plug-in hybrid electric vehicles(PHEV),range-extended electric vehicles(REEV)和 fuel cell electric vehicles(FCEV) | * * * 1. General Introduction 1.1. Greenhouse gases (GHGs) can be measured by recording emissions at source, by continuous emissions monitoring or by estimating the amount emitted using activity data (such as the amount of fuel used) and applying relevant conversion factors (e.g. calorific values, emission factors, etc.). 1.2. These conversion factors allow organisations and individuals to calculate GHG emissions from a range of activities, including energy use, water consumption, waste disposal and recycling, and transport activities. For instance, a conversion factor can be used to calculate the amount of GHG emitted as a result of burning a particular quantity of oil in a heating boiler. 1.3. Chapters 2 to 15 present the conversion factors for a single type of emissionsreleasing activity (for example, using electricity or driving a passenger vehicle). These emissions-releasing activities are categorised into three groups known as scopes. Each activity is listed as either Scope 1, Scope 2 or Scope 3. a) Scope 1 (direct) emissions are those from activities owned or controlled by your organisation. Examples of Scope 1 emissions include emissions from combustion in owned or controlled boilers, furnaces and vehicles; and emissions from chemical production in owned or controlled process equipment. b) Scope 2 (energy indirect) emissions are those released into the atmosphere that b) Scope 2 (energy indirect) emissions are those released into the atmosphere that is associated with the consumption of purchased electricity, heat, steam and cooling. These indirect emissions are a consequence of an organisation’s energy use but occur at sources the organisation does not own or control. c) Scope 3 (other indirect) emissions are a consequence of your actions that occur energy use but occur at sources the organisation does not own or control. c) Scope 3 (other indirect) emissions are a consequence of your actions that occur at sources an organisation does not own or control and are not classed as Scope 2 emissions. Examples of Scope 3 emissions are business travel by means not owned or controlled by an organisation, waste disposal, materials or fuels that an organisation purchase. Deciding if emissions from a vehicle, office or factory that you use are Scope 1 or Scope 3 may depend on how organisations define their operational boundaries. Scope 3 emissions can be from activities that are upstream or downstream of an organisation. More information on Scope 3 and other aspects of reporting can be found in the Greenhouse Gas Protocol Corporate Standard1. 1.4. The 2024 UK Government Greenhouse Gas Conversion factors for Company Reporting2 (hereafter the 2024 UK GHG Conversion factors) represent the current official set of UK government conversion factors. These factors are suitable for use by UK-based organisations of all sizes and international organisations reporting on their UK operations. Therefore, the scope of the factors is defined such that it is relevant to Streamlined Energy and Carbon Reporting (SECR) * * * regulations. The factors may also be used for other purposes, but users do this at their own risk. 1.5. The UK GHG Conversion Factors have been developed as part of the NAEI (National Atmospheric Emissions Inventory) contract, managed by Ricardo, which includes the: b) UK Greenhouse Gas Inventory (GHGI) a) UK Air Quality Pollutant Inventory (AQPI) b) UK Greenhouse Gas Inventory (GHGI) 1.6. The UK GHGI for 2022 (Ricardo, 2024) is available at: [https://naei.beis.gov.uk/reports/reports?report\_id=1135](https://naei.beis.gov.uk/reports/reports?report_id=1135) 1.7. Values for the non-carbon dioxide (CO2) GHGs, methane (CH4) and nitrous oxide (N2O), are presented as CO2 equivalents (CO2e), using Global Warming Potential (GWP) factors from the Intergovernmental Panel on Climate Change (IPCC)’s fifth assessment report (IPCC, 2014)(GWP for CH4 = 28, GWP for N2O = 265). This is consistent with reporting under the United Nations Framework Convention on Climate Change (UNFCCC) and consistent with the UK GHGI, upon which the 2024 GHG Conversion Factors are based. Although the IPCC has prepared a newer version, the methods have not yet been officially accepted for use under the UNFCCC. $$ \\left(\\mathrm {C O} \_ {2}\\right) $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C H} \_ {4} = 2 8 $$ 1.8. The 2024 GHG Conversion Factors are for use with activity data that falls entirely or mostly within 2024. The factors will continue to be improved and updated on an annual basis with the next publication in June 2025. Further information about the 2024 GHG Conversion factors together with previous methodology papers is available at: [https://www.gov.uk/government/collections/government-conversionfactors-for-company-reporting](https://www.gov.uk/government/collections/government-conversionfactors-for-company-reporting). 1.9. It is important to note that the primary aim of this methodology paper is to provide information on the methodology used in creating the UK Government GHG Conversion factors for Company Reporting. This report provides the methodological approach, the key data sources and the assumptions used to define the conversion factors provided in the 2024 GHG Conversion factors. The report aims to expand and complement the information already provided in the data tables themselves. However, it is not intended to be an exhaustively detailed explanation of every calculation performed (this is not practical/possible), nor is it intended to provide guidance on the practicalities of reporting for organisations. Rather, the intention is to provide an overview with key information so that the basis of the conversion factors provided can be better understood and assessed. 1.10. Detailed guidance on how the conversion factors provided should be used is contained in the “Introduction” worksheet of the 2024 GHG Conversion factors set. This guidance must be referred to before using the conversion factors and provides important context for the description of the methodologies presented in this report and in the table footnotes. * * * Overview of major changes since the previous update 1.11. Major changes and updates in terms of methodological approach from the 2024 update are summarised below. All other updates are essentially revisions of the previous year's data based on new/improved data whilst using existing calculation methodologies (i.e. using a similar methodological approach as for the 2023 update): a) Utility factors for PHEVs (plug-in hybrid electric vehicles) are updated to align to the real-world data and better reflect the actual emissions from those vehicles. The utility factor represents the proportion of distance travelled in electric mode versus the total distance travelled. The real-world performance of most PHEVs is significantly different from that defined in regulatory requirements. Currently, utility factors for PHEV within the electric vehicle model (xEVs) are calculated based on regulatory formula, and this approach underestimates emissions in real world. From 2025, the EU will significantly reduce the utility factors for PHEVs to fully align them with the real-world data collected from various studies. The utility factors for the electric operation of PHEVs have been revised downwards, to reflect the average proportion of time that vehicles are in the electric operation mode in real-world condition. In the 2024 update, due to the updated PHEV utility factors, the fraction of distance that PHEVs use predominantly the battery has decreased significantly, and the fraction of distance that PHEV travel using the fuel engine has increased. All the conversion factors that are related to the electricity used by PHEVs have therefore decreased significantly whereas all the factors related to the direct fuel emissions from PHEVs have increased. b) Electric LGVs (light goods vehicles) registered in the UK were predominantly Battery Electric Vehicles (BEV) and there were only a few PHEV LGVs models on the market. As the number of PHEV LGVs has increased over the years, in the 2024 update conversion factors for PHEV LGVs have now been included. c) In the 2024 update, regulatory data for LGVs and xEVs for the year 2021 is d) Material factors have been updated with the latest data. Wood, plastic, paper, and the manufacturing element of the concrete factor were updated with the latest data from the ecoinvent lifecycle database. Scrap metal and steel cans factors were updated with the latest data from WorldSteel. Closed loop factors for wood have been removed as the historical figure was not representative of closed loop recycling processes and a suitable replacement has not been sourced. All recycling processes that involve adding binders or adhesives to the wood at end of life (e.g. manufacture of fibreboard) are covered under the open c) In the 2024 update, regulatory data for LGVs and xEVs for the year 2021 is available and is provided by the UK Vehicle Certification Agency (VCA). As a result, new registration data for LGV and xEVs for the year 2022 is taken from the UK Department for Transport (DfT) and is matched with model specific data from the 2021 VCA dataset such as CO2 emissions, mass, capacity, etc. d) Material factors have been updated with the latest data. Wood, plastic, paper, loop recycling factor. Conversion factors update frequency 1.12. The scope of the conversion factors has expanded over time (mainly due to the addition of new factors and an increased quality assurance (QA) burden). In light of this, a risk-based approach has been adopted which focuses on delivering accurate conversion factors for high-emitting UK sources that vary over time, and reflect changes in key sources for most companies, including electricity, natural gas, waste management, road transport fuels and fleet. However, less focus has been invested on conversion factors for minor sources and minor pollutants, where no or little new reference data exists and / or where there is little variation over time. In these areas, the frequency of updating the conversion factor reflects the level of risk associated with retaining an historical value. 1.13. The conversion factors for high-emitting UK sources vary over time, reflect changes in key sources for most companies and are therefore updated annually or periodically. In this latest release, the Conversion Factors that are updated to reflect latest UK evidence (for example on fuel mix, transport fleet, vehicle utilisation) include: • Fuels: Natural Gas, Diesel, Petrol, Coal, CNG and LNG • Bioenergy • Bioenergy • Electricity use • Electricity use • Passenger vehicles, delivery vehicles, and business travel: Cars, HGVs, LGVs, • Passenger vehicles, delivery vehicles, and business travel: Cars, HGVs, LGVs, xEVs & Buses • Water Supply and Water Treatment3 • Water Supply and Water Treatment3 • Material Use & Waste management • Material Use & Waste management • Outside of scopes4 1.14. Conversion Factors that have been held constant from the 2023 release (aligned with AR5 GWPs values): • Outside of scopes4 • Heat and Steam6 • Aviation7 * * * 2024 Government greenhouse gas conversion factors for company reporting: Methodology paper • Homeworking (held constant but aligned with AR5 GWPs values) • Hotel stay • Hotel stay 1.16. Conversion Factors that have been held constant since the 2021 release (they were in the AR4 basis) but are now aligned with AR5 GWPs, include: • All methane (CH4) and nitrous oxide (N2O) conversion factors • Fuels: butane, LPG, other petroleum gas, propane, aviation spirit, aviation $$ \\left(\\mathrm {N} \_ {2} \\mathrm {O}\\right) $$ • Fuels: butane, LPG, other petroleum gas, propane, aviation spirit, aviation turbine fuel, burning oil, gas oil, fuel oil, lubricants, naphtha, processed fuel oils - residual oil, processed fuel oils - distillate oil, refinery miscellaneous, waste oils, marine gas oil, marine fuel oil, coking coal, petroleum coke • Passenger vehicles, business travel - land, sea: taxis, motorcycles, rail, • Passenger vehicles, business travel - land, sea: taxis, motorcycles, rail, shipping • Well-to-Tank factors8 • Well-to-Tank factors8 1.17. Table 1 shows a summary of which factors are still in an AR4 basis and which have been aligned to AR5 GWPs. These details are covered in “summary of changes since the previous update” in their sections. Table 1: summary of conversion factors that are in AR4 or/and AR5 basis GWPs | | In AR4 basis | In AR5 basis | | --- | --- | --- | | Fuel | | √ | | WTT Fuel | | √ | | UK electricity | | √ | | Transmission & Distribution | | √ | | WTT UK electricity | | √ | | WTT Transmission & Distribution | | √ | | Heat & Steam | | √ | | WTT Heat & Steam | | √ | | Refrigerant and Processes9 | | √ | | Passenger Land Transport | | √ | | WTT Passenger Land Transport | | √ | | Freight Land Transport | | √ | | WTT Freight Land Transport | | √ | | Sea Transport | | √ | | WTT Sea Transport | | √ | | Air Transport | | √ | | WTT Air Transport | | √ | | Bioenergy | √ | | | WTT Bioenergy | √ | | | Water Supply&Treatment | | √ | | Hotel Stay10 | √ | √ | | Material Use | √ | | | Waste Disposal | | √ | | Homeworking | | √ | * * * 2. Fuel Emission Factors Section summary 2.1. The fuels conversion factors should be used for primary fuel sources combusted at a site or in an asset owned or controlled by the reporting organisation. Well-totank (WTT) factors should be used to account for the upstream Scope 3 emissions associated with extraction, refining and transportation of the raw fuel sources to an organisation’s site (or asset), prior to their combustion. 2.2. The fuel properties can be used to determine the typical calorific values/densities of the most common fuels. The fuel properties should be utilised to change units of energy, mass, volume, etc. into alternative units; this is particularly useful where an organisation is collecting data in units of measure that do not have a fuel conversion factor that can be directly used to determine a carbon emission total. where the related worksheets to fuel conversion factors are available in the online spreadsheets of the UK GHG Conversion factors. 2.3. Table 2 shows where the related worksheets to fuel conversion factors are available in the online spreadsheets of the UK GHG Conversion factors. Table 2: Related worksheets to the fuel conversion factors | Worksheet name | Full set | Condensed set | | --- | --- | --- | | Fuels | Y | Y | | WTT- fuels | Y | N | | Fuel properties | Y | Y | | Conversions | Y | Y | Summary of changes since the previous update 2.6. The CO2 emissions factors are based on the same factors used in the UK GHGI and are essentially independent of application as they assume that all fuel is fully oxidised and combusted. These factors have been updated for natural gas, coal, petrol and diesel to be in line with the latest UK GHGI. Emissions of CH4 and N2O 2.4. No methodological updates have been made to the calculation of conversion factors for fuels in the 2024 update. $$ \\mathrm {C O} \_ {2} $$ can vary to some degree for the same fuel depending on the use (e.g. conversion factors for gas oil used in rail, shipping, non-road mobile machinery or different scales/types of stationary combustion plants can all be different). The figures for fuels in the 2024 GHG Conversion factors are based on an activity-weighted average of all the different CH4 and N2O conversion factors from the 2022 GHGI. 2.7. The majority of conversion factors from the GHGI are on a net energy basis (t/TJ), and have been converted into different energy, volume and mass based units using the information on Gross and Net Calorific Values (CV) (see definition of Gross CV and Net CV in the footnote below11) used in the GHGI or for some fuels, DESNZ’s Digest of UK Energy Statistics (DUKES) (DESNZ, 2023). 2.8. There are three tables in the 2024 GHG Conversion factors, the first of which provides conversion factors for gaseous fuels, the second for liquid fuels and the final table provides the conversion factors for solid fuels. 2.9. When making calculations based on energy use, it is important to check (e.g. with your fuel supplier) whether these values were calculated on a Gross CV or Net CV your fuel supplier) whether these values were calculated on a Gross CV or Net CV basis and use the appropriate factor. Natural gas consumption figures quoted in kilowatt hours (kWh) by suppliers in the UK are generally calculated (from the volume of gas used) on a Gross CV basis (National Grid, 2021). Therefore, the emission factor for energy consumption on a Gross CV basis should be used by default for calculation of emissions from natural gas in kWh, unless your supplier specifically states they have used Net CV basis in their calculations instead. your fuel supplier) whether these values were calculated on a Gross CV or Net CV basis and use the appropriate factor. Natural gas consumption figures quoted in kilowatt hours (kWh) by suppliers in the UK are generally calculated (from the volume of gas used) on a Gross CV basis (National Grid, 2021). Therefore, the emission factor for energy consumption on a Gross CV basis should be used by default for calculation of emissions from natural gas in kWh, unless your supplier specifically states they have used Net CV basis in their calculations instead. Indirect/WTT Emissions from Fuels 2.11. These fuel lifecycle emissions (also sometimes referred to as ‘Well-To-Tank’, or simply WTT, emissions usually in the context of transport fuels) are the emissions ‘upstream’ from the point of use of the fuel. They result from the extraction, transport, refining, purification or conversion of primary fuels to fuels for direct use by end-users and the distribution of these fuels. They are classed as Scope 3 according to the GHG Protocol. 2.12. For the upstream conversion factors relating to diesel, petrol, kerosene, natural gas, CNG, and LNG, data are taken from a study by Exergia (Exergia et al., 2015); please refer to Table 5 for definitions of acronyms. As the Exergia report (Exergia et al., 2015) does not estimate upstream emissions for other fuels the JEC Well-To-Wheels study is used for coal, LPG, and lubricants; data are taken from (JEC WTW v5, 2020) as this is the most recent update for this source. Data for naphtha is taken from an older version of the JEC report (JEC WTW v4a, 2014) because it is not present in the most recent update. 2.13. For fuels covered by the 2024 GHG Conversion factors where no fuel lifecycle emission factor was available in either source, these were estimated based on similar fuels, according to the assumptions in Table 5. 2.14. WTT emissions for petrol, diesel and kerosene in the Exergia study (Exergia et al., 2015), used within the 2024 GHG Conversion factors set, are based on: • Detailed modelling of upstream emissions associated with 35 crude oils used in EU refining, which accounted for 88% of imported oil in 2012. • Estimates of the emissions associated with the transport of these crude oils to • Estimates of the emissions associated with the transport of these crude oils to EU refineries by sea and pipeline, based on the location of ports and refineries. • Emissions from refining, modelled on a country by country basis, based on the • Emissions from refining, modelled on a country by country basis, based on the specific refinery types in each country. An EU average is then calculated based on the proportion of each crude oil going to each refinery type. • An estimate of emissions associated with imported finished products from • An estimate of emissions associated with imported finished products from Russia and the US. 2.15. Conversion factors are also calculated for diesel as supplied at public and commercial refuelling stations, by factoring in the WTT component due to biodiesel supplied in the UK as a proportion of the total supply of diesel and biodiesel (4.92% by unit volume, 4.58% by unit energy – see Table 3). These estimates have been made based on the Department for Transport Renewable Fuel Statistics (DfT, 2024). 2.16. Conversion factors are also calculated for petrol as supplied at public and commercial refuelling stations, by factoring in the bioethanol supplied in the UK as a proportion of the total supply of petrol and bioethanol (7.62% by unit volume, 5.03% by unit energy – see Table 3). These estimates have also been made based on Department for Transport Renewable Fuel Statistics (DfT, 2024). Source: Department for Transport, Table RTFO 01. Data used here is from the Renewable fuel statistics 2023 Third provisional tables Table 3: Liquid biofuels for transport consumption | | Total Sales, millions of litres | | Biofuel % Total Sales | | | | --- | --- | --- | --- | --- | --- | | Biofuel | Conventional Fuel | per unit mass | per unit volume | per unit of energy | | | Diesel/Biodiesel | 1400 | 26777 | 5.31% | 4.97% | 4.62% | | Petrol/Bioethanol | 1391 | 15388 | 8.77% | 8.29% | 5.46% | 2.17. Emissions for natural gas, LNG and CNG, used within the 2024 GHG Conversion factors, are based on (Exergia et al., 2015): * * * a) Estimates of emissions associated with supply in major gas producing countries supplying the EU. These include both countries supplying piped gas and countries supplying LNG. b) The pattern of gas supply for each Member State (based on International Energy Agency (IEA) data for natural gas supply in 2012). c) Combining the information on emissions associated with sources of gas, with the data on the pattern of gas supply for each Member State, including the proportion of LNG that is imported. d) For parts of the natural gas supply chain which occur in the UK (transmission and distribution and dispensing of CNG), data from DUKES (DESNZ, 2023) is used to update the emissions for these activities estimated in Exergia. 2.18. The methodology developed allows for the value calculated for gas supply in the UK to be updated annually This allows changes in the sources of imported gas, particularly LNG, to be reflected in the emissions value. 2.19. Information on quantities and source of imported gas are available annually from DUKES12 (DESNZ, 2023a) and can be used to calculate the proportion of gas in UK supply coming from each source. These can then be combined with the emissions factors for gas from each source from the EU study (Exergia et al., 2015), to calculate a weighted emissions factor for UK supply. 2.20. The methodology for calculating the WTT conversion factors for natural gas and CNG is different to the other fuels as it considers the increasing share of UK gas supplied via imports of LNG (which have a higher WTT emission factor than conventionally sourced natural gas) in recent years. Table 4 provides a summary of the information on UK imports of LNG and their significance compared to other sources of natural gas used in the UK grid. Small quantities of imported LNG are now re-exported, so a value for net imports is used in the methodology. The figures in Table 4 have been used to calculate the revised figures for Natural Gas and CNG WTT conversion factors provided in Table 5 below. | Year | LNG % of total natural gas imports(1) | Net Imports as % total UK supply of natural gas(2) | LNG Imports as % total UK supply of natural gas | | --- | --- | --- | --- | | 2011 | 46.0% | 43.7% | 29.5% | | 2012 | 27.1% | 49.2% | 17.5% | | 2013 | 19.1% | 51.7% | 12.1% | | 2014 | 26.0% | 46.3% | 15.9% | | 2015 | 30.2% | 43.4% | 18.8% | | 2016 | 19.8% | 48.2% | 11.6% | | 2017 | 13.0% | 46.7% | 7.7% | | 2018 | 14.3% | 48.0% | 8.2% | | 2019 | 36.9% | 49.1% | 21.7% | | 2020 | 41.8% | 45.6% | 24.7% | | 2021 | 28.5% | 57.5% | 18.8% | | 2022 | 44.9% | 46.0% | 35.5% | Source: DUKES 2023, (1) Table 4.5 - Natural gas imports and exports; (DESNZ, 2023) and (2) Table 4.1 - Commodity balances 2.21. The final combined conversion factors, presented as kilograms of carbon dioxide equivalents per gigajoule on a net calorific value basis (kgCO2e/GJ, Net CV basis), are listed in Table 5. These include WTT emissions of CO2, N2O and CH4. These are converted into other units of energy (e.g. kWh, Therms) and to units of volume and mass using the default Fuel Properties and Unit Conversion factors also provided in the 2024 GHG Conversion factors alongside the emission factor data tables. Table 5: Basis of the indirect/WTT emissions factors for different fuels | Fuel | Indirect/WTT EF(kgCO2e/GJ,Net CV basis) | Source of Indirect/WTT Emission Factor | Assumptions | | --- | --- | --- | --- | | Aviation Spirit | 18.3 | Estimate | Similar to petrol | | Aviation turbine fuel | 15.1 | Exergia,EM Lab and COWI,2015 | Emission factor for kerosene | | Burning oil | 15.1 | Estimate | Same as Kerosene,as above | | Butane | 7.6 | Estimate | Same as LPG | | CNG | 11.7 | Exergia,EM Lab and COWI,2015 | Factors in UK% share LNG imports | | Coal(domestic) | 16.5 | JEC WTW v5(2019) | Emission factor for coal | | Coal(electricity generation) | 16.5 | JEC WTW v5(2019) | Emission factor for coal | | Coal(industrial) | 16.5 | JEC WTW v5(2019) | Emission factor for coal | | Coal(electricity generation-home produced coal only) | 16.5 | JEC WTW v5(2019) | Emission factor for coal | | Coking coal | 16.5 | Estimate | Assume same as factor for coal | | Diesel(100% mineral diesel) | 17.5 | Exergia,EM Lab and COWI,2015 | | | Fuel oil | 17.5 | Estimate | Assume same as factor for diesel | | Gas oil | 17.5 | Estimate | Assume same as factor for diesel | | LPG | 7.6 | JEC WTW v5(2019) | | * * * | Fuel | Indirect/WTT EF(kgCO2e/GJ,Net CV basis) | Source of Indirect/WTT Emission Factor | Assumptions | | --- | --- | --- | --- | | LNG | 20.0 | Exergia,EM Lab and COWI,2015 | | | Lubricants | 27.3 | JEC WTW v5(2019) | | | Marine fuel oil | 17.5 | Estimate | Assume same as factor for fuel oil | | Marine gas oil | 17.5 | Estimate | Assume same as factor for gas oil | | Naphtha | 14.1 | JEC WTW v5(2019) | | | Natural gas | 9.3 | Exergia,EM Lab and COWI,2015 | Factors in UK% share LNG imports | | Other petroleum gas | 6.5 | Estimate | Based on LPG figure, scaled relative to direct emissions ratio | | Petrol(100% mineral petrol) | 18.3 | Exergia,EM Lab and COWI,2015 | | | Petroleum coke | 11.9 | Estimate | Based on LPG figure, scaled relative to direct emissions ratio | | Processed fuel oils-distillate oil | 26.4 | Estimate | Based on lubricants figure | | Processed fuel oils-residual oil | 27.7 | Estimate | Based on lubricants figure | | Propane | 7.6 | Estimate | Same as LPG | | Refinery miscellaneous | 8.5 | Estimate | Based on LPG figure, scaled relative to direct emissions ratio | | Waste oils | 26.5 | Estimate | Based on lubricants figure | Notes: (1) Burning oil is also known as kerosene or paraffin used for heating systems. Aviation Turbine fuel is a similar kerosene fuel specifically refined to a higher quality for aviation. (2) CNG = Compressed Natural Gas is usually stored at 200 bar in the UK for use as an alternative transport fuel. (2) CNG = Compressed Natural Gas is usually stored at 200 bar in the UK for use as an alternative transport fuel. (3) Fuel oil is used for stationary power generation. Also, use this emission factor for similar marine fuel oils. (4) Gas oil is used for stationary power generation and 'diesel' rail in the UK. Also, use this emission factor for similar marine (4) Gas oil is used for stationary power generation and 'diesel' rail in the UK. Also, use this emission factor for similar marine diesel oil and marine gas oil fuels. (5) LNG = Liquefied Natural Gas, usually shipped into the UK by tankers. LNG is usually used within the UK gas grid; however, (5) LNG = Liquefied Natural Gas, usually shipped into the UK by tankers. LNG is usually used within the UK gas grid; however, it can also be used as an alternative transport fuel. * * * 3. UK Electricity, Heat and Steam Emission Factors Section summary 3.1. UK electricity conversion factors should be used to report on electricity used by an organisation at sites owned or controlled by them. This is reported as a Scope 2 (indirect) emission. The conversion factors for electricity are for the electricity supplied to the grid that organisations purchase – i.e. not including the emissions associated with the transmission and distribution of electricity. Conversion factors for transmission and distribution losses (the energy loss that occurs in getting the electricity from the power plant to the organisations that purchase it) are available separately and should be used to report the Scope 3 emissions associated with grid losses. WTT conversion factors for the UK and overseas electricity should be used to report the Scope 3 emissions of extraction, refining and transportation of primary fuels before their use in the generation of electricity. 3.2. Heat and steam conversion factors should be used to report emissions within organisations that purchase heat or steam energy for heating purposes or for the use in specific industrial processes. District heat and steam factors are also available. WTT heat and steam conversion factors should be used to report emissions from the extraction, refinement and transportation of primary fuels that generate the heat and steam organisations purchase. Heat and steam conversion factors should be used to report emissions within organisations that purchase heat or steam energy for heating purposes or for the use in specific industrial processes. District heat and steam factors are also available. WTT heat and steam conversion factors should be used to report emissions from the extraction, refinement and transportation of primary fuels that generate the heat and steam organisations purchase. 3.3. Table 6 shows where the related worksheets to UK electricity and heat & steam conversion factors are available in the online spreadsheets of the UK GHG Conversion factors set. | Worksheet name | Full set | Condensed set | | --- | --- | --- | | UK electricity | Y | Y | | Transmission and distribution | Y | Y | | WTT-UK&overseas Electricity | Y | N | | Heat and steam | Y | N | | WTT-heat and steam | Y | N | 3.4. There have been no significant methodological changes since the previous update. * * * Direct Emissions from UK Grid Electricity 3.5. The electricity conversion factors given represent the average CO2 emission from the UK national grid per kWh of electricity generated, classed as Scope 2 of the GHG Protocol and separately for electricity transmission and distribution losses, classed as Scope 3. The calculations also factor in net imports of electricity via the interconnectors with Ireland, the Netherlands, France, Belgium, and Norway. These factors include only direct CO2, CH4 and N2O emissions at UK power stations and from autogenerators, plus those from the proportion of imported electricity. They do not include emissions resulting from production and delivery of fuel to these power stations (i.e. from gas rigs, refineries and collieries, etc.). $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ 3.6. The UK grid electricity factor changes from year to year as the fuel mix consumed in UK power stations (and autogenerators) changes, and as the proportion of net imported electricity also changes. These annual changes can be large as they depend very heavily on the relative prices of coal and natural gas as well as fluctuations in peak demand and renewables. There has been a sustained decline in the amount of coal used for electricity generation over the past few years, largely driven by the increase in the carbon floor price from £9 per tonne of CO2 The UK grid electricity factor changes from year to year as the fuel mix consumed in UK power stations (and autogenerators) changes, and as the proportion of net imported electricity also changes. These annual changes can be large as they depend very heavily on the relative prices of coal and natural gas as well as fluctuations in peak demand and renewables. There has been a sustained decline in the amount of coal used for electricity generation over the past few years, largely driven by the increase in the carbon floor price from £9 per tonne of CO2 to largely driven by the increase in the carbon floor price from £9 per tonne of CO2 to £15 in 2015 (DESNZ, 2023). The annual variability, and the recent trends in coal use, in UK electricity generation mix is illustrated in Figure 1 below. $$ \\mathrm {C O} \_ {2} $$ Figure 1: Time series of the mix of UK electricity generation by type Notes: The chart presents data for actual years; the emissions factors for a given GHG Conversion Factor update year correspond to the data for the actual year 2 years behind, i.e. the 2024 conversion factors are based on 2022 data. 3.7. The UK electricity conversion factors provided in the 2024 GHG Conversion factors are based on emissions from IPCC sectors 1A1ai (power stations) and 1A2b/1A2gviii (autogenerators) in the UK Greenhouse Gas Inventory (GHGI) for 2022 (Ricardo, 2024). These emissions from the GHGI only include autogeneration from coal and natural gas, and do not include emissions for electricity generated and supplied by autogenerators using oil or other thermal non-renewable fuels13. Estimates of the emissions arising from other fuels used for autogeneration have been made using standard GHGI emission factors, information from DUKES Table 5.6 (DESNZ, 2023), and DESNZ’s DUKES team on the total fuel use (and shares by fuel type). The method also accounts for the share of autogeneration electricity that is exported to the grid (~42% for the 2024 data year), which varies significantly from year-to-year. 3.8. In 2022, the UK was a net exporter of electricity. Because of this the net imported electricity % used in the calculation of the UK electricity conversion factor was set to 0% in the 2024 Conversion Factors update in order to avoid double counting any emissions. In prior years when the UK was a net importer of electricity, this was accounted for by applying a weighted emission factor to the net imported electricity. The weighted emission factor was calculated using the factors for the individual countries that sent electricity to the UK (in recent years France, Ireland, Netherlands, Belgium, and Norway) and the proportion of the imported electricity they contributed. 3.9. The source data and calculated emissions factors are summarised in Table 7, Table 8 and Table 9. Time series source data and conversion factors are fixed/locked from the 2023 GHG Conversion Factor update and for earlier years have been highlighted in light grey. The tables provide the data and conversion factors against the relevant data year. Table 7 also provides a comparison of how the data year reads across to the GHG conversion factors update/reporting year to which the data and conversion factors are applied, which is two years ahead of the data year. For example, the most recent emission factor for the 2024 GHG Conversion factors is based on the data year 2022. 3.10. Earlier years (those prior to the current update) are based on data reported in previous versions of DUKES and following the convention set from 2016 data year, historic time series factors/data have not been updated. Time series data in light grey is locked/fixed for the purposes of company reporting and has not been updated in the database in the 2024 GHG Conversion factors update. 3.11. A full-time series of data using the most recently available GHGI and DUKES datasets for all years is provided in Appendix 2 of this report. This is provided for purposes other than company reporting, where a fully consistent data time series is desirable, e.g. for policy impact analysis. This dataset also reflects the changes in the methodological approach implemented for the 2016 update and is applied across the whole time series. * * * Table 7: Base electricity generation emissions data | Data Year | Applied to Reporting Year | Electricity Generation(1)GWh | Total Grid Losses(2)% | UK electricity generation emissions(3)ktonne | | | | --- | --- | --- | --- | --- | --- | --- | | CO2 | CH4 | N2O | | | | | | 1990 | 1992 | 290,666 | 8.08% | 204,614 | 2.671 | 5.409 | | 1991 | 1993 | 293,743 | 8.27% | 201,213 | 2.499 | 5.342 | | 1992 | 1994 | 291,692 | 7.55% | 189,327 | 2.426 | 5.024 | | 1993 | 1995 | 294,935 | 7.17% | 172,927 | 2.496 | 4.265 | | 1994 | 1996 | 299,889 | 9.57% | 168,551 | 2.658 | 4.061 | | 1995 | 1997 | 310,333 | 9.07% | 165,700 | 2.781 | 3.902 | | 1996 | 1998 | 324,724 | 8.40% | 164,875 | 2.812 | 3.612 | | 1997 | 1999 | 324,412 | 7.79% | 152,439 | 2.754 | 3.103 | | 1998 | 2000 | 335,035 | 8.40% | 157,171 | 2.978 | 3.199 | | 1999 | 2001 | 340,218 | 8.25% | 149,036 | 3.037 | 2.772 | | 2000 | 2002 | 349,263 | 8.38% | 160,927 | 3.254 | 3.108 | | 2001 | 2003 | 358,185 | 8.56% | 171,470 | 3.504 | 3.422 | | 2002 | 2004 | 360,496 | 8.26% | 166,751 | 3.49 | 3.223 | | 2003 | 2005 | 370,639 | 8.47% | 177,044 | 3.686 | 3.536 | | 2004 | 2006 | 367,883 | 8.71% | 175,963 | 3.654 | 3.414 | | 2005 | 2007 | 370,977 | 7.25% | 175,086 | 3.904 | 3.55 | | 2006 | 2008 | 368,314 | 7.21% | 184,517 | 4.003 | 3.893 | | 2007 | 2009 | 365,252 | 7.34% | 181,256 | 4.15 | 3.614 | | 2008 | 2010 | 356,887 | 7.45% | 176,418 | 4.444 | 3.38 | | 2009 | 2011 | 343,418 | 7.87% | 155,261 | 4.45 | 2.913 | | 2010 | 2012 | 348,812 | 7.32% | 160,385 | 4.647 | 3.028 | | 2011 | 2013 | 330,128 | 7.88% | 148,153 | 4.611 | 3.039 | | 2012 | 2014 | 320,470 | 8.04% | 161,903 | 5.258 | 3.934 | | 2013 | 2015 | 308,955 | 7.63% | 146,852 | 4.468 | 3.595 | | 2014 | 2016 | 297,897 | 8.30% | 126,358 | 4.769 | 2.166 | * * * | Data Year | Applied to Reporting Year | Electricity Generation(1)GWh | Total Grid Losses(2)% | UK electricity generation emissions(3)，ktonne | | | | --- | --- | --- | --- | --- | --- | --- | | CO2 | CH4 | N2O | | | | | | 2017 | 2019 | 294,086 | 7.83% | 74,386 | 7.588 | 1.353 | | 2018 | 2020 | 289,120 | 7.92% | 68,046 | 8.443 | 1.368 | | 2019 | 2021 | 282,282 | 8.13% | 60,504 | 9.158 | 1.321 | | 2020 | 2022 | 269,804 | 8.39% | 52,654 | 9.267 | 1.323 | | 2021 | 2023 | 269,343 | 7.96% | 57,803 | 9.808 | 1.396 | | 2022 | 2024 | 286,902 | 8.12% | 58,795 | 8.893 | 1.259 | Notes: (1) From 1990-2013 (data year): Based upon calculated total for centralised electricity generation (GWh supplied) from DUKES Table 5.5 Electricity fuel use, generation and supply for the year 1990 to 2014. The total is consistent with UNFCCC emissions reporting categories 1A1ai+1A2d includes (according to Table 5.5 categories) GWh supplied (gross) from all ‘Major power producers’; plus, GWh supplied from thermal renewables + coal and gas thermal sources, hydro-natural flow and other nonthermal sources from ‘Other generators’. From 2014 (data year) onwards: based on the total for all electricity generation (GWh supplied) from DUKES Table 5.6, with a reduction of the total for autogenerators based on unpublished data from the BEIS (DESNZ) DUKES team on the share of this that is actually exported to the grid (~18% in 2019). (2) Based upon calculated net grid losses from data in DUKES Table 5.1.2 (long term trends, only available online). (3) From 1990-2013 (data year): Emissions from UK centralised power generation (including Crown Dependencies only) listed (3) From 1990-2013 (data year): Emissions from UK centralised power generation (including Crown Dependencies only) listed under UNFCCC reporting category 1A1a and autogeneration - exported to the grid (UK Only) listed under UNFCCC reporting category 1A2f from the UK Greenhouse Gas Inventory for 2012 (Ricardo-AEA, 2014) for data years 1990-2012, and for 2013 (Ricardo Energy & Environment, 2015) for the 2013 data year. From 2014 (data year) onwards: Excludes emissions from Crown Dependencies and also includes an accounting (estimate) From 2014 (data year) onwards: Excludes emissions from Crown Dependencies and also includes an accounting (estimate) for autogeneration emissions not specifically split out in the UK GHGI, consistent with the inclusion of the GWh supply for these elements also from 2014 onwards. Data is from the GHGI (Ricardo, 2024) for the 2022 data year. * * * Table 8: Base electricity generation conversion factors (excluding imported electricity) \| Data Year \| Emission Factor,kgCO2e/kWh \| \| \| \| \| \| \| \| \| \| \| % Net Electricity Imports TOTAL \| \| \| \-\-\- \| \-\-\- \| \-\-\- \| \-\-\- \| \-\-\- \| \-\-\- \| \-\-\- \| \-\-\- \| \-\-\- \| \-\-\- \| \-\-\- \| \-\-\- \| \-\-\- \| \-\-\- \| \| For electricity GENERATED (supplied to the grid) \| \| \| \| Due to grid transmission /distribution LOSSES \| \| \| \| For electricity CONSUMED (includes grid losses) \| \| \| \| \| \| \| CO2 \| CH4 \| N2O \| Total \| CO2 \| CH4 \| N2O \| Total \| CO2 \| CH4 \| N2O \| Total \| \| \| \| 1990 \| 0.70395 \| 0.00019 \| 0.00577 \| 0.70991 \| 0.05061 \| 0.00001 \| 0.00042 \| 0.05104 \| 0.76580 \| 0.00021 \| 0.00628 \| 0.77229 \| 3.85% \| \| 1991 \| 0.68500 \| 0.00018 \| 0.00564 \| 0.69081 \| 0.04318 \| 0.00001 \| 0.00033 \| 0.04352 \| 0.74675 \| 0.00019 \| 0.00615 \| 0.75309 \| 5.18% \| \| 1992 \| 0.64907 \| 0.00017 \| 0.00534 \| 0.65458 \| 0.05678 \| 0.00002 \| 0.00042 \| 0.05722 \| 0.70205 \| 0.00019 \| 0.00578 \| 0.70801 \| 5.29% \| \| 1993 \| 0.58632 \| 0.00018 \| 0.00448 \| 0.59098 \| 0.05101 \| 0.00002 \| 0.00037 \| 0.05140 \| 0.63160 \| 0.00019 \| 0.00483 \| 0.63662 \| 5.25% \| \| 1994 \| 0.56204 \| 0.00019 \| 0.00420 \| 0.56643 \| 0.04471 \| 0.00002 \| 0.00030 \| 0.04502 \| 0.62154 \| 0.00021 \| 0.00464 \| 0.62639 \| 5.22% \| \| 1995 \| 0.53394 \| 0.00019 \| 0.00390 \| 0.53803 \| 0.03813 \| 0.00001 \| 0.00024 \| 0.03839 \| 0.58721 \| 0.00021 \| 0.00429 \| 0.59170 \| 4.97% \| \| 1996 \| 0.50774 \| 0.00018 \| 0.00345 \| 0.51137 \| 0.04182 \| 0.00002 \| 0.00026 \| 0.04210 \| 0.55432 \| 0.00020 \| 0.00376 \| 0.55828 \| 4.80% \| \| 1997 \| 0.46989 \| 0.00018 \| 0.00297 \| 0.47304 \| 0.03816 \| 0.00002 \| 0.00022 \| 0.03840 \| 0.50961 \| 0.00019 \| 0.00322 \| 0.51302 \| 4.76% \| \| 1998 \| 0.46912 \| 0.00019 \| 0.00296 \| 0.47226 \| 0.04084 \| 0.00002 \| 0.00024 \| 0.04111 \| 0.51211 \| 0.00020 \| 0.00323 \| 0.51555 \| 3.51% \| \| 1999 \| 0.43806 \| 0.00019 \| 0.00253 \| 0.44077 \| 0.04375 \| 0.00002 \| 0.00027 \| 0.04404 \| 0.47745 \| 0.00020 \| 0.00275 \| 0.48041 \| 3.94% \| \| 2000 \| 0.46076 \| 0.00020 \| 0.00276 \| 0.46372 \| 0.04083 \| 0.00002 \| 0.00024 \| 0.04109 \| 0.50293 \| 0.00021 \| 0.00301 \| 0.50616 \| 3.82% \| * * * 2024 Government greenhouse gas conversion factors for company reporting: Methodology paper | Data Year | Emission Factor,kgCO2e/kWh | | | | | | | | | | | | % Net Electricity Imports | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | For electricity GENERATED(supplied to the grid) | | | Due to grid transmission/distribution LOSSES | | | | For electricity CONSUMED(includes grid losses) | | | | | | | | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | TOTAL | | | 2009 | 0.45211 | 0.00027 | 0.00263 | 0.45501 | 0.03783 | 0.00002 | 0.00024 | 0.03809 | 0.49074 | 0.00030 | 0.00285 | 0.49389 | 0.80% | | 2010 | 0.45980 | 0.00028 | 0.00269 | 0.46277 | 0.05061 | 0.00001 | 0.00042 | 0.05104 | 0.49613 | 0.00030 | 0.00290 | 0.49933 | 0.73% | | 2011 | 0.44877 | 0.00029 | 0.00285 | 0.45192 | 0.04318 | 0.00001 | 0.00033 | 0.04352 | 0.48715 | 0.00032 | 0.00310 | 0.49056 | 1.76% | | 2012 | 0.50520 | 0.00034 | 0.00381 | 0.50935 | 0.04418 | 0.00003 | 0.00033 | 0.04454 | 0.54938 | 0.00037 | 0.00414 | 0.55389 | 3.40% | | 2013 | 0.47532 | 0.00036 | 0.00347 | 0.47915 | 0.03925 | 0.00003 | 0.00029 | 0.03956 | 0.51457 | 0.00039 | 0.00375 | 0.51871 | 4.10% | | 2014 | 0.42417 | 0.00040 | 0.00217 | 0.42673 | 0.03837 | 0.00004 | 0.00020 | 0.03860 | 0.46254 | 0.00044 | 0.00236 | 0.46534 | 6.44% | | 2015 | 0.35766 | 0.00064 | 0.00214 | 0.36044 | 0.03343 | 0.00006 | 0.00020 | 0.03369 | 0.39108 | 0.00070 | 0.00234 | 0.39412 | 6.59% | | 2016 | 0.28266 | 0.00066 | 0.00154 | 0.28486 | 0.02409 | 0.00006 | 0.00013 | 0.02428 | 0.30675 | 0.00072 | 0.00167 | 0.30913 | 5.57% | | 2017 | 0.25294 | 0.00065 | 0.00137 | 0.25496 | 0.02148 | 0.00005 | 0.00012 | 0.02165 | 0.27442 | 0.00070 | 0.00149 | 0.27660 | 4.78% | | 2018 | 0.23536 | 0.00073 | 0.00141 | 0.23750 | 0.02024 | 0.00006 | 0.00012 | 0.02042 | 0.25559 | 0.00079 | 0.00153 | 0.25792 | 6.20% | | 2019 | 0.21434 | 0.00081 | 0.00139 | 0.21654 | 0.01897 | 0.00007 | 0.00012 | 0.01917 | 0.23331 | 0.00088 | 0.00152 | 0.23571 | 6.98% | Emission Factor (Electricity CONSUMED) = Emission Factor (Electricity GENERATED) / (1 - %Electricity Total Grid LOSSES) Notes: \* From 1990-2013 the emission factor used was for French electricity only and is as published in previous methodology papers. The methodology was updated from 2014 onwards with new data on the contribution of electricity from the other interconnects, hence these figures are based on a weighted average emission factor of the conversion factors for France, the Netherlands and Ireland, based on the % share supplied. Emission Factor (Electricity LOSSES) = Emission Factor (Electricity CONSUMED) - Emission Factor (Electricity GENERATED) ⇒ Emission Factor (Electricity CONSUMED) = Emission Factor (Electricity GENERATED) + Emission Factor (Electricity LOSSES), * * * 2024 Government greenhouse gas conversion factors for company reporting: Methodology paper \\*\\* From 2020-2022, CH4 and N2O emission factors were kept constant from 2019 values due to descoping (see Chapter 1 section "Conversion factors update frequency"). From 2021, CH4 and N2O emission factors were kept constant from 2019 values but aligned with AR5 GWPs. $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ Table 9: Base electricity generation emissions factors (including imported electricity) | Data Year | Emission Factor,kgCO2e/kWh | | | | | | | | | | | % Net Elec Imports | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | For electricity GENERATED(supplied to the grid,plus imports) | | | | Due to grid transmission/distribution LOSSES | | | | For electricity CONSUMED(includes grid losses) | | | | | | | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | Total | | | 1990 | 0.6812 | 0.00019 | 0.00558 | 0.68697 | 0.05985 | 0.00002 | 0.00049 | 0.06036 | 0.74106 | 0.0002 | 0.00607 | 0.74733 | 3.85% | | 1991 | 0.65616 | 0.00017 | 0.0054 | 0.66174 | 0.05915 | 0.00002 | 0.00049 | 0.05966 | 0.71532 | 0.00019 | 0.00589 | 0.72139 | 5.18% | | 1992 | 0.62005 | 0.00017 | 0.0051 | 0.62532 | 0.05061 | 0.00001 | 0.00042 | 0.05104 | 0.67066 | 0.00018 | 0.00552 | 0.67636 | 5.29% | | 1993 | 0.55913 | 0.00017 | 0.00428 | 0.56358 | 0.04318 | 0.00001 | 0.00033 | 0.04352 | 0.60232 | 0.00018 | 0.00461 | 0.6071 | 5.25% | | 1994 | 0.53633 | 0.00018 | 0.00401 | 0.54051 | 0.05678 | 0.00002 | 0.00042 | 0.05722 | 0.59311 | 0.0002 | 0.00443 | 0.59773 | 5.22% | | 1995 | 0.5113 | 0.00018 | 0.00373 | 0.51521 | 0.05101 | 0.00002 | 0.00037 | 0.0514 | 0.56231 | 0.0002 | 0.0041 | 0.56661 | 4.97% | | 1996 | 0.48731 | 0.00017 | 0.00331 | 0.4908 | 0.04471 | 0.00002 | 0.0003 | 0.04502 | 0.53202 | 0.00019 | 0.00361 | 0.53582 | 4.80% | | 1997 | 0.45112 | 0.00017 | 0.00285 | 0.45414 | 0.03813 | 0.00001 | 0.00024 | 0.03839 | 0.48925 | 0.00019 | 0.00309 | 0.49253 | 4.76% | | 1998 | 0.45633 | 0.00018 | 0.00288 | 0.45939 | 0.04182 | 0.00002 | 0.00026 | 0.0421 | 0.49816 | 0.0002 | 0.00314 | 0.5015 | 3.51% | | 1999 | 0.42438 | 0.00018 | 0.00245 | 0.427 | 0.03816 | 0.00002 | 0.00022 | 0.0384 | 0.46254 | 0.0002 | 0.00267 | 0.46541 | 3.94% | | 2000 | 0.44628 | 0.00019 | 0.00267 | 0.44914 | 0.04084 | 0.00002 | 0.00024 | 0.04111 | 0.48712 | 0.00021 | 0.00292 | 0.49024 | 3.82% | * * * 2024 Government greenhouse gas conversion factors for company reporting: Methodology paper | Data Year | Emission Factor,kgCO2e/kWh | | | | | | | | | | | % Net Elec Imports | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | For electricity GENERATED(supplied to the grid,plus imports) | | | Due to grid transmission/distribution LOSSES | | | | For electricity CONSUMED(includes grid losses) | | | | Total | | | | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | | | | 2007 | 0.49054 | 0.00024 | 0.00303 | 0.49381 | 0.03884 | 0.00002 | 0.00024 | 0.0391 | 0.52939 | 0.00025 | 0.00327 | 0.53291 | 1.37% | | 2008 | 0.48219 | 0.00026 | 0.00286 | 0.48531 | 0.03883 | 0.00002 | 0.00023 | 0.03908 | 0.52102 | 0.00028 | 0.00309 | 0.52439 | 2.91% | | 2009 | 0.44917 | 0.00027 | 0.00261 | 0.45205 | 0.03838 | 0.00002 | 0.00022 | 0.03863 | 0.48755 | 0.00029 | 0.00284 | 0.49068 | 0.80% | | 2010 | 0.45706 | 0.00028 | 0.00267 | 0.46002 | 0.03611 | 0.00002 | 0.00021 | 0.03634 | 0.49317 | 0.0003 | 0.00289 | 0.49636 | 0.73% | | 2011 | 0.44238 | 0.00029 | 0.00281 | 0.44548 | 0.03783 | 0.00002 | 0.00024 | 0.03809 | 0.4802 | 0.00031 | 0.00305 | 0.48357 | 1.76% | | 2012 | 0.49023 | 0.00033 | 0.00369 | 0.49426 | 0.04287 | 0.00003 | 0.00032 | 0.04322 | 0.5331 | 0.00036 | 0.00402 | 0.53748 | 3.40% | | 2013 | 0.4585 | 0.00035 | 0.00334 | 0.46219 | 0.03786 | 0.00003 | 0.00028 | 0.03816 | 0.49636 | 0.00038 | 0.00362 | 0.50035 | 4.10% | | 2014 | 0.40957 | 0.00039 | 0.00209 | 0.41205 | 0.03705 | 0.00003 | 0.00019 | 0.03727 | 0.44662 | 0.00042 | 0.00228 | 0.44932 | 6.44% | | 2015 | 0.34885 | 0.00062 | 0.00209 | 0.35156 | 0.03261 | 0.00006 | 0.0002 | 0.03287 | 0.38146 | 0.00068 | 0.00229 | 0.38443 | 6.59% | | 2016 | 0.28088 | 0.00066 | 0.00153 | 0.28307 | 0.02394 | 0.00006 | 0.00013 | 0.02413 | 0.30482 | 0.00072 | 0.00166 | 0.3072 | 5.57% | | 2017 | 0.25358 | 0.00065 | 0.00137 | 0.2556 | 0.02153 | 0.00005 | 0.00012 | 0.0217 | 0.27511 | 0.0007 | 0.00149 | 0.2773 | 4.78% | Notes: \* From 1990-2013 the emission factor used was for French electricity only. The methodology was updated from 2014 onwards with new data on the contribution of electricity from the other interconnects, hence these figures are based on a weighted average emission factor of the conversion factors for France, the Netherlands, Ireland, Belgium, and Norway, based on the % share supplied. Emission Factor (Electricity CONSUMED) = Emission Factor (Electricity GENERATED) / (1 - %Electricity Total Grid LOSSES) $$ \\text{Emission Factor (Electricity CONSUMED)} = \\text{Emission Factor (Electricity GENERATED)} / (1 - % \\text{Electricity Total Grid LOSSES}) $$ $$ \\text{Emission Factor (Electricity LOSSES)} = \\text{Emission Factor (Electricity CONSUMED)} - \\text{Emission Factor (Electricity GENERATED)} $$ $$ \\Rightarrow \\text {E m i s s i o n F a c t o r (E l e c r i c i t y C O N S U M E D)} = \\text {E m i s s i o n F a c t o r (E l e c r i c i t y G E N E R A T E D)} + \\text {E m i s s i o n F a c t o r (E l e c r i c i t y L O S S E S)} $$ * * * 2024 Government greenhouse gas conversion factors for company reporting: Methodology paper \\*\\* From 2020-2022, CH4 and N2O emission factors were kept constant from 2019 values due to descoping (see Chapter 1 section "Conversion factors update frequency"). From 2021, CH4 and N2O emission factors were kept constant from 2019 values but aligned with AR5 GWPs. $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ * * * Indirect/WTT Emissions from UK Grid Electricity 3.12. In addition to the GHG emissions resulting directly from the generation of electricity, there are also indirect/WTT emissions resulting from the production, transport and distribution of the fuels used in electricity generation (i.e. indirect/WTT/-fuel lifecycle emissions as included in the Fuels WTT tables). The average fuel lifecycle emissions per unit of electricity generated will be a result of the mix of different sources of fuel/primary energy used in electricity generation. 3.13. The WTT conversion factor for electricity has been calculated using the corresponding fuels WTT conversion factors and data on the total fuel consumption by type of generation from Table 5.6 and Table 6.6, DUKES 2021 (DESNZ, 2023). 3.14. As the WTT factor for UK Grid Electricity is no longer annually updated as part of the conversion factors, the data for these calculations are no longer presented here. Conversion factors for the Supply of Purchased Heat or Steam 3.15. Heat and Steam conversion factors have been held constant from the 2023 release (aligned with AR5 GWPs values). These factors are scheduled to be updated in the 2025 Conversion Factors publications. 3.16. The conversion factors for the supply of purchased heat or steam represent the average emission from the heat and steam supplied by the UK Combined Heat and Power Quality Assurance (CHPQA) scheme (BEIS, 2019a) operators for a given year. This factor changes from year to year, as the fuel mix consumed changes and is therefore updated annually. No statistics are available that would allow the calculation of UK national average conversion factors for the supply of heat and steam from non-CHP (Combined Heat and Power) operations. 3.17. CHP simultaneously produces both heat and electricity, and there are several conventions used to allocate emissions between these products. At the extremes, emissions could be allocated wholly to heat or wholly to electricity, or in various proportions in-between. a) Method 1: 1/3 : 2/3 Method (DUKES) b) Method 2: Boiler Displacement Method c) Method 3: Power Station Displacement Method 3.19. The GHG Conversion factors use the 1/3 : 2/3 DUKES method (Method 1) to determine emissions from heat and therefore only this method is described below. * * * Summary of Method 1: 1/3: 2/3 Method (DUKES) 14 3.20. Under the UK’s Climate Change Agreements (CCAs) (Environment Agency, 2020), this method, which is used to apportion fuel use to heat and power, assumes that twice as many units of fuel are required to generate each unit of electricity than are required to generate each unit of heat. This follows from the observation that the efficiency of the generation of electricity (at electricity only generating plant) varies from as little as 25% to 50%, while the efficiency of the generation of heat in fired boilers ranges from 50% to about 90%. 3.21. Mathematically, Method 1 can be represented as follows: $$ Heat \_ Energy = \\left(\\frac {T o t a l F u e l I n p u t}{\\left(2 \\times E l e c t r i c i t y \_ O u t p u t\\right) + Heat \_ O u t p u t}\\right) \\times Heat \_ O u t p u t $$ $$ Electricity\_Energy = \\left( \\frac {2 \\times Total Fuel Input}{\\left( 2 \\times Electricity\_Output \\right) + Heat\_Output} \\right) \\times Electricity\_Output $$ Where: • ‘Total Fuel Input (TFI)’ is the total fuel to the prime mover. • ‘Heat Output’ is the useful heat generated by the prime mover. • ‘Heat Output’ is the useful heat generated by the prime mover. • ‘Electricity Output’ is the electricity (or the electrical equivalent of mechanical • ‘Electricity Output’ is the electricity (or the electrical equivalent of mechanical power) generated by the prime mover. • ‘Heat Energy’ is the fuel to the prime mover apportioned to the heat generated. • ‘Heat Energy’ is the fuel to the prime mover apportioned to the heat generated. • ‘Electricity Energy’ is the fuel to the prime mover apportioned to the electricity • ‘Electricity Energy’ is the fuel to the prime mover apportioned to the electricity generated. 3.22. This method is used only in the UK for accounting for primary energy inputs to CHP where the CHP generated heat and electricity is used within a facility with a CCA. Calculation of CO2 Emissions Factor for CHP Fuel Input, FuelMixCO2factor 3.23. The value FuelMixCO2factor referred to above is the carbon emission factor per unit fuel input to a CHP scheme. This factor is determined using fuel input data provided by CHP scheme operators to the CHPQA programme, which is held in confidence. $$ \\mathrm {C O} \_ {2} $$ The value for FuelMixCO2factor is determined using the following expression: $$ \\mathrm {F u e l M i x C O 2 f a c t o r} = \\frac {\\sum (\\mathrm {F u e l I n p u t} \\times \\mathrm {F u e l C O 2 E m i s s i o n s F a c t o r})}{\\mathrm {T F I}} $$ Where: * * * • FuelMixCO2factor is the composite emissions factor (in tCO2/MWh thermal fuel input) for a scheme • Fuel Input is the fuel input (in MWh thermal, MWhth) for a single fuel supplied to the prime mover • Fuel CO2 Emissions factor is the CO2 emissions factor (in tCO2/MWhth) for the fuel considered. • TFI is total fuel input (in MWh thermal) for all fuels supplied to the prime mover. 3.24. Fuel inputs and emissions factors are evaluated on a Gross Calorific Value (Higher Heating Value) basis. The following Table 10 provides the individual fuel types considered under the CHPQA scheme and their associated emissions factors, consistent with other reporting; fuel mix varies every year and thus there are zero entries for specific fuel types. Table 10: Fuel types and associated emissions factors used in the determination of FuelMixCO2factor | Fuel | CO2 Emissions Factor(kgCO2/kWhth) | | --- | --- | | Biodiesel, bioethanol etc | - | | Biomass (such as woodchips, chicken litter etc) | - | | Blast furnace gas | 0.93 | | Butane | 0.21 | | Coal and lignite | 0.32 | | Coke oven gas | 0.14 | | Coke, and semi-coke | 0.34 | | Domestic refuse (raw) | 0.16 | | Ethane | 0.18 | | Fuel oil | 0.27 | | Gas oil | 0.25 | | Hydrogen | - | | Landfill gas | - | | Methane | 0.18 | | Mixed refinery gases | 0.25 | | Natural gas | 0.18 | | Other | 0.18 | | Other Biogas (e.g. gasified woodchips) | - | | Other gaseous waste | 0.18 | | Other liquid waste (non-renewable) | 0.25 | | Other liquid waste (renewable) | - | | Other oils | 0.25 | | Other solid waste | 0.16 | | Petroleum coke | 0.34 | | Petroleum gas | 0.21 | | Propane | 0.21 | | Refuse-derived Fuels (RDF) | 0.16 | | Sewage gas | - | | Unknown process gas | 0.18 | | Uranium | - | | Volatile organic compounds(VOCs) | - | | Waste exhaust heat from high temperature processes | - | | Waste heat from exothermic chemical reactions | - | | Other waste heat | - | | Wood Fuels(woodchips,logs,wood pellets etc) | - | | Fuel cells | 0.18 | | Syngas/Other Biogas(e.g. gasified woodchips) | - | | Pentane | - | | Other Industrial By-Product gases | 0.18 | | Hospital waste | 0.16 | | Hydrogen(as a by-product) | - | | Hydrogen(as a primary fuel) | - | | Oil shale | 0.27 | | Bituminous or asphaltic substance | 0.27 | | Carbon Monoxide | 0.18 | | Agricultural residues | - | | Arboricultural&Forestry residues | - | | Biogas produced by an anaerobic digestion(AD) plant | - | | Branches and prunings | - | | Building and demolition materials | - | | Distillers grain | - | | Dried wood chips | - | | Fatty Acid Methyl Esters(biodiesel) | - | | Gases otherwise produced from AD of biological materials | - | | Industrial waste | 0.16 | | Milling residues | - | | Municipal solid waste | 0.16 | | Organic waste material such as manure,chicken litter,food waste | - | | Other commercial renewable oils | - | | Other Waste Woods | - | | Other wood fuels | - | | Paper sludge | - | | Rapeseed oil | - | | Refinery asphaltic oil | 0.27 | | Refuse derived fuel | 0.16 | | Roundwood | - | | Spent solvents | 0.25 | | Straw | - | | Syngas from Wood Chips | - | | Tallow | - | | Undried woodchips | - | | Used cooking oil | - | | Visibly Clean Waste Wood(gradeA of Publicly Available Specification(PAS)111) | - | | Wood pellets | - | Sources: GHG Conversion factors for Company Reporting (2024 update) and UK GHGI (Ricardo, 2024). Note: For waste derived fuels, the emission factor can vary significantly according to the waste mix. Therefore, if you have sitespecific data, it is recommended that you use that instead of the waste derived fuel emissions factors in this table. 3.25. The 1/3 : 2/3 method (Method 1) was used to calculate the new heat/steam conversion factors provided in the Heat and Steam tables of the 2024 GHG Conversion factors. This is shown in Table 11. It is important to note that the conversion factors update year is two years ahead of the data year. For example, the most recent emission factor for the 2023 GHG Conversion factors is based on the data year of 2021 in the Table 11. The 1/3 : 2/3 method (Method 1) was used to calculate the new heat/steam conversion factors provided in the Heat and Steam tables of the 2024 GHG Conversion factors. This is shown in Table 11. It is important to note that the conversion factors update year is two years ahead of the data year. For example, the most recent emission factor for the 2023 GHG Conversion factors is based on 3.26. While not used in the 2024 GHG conversion factors, the factor for heat from CHP and power from CHP has also been calculated using the other two CHP methods and the DUKES power method. These are: 0.25791 CO2 displacement), 0.22293 CO2/kWh heat (Power station displacement), 0.33813 CO2/kWh power (DUKES method), 0.36609 CO2/kWh power (Boiler displacement), 0.42826 CO2/kWh power (power station displacement). While not used in the 2024 GHG conversion factors, the factor for heat from CHP and power from CHP has also been calculated using the other two CHP methods and the DUKES power method. These are: 0.25791 CO2/kWh heat (Boiler /kWh heat (Power station displacement), 0.33813 /kWh power (Boiler /kWh power (power station displacement). | Data Year | kgCO2/kWh supplied heat/steam | | --- | --- | | Method 1(DUKES:2/3rd-1/3rd) | | | 2001 | 0.23770 | | 2002 | 0.22970 | | 2003 | 0.23393 | | 2004 | 0.22750 | * * * | Data Year | kgCO2/kWh supplied heat/steam | | --- | --- | | Method 1(DUKES:2/3rd-1/3rd) | | | 2005 | 0.22105 | | 2006 | 0.23072 | | 2007 | 0.23118 | | 2008 | 0.22441 | | 2009 | 0.22196 | | 2010 | 0.21859 | | 2011 | 0.21518 | | 2012 | 0.20539 | | 2013 | 0.20763 | | 2014 | 0.20245 | | 2015 | 0.19564 | | 2016 | 0.18618 | | 2017 | 0.17447 | | 2018 | 0.17102 | | 2019 | 0.17150 | | 2020 | 0.17574 | | 2021 | 0.17791 | Calculation of Non-CO2 and Indirect/WTT Emissions Factor for Heat and Steam $$ \\mathrm {N o n - C O} \_ {2} $$ 3.27. CH4 and N2O emissions have been estimated relative to the CO2 emissions, based upon activity weighted average values for each CHP fuel used (using relevant average fuel conversion factors from the UK GHGI). Where fuels are not included in the UK GHGI, the value for the most similar alternative fuel was used. 3.28. Indirect/WTT GHG conversion factors have been estimated relative to the CO2 emissions, based upon activity weighted average indirect/WTT GHG emission factor values for each CHP fuel used (see “Indirect/WTT Emissions from Fuels” section for more information). Where fuels are not included in the set of indirect/WTT GHG conversion factors provided in the 2024 GHG Conversion factors, the value for the most similar alternative fuel was used. Indirect/WTT GHG conversion factors have been estimated relative to the CO2 emissions, based upon activity weighted average indirect/WTT GHG emission factor values for each CHP fuel used (see “Indirect/WTT Emissions from Fuels” section for more information). Where fuels are not included in the set of indirect/WTT GHG conversion factors provided in the 2024 GHG Conversion factors, the value for the most similar alternative fuel was used. $$ \\mathrm {C O} \_ {2} $$ * * * 2024 Government greenhouse gas conversion factors for company reporting: Methodology paper overall GHG emissions where relevant and are counted as Scope 3 emissions under the GHG Protocol (similar to the treatment of transmission and distribution losses for electricity). * * * 4. Refrigerant and Process Emission Factors Section summary 4.1. Refrigerant and process conversion factors should be used for reporting leakage from air-conditioning and refrigeration units or the release to the atmosphere of other substances that have a global warming potential. 4.2. This section of the methodology paper relates to the “Refrigerant & other” worksheet available in both the full and condensed set of the 2024 UK GHG Conversion factors set. 4.3. Refrigerant and process conversion factors have been held constant from the 2023 release (almost all values have been updated to use AR5 GWPs (and where AR5 values were not available, but AR6 values were, AR6 GWPs have been used)) Summary of changes since the previous update 4.4. There were no major methodological changes in the 2024 update. Refrigerant and process conversion factors remain constant since the publish of 2023 GHG Conversion factors. Global Warming Potentials of Greenhouse Gases 4.5. The GWP values have been updated to those published by the IPCC in the Fifth Assessment Report (IPCC, 2014). There are a small number of refrigerants that are not included in the Fifth Assessment Report. In these cases, we have adopted values from either IPCC Sixth Assessment Report (IPCC, 2023), the IPCC Fourth Assessment Report (IPCC, 2007), or Annex IV of the EU F gas regulation 11 (517/2014). Greenhouse Gases Listed in the Kyoto Protocol 4.6. Mixed/Blended gases: GWP values for refrigerant blends are calculated on the basis of the percentage blend composition (e.g. the GWP for R404a that 15 comprises of 44% HFC125, 52% HFC143a and 4% HFC134a is \[3170 x 0.44\] + \[4800 x 0.52\] + \[1300x 0.04\] = 3943). A limited selection of common blends is presented in the Refrigerant tables. This calculation is done separately for Kyoto components and non-Kyoto components, so that users of blends which include both can distinguish what proportion of the GWP relates specifically to Kyoto components while also presenting the total GWP. * * * Other Greenhouse Gases 4.7. CFCs and HCFCs16: While these products typically have high GWPs, they were excluded from Kyoto Protocol reporting due to already being controlled under the Montreal Protocol due to them being Ozone Depleting Substances (ODS). Most use of ODS are now banned in the UK, so these are unlikely to be relevant to UK users unless they have a legacy system and/or are using the product for specific exempted end-uses. 4.8. Other substances which are neither controlled under the Kyoto Protocol or Montreal protocol. Many non-ODS substances which have comparatively low GWPs (typically <10) or are not widely used are not included under the Kyoto Protocol or Montreal protocol but are included in domestic F-gas regulations. These are included here for completeness, and it also means that the GWP values for blends should closely align with the calculations required for labelling Fgas equipment. * * * 5. Passenger Land Transport Emission Factors Section summary 5.1. Conversion factors for passenger land transport are included in this section of the methodology paper. This section includes vehicles owned by the reporting organisation (Scope 1), business travel in other vehicles (e.g. employee own car for business use, hire car, public transport (Scope 3)), and electric vehicles (EVs) (Scope 2). Other Scope 3 conversion factors included here are for transmission and distribution losses for electricity used for electric vehicles, WTT for passenger transport (vehicles owned by reporting organisation) and other business travel. 5.2. Motorcycles, methane and nitrous oxide conversion factors remain constant since the 2021 GHG Conversion factors but have been updated from AR4 to AR5 GWP values. WTT conversion factors also remain constant and have been updated from AR4 to AR5 GWP values. 5.3. Note that passenger land transport factors should only be used in the absence of data for fuel or electricity consumption for the vehicles in question. 5.4. Table 12 shows where the related worksheets to the passenger land transport conversion factors are available in the online spreadsheets of the UK GHG Conversion factors. Table 12: Related worksheets to passenger land transport emission factors | Worksheet name | Full set | Condensed set | | --- | --- | --- | | Passenger vehicles | Y | Y | | UK Electricity for Electric Vehicles(EVs) | Y | Y | | UK Electricity T&D for EVs | Y | Y | | Business travel-land\* | Y | Y | | WTT-pass vehicles&travel-land\* | Y | N | - cars and motorbikes only 5.5. Utility factors for PHEVs (plug-in hybrid electric vehicles) are updated in the 2024 GHG Conversion Factors to align to the real-world data and better reflect the actual emissions from those vehicles. The utility factor represents the proportion of distance travelled in electric mode versus the total distance travelled. The realworld performance of most PHEVs is significantly different from that defined in regulatory requirements. Currently, utility factors for PHEVs within the electric vehicle model (xEVs) are calculated based on regulatory formula, and this approach underestimates emissions in real world. From 2025, the EU will significantly reduce the utility factors for PHEVs to fully align them with the realworld data collected from various studies. The utility factors for the electric operation of PHEVs have been revised downwards, to reflect the average proportion of time that vehicles are in the electric operation mode in real-world condition. In the 2024 update, due to the updated PHEV utility factors, the fraction of distance that PHEVs use predominantly the battery has decreased significantly, and the fraction of distance that PHEVs travel using the fuel engine has increased. All the conversion factors that are related to the electricity used by PHEVs have therefore decreased significantly whereas all the factors related to the direct fuel emissions from PHEVs have increased. 5.6. Conversion factors now include factors for PHEVs (plug-in hybrid electric vehicles) LGVs (light goods vehicles). Electric LGVs registered in the UK were predominantly battery electric vehicles (BEV), and there were only a few PHEV LGVs models on the market. As the number of PHEVs LGVs increased over the years, these factors were added in the 2024 update. 5.7. In 2020 and 2021, transport trends had been affected by measures introduced to prevent and reduce the global spread of coronavirus (COVID-19). DfT's statistics shows that passenger kilometres and thus occupancy levels for certain modes of transport (buses, cars, vans, rail, air) have significantly dropped in 2020 and they didn't go back to pre-COVID levels in 2021 too. For buses factors, it was decided that pre-COVID occupancy levels would be retained for the years 2020 and 2021 in the 2022 and 2023 updates. In the 2024 update of GHG Conversion Factors, 2022/23 occupancy level statistics from DfT were used. Please see the two illustrative tables below for buses: Table 13: DfT's Table BUS03a\_km - Passenger kilometres on local bus services by metropolitan area status and country: Great Britain | Year | Great Britain | | --- | --- | | 2016/17 | 27.28 | | 2017/18 | 26.98 | | 2018/19 | 26.98 | | 2019/20 | 25.88-retained value for the 2022 and 2023 updates | | 2020/21 | 9.91 | | 2021/22 | 18.25 | | 2022/23 | 22.16 | * * * Table 14: DfT's Table BUS03b - Average bus occupancy on local bus services by metropolitan area status and country: Great Britain | Year | Great Britain | | --- | --- | | 2016/17 | 11.3 | | 2017/18 | 11.6 | | 2018/19 | 11.8 | | 2019/20 | 11.5-retained value for the 2022 and 2023 updates | | 2020/21 | 5.3 | | 2021/22 | 8.8 | | 2022/23 | 11.1 | Direct Emissions from Passenger Cars Conversion factors for Petrol and Diesel Passenger Cars by Engine Size 5.8. The methodology for calculating average conversion factors for passenger cars is based upon a combination of datasets on the average new vehicle regulatory emissions for vehicles registered in the UK, and an uplift to account for differences between these and real-world driving performance emissions. 5.9. The regulatory test cycle/procedure transitioned from the previous NEDC to the new WLTP17, which is intended to bring the results of tests under regulatory testing conditions closer to those observed in the real-world. Light duty vehicles (cars and vans) registered in the EU from 2020 have WLTP-based regulatory CO2 emissions values and these are used in the calculation of conversion factors where possible. However, the majority of vehicles in the UK fleet are registered before 2020 and so continue to use NEDC-based values. $$ \\mathrm {C O} \_ {2} $$ 5.10. SMMT18 provides numbers of registrations and average gCO2/km figures for new 19 vehicles registered from 1999 to 2023. The dataset represents a good indication of the relative gCO2/km by size and market segment category. Table 15 presents the average NEDC CO2 conversion factors used for vehicles registered between 2005-2019 and the average WLTP CO2 conversion factors used for vehicles registered from 2020. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ Table 15: Average CO2 conversion factors and total registrations by engine size for 2005 to 2022 (based on data sourced from SMMT) | Vehicle Type | Engine size | Size label | NEDC\*gCO2perkm | WLTPgCO2perkm | Total no.of registrations | % Total | | --- | --- | --- | --- | --- | --- | --- | | Petrol car | <1.4l | Small | 119.9 | 129.7 | 12,435,558 | 62% | | 1.4-2.0l | Medium | 155.2 | 154.8 | 6,700,363 | 34% | | | >2.0l | Large | 234.1 | 247.9 | 789,917 | 4% | | | Average petrol car | | All | 135.8 | 144.3 | 19,925,838 | 100% | | Diesel car | <1.7l | Small | 110.0 | 135.3 | 5,244,443 | 38% | | 1.7-2.0l | Medium | 134.7 | 158.3 | 5,843,132 | 42% | | | >2.0l | Large | 167.0 | 210.5 | 2,810,645 | 20% | | | Average diesel car | | All | 131.4 | 163.7 | 13,898,220 | 100% | $$ \\mathrm {C O} \_ {2} $$ - For 2019 and 2018, NEDCe reported data is converted to NEDC, based on an estimated 9% correlation factor from SMMT based on analysis of vehicle models where both NEDC and NEDCe values exist. NEDCe (NEDC equivalent) data are officially reported figures calculated from WLTP using an official regulatory correlation tool. They are used to check compliance of new vehicle registrations with the EU-wide regulatory CO2 targets set on NEDC basis. $$ \\mathrm {C O} \_ {2} $$ 5.12. The ANPR data has been collected annually (since 2007) over 256 sites in the UK on different road types (urban and rural major/minor roads, and motorways) and regions. Measurements are made at each site on one weekday (8 am-2 pm and 3 pm-9 pm) and one-half weekend day (either 8 am-2 pm or 3 pm-9 pm) each year in June and are currently available for 2007 - 2011, 2013 – 2015, 2017, 2019 and 2021\. There are approximately 1.4 -1.7 million observations recorded from all the sites each year, and they cover various vehicle and road characteristics such as fuel type, age of the vehicle, engine sizes, vehicle weight and road types. $$ \\mathrm {g C O} \_ {2} / \\mathrm {k m} = \\sum \\left(\\mathrm {g C O} \_ {2} / \\mathrm {k m} \_ {\\mathrm {y r} \\mathrm {r e g}} \\times \\frac {\\mathrm {A N P R} \_ {\\mathrm {y r} \\mathrm {r e g}}}{\\mathrm {A N P R} \_ {\\mathrm {t o t a l} 2 0 1 9}}\\right) $$ * * * 5.14. A limitation of the NEDC is that it takes no account of further ‘real-world’ effects that can have a significant impact on fuel consumption. These include use of accessories (air conditioning, lights, heaters etc.), vehicle payload (only driver +25kg is considered in tests, no passengers or further luggage), poor maintenance (tyre under inflation, maladjusted tracking, etc.), gradients (tests effectively assume a level road), weather, more aggressive driving style, etc. It is therefore desirable to uplift NEDC based data to bring it closer to anticipated ‘realworld’ vehicle performance. 5.15. An uplift factor over NEDC based gCO2/km factors is applied to account for the combined ‘real-world’ effects on fuel consumption. The uplift applied varies over time and is based on work performed by (ICCT, 2017); this study used data on almost 1.1 million vehicles from fourteen data sources and eight countries, covering the fuel consumption/CO2 from actual real-world use and the corresponding type-approval values. The values used are based on average data from the two UK-based sources analysed in the ICCT study, as summarised in Table 16 below and illustrated in Figure 2 alongside the source data/chart reproduced from the ICCT (2017) report. Table 16: Average ‘real-world’ uplift for the UK applied to gCO2/km data | Data year | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | RW uplift(%) | 15.65 | 18.30 | 20.95 | 23.60 | 26.25 | 27.63 | 29.00 | 33.33 | 41.50 | | Data year | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | | | RW uplift(%) | 38.00 | 31.50 | 31.50 | 31.50 | 21.67 | 21.75 | 22.24 | 22.31 | | 5.17. The above uplifts have been applied to the ANPR weighted SMMT gCO2/km to give the ‘Real-World’ 2024 GHG Conversion factors. The average car conversion factors were calculated by weighting with the relative mileage of the different categories. This calculation utilised data from the UK GHG Inventory on the relative % total mileage by petrol and diesel cars. Overall, for petrol and diesel, this split in total annual mileage was 55.8% petrol and 44.2% diesel, and can be compared to the respective total registrations of the different vehicle types for 2006-2023, which were 58.9% petrol and 41.1% diesel. 5.18. An adjustment factor is applied to account for the biofuel content of transportation fuels. 5.19. Conversion factors for CH4 and N2O are based on the emission factors from the UK GHGI 2019 (Ricardo Energy & Environment, 2021) and updated to align with AR5 GWP values. The emission factors used in the UK GHGI are based on COPERT 5 version 6 (EMISIA, 2022). $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ 5.20. The final conversion factors for petrol and diesel passenger cars by engine size are presented in the ‘Passenger vehicles’ and ‘Business travel- land’ worksheets of the 2024 GHG Conversion factors set. * * * Figure 2: Updated GCF 'Real world' uplift values for the UK based on (ICCT, 2017) * * * Figure 3: Comparison of 'Real world' uplift values from various sources (ICCT, 2017) Notes: In the above charts a y-axis value of 0% would mean no difference between the CO2 emissions per km experienced in ‘real-world’ driving conditions and those from official type-approval testing protocol. $$ \\mathrm {C O} \_ {2} $$ * * * Hybrid, LPG and CNG Passenger Cars 5.21. The methodology used in the 2024 update for small, medium and large hybrid petrol/diesel electric cars is the same as that used for conventional petrol and diesel vehicles. The conversion factors are based on the number of registrations and average of the gCO2/km figures provided by SMMT for new hybrid vehicles registered between 2013 and 2023. These are weighted using DfT's ANPR (Automatic Number Plate Recognition) data and an uplift applied to account for ‘real-world’ driving. 5.22. The SMMT source dataset used in the derivation of passenger car conversion factors has information on plug-in hybrid cars, which is utilised as described below, though has not been used in the calculation of hybrid conversion factors. 5.23. Due to the significant size and weight of the LPG and CNG fuel tanks, it is assumed only medium and large sized vehicles are available. In the 2024 GHG Conversion factors, CO2 conversion factors for CNG and LPG medium and large cars are derived by multiplying the equivalent petrol EF by the ratio of CNG (and LPG) to petrol conversion factors on a unit energy (Net CV) basis. For example, for a Medium car run on CNG: $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {g C O} \_ {2} / \\mathrm {k m} \_ {\\mathrm {C N G M e d i u m c a r}} = \\mathrm {g C O} \_ {2} / \\mathrm {k m} \_ {\\mathrm {P e t r o l M e d i u m c a r}} \\times \\frac {\\mathrm {g C O} \_ {2} / \\mathrm {k W h} \_ {\\mathrm {C N G}}}{\\mathrm {g C O} \_ {2} / \\mathrm {k W h} \_ {\\mathrm {P e t r o l}}} $$ 5.24. Conversion factors for CH4 and N2O are based on the emission factors from the UK GHGI 2019 (Ricardo Energy & Environment, 2021) and updated to align with AR5 GWP values. The emission factors used in the UK GHGI are based on COPERT 5 version 6 (EMISIA, 2022). $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ Plug-in Hybrid Electric and Battery Electric Passenger Cars (xEVs) 5.25. Since the number of electric vehicles (xEVs21) in the UK fleet is rapidly increasing (and will continue to increase in the future), at least for passenger cars and vans, there is a need for specific conversion factors for such vehicles to complement conversion factors for vehicles fuelled primarily by petrol, diesel, natural gas or LPG. $$ \\left(\\mathrm {x E V s} ^ {2 1}\\right) $$ 5.26. These conversion factors are currently presented in a number of data tables in the GHG Conversion factors workbook, according to the type / ‘Scope’ of the emission component. The following tables / worksheets, shown in Table 17, are required for BEVs (battery electric vehicles) and PHEVs (plug-in hybrid electric vehicles), and related REEVs (range-extended electric vehicles). Since there are still relatively few models available on the market, all PHEVs and REEVs are grouped into a single category. There are not yet meaningful numbers of fuel cell electric vehicles (FCEVs) in use, so these are not included at this time. $$ { } ^ { 2 1 } \\mathrm { x E V s } $$ * * * 5.27. Table 17 provides an overview of the GHG Conversion Factor tables that have been developed for the reporting of emissions from electric vehicles, which aligns with current reporting. Table 17: Summary of emissions reporting and tables for electric vehicle emission factors | Emission component | Emissions Scope and Reporting Worksheet | Plug-in hybrid electric vehicles(PHEVs) | Battery electric vehicles(BEVs) | | --- | --- | --- | --- | | Direct emissions from the use of petrol or diesel | Scope1: | | | | • Passenger vehicles | | | | | • Delivery vehicles | Yes | (Zero emissions) | | | Emissions resulting from electricity use: | | | | | (a) Electricity Generation | | | | | (b) Electricity Transmission&Distribution losses | (a)Scope2: | | | | •UK electricity for EVs | | | | | (b)Scope3: | | | | | •UK electricity T&D for EVs | Yes | Yes | | | Upstream emissions from the use of liquid fuels and electricity | Scope3: | | | | •WTT- passenger vehicles&travel-land | | | | | •WTT- delivery vehicles&freight | Yes | Yes | | | Total GHG emissions for all components for not directly owned /controlled assets | Scope3: | | | | •Business travel-land | | | | | •Freighting goods | | | | | •Managed assets-vehicles | Yes | Yes | | 5.28. A number of data inputs and assumptions were needed to calculate the final GHG conversion factors for electric cars and vans. Table 19 provides a summary of the key data inputs, the key data sources and other assumptions used for the calculation of the final xEV conversion factors. $$ \\mathrm {C O} \_ {2} $$ vehicles into market segments and the calculation of registrations weighted average performance figures. 5.30. Starting from 2021, the European Environment Agency (EEA) no longer provides new UK vehicle data which was previously used in calculating the factors for xEVs cars. Responsibility for the publication of the UK vehicle regulatory data has now transferred from the EEA to the UK Vehicle Certification Agency (VCA) with the data expected to be published annually. As of the time of this publication only the 2021 data (VCA, 2023) was available, therefore in the 2024 update, the number of new registrations of xEVs cars in UK in 2022 have been obtained from the UK DfT’s vehicle licensing statistics data file VEH\_0270 (DfT, 2023). Vehicle model specific CO2 emissions and energy consumption for individual models are assumed to have remained the same since the previous year and derived from the previous version of the VCA regulatory database (VCA, 2023). For new xEVs models that were not included in previous version of VCA regulatory database, their vehicle model specific CO2 emissions and energy consumption were assumed to be the same as those values from the same vehicle models in seven other EEA countries (France, Germany, Ireland, Belgium, Netherlands, Spain, and Portugal) in the latest EEA database (EEA, 2023). $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ 5.31. The xEV models included in the current databases (which cover registrations up to the end of 2022) and their allocation to different market segments, are presented in Table 18. To calculate the corresponding conversion factors for the tables split by car ‘size’ category, it is assumed segments A and B are ‘Small’ cars, segments C and D are ‘Medium’ cars and all other segments are ‘Large’ cars. Table 18: xEV car models and their allocation to different market segments | Make | Model | UK Segment | UK Segment Name | BEV | PHEV | | --- | --- | --- | --- | --- | --- | | AUDI | A3 | C | Lower Medium | - | Yes | | AUDI | A5 | E | Executive | Yes | - | | AUDI | A6 | E | Executive | - | Yes | | AUDI | A7 | E | Executive | - | Yes | | AUDI | A8 | F | Luxury Saloon | - | Yes | | AUDI | E-TRON | H | Dual Purpose | Yes | - | | AUDI | Q3 | H | Dual Purpose | - | Yes | | AUDI | Q4 | H | Dual Purpose | Yes | - | | AUDI | Q5 | H | Dual Purpose | - | Yes | | AUDI | Q7 | H | Dual Purpose | - | Yes | | AUDI | Q8 | H | Dual Purpose | - | Yes | | BENTLEY | BENTAYGA | F | Luxury Saloon | - | Yes | | BENTLEY | FLYING SPUR | F | Luxury Saloon | - | Yes | | BMW | I3 | B | Supermini | Yes | - | | BMW | I3 REEV | B | Supermini | - | Yes | | BMW | I4 | D | Upper Medium | Yes | - | | BMW | I8 | G | Specialist Sports | - | Yes | | BMW | IX | H | Dual Purpose | Yes | - | | BMW | IX3 | H | Dual Purpose | Yes | - | | BMW | SERIES 2 | C | Lower Medium | - | Yes | | BMW | SERIES 3 | D | Upper Medium | - | Yes | | BMW | SERIES 5 | E | Executive | - | Yes | | BMW | SERIES 7 | F | Luxury Saloon | Yes | Yes | | BMW | X1 | H | Dual Purpose | - | Yes | | BMW | X2 | H | Dual Purpose | - | Yes | | BMW | X3 | H | Dual Purpose | - | Yes | | BMW | X5 | H | Dual Purpose | - | Yes | | BYD | E6Y | C | Lower Medium | Yes | - | | CHEVROLET/DAEWOO | VOLT | C | Lower Medium | - | Yes | | CITROEN | BERLINGO | I | Multi Purpose Vehicle | Yes | - | | CITROEN | C4 | C | Lower Medium | Yes | - | | CITROEN | C5 | D | Upper Medium | - | Yes | | CITROEN | C-ZERO | A | Mini | Yes | - | | CITROEN | E-SPACETOURER | I | Multi Purpose Vehicle | Yes | - | | CUPRA | BORN | C | Lower Medium | Yes | - | | DS | DS3 | B | Supermini | Yes | - | | DS | DS4 | C | Lower Medium | - | Yes | | DS | DS7 | H | Dual Purpose | - | Yes | | DS | DS9 | E | Executive | - | Yes | | FERRARI | SF90 | G | Specialist Sports | - | Yes | | FIAT/ALFA ROMEO | 500 | A | Mini | Yes | - | | FORD | FOCUS | C | Lower Medium | Yes | - | | FORD | KUGA | H | Dual Purpose | - | Yes | | FORD | MUSTANG | H | Dual Purpose | Yes | - | | FORD | MONDEO | D | Upper Medium | - | Yes | | FORD | TOURNEO | H | Dual Purpose | - | Yes | | GENESIS | G80 | E | Executive | Yes | - | | GENESIS | GV60 | H | Dual Purpose | Yes | - | | GENESIS | GV70 | H | Dual Purpose | Yes | - | | GREAT WALL | FUNKY CAT | C | Lower Medium | Yes | - | | HONDA | E' | B | Supermini | Yes | - | | HYUNDAI | IONIQ | C | Lower Medium | Yes | Yes | | HYUNDAI | IX 35/TUCSON | H | Dual Purpose | - | Yes | | HYUNDAI | KONA | H | Dual Purpose | Yes | - | | HYUNDAI | SANTA FE | H | Dual Purpose | - | Yes | | JAGUAR | E-PACE | C | Lower Medium | - | Yes | | JAGUAR | F-PACE | C | Lower Medium | - | Yes | | JAGUAR | I-PACE | H | Dual Purpose | Yes | - | | JEEP | COMPASS | H | Dual Purpose | - | Yes | | JEEP | RENEGADE | H | Dual Purpose | - | Yes | | KIA | CEE'D | C | Lower Medium | - | Yes | | KIA | EV6 | C | Lower Medium | Yes | - | | KIA | OPTIMA | D | Upper Medium | - | Yes | | KIA | SORENTO | H | Dual Purpose | - | Yes | | KIA | SOUL | C | Lower Medium | Yes | - | | KIA | SPORTAGE | H | Dual Purpose | - | Yes | | KIA | NIRO | H | Dual Purpose | Yes | Yes | | KIA | XCEED | H | Dual Purpose | - | Yes | | LAND ROVER | DEFENDER | H | Dual Purpose | - | Yes | | LAND ROVER | DISCOVERY | H | Dual Purpose | - | Yes | | LAND ROVER | RANGE ROVER | H | Dual Purpose | - | Yes | | LAND ROVER | RANGE ROVER EVOQUE | H | Dual Purpose | - | Yes | | LAND ROVER | RANGE ROVER SPORT | H | Dual Purpose | - | Yes | | LAND ROVER | RANGE ROVER VELAR | H | Dual Purpose | - | Yes | | LEVC | TX | I | Multi Purpose Vehicle | - | Yes | | LEXUS | NX | H | Dual Purpose | - | Yes | | LEXUS | UX | H | Dual Purpose | Yes | - | | MAHINDRA | E20PLUS | C | Lower Medium | Yes | - | | MAZDA | CX-60 | H | Dual Purpose | - | Yes | | MAZDA | MX30 | C | Lower Medium | Yes | - | | MCLAREN | ARTURA | G | Specialist Sports | - | Yes | | MCLAREN | P1 | G | Specialist Sports | - | Yes | | MCLAREN | SPEEDTAIL | G | Specialist Sports | - | Yes | | MERCEDES BENZ | A CLASS | B | Supermini | Yes | - | | MERCEDES BENZ | A CLASS(2012) | C | Lower Medium | - | Yes | | MERCEDES BENZ | B CLASS | C | Lower Medium | Yes | Yes | | MERCEDES BENZ | C CLASS | D | Upper Medium | - | Yes | | MERCEDES BENZ | CLA | D | Upper Medium | - | Yes | | MERCEDES BENZ | E CLASS | E | Executive | - | Yes | | MERCEDES BENZ | EQA | C | Lower Medium | Yes | - | | MERCEDES | EQB | H | Dual Purpose | Yes | - | | MERCEDES BENZ | EQC | H | Dual Purpose | Yes | - | | MERCEDES | EQE | E | Executive | Yes | - | | MERCEDES BENZ | EQS | F | Luxury Saloon | Yes | - | | MERCEDES BENZ | EQV | I | Multi Purpose Vehicle | Yes | - | | MERCEDES BENZ | EVITO | I | Multi Purpose Vehicle | Yes | - | | MERCEDES BENZ | GL | H | Dual Purpose | - | Yes | | MERCEDES BENZ | GLA | C | Lower Medium | - | Yes | | MERCEDES BENZ | GLC | H | Dual Purpose | - | Yes | | MERCEDES BENZ | GLE | H | Dual Purpose | - | Yes | | MERCEDES-AMG | GT | G | Specialist Sports | - | Yes | | MERCEDES BENZ | S CLASS | F | Luxury Saloon | - | Yes | | MG | HS | I | Multi Purpose Vehicle | - | Yes | | MG | MG 4 | C | Lower Medium | Yes | - | | MG | MG 5 | D | Upper Medium | Yes | - | | MG | ZS | H | Dual Purpose | Yes | - | | MIA | MIA | A | Mini | Yes | - | | MINI | COOPER | B | Supermini | Yes | - | | MINI | COUNTRYMAN | C | Lower Medium | - | Yes | | MITSUBISHI | L200 | H | Dual Purpose | Yes | - | | MITSUBISHI | I-MIEV | A | Mini | Yes | - | | MITSUBISHI | OUTLANDER | H | Dual Purpose | - | Yes | | NISSAN | ARIYA | H | Dual Purpose | Yes | - | | NISSAN | DYNAMO | I | Multi Purpose Vehicle | Yes | - | | NISSAN | E-NV200 | I | Multi Purpose Vehicle | Yes | - | | NISSAN | LEAF | C | Lower Medium | Yes | - | | OPEL | AMPERA | D | Upper Medium | - | Yes | | OPEL | ASTRA | C | Lower Medium | - | Yes | | OPEL | COMBO | I | Multi Purpose Vehicle | Yes | - | | OPEL | CORSA | B | Supermini | Yes | - | | OPEL | GT | G | Specialist Sports | - | Yes | | OPEL | GRANDLAND | I | Multi Purpose Vehicle | - | Yes | | OPEL | MOKKA | C | Lower Medium | Yes | - | | OPEL | VIVARO | V | Van | Yes | - | | PEUGEOT | 208 | B | Supermini | Yes | - | | PEUGEOT | 308 | C | Lower Medium | - | Yes | | PEUGEOT | 508 | D | Upper Medium | - | Yes | | PEUGEOT | 2008 | C | Lower Medium | Yes | - | | PEUGEOT | 3008 | H | Dual Purpose | - | Yes | | PEUGEOT | ION | A | Mini | Yes | - | | PEUGEOT | RIFTER | V | Van | Yes | - | | PEUGEOT | TRAVELLER | V | Van | Yes | - | | PORSCHE | 918 | G | Specialist Sports | - | Yes | | PORSCHE | CAYENNE | H | Dual Purpose | - | Yes | | PORSCHE | PANAMERA | F | Luxury Saloon | - | Yes | | PORSCHE | TAYCAN | G | Specialist Sports | Yes | - | | RENAULT | FLUENCE Z.E. | D | Upper Medium | Yes | - | | RENAULT | KANGOO | I | Multi Purpose Vehicle | Yes | - | | RENAULT | MEGANE | C | Lower Medium | Yes | Yes | | RENAULT | TWIZY | A | Mini | Yes | - | | RENAULT | CAPTUR | H | Dual Purpose | - | Yes | | RENAULT | ZOE | C | Lower Medium | Yes | - | | SEAT | FORMENTOR | H | Dual Purpose | - | Yes | | SEAT | LEON | C | Lower Medium | - | Yes | | SEAT | MII | A | Mini | Yes | - | | SKODA | CITIGO | A | Mini | Yes | - | * * * Make Model UK Segment UK Segment Name BEV PHEV SKODA ENYAQ H Dual Purpose Yes - SKODA OCTAVIA D Upper Medium - Yes SKODA SUPERB E Executive - Yes SMART FORTWO A Mini Yes - SMART FORFOUR B Supermini Yes - SSANGYONG KORANDO H Dual Purpose Yes - SUBARU SOLTERRA H Dual Purpose Yes - SUZUKI ACROSS H Dual Purpose - Yes TESLA MODEL 3 E Executive Yes - TESLA MODEL S F Luxury Saloon Yes - TESLA MODEL X H Dual Purpose Yes - TESLA MODEL Y H Dual Purpose Yes - TESLA ROADSTER G Specialist Sports Yes - THINK THINKCITY A Mini Yes - TOYOTA BZ4X H Dual Purpose Yes - TOYOTA PRIUS C Lower Medium - Yes TOYOTA RAV4 H Dual Purpose - Yes VOLKSWAGEN ARTEON D Upper Medium - Yes VOLKSWAGEN E-GOLF C Lower Medium Yes - VOLKSWAGEN E-UP A Mini Yes - VOLKSWAGEN GOLF C Lower Medium - Yes VOLKSWAGEN ID BUZZ I Multi Purpose Vehicle Yes - VOLKSWAGEN ID3 C Lower Medium Yes - VOLKSWAGEN ID4 H Dual Purpose Yes - VOLKSWAGEN ID5 H Dual Purpose Yes - VOLKSWAGEN PASSAT D Upper Medium - Yes VOLKSWAGEN TIGUAN H Dual Purpose - Yes VOLKSWAGEN TOUAREG H Dual Purpose - Yes VOLKSWAGEN UP A Mini Yes - VOLVO C40 C Lower Medium Yes - VOLVO POLESTAR E Executive Yes Yes VOLVO S60 D Upper Medium - Yes VOLVO S90 E Executive - Yes VOLVO V60 D Upper Medium - Yes VOLVO V90 E Executive - Yes VOLVO XC40 H Dual Purpose Yes Yes * * * Make Model UK Segment UK Segment Name BEV PHEV VOLVO XC60 H Dual Purpose - Yes Notes: Only includes models with registrations in the UK fleet up to the end of 2022 (DFT, 2023). 5.32. During the derivation of the conversion factors, some discrepancies were found in the EEA CO₂ monitoring databases for the gCO₂/km and Wh/km data for certain models, which were then updated based on other sources of official regulatory type-approval data, for example from manufacturer's websites, EV Database (EV Database, 2023) and the Green Car Guide (Green Car Guide, 2023). 5.33. Consistent with the approach used for the calculation of conversion factors for conventionally fuelled passenger cars, the gCO₂/km and Wh/km figures from type approval with NEDC need adjusting to account for real-world performance (charging losses are already accounted for under the type approval methodology (VDA, 2014)). Several assumptions are therefore made in order to calculate adjusted 'Real-World' energy consumption and emission factors. These assumptions were discussed and agreed with DFT. 5.34. As for conventional vehicles (see earlier section for petrol and diesel cars), there has been a transition from NEDC to the new regulatory test – WLTP, to bring the results of tests under regulatory testing conditions closer to those observed in the real-world. However, the majority of vehicles in the UK fleet are registered before 2020 and so the reported emission and electricity consumption values for BEVs and PHEVs registered before 2020 are still based on the previous NEDC testing regime or both NEDC and WLTP values are provided. Therefore, the GHG CF calculations for xEVs are unchanged for those vehicles registered before 2021. Starting from the 2024 update, xEVs registered from 2021 will be calculated based on WLTP testing regime using real-world uplift factors for WLTP vehicles. 5.35. A further complication for PHEVs is that the real-world electric range is lower than that calculated on the standard regulatory testing protocol, which also needs to be accounted for in the assumption of the average share of total km running on electricity. Figure 4 illustrates the utility function used to calculate the share of electric km based on the electric range of a PHEV. Real-World factors for average gCO₂/km and Wh/km for PHEVs are therefore further adjusted based on the ratio of calculated electric shares of total km under Test-Cycle and Real-World conditions. This utility function was updated in the 2024 Conversion Factors update, to better reflect the actual share of electric km in real-world. 5.36. The key assumptions used in the calculation of adjusted Real-World gCO₂/km and Wh/km figures are summarised in Table 19. The calculated real-world figures for individual vehicle models are used to calculate the final registrations-weighted average factors for different vehicle segments/sizes. These are then combined with other GHG Conversion factors to calculate the final set of conversion factors for different Scopes/reporting tables (i.e. as summarised in earlier Table 17). * * * Table 19: Summary of key data elements, sources and key assumptions used in the calculation of GHG conversion factors for electric cars and vans Data type Raw data source Other notes Numbers of registrations of different vehicle types/models Data for 2010-2020 cars and vans: • EEA CO2 monitoring databases Data for 2021 cars and vans: • VCA regulatory databases (VCA, 2023) Data for 2022 cars and vans: • UK DFT's vehicle licensing statistics data file VEH\_0270 (DFT, 2023) This data is used in conjunction with CO₂/km and Wh/km data to calculate registrations-weighted average figures by market segment or vehicle size category. CO₂ emissions from petrol or diesel fuel use per km (test-cycle) Data for 2010-2020 cars and vans: • EEA CO2 monitoring databases Data for 2021 and 2022 cars and vans: • VCA regulatory databases (VCA, 2023) Zero for BEVs. For PHEVs, the conversion factors are for the average share of km driven in charge-sustaining mode / average liquid fuel consumption per km. Wh electricity consumption per km (test-cycle) As for CO₂ emissions Average electricity consumption per average km (i.e. factoring in for PHEVs that only a fraction of total km will be in electric mode). Test-Cycle to Real-World conversion for gCO₂ / km Assumption based on literature, consistent with the source used for the car EFs for conventional powertrains. For NEDC: • An uplift of 35% is applied to the test-cycle emission component For WLTP: • An uplift of 23.7% is applied to the test-cycle emission component * * * Data type Raw data source Other notes Test-Cycle to Real-World conversion for Wh per km Assumption based on best available information on the average difference between test-cycle and real-world performance For NEDC: • An uplift of 40% is applied to the test-cycle electrical energy consumption component. This is consistent with the uplift currently being used in the analysis for the EC DG CLIMA, developed/agreed with the EC's JRC. For WLTP: • An uplift of 12% to 20% is applied to the test-cycle electrical energy consumption component. Electric range for PHEVs under Test-Cycle conditions Available from various public sources for specific models Values representative of the models currently available on the market are used, i.e. generally between 30-50km. The notable exception is the BMW i3 REX, which was 200km up to 2015. Electric range for PHEVs under Real-World conditions Calculated based on Test-Cycle electric range and Test-Cycle to Real-World conversion for Wh per km Calculated based on Test-Cycle electric range and Test-Cycle to Real-World conversion for Wh/km Share of electric km on Test-Cycle Calculated using the standard formula used in type-approval\*: Electric km % = 1 – (25 / (25 + Electric km range)) Uses Test-Cycle electric range in km Share of electric km in Real-World conditions Calculated using the equation in Annexes 4-15 of "Commission Regulation (EU) 2017/1151 as regards the emission type approval procedures for light passenger and commercial vehicles"22 Uses Real-World electric range in km 22 [https://ec.europa.eu/transparency/comitology-register/screen/documents/082562/1/c](https://ec.europa.eu/transparency/comitology-register/screen/documents/082562/1/c) consult?lang=en * * * Data type Raw data source Other notes Loss factor for electric charging N/A Charging losses are already accounted for under the type approval testing protocol in the Wh/km dataset. GHG conversion factors for electricity consumption UK electricity conversion factors (kgCO₂e / kWh): • Electricity generated • Electricity T&D • WTT electricity generated • WTT electricity T&D From the UK GHG Conversion factors model outputs for UK Electricity CH₄, N₂O and WTT CO₂e emissions from petrol/diesel use Calculated based on derived Real-World g/km for petrol/diesel. Calculation uses GHG Conversion factors for petrol/diesel: uses the ratio of direct CO₂ emission component to CH₄, N₂O or WTT CO₂e component for petrol/diesel. Notes: \* the result of this formula is illustrated in Figure 4 below. Figure 4: Illustration of the relationship of electric range to average electric share of total km for PHEVs assumed in the calculations Notes: NEDC’s curve calculated by Ricardo based on the standard formula: Electric km % = 1 – (25 / (25 + Electric km range)). WLTP pre-2025 curve calculated by Ricardo based on the equation in Sub-Annex 8 Appendix 5 of "Commission Regulation (EU) 2017/1151". WLTP post-2025 curve calculated by Ricardo based on the equation in Annexes 4-15 of "Commission Regulation (EU) 2017/1151 as regards the emission type approval procedures for light passenger and commercial vehicles" * * * Conversion factors by Passenger Car Market Segments 5.37. For the 2024 GHG Conversion factors, the market classification split (according to SMMT classifications) was derived using detailed SMMT data on new car registrations between 2006 and 2023 split by fuel (Table 20) and again combining this with information extracted from the 2021 ANPR dataset. Adjustment factors are then applied to consider 'real-world' impacts and the biofuel content of fuels, consistent with the methodology used to derive the car engine size emission factors. 5.38. Conversion factors for CH₄ and N₂O are based on the emission factors from the UK GHGI 2019 (Ricardo Energy & Environment, 2021) and updated to align with AR5 GWP values. The emission factors used in the UK GHGI are based on COPERT 5 version 6 (EMISIA, 2022). 5.39. The supplementary market segment based conversion factors for passenger cars are presented in the 'Passenger vehicles' and 'Business travel- land' worksheets of the 2024 GHG Conversion factors set. Table 20: Average car CO₂ conversion factors and total registrations by market segment for 2006 to 2022 (based on data sourced from SMMT) Fuel Type Market Segment Example Model NEDC\* gCO₂ per km WLTP gCO₂ per km Registrations % Total Diesel A. Mini Smart Fortwo 90.0 N/A 7,517 0.1% B. Super Mini VW Polo 105.4 119.7 1,510,412 10.87% C. Lower Medium Ford Focus 114.5 130.2 3,956,203 28.47% D. Upper Medium Toyota Avensis 131.0 146.3 2,551,074 18.36% E. Executive BMW 5-Series 137.7 153.0 1,213,651 8.73% F. Luxury Saloon Bentley Continental GT 170.1 179.0 70,901 0.51% G. Specialist Sports Mercedes CLS 136.2 180.2 118,920 0.86% H. Dual Purpose Land Rover Discovery 157.6 179.9 3,329,048 23.95% I. Multi-Purpose Renault Espace 141.7 173.6 1,140,495 8.21% All Total 131.4 163.7 13,898,221 100% Petrol A. Mini Smart Fortwo 108.5 122.5 790,603 3.96% B. Super Mini VW Polo 121.9 127.6 10,176,133 50.99% * * * Fuel Type Market Segment Example Model NEDC\* gCO₂ per km WLTP gCO₂ per km Registrations % Total C. Lower Medium Ford Focus 142.1 141.9 5,252,528 26.32% D. Upper Medium Toyota Avensis 168.4 163.1 888,264 4.45% E. Executive BMW 5-Series 181.1 190.0 288,487 1.45% F. Luxury Saloon Bentley Continental GT 284.0 274.5 50,168 0.25% G. Specialist Sports Mercedes CLS 205.7 217.1 528,845 2.65% H. Dual Purpose Land Rover Discovery 163.7 175.5 1,462,457 7.33% I. Multi-Purpose Renault Espace 160.1 148.8 519,921 2.61% All Total 135.9 144.3 19,957,406 100% A. Mini Smart Fortwo 108.0 122.5 798,120 2.36% B. Super Mini VW Polo 119.0 127.5 11,686,545 34.52% C. Lower Medium Ford Focus 128.6 140.6 9,208,731 27.20% D. Upper Medium Toyota Avensis 140.3 156.4 3,439,338 10.16% E. Executive BMW 5-Series 145.3 168.0 1,502,138 4.44% F. Luxury Saloon Bentley Continental GT 212.1 236.7 121,069 0.36% G. Specialist Sports Mercedes CLS 186.8 216.6 647,765 1.91% H. Dual Purpose Land Rover Discovery 159.2 177.3 4,791,505 14.15% I. Multi-Purpose Renault Espace 147.8 167.0 1,660,416 4.90% All Total 133.6 147.6 33,855,627 100% - For 2019 and 2018, NEDCe reported data is converted to NEDC, based on an estimated 9% correlation factor from SMMT based on analysis of vehicle models where both NEDC and NEDCe values exist. NEDCe (NEDC equivalent) data are officially reported figures calculated from WLTP using an official regulatory correlation tool. They are used to check compliance of new vehicle registrations with the EU-wide regulatory CO₂ targets set on NEDC basis. * * * Direct Emissions from Taxis 5.40. The conversion factors for black cabs are based on data provided by Transport for London (TfL)23 on the testing of emissions from black cabs using real-world London Taxi cycles, and an average passenger occupancy of 1.5 (average 2.5 people per cab, including the driver) from LTI, 2007 – a more recent source has not yet been identified. This methodology accounts for the significantly different operational cycle of black cabs/taxis in the real world when compared to the NEDC (official vehicle type-approval) values, which significantly increases the emission factor (by ~40% vs NEDC). 5.41. The conversion factors (per passenger km) for regular taxis were estimated based on the average type-approval CO₂ factors for medium and large cars, uplifted by the same factor as for black cabs (i.e. 40%, based on TfL data) to reflect the difference between the type-approval figures and those operating a real-world taxi cycle (i.e. based on different driving conditions to average car use), plus an assumed average passenger occupancy of 1.4 (L.E.K. Consulting, 2002). 5.42. Conversion factors per passenger km for taxis and black cabs are presented in the 'Business travel-land' worksheet of the 2024 GHG Conversion factors set. The base conversion factors per vehicle km are also presented in the 'Business travel-land' worksheet of the 2024 GHG Conversion factors set. 5.43. Conversion factors for CH₄ and N₂O are based on the conversion factors for diesel cars from the UK GHGI 2019 (Ricardo Energy & Environment, 2021), updated to align with AR5 GWP values and are presented together with the overall total conversion factors in the 'Business travel-land' worksheet of the 2024 GHG Conversion factors set. 5.44. It should be noted that the current conversion factors for taxis do not take into account emissions spent from "cruising" for fares. Currently, robust data sources do not exist that could inform such an "empty running" factor. If suitably robust sources are identified in the future, the methodology for taxis may be revisited and revised in a future update to account for this. Direct Emissions from Vans/Light Goods Vehicles (LGVs) 5.45. Average conversion factors by fuel, for vans/light good vehicles (LGVs: N1 vehicles, vans up to 3.5 tonnes gross vehicle weight - GWW) and by size (Class I, II or III) are presented in Table 21 and in the "Delivery vehicles" worksheet of the 2024 GHG Conversion factors set. 23 The data was provided by TfL in a personal communication and is not available in a public TfL source. * * * 5.46. Conversion factors for petrol and diesel vans/LGVs are based upon emission factors and vehicle km for average sized LGVs from the UK GHGI for 2022. The factors for each class are then calculated relative to the average from quantitative analysis of regulatory data across the years 2012-2022. For the years 2012-2020 CO2 emissions factors for different size classes were derived from analysis of the EEA dataset, as detailed in previous updates. This dataset is no longer published by the EEA for UK vehicles, so an alternative approach was developed. In the previous publication (GHG CF, 2023) the 2021 regulatory data was derived from new LGV registrations from the UK DfT table VEH0160\_GB (DfT and DVLA, 2023) matched with reference weight and emissions data from the 2020 EEA database. Responsibility for the publication of the UK vehicle regulatory data has now transferred from the EEA to the UK Vehicle Certification Agency (VCA) with the data expected to be published annually. As of the time of this publication only the 2021 data (VCA, 2023) as available, therefore, a similar approach has been taken to the previous update, 2022 vehicle registration statistics from DfT table VEH0160\_GB (DfT and DVLA, 2023) is matched with reference weight and emissions data from the 2021 VCA regulatory dataset. Missing data for models with a high number of registrations is gap filled using data obtained from manufacturers websites where possible. The conversion factors are further uplifted by 15% to represent ‘real-world’ emissions (i.e. also factoring in typical vehicle loading versus unloaded test-cycle based results), consistent with the previous approach used for cars, and agreed with DfT in the absence of a similar time-series dataset of ‘real-world’ vs type-approval emissions from vans (see earlier section on passenger cars). In a future update, it is envisaged this uplift will be further reviewed. $$ E E A $$ $$ \\mathrm {C O} \_ {2} $$ $$ E E A $$ 5.47. The dataset used to allocate different vehicles to each van class is based on a reference weight (approximately equivalent to kerb weight plus 60kg) provided in the VCA van CO2 monitoring database (VCA, 2023) and are carried over from the 2021 in the absence of new 2022 data, on the assumption that there is unlikely to be significant changes in reference weight on a model by model basis from the previous year. The dataset holds a variety of information about new vans registered in 2021 (the most recent year available) and is used to derive the split of petrol and diesel van stock between size classes, as well as the CO2 emissions performance of different petrol/diesel van size categories. Importantly, this dataset is also the basis of the average van loading capacity calculations (see later section on van freight emission factors) and has replaced the dataset previously published by the EEA. It is not yet clear, given the VCA has recently taken over publication of the regulatory data, whether the most recent year required for the Conversion Factors (2 years in arrears) will be available for future years, or if vehicle registrations from the DfT will continue to be needed for the latest year. In the 2024 update, CO2 conversion factors for CNG and LPG vans are calculated from the conversion factors for conventionally fuelled vans using the same methodology as for passenger cars (section ). The average van conversion factor is calculated based on the relative UK GHGI vehicle km for petrol and diesel vans for 2022, as presented in Table 21. $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C O} \_ {2} $$ * * * 5.49. As a final additional step, an accounting for biofuel use has been included in the calculation of the final vans/LGVs emission factors. Table 21: New conversion factors for vans for the 2024 GHG Conversion factors | Van fuel | Van size | Direct gCO2e per km | | | | vkm | Payload Capacity | | --- | --- | --- | --- | --- | --- | --- | --- | | CO2 | CH4 | N2O | Total | % split | Tonnes | | | | Petrol(Class I) | Up to 1.305 tonne | 200.0 | 0.3 | 0.4 | 200.7 | 24.4% | 0.47 | | Petrol(Class II) | 1.305 to 1.740 tonne | 216.4 | 0.3 | 0.4 | 217.1 | 69.7% | 0.71 | | Petrol(Class III) | Over 1.740 tonne | 348.5 | 0.3 | 0.4 | 349.2 | 5.9% | 0.98 | | Petrol(average) | Up to 3.5 tonne | 220.2 | 0.3 | 0.4 | 220.9 | 100.0% | 0.67 | | Diesel(Class I) | Up to 1.305 tonne | 151.9 | 0.0 | 1.7 | 153.6 | 2.6% | 0.49 | | Diesel(Class II) | 1.305 to 1.740 tonne | 186.7 | 0.0 | 1.7 | 188.3 | 23.8% | 0.84 | | Diesel(Class III) | Over 1.740 tonne | 272.0 | 0.0 | 1.7 | 273.7 | 73.6% | 1.08 | | Diesel(average) | Up to 3.5 tonne | 248.6 | 0.0 | 1.7 | 250.2 | 100.0% | 1.01 | | LPG | Up to 3.5 tonne | 275.6 | 0.0 | 0.5 | 276.2 | 100.0% | 1.00 | | CNG | Up to 3.5 tonne | 249.4 | 1.3 | 0.5 | 251.2 | 100.0% | 1.00 | | Average | | 247.7 | 0.0 | 1.8 | 249.5 | 100.0% | 1.00 | * * * Plug-in Hybrid Electric and Battery Electric Vans (xEVs) 5.50. As outlined earlier for cars, since the number of electric cars and vans (xEVs24) in the UK fleet is rapidly increasing, there is now a need to include specific conversion factors for such vehicles to complement the existing conversion factors for other vehicle types. 5.51. The methodology, data sources and key assumptions utilised in the development of the conversion factors for xEVs are the same for vans as outlined earlier for cars. 5.52. It should be noted that only models with registrations in the UK fleet up to the end of 2022 are included in the model. 5.53. Table 22 provides a summary of the van models registered into the UK market by the end of 2022 (the most recent data year for the source UK DfT’s vehicle licensing statistics data file VEH\_0270 (DfT, 2023) at the time of the development of the 2024 GHG Conversion factors). At this point, the vast majority of models registered are battery electric vehicles (BEV) and so only BEVs are considered in the conversion factors. Plug-in hybrid electric vehicle (PHEV) registrations are expected to increase in the EEA database and a methodology will be developed to accommodate them in future updates to the conversion factors. Table 22: xEV van models and their allocation to different size categories | Make | Model | Van Segment | BEV | PHEV | | --- | --- | --- | --- | --- | | ADDAX | MT | Class I | Yes | - | | ALKE | ATX | Class I | Yes | - | | BYD | ETP3 | Class III | Yes | - | | CENNTRO | METRO | Class I | Yes | - | | CITROEN | BERLINGO | Class II | Yes | - | | CITROEN | E-DISPATCH | Class III | Yes | - | | CITROEN | RELAY | Class III | Yes | - | | DFSK | EC35 | Class II | Yes | - | | FIAT | DOBLO | Class II | Yes | - | | FIAT | DUCATO | Class III | Yes | - | | FIAT | SCUDO | Class III | Yes | - | | FORD | TRANSIT CONNECT | Class III | Yes | - | | FORD | TRANSIT-CUSTOM | Class III | - | Yes | | GOUPIL | G4 | Class I | Yes | - | | IVECO | DAILY | Class III | Yes | - | | LDV | V80 | Class III | Yes | - | | LONDON EV COMPANY | VN5 | Class III | - | Yes | | MAN | ETGE | Class III | Yes | - | | MERCEDES | VITO | Class III | Yes | - | | MERCEDES | ESPRINTER | Class III | Yes | - | | MERCEDES | EVITO | Class III | Yes | - | | MIA | MIA | Class I | Yes | - | | NISSAN | E-NV200 | Class II | Yes | - | | OPEL | COMBO | Class III | Yes | - | | OPEL | VIVARO | Class III | Yes | - | | PEUGEOT | E-BOXER | Class III | Yes | - | | PEUGEOT | EXPERT | Class III | Yes | - | | PEUGEOT | PARTNER | Class II | Yes | - | | RENAULT | MASTER | Class III | Yes | - | | RENAULT | KANGOO | Class II | Yes | - | | RENAULT | ZOE | Class II | Yes | - | | SAIC MAXUS | E DELIVER | Class II | Yes | - | | SAIC MAXUS | V80 | Class III | Yes | - | | TATA | ACE | Class I | Yes | - | | TOYOTA | PROACE | Class III | Yes | - | | VOLKSWAGEN | ETRANSPORTER | Class III | Yes | - | | VOLKSWAGEN | ID BUZZ | Class III | Yes | - | Notes: Only includes models with registrations in the UK fleet up to the end of 2022 5.54. All other methodological details are as already outlined for xEV passenger cars. Direct Emissions from Buses 5.55. The 2015 and earlier updates used data from DfT from the Bus Service Operators Grant (BSOG) in combination with DfT bus activity statistics (vehicle km, passenger km, average passenger occupancy) to estimate conversion factors for local buses. DfT holds very accurate data on the total amount of money provided to bus service operators under the scheme, which provides a fixed amount of financial support per unit of fuel consumed. Therefore, the total amount of fuel consumed (and hence CO2 emissions) could be calculated from this, which when combined with DfT statistics on total vehicle km, bus occupancy and passenger km allow the calculation of emission factors25. * * * 5.56. From the 2016 update onwards, it was necessary to make some methodological changes to the calculations due to changes in the Scope/coverage of the underlying DfT datasets, which include: a) BSOG data are now only available for commercial services, and not also for local authority supported services. b) BSOG data are now only available for England, outside of London: i.e. data are no b) BSOG data are now only available for England, outside of London: i.e. data are no longer available for London, due to a difference in how funding for the city is managed/provided, nor for other parts of the UK. 5.57. The conversion factors for buses account for additional direct CO2 emissions from the use of selective catalytic reduction (SCR). This technology uses a urea solution (also known as ‘AdBlue’) to effectively remove NOx and NO2 from diesel engines’ exhaust gases; this process occurs over a specially formulated catalyst. The urea solution is injected into the vehicles’ exhaust system before harmful NOx emissions are generated from the tail pipe. When the fuel is burnt, urea solution is injected into the SCR catalyst to convert the NOx into a less harmful mixture of nitrogen and water vapour; small amounts of carbon dioxide are also produced as a result of this reaction. Emissions from the consumption of urea in buses have been included in the estimates for overall CO2 conversion factors for buses. A summary of the key assumptions used in the calculation of emissions from urea is provided in the following Table 23. These are based on assumptions in the EMEP/EEA Emissions Inventory Guidebook (EEA, 2019). $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {N O} \_ {\\mathrm {x}} $$ $$ \\mathrm {N O} \_ {\\mathrm {x}} $$ $$ \\mathrm {C O} \_ {2} $$ Table 23: Key assumptions used in the calculation of CO2 emissions from Urea (aka ‘AdBlue’) use $$ \\mathrm {C O} \_ {2} $$ | | CO2EF for urea consumption(kgCO2/kg urea solution)1 | Percentage of vehicles using urea | Urea consumption rate as a percentage of fuel consumed by vehicles using urea | | --- | --- | --- | --- | | Euro IV | 0.238 | 75% | 4% | | Euro V | 0.238 | 75% | 6% | | Euro VI | 0.238 | 100% | 3.5% | 1 Notes: Assumes 32.5% (by mass) aqueous solution of urea a) Total fuel consumption (Million litres) = Total BSOG (£million) / BSOG fuel rate (p/litre) x 100 b) Total bus passenger-km (Million pkm) = Total activity (Million vkm) x Average bus b) Total bus passenger-km (Million pkm) = Total activity (Million vkm) x Average bus occupancy (#) c) Average fuel consumption (litres/pkm) = Total fuel consumption / Total bus 5.58. Briefly, the main calculation for local buses can be summarised as follows: c) Average fuel consumption (litres/pkm) = Total fuel consumption / Total bus passenger-km d) Average bus emission factor = Average fuel consumption x Fuel Emission Factor d) Average bus emission factor = Average fuel consumption x Fuel Emission Factor (kgCO2e/litre) + Average Emission Factor from Urea Use 5.59. As a final additional step, biofuel use is accounted for in the final bus emission factors. * * * 5.60. Conversion factors for coach services were estimated based on figures from National Express, who provide the majority of scheduled coach services in the UK. 5.61. Conversion factors for CH4 and N2O are based on the conversion factors from the UK GHG Inventory 2019 and updated to align with AR5 GWP values. These factors are also presented together with an overall total factor in Table 24. $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ 5.62. Table 24 gives a summary of the 2024 GHG Conversion factors and average passenger occupancy. It should also be noted that fuel consumption and conversion factors for individual operators and services will vary significantly depending on the local conditions, the specific vehicles used and on the typical occupancy achieved. Table 24: Conversion factors for buses for the 2024 GHG Conversion factors | Bus type | Average passenger occupancy | gCO2e per passenger km | | | | | --- | --- | --- | --- | --- | --- | | CO2 | CH4 | N2O | Total | | | | Local bus(not London) | 10.07 | 129.09 | 0.02 | 0.88 | 129.99 | | Local London bus | 16.70 | 73.99 | 0.01 | 0.47 | 74.47 | | Average local bus | 11.90 | 107.72 | 0.01 | 0.73 | 108.46 | | Coach | 17.56 | 26.68 | 0.01 | 0.48 | 27.17 | Notes: Average load factors/passenger occupancy mainly taken from DfT Bus statistics, Table BUS0304 “Average bus occupancy on local bus services by metropolitan area status and country: Great Britain, annual from 2004/05”. - Combined figure based on data from DfT for non-local buses and coaches combined calculated based on an average of the last 5 years for which this was available (up to 2007). Actual occupancy for coaches alone is likely to be significantly higher. Direct Emissions from Motorcycles 5.65. Conversion factors for motorcycles are split into 3 categories: 5.64. Data from type approval is not currently readily available for motorbikes and CO2 emission measurements were only mandatory in motorcycle type approval from 2005. a) Small motorbikes (mopeds/scooters up to 125cc); b) Medium motorbikes (125-500cc); and $$ \\mathrm {C O} \_ {2} $$ c) Large motorbikes (over 500cc). * * * 5.66. The conversion factors are calculated based on a large dataset kindly provided by 26 (Clear, 2008), based on a mix of magazine road test reports and user reported data. A summary is presented in Table 25, with the corresponding complete conversion factors developed for motorcycles presented in the ‘Passenger vehicles’ worksheet of the 2024 GHG Conversion factors set. The total average has been calculated weighted by the relative number of registrations of each category according to DfT licencing statistics for 2019 (DVLA, 2020). 5.67. These conversion factors are based predominantly on data derived from realworld riding conditions (rather than test-cycle based data) and are therefore likely to be more representative of typical in-use performance. The average difference between the factors based on real-world observed fuel consumption and other figures based upon test-cycle data from the European Motorcycle Manufacturers Association (ACEM) (+9%) is smaller than the corresponding differential previously used to uplift cars and vans test cycle data to real-world equivalents (+15%). 5.68. Conversion factors for CH4 and N2O are based on the conversion factors from the UK GHGI 2019 (Ricardo Energy & Environment, 2021) and have been updated to align with AR5 GWP values. These factors are also presented together with overall total conversion factors in the “Passenger vehicles”, “Business travel - land”, and “Managed assets- vehicles” worksheets of the 2024 GHG Conversion factors set. $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ Table 25: Summary dataset on CO2 emissions from motorcycles based on detailed data provided by Clear (2008) | CC Range | Model Count | Number | Av. gCO2/km | Av. MPG\* | | --- | --- | --- | --- | --- | | Up to 125cc | 24 | 58 | 85.0 | 77.3 | | 125cc to 200cc | 3 | 13 | 77.8 | 84.4 | | 200cc to 300cc | 16 | 57 | 93.1 | 70.5 | | 300cc to 400cc | 8 | 22 | 112.5 | 58.4 | | 400cc to 500cc | 9 | 37 | 122.0 | 53.9 | | 500cc to 600cc | 24 | 105 | 139.2 | 47.2 | | 600cc to 700cc | 19 | 72 | 125.9 | 52.2 | | 700cc to 800cc | 21 | 86 | 133.4 | 49.3 | | 800cc to 900cc | 21 | 83 | 127.1 | 51.7 | | 900cc to 1000cc | 35 | 138 | 154.1 | 42.6 | | 1000cc to 1100cc | 14 | 57 | 135.6 | 48.5 | | 1100cc to 1200cc | 23 | 96 | 136.9 | 48.0 | | 1200cc to 1300cc | 9 | 32 | 136.6 | 48.1 | | 1300cc to 1400cc | 3 | 13 | 128.7 | 51.1 | 26 Dataset of motorcycle fuel consumption compiled by Clear ( [http://www.clear-offset.com/](http://www.clear-offset.com/)) for the development of its motorcycle CO2 model used in its carbon offsetting products. $$ \\mathrm {C O} \_ {2} $$ * * * | CC Range | Model Count | Number | Av. gCO2/km | Av. MPG\* | | --- | --- | --- | --- | --- | | 1400cc to 1500cc | 61 | 256 | 132.2 | 49.7 | | 1500cc to 1600cc | 4 | 13 | 170.7 | 38.5 | | 1600cc to 1700cc | 5 | 21 | 145.7 | 45.1 | | 1700cc to 1800cc | 3 | 15 | 161.0 | 40.8 | | 1800cc to 1900cc | 0 | 0 | | 0.0 | | 1900cc to 2000cc | 0 | 0 | | 0.0 | | 2000cc to 2100cc | 1 | 5 | 140.9 | 46.6 | | <125cc | 24 | 58 | 85.0 | 77.3 | | 126-500cc | 36 | 129 | 103.2 | 63.7 | | >500cc | 243 | 992 | 137.2 | 47.9 | | Total | 303 | 1179 | 116.9 | 56.2 | Note: Summary data based on data provided by Clear ( [www.clear-offset.com](http://www.clear-offset.com/)) from a mix of magazine road test reports and user reported data. \* MPG has been calculated from the supplied gCO 2/km dataset, using the fuel properties for petrol from the latest conversion factors dataset. Direct Emissions from Passenger Rail 5.69. Conversion factors for passenger rail services remain constant since the publish of 2021 GHG Conversion factors but have been updated to align with AR5 instead of AR4 GWP valuesin the 2023 update. These factorsare provided in the “Business travel – land” worksheetof the 2024 GHG Conversion factors set. These include updates to the national rail, international rail (Eurostar), light rail schemes and the London Underground. These factors are based on the assumptions outlined in the following paragraphs. Note that all references to occupancy, passenger numbers/km data and another ridership associated data is based on 2019 rather than 2020 data as it is less unaffected by the COVID-19 pandemic. International Rail (Eurostar) 5.70. The international rail factor is based on a passenger-km weighted average of the conversion factors for the following Eurostar routes: London Brussels, London-- Paris, LondonMarne Le Vallee (Disney), London-Avignon-, LondonAmsterdam- 27 and the ski train from Londonto Bourg St Maurice. The conversion factors were provided by Eurostar for the 2021 update, together with information on the basis of the electricity figures used in their calculation. * * * a) Total electricity use by Eurostar trains on the UK and France/Belgium track sections; b) Total passenger numbers (and therefore calculated passenger km) on all b) Total passenger numbers (and therefore calculated passenger km) on all Eurostar services; c) Conversion factors for electricity (in kgCO2 per kWh) for the UK and c) Conversion factors for electricity (in kgCO2 per kWh) for the UK and France/Belgium journey sections. These are based on the UK grid average electricity from the GHG Conversion factors and the France/Belgium grid averages from the last freely available version of the IEA CO2 Emissions from Fuel Combustion highlights dataset (from 2013). 5.72. CH4 and N2O conversion factors remain constant since the publish of 2021 GHG Conversion factors, but have been updated to align with AR5 GWP values. These factors in the 2021 GHG Conversion factors were estimated from the corresponding conversion factors for electricity generation, proportional to the CO2 emission factors. $$ \\mathrm {C O} \_ {2} $$ National Rail 5.73. The national rail factor refers to an average emission per passenger kilometre for diesel and electric trains in 2020-21. The factor is sourced from information from the Office of the Rail Regulator’s National rail trends for 2019-20 (ORR, 2020). This has been calculated based on total electricity and diesel consumed by the railway for the year sourced from the Association of Train Operating Companies (ATOC), and the total number of passenger kilometres (from National Rail Trends). 5.74. CH4 and N2O conversion factors remain constant since the publish of 2021 GHG Conversion factors, but have been updated to align with AR5 GWP values. These factors in the 2021 GHG Conversion factors were estimated from the corresponding emissions factors for electricity generation and diesel rail from the UK GHG Inventory 2021, proportional to the CO2 emission factors. The conversion factors were calculated based on the relative passenger km proportions of diesel and electric rail provided by DfT for 2006-2007 (since no newer datasets are available from DfT). Light Rail Light Rail 5.75. The light rail factors were based on an average of factors for a range of UK tram and light rail systems, as detailed in Table 26. 5.78. The factor for the Glasgow Underground was calculated based on the annual passenger km data from DfT’s Glasgow Underground statistics, and the new 2021 grid electricity CO2 emission factor. * * * 5.79. The average emission factor for light rail and tram was estimated based on the relative passenger km of the eight different rail systems (see Table 26). 5.80. CH4 and N2O conversion factors remain constant since the publish of 2021 GHG Conversion factors but have been updated to align with AR5 GWP values. These factors in the 2021 GHG Conversion factors were estimated from the corresponding emissions factors for electricity generation, proportional to the CO2 emission factors. $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C O} \_ {2} $$ Table 26: GHG emission factors, electricity consumption and passenger km for different tram and light rail services | | Type | Electricity use | gCO2e per passenger km | | | | Million pkm | | --- | --- | --- | --- | --- | --- | --- | --- | | kWh/pkm | CO2 | CH4 | N2O | Total | | | | | DLR(Docklands Light Rail) | Light Rail | 0.109 | 22.74 | 0.10 | 0.17 | 23.01 | 620.70 | | Glasgow Underground | Light Rail | 0.164 | 34.29 | 0.15 | 0.26 | 34.70 | 40.70 | | Midland Metro | Light Rail | 0.135 | 28.24 | 0.12 | 0.21 | 28.57 | 84.30 | | Tyne and Wear Metro | Light Rail | 0.233 | 48.61 | 0.21 | 0.36 | 49.19 | 289.10 | | London Overground | Light Rail | 0.109 | 22.83 | 0.10 | 0.17 | 23.10 | 1,285.05 | | London Tramlink | Tram | 0.119 | 24.85 | 0.11 | 0.19 | 25.14 | 149.19 | | Manchester Metrolink | Tram | 0.078 | 16.37 | 0.07 | 0.12 | 16.56 | 463.00 | | Supertram | Tram | 0.350 | 73.05 | 0.32 | 0.55 | 73.92 | 68.20 | | Average\* | | 0.124 | 25.85 | 0.11 | 0.19 | 26.16 | 3000 | Notes: \* Weighted by relative passenger km London Underground 5.82. CH4 and N2O conversion factorsremain constant since the publish of 2021 GHG Conversion factors, but have been updated to align with AR5 GWP values. These factors in the 2021 GHG Conversion factors were estimated from the corresponding emissions factors for electricity generation, proportional to the CO 2 emission factors. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ * * * Indirect/WTT Emissions from Passenger Land Transport Cars, Vans, Motorcycles, Taxis, Buses and Ferries 5.83. Indirect/WTT conversion factors for cars, vans, motorcycles, taxis, buses and ferries include only emissions resulting from the fuel lifecycle (i.e. production and distribution of the relevant transport fuel). These indirect/WTT conversion factors were derived using simple ratios of the direct CO2 conversion factors and the indirect/WTT conversion factors for the relevant fuels from the “Fuels” worksheet, and applying the same ratios to the corresponding direct CO2 conversion factors for vehicle types using these fuels. Indirect/WTT conversion factors are shown in the “Passenger vehicles”, “Business travel – land” and “Business travel – air” worksheets in the 2024 GHG Conversion factors set. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ Rail 5.84. Indirect/WTT conversion factors for international rail (Eurostar), light rail and the London Underground were derived using a simple ratio of the direct CO2 conversion factors and the indirect/WTT conversion factors for grid electricity from the “UK Electricity” worksheet and the corresponding direct CO2 factors for vehicle types in the “Passenger vehicles”, “Business travel – land” and “Business travel – air” worksheets in the GHG Conversion factors set. Indirect/WTT conversion factors for international rail (Eurostar), light rail and the London Underground were derived using a simple ratio of the direct CO2 conversion factors and the indirect/WTT conversion factors for grid electricity from the “UK Electricity” worksheet and the corresponding direct CO2 conversion factors for vehicle types in the “Passenger vehicles”, “Business travel – land” and “Business travel – air” worksheets in the GHG Conversion factors set. $$ \\mathrm {C O} \_ {2} $$ 5.85. The conversion factors for National rail services are based on a mixture of emissions from diesel and electric rail. Indirect/WTT conversion factors were therefore calculated from corresponding estimates for diesel and electric rail combined using relative passenger km proportions of diesel and electric rail provided by DfT for 2006-7 (no newer similar dataset is available). * * * 6. Freight Land Transport Emission Factors Section summary 6.1. This section describes the calculation of the conversion factors for the transport of freight on land (road and rail). Scope 1 factors included are for delivery vehicles owned or controlled by the reporting organisation. Scope 3 factors are described for freighting goods over land through a third-party company, including factors for both the whole vehicle’s load of goods, or per tonne of goods shipped. WTT factors for both delivery vehicles owned by the reporting organisation and for freighting goods via a third party. Factors for managed assets (vans/LGVs, HGVs) are also detailed in this section. 6.2. Table 27 shows where the related worksheets to the freight land transport conversion factors are available in the online spreadsheets of the UK GHG Conversion factors set. Table 27 Related worksheets to freight land transport emission factors | Worksheet name | Full set | Condensed set | | --- | --- | --- | | Delivery vehicles | Y | N | | Freighting goods\* | Y | Y | | WTT- delivery vehicles & freight\* | Y | N | | Managed assets- vehicles\*\* | Y | Y | Note: \* vans, HGVs and rail only; \*\* vans and HGVs only Summary of changes since the previous update 6.3. Regulatory data for LGVs is now published by the VCA (previously the EEA), however, the 2022 dataset had not been published at the time of publication. For the 2024 update, DfT statistics on new vehicle registrations LGVs are matched mass and emission factor variables for individual models from the 2021 VCA dataset, which are used to determine factors for each class relative to the average. * * * ARTEMIS28 project showing how fuel efficiency, and therefore the CO2 emissions, varies with vehicle load. $$ \\mathrm {C O} \_ {2} $$ 6.5. The miles per gallon (MPG) figures in Table RFS0141 (DfT, 2017) are converted to gCO2 per km factors using the standard fuel conversion factor for diesel in the 2024 GHG Conversion factors. Table RFS0125 (DfT, 2023a) shows the percent loading factors are on average between 33-82% in the UK HGV fleet. Figures from the ARTEMIS project show that the effect of the load becomes proportionately greater for heavier classes of HGVs. In other words, the relative difference in fuel consumption between running an HGV completely empty or fully laden is greater for a large >33t HGV than it is for a small <7.5t HGV. From the analysis of the ARTEMIS data, it was possible to derive the figures in Table 28 showing the change in CO2 emissions for a vehicle completely empty (0% load) or fully laden (100% load) on a weight basis compared with the emissions at half-load (50% load). The data show the effect of the load is symmetrical and largely independent of the HGVs Euro emission classification and type of drive cycle. So, for example, a >17t rigid HGV emits 18% more CO2 per kilometre when fully laden and 18% less CO2 per kilometre when empty relative to emissions at half-load. $$ \\mathrm {g C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ 6.6. The refrigerated/temperature-controlled HGVs included a 19.3% and 15.9% uplift which is applied to rigid and arctic refrigerated/temperature-controlled HGVs respectively. The refrigerated/temperature-controlled average factors have a 17.3% uplift applied. This is based on average data for different sizes of refrigerated HGV from (Tassou, S.A., et al., 2009). This accounts for the typical additional energy needed to power refrigeration equipment in such vehicles over similar non-refrigerated alternatives (AEA/Ricardo, 2011). The refrigerated/temperature-controlled HGVs included a 19.3% and 15.9% uplift which is applied to rigid and arctic refrigerated/temperature-controlled HGVs respectively. The refrigerated/temperature-controlled average factors have a 17.3% uplift applied. This is based on average data for different sizes of refrigerated HGV from (Tassou, S.A., et al., 2009). This accounts for the typical additional energy needed to power refrigeration equipment in such vehicles over similar non-refrigerated alternatives (AEA/Ricardo, 2011). Table 28: Change in CO2 emissions caused by +/- 50% change in load from the average loading factor of 50% $$ \\mathrm {C O} \_ {2} $$ | | Gross Vehicle Weight(GVW) | % change in CO2 emissions | | --- | --- | --- | | Rigid | <7.5t | ±8% | | 7.5-17t | ±12.5% | | | >17t | ±18% | | | Articulated | <33t | ±20% | | >33t | ±25% | | Source: EU-ARTEMIS project $$ \\pm 8 % $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ are shown in the final factors presented in the “Delivery vehicles” and “Freighting goods” worksheets of the 2024 GHG Conversion factors set. 6.8. The loading factors in Table 28 were then used to derive corresponding CO2 factors for 0% and 100% loadings in the above sections. Because the effect of vehicle loading on CO2 emissions is linear with load (according to the ARTEMIS data), then these factors can be linearly interpolated if a more precise figure on vehicle load is known. For example, an HGV running at 75% load would have a CO2 factor halfway between the values for 50% and 100% laden factors. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ 6.9. It might be surprising to see that the CO2 than for a >33t articulated HGV. However, these factors reflect the estimated MPG figures from DfT statistics that consistently show worse MPG fuel efficiency, on average, for large rigid HGVs than large articulated HGVs once the relative degree of loading is accounted for. This is likely to be a result of the usage pattern for different types of HGVs where large rigid HGVs may spend more time travelling at lower, more congested urban speeds, operating at lower fuel efficiency than articulated HGVs which spend more time travelling under higher speed, free-flowing traffic conditions on motorways where fuel efficiency is closer to optimum. Under the drive cycle conditions more typically experienced by large articulated HGVs, the CO2 factors for large rigid HGVs may be lower than It might be surprising to see that the CO2 factor for a >17t rigid HGV is greater than for a >33t articulated HGV. However, these factors reflect the estimated MPG figures from DfT statistics that consistently show worse MPG fuel efficiency, on average, for large rigid HGVs than large articulated HGVs once the relative degree of loading is accounted for. This is likely to be a result of the usage pattern for different types of HGVs where large rigid HGVs may spend more time travelling at lower, more congested urban speeds, operating at lower fuel efficiency than articulated HGVs which spend more time travelling under higher speed, free-flowing traffic conditions on motorways where fuel efficiency is closer to optimum. Under the drive cycle conditions more typically experienced by large factors for large rigid HGVs may be lower than articulated HGVs, the CO2 factors for large rigid HGVs may be lower than indicated in “Delivery vehicles” and “Freighting goods” worksheets of the 2024 indicated in “Delivery vehicles” and “Freighting goods” worksheets of the 2024 GHG Conversion factors set. Thus, the factors in “Delivery vehicles” and GHG Conversion factors set. Thus, the factors in “Delivery vehicles” and “Freighting goods” worksheets, linked to the DfT statistics (DfT, 2017) on MPG (estimated by DfT from the survey data), reflect each HGV class’s typical usage pattern on the GB road network. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ 6.10. UK average factors for all rigid and articulated classes of HGVs are also provided in the “Delivery vehicles” and “Freighting goods” worksheets of the 2024 GHG Conversion factors set, if the user requires aggregate factors for these main classes of HGVs, perhaps in case the weight class of the HGV is not known. Again, these factors represent averages for the GB HGV fleet in 2022. These are derived directly from the mpg values for rigid and articulated HGVs in Table RFS0141 (DfT, 2017). 6.12. The conversion factors included in the “Delivery vehicles” worksheet of the 2024 GHG Conversion factors set are provided in distance units to enable CO2 emissions to be calculated from the distance travelled by the HGV in km multiplied by the appropriate conversion factor for the type of HGV and, if known, the extent of loading. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ each weight class of rigid and articulated HGVs, for all rigid and for all articulated, and aggregated for all HGVs. These are derived from the fleet average gCO2 per vehicle km factors in the “Delivery vehicles” worksheet. The average tonnes of freight lifted figures are derived from the tkm and vehicle km (vkm) figures given for each class of HGVs in Tables RFS0113 and RFS0110, respectively (DfT, 2023a). Dividing the tkm by the vkm figures gives the average tonnes of freight lifted by each HGV class. The 2024 GHG Conversion factors include factors in tonne km (tkm) for all loads (0%, 50%, 100% and average). 6.14. A tkm is the distance travelled multiplied by the weight of freight carried by the HGV. So, for example, an HGV carrying 5 tonnes freight over 100 km has a tkm value of 500 tkm. The CO2 emissions are calculated from these factors by multiplying the number of tkm the user has for the distance and weight of the goods being moved by the CO2 conversion factor in the “Freighting goods” worksheet of the 2024 GHG Conversion factors for the relevant HGV class. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ 6.15. Conversion factors for CH4 and N2O for all HGV classes remain constant since the publish of 2021 GHG Conversion factors but have been updated to align with AR5 GWP values. These factors in the 2021 GHG Conversion factors are based on the conversion factors from the UK GHG Inventory 2021. CH4 and N2O emissions are assumed to scale relative to vehicle class/CO2 emissions for HGVs. These factors are presented with an overall total factor in the “Delivery vehicles” and “Freighting goods” worksheets of the 2024 GHG Conversion factors set. $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C O} \_ {2} $$ 6.16. Emissions from the consumption of urea to control NOx exhaust emissions (in SCR systems) in HGVs are included in the estimates for overall CO2 emission factors. The method for this is the same as for buses, as described in the “Direct Emissions from Buses” section. $$ \\mathrm {N O} \_ {\\mathrm {x}} $$ $$ \\mathrm {C O} \_ {2} $$ Direct Emissions from Vans/Light Goods Vehicles (LGVs) 6.17. Conversion factors for light good vehicles (LGVs, vans up to 3.5 tonnes gross vehicle weight - GVW), were calculated based on the conversion factors per vehicle-km in the earlier section on “Direct Emissions from Vans/Light Goods Vehicles (LGVs)”. 6.18. The typical / average capacities and average payloads that are used in the calculation of van conversion factors per tonne km are presented in Table 29. The average payload capacity values are based on the quantitative (registrationsweighted) assessment of the EEA and VCA van CO2 monitoring databases for 2012-2022 registrations in the UK (EEA, 2021b), As previously mentioned new registrations for 2022 are obtained from the DfT table VEH0160\_GB (DfT and DVLA, 2023), with typical / average capacities and average payloads for 2022 registrations based on the 2021 VCA database as used in the previous update. These databases provide information on the number of registrations for different vehicle makes and models with specifications including the unloaded (reference) mass of the vehicle, maximum permitted weight rating (i.e. Gross Vehicle Weight, GVW) and regulatory CO2 emission factor. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ * * * Table 29: Typical van freight capacities and estimated average payload | Van fuel | Van size,Gross Vehicle Weight | Vkm% split | Av. Payload Capacity,tonnes | Av. Payload,tonnes | | --- | --- | --- | --- | --- | | Petrol(Class I) | Up to 1.305 tonne | 24% | 0.47 | 0.17 | | Petrol(Class II) | 1.305 to 1.740 tonne | 70% | 0.71 | 0.26 | | Petrol(Class III) | Over 1.740 tonne | 6% | 0.98 | 0.40 | | Petrol(average) | Up to 3.5 tonne | 100% | 0.67 | 0.27 | | Diesel(Class I) | Up to 1.305 tonne | 3% | 0.49 | 0.18 | | Diesel(Class II) | 1.305 to 1.740 tonne | 24% | 0.84 | 0.31 | | Diesel(Class III) | Over 1.740 tonne | 74% | 1.08 | 0.45 | | Diesel(average) | Up to 3.5 tonne | 100% | 1.01 | 0.41 | | LPG(average) | Up to 3.5 tonne | 100% | 1.00 | 0.40 | | CNG(average) | Up to 3.5 tonne | 100% | 1.00 | 0.40 | | Average | Up to 3.5 tonne | 100% | 1.00 | 0.40 | 6.19. The average load factors assumed for different vehicle types used to calculate the average payloads in Table 29are summarised inTable 30, on the basis of DfT statistics from a survey of company owned vans. No new/more recent datasets were available for the average % loading of vans/LGVs for the 2024 update. | Average van loading | Utilisation of vehicle volume capacity | | | | | | --- | --- | --- | --- | --- | --- | | 0-25% | 26-50% | 51-75% | 76-100% | Total | | | Mid-point for van loading ranges | 12.5% | 37.5% | 62.5% | 87.5% | | | Proportion of vehicles in the loading range | | | | | | | Up to 1.8 tonnes | 45% | 25% | 18% | 12% | 100% | | 1.8-3.5 tonnes | 36% | 28% | 21% | 15% | 100% | | All LGVs | 38% | 27% | 21% | 14% | 100% | | Estimated weighted average % loading | | | | | | | Up to 1.8 tonnes | - | - | - | - | 36.8% | | 1.8-3.5 tonnes | - | - | - | - | 41.3% | | All LGVs | - | - | - | - | 40.3% | 6.20. Conversion factors for CH4 and N2O remain constant since the publish of 2021 GHG Conversion factors, but have been updated to align with AR5 GWP values. These factors in the 2021 GHG Conversion factorsare based on the conversion factors from the UK GHG Inventory2021. N2O emissions are assumed to scale relative to vehicle class/CO2 emissions for diesel vans. $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ * * * 6.21. Conversion factors per tonne km are calculated from the average load factors for the different weight classes in combination with the average freight capacities of the different vans in Table 29 and the conversion factors per vehicle-km in the “Delivery vehicles” and “Freighting goods” worksheets of the 2024 GHG Conversion factors set. Direct Emissions from Rail Freight 6.22. Rail freight conversion factors remain constant since the publish of 2021 GHG Conversion factors, but have been updated from AR4 to AR5 GWP values. 6.23. The data used to update the rail freight conversion factors for the 2024 GHG Conversion factors set, was provided by the Office of the Rail Regulator’s (ORR, 2021a). This factor is presented in “Freighting goods” worksheet of the 2024 GHG Conversion factors set. 6.24. The factor can be expected to vary with rail traffic route, speed and train weight. Freight trains are hauled by electric and diesel locomotives, but the vast majority of freight is carried by diesel rail and correspondingly CO2 emissions from diesel rail freight are over 96% of the total CO2 from rail freight for 2019-20 which is extrapolated to 2020-21 (ORR, 2021a). 6.25. Traffic-, route- and freight-specific factors are not currently available, though these would present a more appropriate means of comparing modes (e.g. for bulk aggregates, intermodal, other types of freight). The rail freight CO2 factor will be reviewed and updated if data become available relevant to rail freight movement in the UK. 6.26. CH4 and N2O conversion factors remain constant since the publish of 2021 GHG Conversion factors but have been updated to align with AR5 GWP values. These factors in the 2021 GHG Conversion factors were estimated from the corresponding emissions for diesel rail from the UK GHG Inventory 2021, factors in the 2021 GHG Conversion factors were estimated from the corresponding emissions for diesel rail from the UK GHG Inventory 2021, proportional to the CO2 emissions. The conversion factors were calculated based on the relative passenger km proportions of diesel and electric rail provided by DfT for 2006-7 in the absence of more suitable tonne km data for freight. factors in the 2021 GHG Conversion factors were estimated from the corresponding emissions for diesel rail from the UK GHG Inventory 2021, emissions. The conversion factors were calculated based on the relative passenger km proportions of diesel and electric rail provided by DfT for 2006-7 in the absence of more suitable tonne km data for freight. $$ \\mathrm {C O} \_ {2} $$ Indirect/WTT Emissions from Freight Land Transport Vans and HGVs 6.27. Indirect/WTT conversion factors for Vans and HGVs include only emissions resulting from the fuel lifecycle (i.e. production and distribution of the relevant transport fuel). These indirect/WTT conversion factors were derived using simple ratios of the direct CO2 conversion factors and the indirect/WTT conversion factors for the relevant fuels from the “Fuels” worksheet and applying the same ratios to the corresponding direct CO2 conversion factors for vehicle types using these fuels. Indirect/WTT conversion factors for Vans and HGVs include only emissions resulting from the fuel lifecycle (i.e. production and distribution of the relevant transport fuel). These indirect/WTT conversion factors were derived using simple conversion factors and the indirect/WTT conversion factors for the relevant fuels from the “Fuels” worksheet and applying the same ratios to conversion factors for vehicle types using these * * * 6.29. The conversion factors for freight rail services are based on a mixture of emissions from diesel and electric rail. Indirect/WTT conversion factors were therefore calculated in a similar way to the other freight transport modes, except for combining indirect/WTT conversion factors for diesel and electricity into a weighted average for freight rail using relative CO2 emissions from traction energy for diesel and electric freight rail provided from ORR in “Table 2.100 Estimates of passenger and freight energy consumption and CO2e emissions” (ORR, 2021a). $$ \\mathrm {C O} \_ {2} $$ * * * 7. Sea Transport Emission Factors Section summary 7.1. This section contains Scope 3 factors only, relating to direct emissions from transport by sea, and WTT emissions for business travel by sea, and for freighting goods by sea. The business travel factors should be used for passenger ferries used for business trips. The WTT factors relate to emissions from the upstream extraction, refining and transport of fuels before they are used to power the ships. 7.2. Sea Transport factors remain constant since the publish of 2021 GHG Conversion factors but have been updated from AR4 to AR5 GWP values in the 2023 update. 7.3. Table 31 shows where the related worksheets to the sea transport conversion factors are available in the online spreadsheets of the UK GHG Conversion factors set. Table 31: Related worksheets to sea transport emission factors | Worksheet name | Full set | Condensed set | | --- | --- | --- | | Business travel- sea | Y | Y | | WTT-business travel- sea | Y | N | | Freighting goods\* | Y | Y | | WTT-delivery vehicles&freight\* | Y | N | Summary of changes since the previous update 7.4. There were no major methodological changes in the 2024 update. 7.4. There were no major methodological changes in the 2024 update. Direct Emissions from RoPax Ferry Passenger Transport and freight 7.5. Direct conversion factors from RoPax (roll on/roll off a passenger) passenger ferries and ferry freight transport is based on information from the Best Foot Forward (BFF) work for the Passenger Shipping Association (PSA) (BFF, 2007). No new methodology or updated dataset has been identified for the 2024 GHG Conversion factors set. * * * passenger numbers, total car numbers, total freight units and total fuel consumption. 7.7. From the information provided by the operators, figures for passenger-km, tonnekm and CO2 emissions were calculated. CO2 emissions from ferry fuels were allocated between passengers and freight on the basis of tonnages transported, taking into account freight, vehicles and passengers. Some of the assumptions included in the analysis are presented in the following table. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ Table 32: Assumptions used in the calculation of ferry emission factors | Assumption | Weight, tonnes | Source | | --- | --- | --- | | Average passenger car weight | 1.250 | (MCA,2017) | | Average weight of passenger+luggage,total | 0.100 | (MCA,2017) | | Average Freight Unit\*，total | 22.173 | (BFF,2007)^{29}$ | | Average Freight Load(per freight unit)\*，tonnes | 13.624 | (DfT,2006) | Notes: \* Freight unit includes weight of the vehicle/container as well as the weight of the actual freight load 7.8. CO2 emissions are allocated to passengers based on the weight of passengers + luggage + cars relative to the total weight of freight including freight vehicles/containers. For the data supplied by the 11 (out of 17) PSA operators this equated to just under 12% of the total emissions of the ferry operations. The emission factor for passengers was calculated from this figure and the total number of passenger-km, and is presented in the “Business travel – sea” worksheet of the 2024 GHG Conversion factors set. A further split has been provided between foot-only passengers and passengers with cars in the 2024 GHG Conversion factors set, again on a weight allocation basis. Passengers with cars' passenger-km factors should be used on a single-person basis, not account for the whole vehicle. emissions are allocated to passengers based on the weight of passengers + luggage + cars relative to the total weight of freight including freight vehicles/containers. For the data supplied by the 11 (out of 17) PSA operators this equated to just under 12% of the total emissions of the ferry operations. The emission factor for passengers was calculated from this figure and the total number of passenger-km, and is presented in the “Business travel – sea” worksheet of the 2024 GHG Conversion factors set. A further split has been provided between foot-only passengers and passengers with cars in the 2024 GHG Conversion factors set, again on a weight allocation basis. Passengers with cars' passenger-km factors should be used on a single-person basis, not account for the whole vehicle. $$ \\mathrm {C O} \_ {2} $$ 7.10. It is important to note that this conversion factor is relevant only for ferries carrying passengers and freight and that conversion factors for passenger only ferries are likely to be significantly higher. No suitable dataset has yet been identified to enable the production of a ferry emission factor for passenger-only services (which were excluded from the BFF (2007) work). * * * 7.11. CH4 and N2O conversion factors remain constant since the publish of 2021 GHG Conversion factors but have been updated to align with AR5 GWP values. These conversion factors had been estimated from the corresponding emissions for shipping from the 2021 update of the UK GHG Inventory (Ricardo Energy & Environment, 2021), proportional to the CO2 emissions. Direct Emissions from Other Marine Freight Transport 7.12. CO2 conversion factors for the other representative ships (apart from RoPax ferries discussed above) are based on information- estimates of CO2 efficiency for cargo ships, from Table 9-1 of the (IMO, 2009) report on GHG emissions from ships. The figures in the “Freighting goods” worksheet of the 2024 GHG Conversion factors set represent international average data (i.e. including vessel characteristics and typical loading factors), as UK-specific datasets are not available. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ 7.13. CH4 and N2O conversion factors remain constant since the publish of 2021 GHG Conversion factors but have been updated from AR4 to AR5 GWP values. These conversion factors had been estimated from the corresponding emissions for shipping from the 2021 update of UK GHG Inventory (Ricardo Energy & Environment, 2021), proportional to the CO2 emissions. $$ \\mathrm {C O} \_ {2} $$ Indirect/WTT Emissions from Sea Transport 7.14. Indirect/WTT emissions factors for ferries and ships include only emissions resulting from the fuel lifecycle (i.e. production and distribution of the relevant transport fuel). These indirect/WTT conversion factors were derived using simple ratios of the direct CO2 conversion factors and the indirect/WTT conversion factors for the relevant fuels and the corresponding direct CO2 conversion factors for ferries and ships using these fuels. $$ \\mathrm {C O} \_ {2} $$ * * * 8. Air Transport Emission Factors Section summary 8.1. This section contains Scope 3 factors only, related to direct emissions from and WTT emissions for business travel and freight transport by air. Air transport conversion factors should be used to report Scope 3 emissions for individuals flying for work purposes, and the related WTT factors account for the upstream emissions associated with the extraction, refining and transport of the aviation fuels prior to take-off. For freighting goods, conversion factors are provided per tonne.km of goods transported. 8.2. Air Transport conversion factors have been constant since the publish of 2023 GHG Conversion factors (aligned with AR5 GWPs values), and they are scheduled to be updated in the 2025 Conversion Factors publications. 8.3. Table 33 shows where the related worksheets to the air transport conversion factors are available in the online spreadsheets of the UK GHG Conversion factors set. Table 33: Related worksheets to air transport emission factors | Worksheet name | Full set | Condensed set | | --- | --- | --- | | Business travel-air | Y | Y | | WTT-business travel-air | Y | N | | Freighting goods\* | Y | Y | | WTT-delivery vehicles&freight\* | Y | N | Notes: \* freight flights only Summary of changes since the previous update 8.5. Conversion factors for non-UK international flights were calculated in a similar way to the main UK flight emission factors, using DfT data on flights between different regions by aircraft type, and conversion factors calculated using the EUROCONTROL small emitter’s tool. $$ \\mathrm {C O} \_ {2} $$ 8.6. The 2023 update of the average factors (presented at the end of this section) uses the EUROCONTROL small emitters tool to calculate the CO2 emissions factors $$ \\mathrm {C O} \_ {2} $$ resulting from fuel burnt over average flights for different aircraft. This data source has been selected because: a) The tool is based on a methodology designed to estimate the fuel burnt for an entire flight, it is updated on a regular basis in order to improve when possible its accuracy, and has been validated using actual fuel consumption data from airlines operating in Europe. b) The tool covers a wide range of aircraft, including many newer (and more b) The tool covers a wide range of aircraft, including many newer (and more efficient) aircraft increasingly used in flights to/from the UK, and also variants in aircraft families. c) The tool is approved for use for flights falling under the EU ETS via the Commission Regulation (EU) No. 606/2010. 8.7. A full summary of the representative aircraft selection and the main assumptions influencing the emission factor calculation are presented in Table 34. Key features of the calculation methodology, data and assumptions include: a) A wide variety of representative aircraft have been used to calculate conversion factors for domestic, short- and long-haul flights; b) Average seating capacities, load factors and proportions of passenger km by b) Average seating capacities, load factors and proportions of passenger km by the different aircraft types (subsequently aggregated to overall averages for domestic, short- and long-haul flights) have all been calculated from detailed UK Civil Aviation Authority (CAA, 2021) statistics for UK registered airlines for the year 2021 (the most recent complete dataset available at the time of calculation), split by aircraft and route type (Domestic, European Economic 30 Area, other International); c) Freight transported on passenger services has also been accounted for (with c) Freight transported on passenger services has also been accounted for (with the approach taken summarised in the following section). Accounting for freight makes a significant difference to long-haul factors. Table 34: Assumptions used in the calculation of revised average CO2 conversion factors Table 34: Assumptions used in the calculation of revised average CO2 conversion factors for passenger flights for 2024 | | Av. No. Seats | Av. Load Factor | Proportion of passenger km | Emissions Factor,kgCO2/vkm | Av. flight length,km | | --- | --- | --- | --- | --- | --- | | Domestic Flights | | | | | | | AIRBUS A320neo | 185 | 66% | 20% | 13.3 | 455 | | AIRBUS A321neo | 222 | 59% | 3% | 15.5 | 409 | | AIRBUS A319 | 151 | 71% | 24% | 15.1 | 468 | | AIRBUS A320-100/200 | 181 | 66% | 36% | 16.4 | 458 | | AIRBUS A321 | 223 | 61% | 0% | 20.0 | 376 | * * * | | Av. No. Seats | Av. Load Factor | Proportion of passenger km | Emissions Factor, kgCO2/vkm | Av. flight length,km | | --- | --- | --- | --- | --- | --- | | ATR-42-300 | 49 | 58% | 0% | 5.4 | 224 | | ATR-42-500 | 49 | 50% | 1% | 5.2 | 359 | | ATR72 200/500/600 | 70 | 51% | 3% | 5.8 | 278 | | BOEING 737-800 | 189 | 40% | 0% | 16.0 | 343 | | DORNIER 328 | 35 | 26% | 0% | 4.1 | 425 | | EMBRAER ERJ135 | 38 | 48% | 0% | 7.4 | 398 | | EMBRAER ERJ145 | 49 | 50% | 5% | 7.6 | 454 | | EMB ERJ170(170-100) | 74 | 52% | 0% | 11.3 | 368 | | EMBRAER ERJ190 | 99 | 63% | 4% | 12.3 | 491 | | EMBRAER ERJ195 | 120 | 60% | 1% | 16.0 | 257 | | Jetstream 41 | 30 | 50% | 0% | 3.5 | 361 | | SAAB FAIRCHILD 340 | 34 | 55% | 1% | 4.3 | 245 | | Average | 158 | 65% | 100%\* (total) | 12.0 | 414 | Short-haul Flights | Short-haul Flights | | | | | | | --- | --- | --- | --- | --- | --- | | AIRBUS A320neo | 183 | 56% | 11% | 8.8 | 1805 | | AIRBUS A321neo | 224 | 59% | 8% | 10.1 | 1906 | | AIRBUS A318 | 123 | 60% | 0% | 11.2 | 1087 | | AIRBUS A319 | 149 | 57% | 4% | 11.4 | 1097 | | AIRBUS A320-100/200 | 181 | 59% | 17% | 11.6 | 1416 | | AIRBUS A321 | 223 | 60% | 3% | 13.2 | 1710 | | AIRBUS A330-200 | 280 | 59% | 0% | 22.2 | 1477 | | AIRBUS A330-300 | 288 | 48% | 1% | 23.8 | 1536 | | AIRBUS A350-900 | 346 | 48% | 0% | 25.0 | 1317 | | ATR72 200/500/600 | 70 | 37% | 0% | 5.0 | 470 | | BOEING 737 MAX 8 | 194 | 62% | 5% | 9.2 | 2024 | | BOEING 737 MAX 9 | 190 | 61% | 0% | 10.2 | 1914 | | BOEING 737-300 | 148 | 36% | 0% | 12.0 | 1176 | | BOEING 737-400 | 168 | 63% | 0% | 11.9 | 1824 | | BOEING 737-500 | 105 | 64% | 0% | 10.7 | 1987 | | BOEING 737-600 | 126 | 32% | 0% | 9.5 | 1830 | | BOEING 737-700 | 140 | 60% | 0% | 13.8 | 531 | | BOEING 737-800 | 189 | 57% | 44% | 11.0 | 1627 | | BOEING 737-900 | 180 | 62% | 0% | 12.2 | 1280 | | BOEING 757-200 | 220 | 73% | 1% | 14.4 | 2262 | | BOEING 757-300 | 221 | 77% | 0% | 16.5 | 1870 | * * * Government greenhouse gas conversion factors for company reporting: Methodology paper | | Av. No. Seats | Av. Load Factor | Proportion of passenger km | Emissions Factor, kgCO₂/vkm | Av. flight length, km | | :-- | :-- | :-- | :-- | :-- | :-- | | BOEING 767-300ER/F | 305 | 71% | 1% | 19.3 | 2388 | | BOEING 777-200 | 264 | 60% | 0% | 25.1 | 1701 | | BOEING 777-300ER | 344 | 50% | 1% | 27.9 | 2584 | | BOEING 787-800 DREAMLINER | 244 | 66% | 1% | 18.7 | 2379 | | BOEING 787-900 DREAMLINER | 312 | 59% | 1% | 18.6 | 2945 | | AIRBUS A220-300 | 129 | 51% | 0% | 9.7 | 883 | | AIRBUS A220-300 | 145 | 47% | 0% | 9.5 | 1183 | | CL-600 Regional Jet CRJ-900 | 89 | 46% | 0% | 8.4 | 949 | | BOMBARDIER DASH 8 Q400 | 77 | 32% | 0% | 6.7 | 513 | | EMB ERJ170 (170-100) | 84 | 52% | 0% | 9.3 | 640 | | Average | 193 | 58% | 100%\* (total) | 11.1 | 1,537 | Long-haul Flights AIRBUS A320neo \| 179 \| 55% \| 0% \| 8.5 \| 3845 \| AIRBUS A321neo \| 184 \| 64% \| 1% \| 10.0 \| 3859 \| AIRBUS A320-100/200 \| 180 \| 73% \| 0% \| 10.8 \| 2326 \| AIRBUS A321 \| 218 \| 68% \| 0% \| 12.8 \| 2318 \| AIRBUS A330-200 \| 274 \| 64% \| 1% \| 20.8 \| 4732 \| AIRBUS A330-300 \| 281 \| 53% \| 4% \| 22.0 \| 6075 \| AIRBUS A330-900 \| 385 \| 57% \| 0% \| 19.6 \| 6627 \| AIRBUS A340-300 \| 267 \| 85% \| 0% \| 24.7 \| 6050 \| AIRBUS A350-900 \| 281 \| 32% \| 3% \| 21.7 \| 8210 \| AIRBUS A350-1000 \| 329 \| 47% \| 7% \| 24.5 \| 6599 \| AIRBUS A380-800 \| 513 \| 63% \| 8% \| 46.3 \| 5781 \| BOEING 737 MAX 8 \| 193 \| 84% \| 0% \| 8.9 \| 4430 \| BOEING 737-800 \| 188 \| 59% \| 0% \| 10.6 \| 2127 \| BOEING 757-200 \| 204 \| 39% \| 0% \| 14.2 \| 6045 \| BOEING 767-300ER/F \| 173 \| 64% \| 1% \| 18.8 \| 5876 \| BOEING 767-400 \| 246 \| 40% \| 1% \| 20.5 \| 5634 \| BOEING 777-200 \| 262 \| 60% \| 16% \| 24.8 \| 6350 \| BOEING 777-300 \| 374 \| 68% \| 1% \| 26.9 \| 5816 \| BOEING 777-F \| 259 \| 85% \| 0% \| 28.3 \| 5263 \| BOEING 777-300ER \| 317 \| 46% \| 20% \| 29.2 \| 6479 \| BOEING 787-800 DREAMLINER \| 243 \| 56% \| 10% \| 18.2 \| 6449 \| * * * 2024 Government greenhouse gas conversion factors for company reporting: Methodology paper | | Av. No. Seats | Av. Load Factor | Proportion of passenger km | Emissions Factor, kgCO₂/vkm | Av. flight length, km | | :-- | :-- | :-- | :-- | :-- | :-- | | BOEING 787-900 DREAMLINER | 256 | 47% | 21% | 18.9 | 6639 | | BOEING 787-1000 DREAMLINER | 308 | 36% | 3% | 21.2 | 5842 | | Average | 295 | 52% | 100%\* (total) | 23.1 | 6,213 | Notes: Figures on seats, load factors, % tkm and av. flight length have been calculated from 2021 CAA statistics for UK registered airlines for the different aircraft types. Figures of kgCO₂/vkm were calculated using the average flight lengths in the EUROCONTROL small emitters tool. \* 100% denotes the pkm share of the aircraft included in the assessment - as listed in the table. The aircraft listed in the table above accounts for 100% of domestic pkm, 100% of short-haul pkm and 100% of long-haul pkm. The averages presented have different weightings applied. The average number of seats and average load factors are weighted by pkm, whereas the average emission factor is weighted by vkm and the average flight length is weighted by the number of flights. They are provided for illustration only. Allocating flights into short- and long-haul: 8.8. Domestic flights are those that start and end in the United Kingdom (including the Isle of Man and the Channel Islands, but excluding Gibraltar), which are relatively simple to categorise. However, allocating flights into short- and long-haul is more complicated. In earlier versions of the GHG Conversion factors, it was suggested at a crude level to assign all flights <3700km to short haul and all >3,700km to long-haul (on the basis of the maximum range of a Boeing 737). However, this approach was relatively simplistic, difficult to apply without detailed flight distance calculations, and was not completely consistent with CAA statistical dataset used to define the emission factors. 8.9. The current preferred definition, which aligns with the CAA statistical dataset, is to assume that all fights between the UK and Europe (excluding Moldova and Ukraine, but including the Channel Islands, Gibraltar, Greenland and Turkey) and between the UK and North Africa (Algeria, Egypt, Libya, Morocco and Tunisia) are also short-haul. Flights between the UK and other destinations (North and South America, Asia (including Russia, but excluding Turkey), most of Africa, Australasia, Moldova and Ukraine should be counted as long-haul. Some examples of have been provided in the following Table 35. Table 35: Illustrative short- and long-haul flight distances from the UK | Area | Destination Airport | Distance, km | | :-- | :-- | :-- | | Domestic | | | | Average (CAA statistics) | | 414 | | Short-haul | | | | Europe | Amsterdam, Netherlands | 400 | * * * Area Destination Airport Distance, km Europe Prague (Ruzyne), Czech Rep 1,000 Europe Malaga, Spain 1,700 Europe Athens, Greece 2,400 North Africa Abu Simbel/Sharm El Sheikh, Egypt 3,300 Average (CAA statistics) 1,537 Long-haul Southern Africa Johannesburg/Pretoria, South Africa 9,000 Middle East Dubai, UAE 5,500 North America New York (JFK), USA 5,600 North America Los Angeles California, USA 8,900 South America Sao Paulo, Brazil 9,400 Indian sub-continent Bombay/Mumbai, India 7,200 Far East Hong Kong 9,700 Australasia Sydney, Australia 17,000 Average (CAA statistics) 6,213 Note: Distances based on International Passenger Survey (Office for National Statistics) calculations using airport geographic information. Average distances calculated from CAA statistics for all flights to/from the UK in 2013 8.10. Aviation factors are also included for international flights between non-UK destinations. This relatively high-level analysis of Innovata data on intercontinental flights provided by DfT’s aviation team allows users to choose a different factor for passenger air travel if flying between countries outside of the UK. All factors presented are for direct (non-stop) flights only. This analysis was only possible for passenger air travel and so international freight factors are assumed to be equal to the current UK long haul air freight factors$^{31}$. Taking Account of Freight 8.11. Freight, including mail, are transported by two types of aircraft – dedicated cargo aircraft which carry freight only, and passenger aircraft which carry both passengers and their luggage, as well as freight. The CAA data show that almost all freight carried by passenger aircraft is done on scheduled long-haul flights. In fact, the quantity of freight carried on scheduled long-haul passenger flights is more than 4 times higher than the quantity of freight carried on scheduled long- $^{31}$ Please note - The international factors included are an average of short and long-haul flights which explains the difference between the UK factors and the international ones. * * * haul cargo services (however this is not the case when comparing individual flights). 8.12. The CAA data provides a split of tonne km for freight and passengers (plus luggage) by airline for both passenger and cargo services. This data may be used as a basis for an allocation methodology. There are essentially three options, with the resulting conversion factors presented in Table 36: a. No Freight Weighting: Assume all the CO₂ is allocated to passengers on these services. b. Freight Weighting Option 1: Use the CAA tonne km (tkm) data directly to apportion the CO₂ between passengers and freight. However, in this case, the derived conversion factors for freight are significantly higher than those derived for dedicated cargo services using similar aircraft. c. Freight Weighting Option 2: Use the CAA tkm data modified to treat freight on a more equivalent/consistent basis to dedicated cargo services. This accounts for the additional weight of equipment specific to passenger services (e.g. seats, galleys, etc.) in the calculations. Table 36: CO₂ conversion factors for alternative freight allocation options for passenger flights based on 2024 GHG Conversion factors | Freight Weighting: Mode | None | Option 1: Direct | Option 2: Equivalent | | :-- | :-- | :-- | :-- | | Passenger tkm % of total | gCO₂ /pkm | Passenger tkm % of total | gCO₂ /pkm | | Domestic flights | 100.00% | 148.0 | 99.76% | | Short-haul flights | 100.00% | 101.8 | 99.04% | | Long-haul flights | 100.00% | 163.1 | 64.19% | 8.13. The basis of the freight weighting Option 2 is to take account of the supplementary equipment (such as seating, galley) and other weight for passenger aircraft compared to dedicated cargo aircraft in the allocation. In comparing the freight capacities of the cargo configuration compared to passenger configurations, we may assume that the difference represents the tonne capacity for passenger transport. This includes the weight of passengers and their luggage (around 100 kg per passenger according to IATA), plus the additional weight of seating, the galley, and other airframe adjustments necessary for passenger service operations. The derived weight per passenger seat used in the calculations for the 2024 GHG Conversion factors were calculated for the specific aircraft used and are on average over three times (3.09) the weight per passenger and their luggage alone. In the Option 2 methodology the derived ratio for different aircraft types were used to upscale the CAA passenger tonne km data, increasing this as a percentage of the total tonne km – as shown in Table 36. 8.14. It does not appear that there is a distinction made (other than in purely practical size/bulk terms) in the provision of air freight transport services in terms of whether something is transported by dedicated cargo service or on a passenger service. The related calculation of freight conversion factors (discussed in a later section) leads to very similar conversion factors for both passenger service freight and dedicated cargo services for domestic and short-haul flights. This is also the case for long-haul flights under freight weighting Option 2, whereas under Option 1 the passenger service factors are substantially higher than those calculated for dedicated cargo services. It therefore seems preferable to treat freight on an equivalent basis by utilising freight weighting Option 2. 8.15. Option 2 is the preferred methodology to allocate emissions between passengers and freight, Option 1 is included for information only. 8.16. Validation checks using the derived conversion factors calculated using the EUROCONTROL small emitters tool and CAA flights data have shown a very close comparison in derived CO₂ emissions with those from the UK GHG Inventory (which is scaled using actual fuel supplied) (Ricardo, 2024). 8.17. The final average conversion factors for aviation are presented in Table 37. The figures in Table 37 DO NOT include the 8% uplift for Great Circle distance NOR the uplift to account for additional impacts of radiative forcing which are applied to the conversion factors provided in the 2024 GHG Conversion Factor set. Table 37: Final average CO₂ conversion factors for passenger flights for 2024 GHG Conversion factors (excluding distance and RF uplifts) | Mode | Factors for 2024 | | :-- | :-- | | Av. Load Factor% | gCO₂/pkm | | Domestic flights | 64.9% | | Short-haul flights | 57.6% | | Long-haul flights | 51.5% | Notes: Average load factors based on data provided by DIT that contains detailed analysis of CAA statistics for the year 2021 Taking Account of Seating Class Factors 8.18. The efficiency of aviation per passenger km is influenced not only by the technical performance of the aircraft fleet, but also by the occupancy/load factor of the flight. Different airlines provide different seating configurations that change the total number of seats available on similar aircraft. Premium priced seating, such as in First and Business class, takes up considerably more room in the aircraft than economy seating and therefore reduces the total number of passengers that can be carried. This in turn raises the average CO₂ emissions per passenger km. 8.19. There is no agreed data/methodology for establishing suitable scaling factors representative of average flights. However, in 2008 a review was carried out of the seating configurations from a selection of 16 major airlines and average seating configuration information from Boeing and Airbus websites. This evaluation was used to form a basis for the seating class based conversion factors provided in Table 38, together with additional information obtained either directly from airline websites or from other specialist websites that had already collated such information for most of the major airlines. * * * 8.20. For long-haul flights, the relative space taken up by premium seats can vary by a significant degree between airlines and aircraft types. The variation is at its most extreme for First class seats, which can account for from 3 to over 6 times$^{32}$ the space taken up by the basic economy seating. Table 38 shows the seating class-based emission factors, together with the assumptions made in their calculation. An indication is also provided of the typical proportion of the total seats that the different classes represent in short- and long-haul flights. The effect of the scaling is to lower the economy seating emission factor in relation to the average, and increase the business and first class factors. 8.21. For domestic flights, the space taken up by premium seats is not significantly more than that taken up by the basic economy seating. It was therefore deemed unnecessary to provide further breakdown by seating class. 8.22. The relative share in the number of seats by class for short-haul and long-haul flights was updated/revised in 2015 using data provided by DFT's aviation team, following checks conducted by them on the validity of the current assumptions based on more recent data. Table 38: CO$\_2$ conversion factors by seating class for passenger flights for 2024 GHG Conversion factors (excluding distance and RF uplifts) | Flight type | Cabin Seating Class | Av. Load Factor % | gCO$\_2$/pkm | Number of economy seats | % of average gCO$\_2$/pkm | % Total seats | | :-- | :-- | :-- | :-- | :-- | :-- | :-- | | Domestic | Weighted average | 64.9% | 147.6 | 1.00 | 100.0% | 100.0% | | Short-haul | Weighted average | 57.6% | 100.8 | 1.02 | 100.0% | 100.0% | | | Economy class | 57.6% | 99.1 | 1.00 | 98.4% | 96.7% | | | First/Business class | 57.6% | 148.7 | 1.50 | 147.5% | 3.3% | | Long-haul | Weighted average | 51.5% | 141.6 | 1.31 | 100.0% | 100.0% | | | Economy class | 51.5% | 108.4 | 1.00 | 76.6% | 83.0% | | | Economy+ class | 51.5% | 173.5 | 1.60 | 122.5% | 3.0% | | | Business class | 51.5% | 314.5 | 2.90 | 222.1% | 11.9% | | | First class | 51.5% | 433.8 | 4.00 | 306.3% | 2.0% | Notes: Average load factors based on data provided by DIT that contains detailed analysis of CAA statistics for the year 2021 Freight Air Transport Direct CO$\_2$ Emission Factors 8.23. Freight Air transport factors remain constant since the publish of 2023 GHG Conversion factors, and they are scheduled to be updated in the 2025 Conversion Factors publications. $^{32}$ For the first-class sleeper seats/beds frequently used in long-haul flights. * * * 8.24. Air Freight, including mail, are transported by two types of aircraft – dedicated cargo aircraft which carry freight only, and passenger aircraft which carry both passengers and their luggage, as well as freight. 8.25. Data on freight movements by type of service are available from the Civil Aviation Authority (CAA, 2021). These data show that almost all freight carried by passenger aircraft is done on scheduled long-haul flights and accounts approximately for 100% of all long-haul air freight transport. How this freight carried on long-haul passenger services is treated has a significant effect on the average emission factor for all freight services. 8.26. The next section describes the calculation of conversion factors for freight carried by cargo aircraft only and then the following sections examine the impact of freight carried by passenger services and the overall average for all air freight services. Conversion factors for Dedicated Air Cargo Services 8.27. Table 39 presents the average conversion factors for dedicated air cargo. As with the passenger aircraft methodology, the factors presented here do not include the distance or radiative forcing uplifts applied to the conversion factors provided in the 2024 GHG Conversion Factor data tables. Table 39: Revised average CO₂ conversion factors for dedicated cargo flights for 2024 GHG Conversion factors (excluding distance and RF uplifts) | Mode | Factors for 2024 | kgCO₂/tkm | | :-- | :-- | :-- | | Domestic flights | 50.6% | 3.0 | | Short-haul flights | 74.9% | 1.2 | | Long-haul flights | 73.8% | 0.6 | Note: Average load factors based on Annual UK Airlines Statistics by Aircraft Type – CAA 2012 (Equivalent datasets after this are unavailable due to changes to CAA’s confidentiality rules) 8.28. The updated factors have been calculated in the same basic methodology as for the passenger flights, using the EUROCONTROL small emitters tool (EUROCONTROL, 2019). A full summary of the representative aircraft selection and the main assumptions influencing the emission factor calculation are presented in Table 40. The key features of the calculation methodology, data and assumptions for the GHG Conversion factors include: a) A wide variety of representative aircraft have been used to calculate conversion factors for domestic, short- and long-haul flights; b) Average freight capacities, load factors and proportions of tonne km by the different airlines/aircraft types have been calculated from CAA (Civil Aviation Authority) statistics for UK registered airlines for the year 2021 (the latest available complete dataset) (CAA, 2021). * * * Table 40: Assumptions used in the calculation of average CO₂ conversion factors for dedicated cargo flights for the 2024 GHG Conversion factors | | Average Cargo Capacity, tonnes | Av. Load Factor | Proportion of tonne km | EF, kgCO₂ /km | Av. flight length, km | | :-- | :-- | :-- | :-- | :-- | :-- | | Domestic Flights | | | | | | | BAE 146-300/QT | 10.0 | 34% | 6.8% | 11.61 | 1019 | | AIRBUS A321 | 18.8 | 45% | 12.0% | 18.45 | 459 | | AIRBUS A350-1000 | 68.0 | 50% | 21.5% | 31.94 | 804 | | BOEING 737-300 | 15.2 | 45% | 17.2% | 20.86 | 229 | | BOEING 757-200 | 23.2 | 56% | 37.5% | 44.01 | 148 | | BOEING 767-300ER/F | 52.7 | 50% | 0.7% | 30.44 | 369 | | BOEING 787-1000 DREAMLINER | 57.3 | 50% | 0.1% | 33.82 | 507 | | BOEING 787-800 DREAMLINER | 43.3 | 50% | 0.5% | 23.13 | 731 | | BOEING 787-900 DREAMLINER | 52.6 | 50% | 3.6% | 24.49 | 836 | | Average | 31.4 | 50% | 100% | 26.29 | 379 | | Short-haul Flights | | | | | | | AIRBUS A321 | 20.5 | 45% | 3.5% | 13.39 | 1545 | | AIRBUS A350-1000 | 68.0 | 73% | 34.2% | 25.04 | 2974 | | BOEING 737-400 | 15.0 | 45% | 2.3% | 14.63 | 578 | | BOEING 737-800 | 15.8 | 45% | 0.8% | 14.69 | 441 | | BOEING 757-200 | 22.0 | 77% | 50.7% | 18.88 | 718 | | BOEING 767-300ER/F | 52.7 | 73% | 7.6% | 20.53 | 1365 | | BOEING 787-1000 DREAMLINER | 57.3 | 73% | 0.9% | 23.85 | 1873 | | Average | 40.1 | 73% | 100% | 19.03 | 1,432 | | Long-haul Flights | | | | | | | AIRBUS A321 | 20.2 | 45% | 0.2% | 12.69 | 2633 | | AIRBUS A330-300 | 47.8 | 45% | 3.3% | 22.28 | 3666 | | AIRBUS A350-1000 | 68.0 | 68% | 16.4% | 24.38 | 8011 | | BOEING 747-400F | 111.5 | 73% | 14.1% | 39.97 | 5098 | * * * | | Average Cargo Capacity, tonnes | Av. Load Factor | Proportion of tonne km | EF,kgCO2/vkm | Av. flight length,km | | --- | --- | --- | --- | --- | --- | | BOEING 757-200 | 21.6 | 79% | 1.2% | 16.12 | 1241 | | BOEING 777-200 | 37.3 | 68% | 5.4% | 24.90 | 6787 | | BOEING 777-300ER | 50.8 | 68% | 17.1% | 29.68 | 8474 | | BOEING 787-1000 DREAMLINER | 57.3 | 68% | 0.7% | 21.54 | 5045 | | BOEING 787-800 DREAMLINER | 43.3 | 68% | 4.4% | 18.21 | 7281 | | BOEING 787-900 DREAMLINER | 52.6 | 68% | 33.1% | 19.00 | 8325 | | BOEING 767-300ER/F | 29.6 | 68% | 4.0% | 19.31 | 3676 | | Average | 60.4 | 68% | 100% | 24.85 | 4,381 | Note: Figures on cargo, load factors, % tkm and av. flight length have been calculated from CAA statistics for UK registered airlines for different aircraft in the year 2021. Figures of kgCO2/vkm were calculated using the average flight lengths in the EUROCONTROL small emitters tool (EUROCONTROL, 2019). 8.29. The CAA data provides a similar breakdown for freight on passenger services as it does for cargo services. As previously discussed, the statistics give tonne-km data for passengers and for freight. This information has been used in combination with the assumptions for the earlier calculation of passenger conversion factors to calculate the respective total emission factor for freight carried on passenger services. These conversion factors are presented in Table 41 with the two different allocation options for long-haul services. The factors presented here do not include the distance or radiative forcing uplifts applied to the conversion factors provided in the 2024 GHG Conversion Factor set (discussed later). The CAA data provides a similar breakdown for freight on passenger services as it does for cargo services. As previously discussed, the statistics give tonne-km data for passengers and for freight. This information has been used in combination with the assumptions for the earlier calculation of passenger conversion factors to calculate the respective total emission factor for freight carried on passenger services. These conversion factors are presented in Table 41 with the two different allocation options for long-haul services. The factors presented here do not include the distance or radiative forcing uplifts applied to the conversion factors provided in the 2024 GHG Conversion Factor set (discussed later). Table 41: Air freight CO2 conversion factors for alternative freight allocation options for passenger flights for 2024 GHG Conversion factors (excluding distance and RF uplifts) Freight % Total Freight tkm Option 1: Direct Option 2: Equivalent | Freight Weighting: Mode | % Total Freight tkm | | Option 1: Direct | | Option 2: Equivalent | | | --- | --- | --- | --- | --- | --- | --- | | Passenger Services (PS) | Cargo Services | PS Freight tkm,% total | Overall kgCO2/tkm | PS Freight tkm,% total | Overall kgCO2/tkm | | | Domestic flights | 0.8% | 99.2% | 0.2% | 2.5 | 0.2% | 2.5 | | Short-haul flights | 0.1% | 99.9% | 1.0% | 0.9 | 1.0% | 0.9 | | Long-haul flights | 43.5% | 56.5% | 35.8% | 0.7 | 12.7% | 0.6 | $$ \\mathrm {O} \_ {2} $$ * * * 8.30. CAA statistics include excess passenger baggage in the ‘freight’ category, which would under Option 1 result in a degree of under-allocation to passengers. Option 2 therefore appears to provide the more reasonable means of allocation. 8.31. Option 2 has been selected as the preferred methodology for freight allocation and is included in all of the presented conversion factors for 2024. Average Conversion factors for All Air Freight Services 8.32. Table 42 presents the final average air freight conversion factors for all air freight for the 2024 GHG Conversion factors. The conversion factors have been calculated from the individual factors for freight carried on passenger and dedicated freight services, weighted according to their respective proportion of the total air freight tonne km. The factors presented here do not include the distance or radiative forcing uplifts applied to the conversion factors provided in the 2024 GHG Conversion Factor set (discussed later). Table 42: Final average CO2 conversion factors for all air freight for 2024 GHG Conversion factors (excluding distance and RF uplifts) $$ \\mathrm {C O} \_ {2} $$ | Mode | % Total Air Freight tkm | | All Air FreightkgCO2/tkm | | --- | --- | --- | --- | | Passenger Services | Cargo Services | | | | Domestic flights | 0.8% | 99.2% | 2.5 | | Short-haul flights | 0.1% | 99.9% | 0.9 | | Long-haul flights | 43.5% | 56.5% | 0.6 | Air Transport Direct Conversion factors for CH4 and N2O $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ Emissions of CH4 $$ \\mathrm {C O} \_ {2}, $$ 8.33. Total emissions of CO2, CH4 aggregate level for aviation as a whole in the UK GHG inventory. The relative proportions of total CO2 and CH4 (Ricardo, 2024) (see Table 43) were used to calculate the specific CH4 factors per passenger km or tonne-km relative to the corresponding CO2 factors. The resulting air transport conversion factors for the 2024 GHG Conversion factors are presented in Table 44 for passengers and Table 45 for freight. , CH4 and N2O are calculated in detail and reported at an aggregate level for aviation as a whole in the UK GHG inventory. The relative and CH4 emissions from the UK GHG inventory for 2021 (Ricardo, 2024) (see Table 43) were used to calculate the specific CH4 conversion factors per passenger km or tonne-km relative to the corresponding CO2 emission factors. The resulting air transport conversion factors for the 2024 GHG Conversion factors are presented in Table 44 for passengers and Table 45 for $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {C O} \_ {2} $$ * * * Table 43: Total emissions of CO2, CH4 and N2O for domestic and international aircraft from the UK GHG inventory for 2021 $$ \\mathrm {C O} \_ {2}, $$ | | CO2 | | CH4 | | N2O | | | --- | --- | --- | --- | --- | --- | --- | | Mt CO2e | % Total CO2e | Mt CO2e | % Total CO2e | Mt CO2e | % Total CO2e | | | Aircraft - domestic | 0.74 | 98.94% | 0.0009 | 0.13% | 0.007 | 0.94% | | Aircraft - international | 13.09 | 99.06% | 0.0009 | 0.01% | 0.124 | 0.94% | Emissions of N2O $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ 8.34. Similar to those for CH4, conversion factors for N2O per passenger-km or tonnekm were calculated on the basis of the relative proportions of total CO2 and N2O emissions from the UK GHG inventory for 2021 (Ricardo, 2024) (see Table 43), and the corresponding CO2 emission factors. The resulting air transport conversion factors for the 2024 GHG Conversion factors are presented in Table 44 for passengers and Table 45 for freight. The factors presented here do not include the distance or radiative forcing uplifts applied to the conversion factors provided in the 2024 GHG Conversion Factor set (discussed later). $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2}, $$ $$ \\mathrm {C H} \_ {4} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ | Air Passenger Mode | Seating Class | CO2gCO2/pkm | CH4gCO2e/pkm | N2OgCO2e/pkm | Total GHGgCO2e/pkm | | --- | --- | --- | --- | --- | --- | | Domestic flights | Average | 147.6 | 0.2 | 1.4 | 149.2 | | Short-haul flights | Average | 100.8 | 0.0 | 1.0 | 101.7 | | Economy | 99.1 | 0.0 | 0.9 | 100.0 | | | First/Business | 148.7 | 0.0 | 1.4 | 150.1 | | | Long-haul flights | Average | 141.6 | 0.0 | 1.3 | 143.0 | | Economy | 108.4 | 0.0 | 1.0 | 109.5 | | | Economy+ | 173.5 | 0.0 | 1.6 | 175.2 | | | Business | 314.5 | 0.0 | 3.0 | 317.5 | | | First | 433.8 | 0.0 | 4.1 | 437.9 | | | International flights(non-UK) | Average | 95.3 | 0.0 | 0.9 | 96.2 | | Economy | 73.0 | 0.0 | 0.7 | 73.7 | | | Economy+ | 116.7 | 0.0 | 1.1 | 117.9 | | | Business | 211.6 | 0.0 | 2.0 | 213.6 | | * * * | Air Passenger Mode | Seating Class | CO2gCO2/pkm | CH4gCO2e/pkm | N2OgCO2e/pkm | Total GHGgCO2e/pkm | | --- | --- | --- | --- | --- | --- | | | First | 291.9 | 0.0 | 2.8 | 294.6 | Note: Totals may vary from the sums of the components due to rounding in the more detailed dataset. Table 45: Final average CO2, CH4 and N2O conversion factors for air freight transport for 2024 GHG Conversion factors (excluding distance and RF uplifts) $$ \\mathrm {C O} \_ {2}, $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ | Air Freight Mode | CO2kgCO2/tkm | CH4kgCO2e/tkm | N2OkgCO2e/tkm | Total GHGkgCO2e/tkm | | --- | --- | --- | --- | --- | | Passenger Freight | | | | | | Domestic flights | 1.92 | 0.0025 | 0.0182 | 1.95 | | Short-haul flights | 1.17 | 0.0001 | 0.0111 | 1.18 | | Long-haul flights | 0.57 | 0.0000 | 0.0054 | 0.57 | | Dedicated Cargo | | | | | | Domestic flights | 2.54 | 0.0033 | 0.0240 | 2.56 | | Short-haul flights | 0.90 | 0.0001 | 0.0086 | 0.91 | | Long-haul flights | 0.62 | 0.0000 | 0.0058 | 0.62 | | All Air Freight | | | | | | Domestic flights | 2.53 | 0.0032 | 0.0240 | 2.56 | | Short-haul flights | 0.90 | 0.0001 | 0.0086 | 0.91 | | Long-haul flights | 0.60 | 0.0000 | 0.0056 | 0.60 | Note: Totals may vary from the sums of the components due to rounding in the more detailed dataset. 8.36. We wish to see standardisation in the way that emissions from flights are calculated in terms of the distance travelled and any uplift factors applied to account for circling and delay. However, we acknowledge that a number of methods are currently used. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ * * * 8.37. An 8% uplift factor is used in the UK Greenhouse Gas Inventory to scale up Great Circle distances (GCD) for flights between airports to take into account indirect flight paths and delays, etc. This is lower than the 9-10% suggested by IPCC Aviation and the global atmosphere and has been agreed with DfT based on recent analysis as more appropriate for flights arriving and departing from the UK. This factor has been used since the 2014 update of both the GHGI, and the GHG Conversion factors set. 8.38. It is not practical to provide a database of origin and destination airports to calculate flight distances in the GHG Conversion factors. However, the principal of adding a factor of 8% to distances calculated on a Great Circle is recommended (for consistency with the existing approach) to take account of indirect flight paths and delays/congestion/circling. This is the methodology recommended to be used with the GHG Conversion factors and is applied already to the conversion factors presented in the 2024 GHG Conversion factors set. Non-CO2 impacts and Radiative Forcing $$ \\mathrm {n - C O} \_ {2} $$ 8.39. The conversion factors provided in the 2024 GHG Conversion factors “Business travel – air” and “Freighting goods” worksheets refer to aviation's direct CO2, CH4 and N2O emissions only. There is currently uncertainty over the magnitude of the and N2O emissions only. There is currently uncertainty over the magnitude of the other non-CO2 contrails, NOX, etc.) which have been indicatively accounted for by applying a multiplier to account for CO2 O emissions only. There is currently uncertainty over the magnitude of the radiative forcing effects of aviation (including water vapour, , etc.) which have been indicatively accounted for by applying a multiplier to account for CO2 equivalent emissions in some cases. $$ “ F $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {N O} \_ {\\mathrm {X}}, $$ $$ \\mathrm {C O} \_ {2} $$ 8.40. The use of CO2 Potential or the Global Temperature change Potential requires definition of a time horizon – the period over which the metric is calculated for. Such a choice is not a scientific one but a policy one. In the UNFCCC, the Global Warming Potential for 100 years is used (GWP100). The application of GWPs to short-lived climate forcers, such as the non-CO2 an active area of research. Nonetheless, aviation imposes other effects on the climate which are greater than that implied from simply considering its CO2 emissions alone. equivalent emissions metrics such as the Global Warming Potential or the Global Temperature change Potential requires definition of a time horizon – the period over which the metric is calculated for. Such a choice is not a scientific one but a policy one. In the UNFCCC, the Global Warming Potential for 100 years is used (GWP100). The application of GWPs to short-lived climate forcers, such as the non-CO2 effects of aviation has particular problems, but this is an active area of research. Nonetheless, aviation imposes other effects on the climate which are greater than that implied from simply considering its CO2 emissions alone. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ 8.42. On the other hand, consideration of the non-CO2 climate change effects of aviation can be important in some cases, and there is currently no better way of taking these effects into account than applying an aggregate multiplier. A multiplier of 1.7 is recommended as a central estimate, based on the best available scientific evidence, as summarised in Table 46 and the GWP100 figure (consistent with UNFCCC reporting convention) in Table 47 below and in analysis by Lee et al. (2021). $$ \\mathrm {G W P} \_ {1 0 0} $$ * * * 8.43. It is important to note that the value of this 1.7 multiplier is subject to significant uncertainty and should only be applied to the CO2 component of direct emissions (i.e. not also to the CH4 and N2O emissions components). The 2024 GHG Conversion factors provide separate conversion factors including this radiative forcing uplift in separate tables in the “Business travel – air” and “Freighting goods” worksheets. The 1.7 multiplier is equally applicable to the CO2 component of the scope 1 litres based emission factors for aviation turbine fuel. $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ 8.44. The non-CO2 effects are likely to be more pronounced at higher altitudes. However, the current scientific evidence relates to aviation emissions in their entirety, and it provides no means of distinguishing the affects at different altitudes or during different phases of the flight. The multiplier is therefore recommended to be applied equally to all flights irrespective of distance or altitude and to equally to all phases of the flight, albeit accepting the approximations involved in this approach. Similarly, due to the flight altitudes, the non-CO2 effects are likely to be less pronounced for turboprops than for commercial jet aircraft, but again the scientific evidence does not provide a mechanism to treat them differently, so the recommendation remains to apply the multiplier equally to all flights. $$ - \\mathrm {C O} \_ {2} $$ Table 46: Impacts of radiative forcing according to Lee et al., (2021) | ERF(mWm-2) | 2018a | 2011a | 2005a | Sensitivity to emissions | ERF/RF | | --- | --- | --- | --- | --- | --- | | Contrail cirrus | 57.4(17,98) | 44.1(13,75) | 34.8(10,59) | 9.36x10-10mWm-2km-1 | 0.42 | | CO2 | 34.3(28,40) | 29.0(24,34) | 25.0(21,29) | | 1.0 | | Short-termO3increase | 49.3(32,76) | 37.3(24,58) | 33.0(21,51) | 34.4±9.9mWm-2(Tg(N)yr1)-1 | 1.37 | | Long-termO3decrease | -10.6(-20,-7.4) | -7.9(-15,-5.5) | -6.7(-13,-4.7) | -9.3±3.4mWm-2(Tg(N)yr1)-1 | 1.18 | | CH4decrease | -21.2(-40,-15) | -15.8(-30,-11) | -13.4(-25,-9.4) | -18.7±6.9mWm-2(Tg(N)yr1)-1 | 1.18 | | Stratosphericwater vapordecrease | -3.2(-6.0,-2.2) | -2.4(-4.4,-1.7) | -2.0(-3.8,-1.4) | -2.8±1.0mWm-2(Tg(N)yr1)-1 | 1.18 | | NetNOx | 17.5(0.6,29) | 13.6(0.9,22) | 12.9(1.9,20) | 5.5±8.1mWm-2(Tg(N)yr1)-1 | | | StratosphericH2Oincrease | 2.0(0.8,3.2) | 1.5(0.6,2.4) | 1.4(0.6,2.3) | 0.0052±0.0026mWm-2(Tg(H2O)yr1)-1 | \-\-\- | | Soot(aerosol-radiation) | 0.94(0.1,4.0) | 0.71(0.1,3.0) | 0.67(0.1,2.8) | 100.7±165.5mWm-2(Tg(BC)yr1)-1 | \-\-\- | | Sulfate(aerosol-radiation) | -7.4(-19,-2.6) | -5.6(-14,-1.9) | -5.3(-13,-1.8) | -19.9±16.0mWm-2(Tg(SO2)yr1)-1 | \-\-\- | $$ \\mathrm {C O} \_ {2} $$ $$ \\begin{array}{l} 9. 3 6 \\times 1 0 ^ {- 1 0} \\mathrm {m W m} ^ {-} \ ^ {2} \\mathrm {k m} ^ {- 1} \ \\end{array} $$ $$ 9. 3 \\pm 3. 4 \\mathrm {m W} \\mathrm {m} ^ {- 2} $$ $$ \\mathrm {H} \_ {2} \\mathrm {O} $$ $$ \\left(\\mathrm {T g} \\left(\\mathrm {H} \_ {2} \\mathrm {O}\\right) \\mathrm {y r} ^ {- 1}\\right) ^ {- 1} $$ $$ \\begin{array}{l} 0. 0 0 5 2 \\pm 0. 0 0 2 6 \ \\mathrm {m W m} ^ {- 2} \ \\end{array} $$ $$ \\mathrm {m} \_ {1} ^ {- 2} \\left(\\mathrm {T g} \\left(\\mathrm {S O} \_ {2}\\right) \\mathrm {y r} ^ {- 1}\\right) ^ {-} $$ * * * | ERF(mWm-2) | 2018a | 2011a | 2005a | Sensitivity to emissions | ERF/RF | | --- | --- | --- | --- | --- | --- | | Sulfate and soot(aerosol-cloud) | \-\-\-- | \-\-\-- | \-\-\-- | \-\-\-- | \-\-\- | | Net ERF(only non-CO2terms) | 66.6(21,111) | 51.4(16,85) | 41.9(14,69) | \-\-\-- | \-\-\- | | Net aviationERF | 100.9(55,145) | 80.4(45,114) | 66.9(38,95) | \-\-\-- | \-\-\- | | Net anthropogenicERF in2011 | \-\-\-- | 2290(1130,3330)b | \-\-\-- | \-\-\-- | \-\-\- | a The uncertainty distributions for all forcing terms are lognormal except for CO2 and contrail cirrus (normal) and Net NOx (discrete pdf). b Boucher et al., 2013. IPCC also separately estimated the contrail cirrus term for 2011 as 50 (20, 150) mW m-2 Table 47: Aviation non-CO2 emissions equivalence metrics for GWP, GTP and GWP\* taken from Lee et al. (2021) Metrics | ERF term | GWP20 | GWP50 | GWP100 | GTP20 | GTP50 | GTP100 | | --- | --- | --- | --- | --- | --- | --- | | CO2 | 1 | 1 | 1 | 1 | 1 | 1 | | Contrail cirrus(TgCO2 basis) | 2.32 | 1.09 | 0.63 | 0.67 | 0.11 | 0.09 | | Contrail cirrus(km basis) | 39 | 18 | 11 | 11 | 1.8 | 1.5 | | NetNOx | 619 | 205 | 114 | -222 | -69 | 13 | | Aerosol radiation | | | | | | | | Soot emissions | 4288 | 2018 | 1166 | 1245 | 195 | 161 | | SO2 emissions | -832 | -392 | -226 | -241 | -38 | -31 | | Water vapor emissions | 0.22 | 0.10 | 0.06 | 0.07 | 0.01 | 0.008 | $$ \\mathrm {S O} \_ {2} $$ * * * -1 CO2-eq emissions (Tg CO2 yr) for 2018 $$ \\mathrm {y r} ^ {- 1}) $$ | ERF term | GWP20 | GWP50 | GWP100 | GTP20 | GTP50 | GTP100 | GWP _100(E_ CO2e) | | --- | --- | --- | --- | --- | --- | --- | --- | | CO2 | 1034 | 1034 | 1034 | 1034 | 1034 | 1034 | 1034 | | Contrail cirrus(TgCO2 basis) | 2399 | 1129 | 652 | 695 | 109 | 90 | 1834 | | Contrail cirrus(km basis) | 2395 | 1127 | 651 | 694 | 109 | 90 | 1834 | | Net NOx | 887 | 293 | 163 | -318 | -99 | 19 | 339 | | Aerosol-radiation | | | | | | | | | Soot emissions | 40 | 19 | 11 | 12 | 2 | 2 | 20 | | SO2 emissions | -310 | -146 | -84 | -90 | -14 | -12 | -158 | | Water vapor emissions | 83 | 39 | 23 | 27 | 4 | 3 | 42 | | Total CO2-eq(using km basis) | 4128 | 2366 | 1797 | 1358 | 1035 | 1135 | 3111 | | Total CO2-eq/CO2 | 4.0 | 2.3 | 1.7 | 1.3 | 1.0 | 1.1 | 3.0 | $$ \\mathrm {C O} \_ {2} $$ $$ \\left(\\mathrm {E} ^ {\*} \\mathrm {c o 2 e}\\right) $$ Note: GWP = Global Warming Potential, GTP = Global Temperature Potential * * * 9. Bioenergy and Water Section summary 9.1. Bioenergy conversion factors should be used for the combustion of fuels produced from recently living sources (such as trees) at a site or in an asset under the direct control of the reporting organisation. This section of the report describes both the direct (Scope 1) emissions and the indirect (Scope 3) emissions associated with bioenergy sources. 9.2. The section also includes factors for emissions associated with water supply, to account for water delivered through the mains supply network, and water treatment, which are used for water returned to the sewage system through mains drains. These are classified as Scope 3 emissions. 9.3. For the 2024 update, factors for water supply and water treatment are calculated using a revised methodology based on the 2021 data from the UK water companies Carbon Accounting Workbooks (CAW), including the actual volume of wastewater treated and drinking water supplied by each company. Table 48: Related worksheets for bioenergy and water emission factors | Worksheet name | Full set | Condensed set | | --- | --- | --- | | Bioenergy | Y | Y | | WTT- bioenergy | Y | N | | Water supply | Y | Y | | Water treatment | Y | Y | 9.5. The Renewable Transport Fuel Obligation (RTFO) is likely to be highly variable year on year as suppliers can choose what types of biofuels and sources of biofuels, they want to use to fulfil that obligation. Therefore, more fuel sources and more advanced types of biofuels are continually brought into the market, so the underlying biofuels base is and will continue to change. The WTT factors reported in DfT’s RTFO 0105 dataset are specific to both the fuel type and the feedstock. In the 2023 publication of the statistics (third provisional), the dataset shows a The Renewable Transport Fuel Obligation (RTFO) is likely to be highly variable year on year as suppliers can choose what types of biofuels and sources of biofuels, they want to use to fulfil that obligation. Therefore, more fuel sources and more advanced types of biofuels are continually brought into the market, so the underlying biofuels base is and will continue to change. The WTT factors reported in DfT’s RTFO 0105 dataset are specific to both the fuel type and the feedstock. In the 2023 publication of the statistics (third provisional), the dataset shows a the 2023 publication of the statistics (third provisional), the dataset shows a marked increase in biodiesel HVO and a moderate increase in biodiesel ME consumption with their associated Scope 3 emissions being increased. Consumption of bioethanol has increased since last year, but its scope 3 Consumption of bioethanol has increased since last year, but its scope 3 Consumption of bioethanol has increased since last year, but its scope 3 Summary of changes since the previous update emissions have gone down due to changes in the feedstocks used and the production plants it is sourced from. 9.6. A marked increase in the proportion of bioethanol and biodiesel in petrol and diesel sold on petrol station forecourts has led to an increase in the bio-carbon emissions factors for forecourt petrol and diesel. General Methodology 9.7. The 2024 GHG Conversion factors provide tables of conversion factors for: water supply and treatment, biofuels, biomass and biogas. 9.8. The conversion factors for bioenergy incorporate emissions from the fuel life cycle and include net CO2, CH4, N2O emissions and indirect/WTT emissions factors. These are presented for biofuels, biomass and biogas and still use the AR4 GWP values, while for water they are aligned with AR5 GWP values. $$ \\mathrm {C O} \_ {2}, \\mathrm {C H} \_ {4}, \\mathrm {N} \_ {2} \\mathrm {O} $$ Water 9.9. The conversion factors for water supply and treatment in sections “Water supply” and “Water treatment” worksheets of the 2024 GHG Conversion factors were calculated based on 2022 data from UK water companies Carbon Accounting Workbooks (CAW). These data are used for reporting to the UK regulator (Ofwat) 33 and all UK water companies use this common approach to reporting these data. 9.10. The CAW data gives GHG intensity for each water company from water supply and wastewater treatment, accounting for emissions associated with offices and transport. The 2024 dataset includes the volume of wastewater treated and of drinking water supplied by each company. This is a more robust metric compared to previous years' which led to a revised methodology for 2023. This data is used to generate a weighted average of the volume of wastewater treated and drinking water supplied. It should also be noted that the data received from the water industry did not include complete reporting from all water companies, which introduces uncertainty in both water supply and water treatment estimates. Biofuels 9.12. Unlike the direct emissions of CO2, the CH4 and N2O emissions are not offset by absorption in the growth of the feedstock used to produce the biofuel. Specific emission factors are available for solid biomass and biogas but not for liquid and $$ \\mathrm {C O} \_ {2} $$ gaseous biofuels. In the absence of other information, these emission factors have been assumed to be equivalent to those produced by combusting the corresponding liquid and gaseous fossil fuels (i.e. diesel, petrol, LNG or CNG) from the “Fuels” section. 9.13. The net GHG emissions for biofuels vary significantly depending on the feedstock source and production pathway. Therefore, for accuracy, it is recommended that more detailed/specific figures are used where available. For example, detailed indirect/WTT conversion factors by source/supplier are provided and updated regularly in the Quarterly Reports on the RTFO website (DfT, 2024). 9.14. The indirect/WTT/fuel lifecycle conversion factors for biofuels were based on UK average factors from the Quarterly Reports35 on the Renewable Transport Fuel Obligation (RTFO) (DfT, 2024). These average factors and the direct CH4 and N2O factors are presented in Table 49. 9.15. In addition to the direct and indirect/WTT conversion factors provided in Table 49, conversion factors for the Out of Scope CO2 emissions have also been provided based on data sourced from the UK GHG Inventory (GHGI) for 2022 (managed by Ricardo Energy & Environment) and the JEC WTT v5 study (JEC WTW v5, 2020). Table 49: Fuel lifecycle GHG Conversion factors for biofuels $$ \\mathrm {C O} \_ {2} $$ | Biofuel | Emissions Factor,gCO2e/MJ | | | | | | | --- | --- | --- | --- | --- | --- | --- | | RTFO Lifecycle(1) | DirectCH4(2) | DirectN2O(2) | DirectCO2(2\*) | Total Lifecycle | DirectCO2 Emissions(Out of Scope(3)) | | | Avtur(renewable) | 10.32 | 0.04 | 0.68 | 0.00 | 11.05 | 71.53 | | Biodiesel HVO | 16.29 | 0.01 | 1.03 | 0.00 | 17.32 | 70.83 | | Biodiesel ME | 14.53 | 0.01 | 1.03 | 4.02 | 19.59 | 72.16 | | Biodiesel ME(from Tallow) | 19.84 | 0.01 | 1.03 | 4.02 | 24.90 | 72.16 | | Biodiesel ME(from used cooking oil) | 11.69 | 0.01 | 1.03 | 4.02 | 16.75 | 72.16 | | Bioethanol | 24.39 | 0.22 | 0.20 | 0.00 | 24.82 | 71.37 | | Biomethane(compressed) | 13.06 | 0.08 | 0.03 | 0.00 | 13.17 | 55.28 | | Biomethane(liquified) | 10.61 | 0.08 | 0.03 | 0.00 | 10.72 | 56.66 | * * * | Biopropane | 9.06 | 0.05 | 0.04 | 0.00 | 9.15 | 64.51 | | --- | --- | --- | --- | --- | --- | --- | | Development diesel | 23.99 | 0.01 | 1.03 | 0.00 | 25.03 | 73.54 | | Development petrol | 24.01 | 0.22 | 0.20 | 0.00 | 24.43 | 70.29 | | Methanol(bio) | 37.39 | 0.22 | 0.20 | 0.00 | 37.82 | 68.92 | | Off road biodiesel | 14.53 | 0.01 | 1.03 | 4.02 | 19.59 | 72.16 | Notes: (1) Based on UK averages from the RTFO Quarterly Report from DfT (DfT, 2024). (2) Based on corresponding emission factors for diesel, petrol, LNG or CNG. \*Biodiesel, as of April 2020, is now accounting for fossil component of biodiesel to align with the UK GHGI estimates; based on stoichiometric analysis of chemical compounds. (3) The Total GHG emissions outside of the GHG Protocol Scope 1, 2 and 3 is the actual amount of CO2 emitted by the biofuel when combusted. This will be counter-balanced by the equivalent to the CO2 absorbed in the growth of the biomass feedstock used to produce the biofuel. These factors are based on data from the JEC Well to Tank Study (v5). Other biomass and biogas 9.16. A number of different biomass types can be used in dedicated biomass heating systems, including wood logs, chips and pellets, as well as grasses/straw or biogas. Conversion factors produced for these bioenergy sources are presented in the “Bioenergy” worksheet of the 2024 GHG Conversion factors set. 9.17. The indirect/WTT/fuel lifecycle conversion factors for biomass, except for wood logs, are sourced from the Ofgem solid and gaseous biomass carbon calculator (Ofgem, 2015). This calculator has been developed to support operators determining the GHG emissions associated with the cultivation, processing and transportation of their biomass fuels. 9.18. Indirect/WTT/fuel lifecycle conversion factors for wood logs, which are not covered by the Ofgem tool, were obtained from the Biomass Environmental Assessment Tool (BEAT2) (Forest Research, 2016a), provided by Defra. And for the indirect conversion factor for biogas the RTFO standard data statistics has been used this year using the value for biowaste - close digestate, no off-gas combustion (DfT, 2023). 9.19. The direct CH4 and N2O conversion factors presented in the 2024 GHG Conversion factors are based on the conversion factors used in the UK GHG Inventory (GHGI) for 2022 (Ricardo, 2024). 9.21. In addition to the direct and indirect/WTT conversion factors provided, conversion factors for the out of scope CO2 emissions are also provided in the 2024 GHG $$ \\mathrm {C O} \_ {2} $$ * * * Conversion factors (see “Outside of Scopes” and the relevant notes on the page), based on data sourced from Forest Research, the Forestry Commission’s research agency (previously BEC) (Forest Research, 2016a). Table 50: Fuel sources and properties used in the calculation of biomass and biogas emission factors | Biomass | Moisture content | Net calorific value(GJ/tonne) | Source | | --- | --- | --- | --- | | Wood chips | 25% moisture | 13.6 | Forestry Research | | Wood logs | Air dried 20% moisture | 14.7 | UK GHGI | | Wood pellets | 10% moisture | 17.3 | DUKES | | Grass/Straw | 10% moisture | 13.4 | UK GHGI | | Biogas | Based on 65%CH4 | 20.0 | Swedish Gas Technology Centre 2012 | | Landfill gas | Based on 40%CH4 | 12.3 | Swedish Gas Technology Centre 2012 | * * * 10. Overseas Electricity Emission Factors Section summary 10.1. This section contains guidance for users on how to find Scope 2 conversion factors for electricity generation in overseas countries and how to calculate the indirect/WTT emissions associated with these activities. These should be used for sites owned or controlled by the reporting organisation in another country. The Scope 2 indirect factors are no longer included within the Conversion factors but are available for sale from the CO2 Emissions from Fuel Combustion online data service at the IEA website. Indirect/WTT factors are no longer being provided as part of the UK GHG conversion factors. Instead, guidance will be provided in the sections below on how to manually calculate the desired factors. 10.2. The related worksheet for this section is the “WTT – UK & overseas elec”, available only in the full set of the UK GHG Conversion factors. Summary of changes since the previous update 10.3. Indirect/WTT factors are no longer being provided as part of the UK GHG conversion factors. Instead, guidance will be provided in the sections below on how to manually calculate the desired factors. Direct Emissions and Emissions resulting from Transmission and Distribution Losses from Overseas Electricity Generation 10.4. UK companies reporting on their emissions may need to include emissions resulting from overseas activities. Whilst many of the fuel conversion factors are likely to be similar for fuels used in other countries, electricity conversion factors vary considerably due to fuel mix. 10.7. Since the 2018 update year, the emissions associated with electricity losses during transmission and distribution of electricity between the power station and an organisation's site(s) are also provided in the IEA dataset, these are also now no longer provided in the UK GHG Conversion factors dataset. 10.8. The conversion factors supplied by the IEA do not include indirect/WTT emissions. 10.9. For European countries, an alternative data set is available for free from the Association of Issuing Bodies (AIB). Within the 2021 edition of the European Residual Mix report37, Table 5 presents the production mix for each country and their direct CO2 conversion factor (the ‘CO2 (gCO2/kWh)’ column). These values differ from the IEA values due to differences in methodology. Indirect/WTT Emissions from Overseas Electricity Generation 10.10. As of the 2024 publication of the UK GHG Conversion Factors, indirect/WTT emission factors for overseas electricity generation is no longer provided. Instead, the method for calculating the factors manually will be provided. The methodology used in previous editions of the UK GHG conversion factors was to take the direct emission factor for the country in questions and multiply it by the ratio between the UK’s indirect/WTT factor and the UK’s direct factor. This approach allows an indirect factor to be estimated for a country without fully modelling the electricity generation system of the country. Examples of the calculations are provided below. 10.11. As the Indirect/WTT factor for UK Electricity is no longer updated annually, the ratio between the published indirect/WTT factor and the direct factor in the latest year will not be suitable for users looking to calculate an estimate for the indirect/WTT factor for another country. Therefore, users are advised to use the ratio for the year 2020 from the 2022 publication of the UK Conversion Factors going forward, as described below. 10.12. The ratio between the UK’s Indirect/WTT factor and direct factor is presented in Table 11 in the 2022 publication of the UK GHG Conversion Factors, for 2020 this weighted average is 24.19%. If, for example, the direct factor for French electricity generation was 61 gCO2e/kWh then the Indirect/WTT factor can be calculated as follows: $$ W T T = D i r e c t \\times U K \\frac {W T T}{D i r e c t} R a t i o = 6 1 \\times \\frac {2 4. 1 9}{1 0 0} = 1 4. 7 6 g C O \_ {2} e / k W H $$ * * * 10.13. To calculate the transmission and distribution (T&D) WTT factor, the percentage of losses for the country must be applied to the direct factor. For example, if the French electricity losses were 8%, the WTT T&D Losses factor could be calculated as follows: $$ W T T \_ {T & D} = \\left(\\frac {D i r e c t}{1 - L o s s e s} - D i r e c t\\right) \\times U K \\frac {W T T}{D i r e c t} R a t i o = \\left(\\frac {6 1}{1 - \\frac {8}{1 0 0}} - 6 1\\right) \\times \\frac {2 4. 1 9}{1 0 0} = 1. 2 8 g C O \_ {2} e / k W h $$ * * * 11. Hotel Stay Section summary 11.1. This section describes the calculation of conversion factors for Hotel Stays, which should be used to report the Scope 3 emissions associated with overnight hotel stays for business travel. 11.2. These factors appear in the “Hotel Stay” worksheet, available only in the full set of the UK GHG Conversion factors set. 11.3. Hotel Stay conversion factors remain constant since the publish of 2022 GHG Conversion factors. Summary of changes since the previous update 11.4. Hotel Stay conversion factors are not all aligned with the AR5 GWPs in the 2024 update, because the data from Hotel Sustainability Benchmarking Index 2021 were in CO2e with no breakdown of CH4 and N2O emissions. The conversion factors of different countries could be in either AR4 or AR5 basis, depending on the GWPs used by the reporting hotels if the data were reported in CO2e instead of the raw values of CO2, CH4 and N2O emissions. Direct emissions from a hotel stay 11.5. All the hotel stay conversion factors presented in the 2024 GHG Conversion factors are in a CO2e basis. These are taken directly from the Cornell Hotel Sustainability Benchmarking Index (CHSB) Tool, produced by the International Tourism Partnership (ITP) and Greenview (ITP/Greenview, 2021). The factors use annual data comprising several international hotel organisations. 11.6. For the 2022 GHG Conversion factors the median benchmark for each country, for all hotel classes included within the tool, was used. a) Harmonising. The data received was converted into the same units and then converting to kg CO2e. b) Validity tests were carried out to remove outliers or errors from the data sets b) Validity tests were carried out to remove outliers or errors from the data sets received. d) Property segmentation. Hotels were grouped by property segment, applying a revenue-based approach and property-type segmentation used by STR Global (using 2020 global chain scales), the asset class segmentation of full-service and limited-service hotels, and a global data set of star levels for hotels as identified by Expedia. * * * e) Minimum output thresholds. A minimum threshold of eight hotels per geographical region was required before it was populated within the tool. If there were less than eight hotels, these were excluded from the final outputs. 11.8. It should be noted that there are certain limitations with the CHSB tool used to derive the 2022 GHG Conversion factors. The main limitations are detailed below: a) The factors are skewed toward large, more upmarket hotels and to branded chains. This is because it was mainly large owners or operators of hotels who submitted the aggregated data sets. Hotels in the lower tier segments are not as strongly represented in these data. b) The data sets used to derive the factors have not been verified and therefore it cannot be concluded to be 100% accurate. c) 65% of the benchmarks are within United States geographies. The datasets used are updated each year, therefore it is expected that a wider range of countries will be covered in the future and the tool aims to seek data sets from outside the U.S in future years. d) The factors do not distinguish a property’s amenities except for outsourced laundry services, which are taken into consideration. The factors are an aggregation of all types of hotels within the revenue-based segmentation and geographic location. Which means it is very difficult to compare two hotels since some may contain distinct attributes, (such as restaurants, fitness centres, swimming pool and spa) while others do not. e) At present, there is no breakdown of CH4 and N2O emissions, plus there are also e) At present, there is no breakdown of CH4 and N2O emissions, plus there are also no indirect/ WTT factors. 11.9. For more information about how the factors have been derived, please see (ITP/Greenview, 2021), where more granular data is also available by city and segment. * * * 12. Material Consumption/Use and Waste Disposal Section summary 12.1. Material use conversion factors should be used only to report on procured products and materials based on their origin (that is, comprised of primary material or recycled materials). The factors are not suitable for quantifying the benefits of collecting products or materials for recycling. 12.2. For primary materials, these factors cover the extraction, primary processing, manufacture and transportation of materials to the point of sale, not the materials in use. For secondary materials, the factors cover sorting, processing, manufacture and transportation to the point of sale, not the materials in use. These factors are useful for reporting efficiencies gained through reduced material procurement or the benefit of procuring items that are the product of a previous recycling process. 12.3. Waste-disposal figures should be used for Greenhouse Gas Protocol reporting of Scope 3 emissions associated with end-of-life disposal of different materials. With the exception of landfill, these figures only cover emissions from the collection of materials and delivery to the point of treatment or disposal. They do not cover the environmental impact of different waste management options. They are suitable only for Scope 3 reporting of emissions impacts under the GHG Protocol Corporate Value Chain (Scope 3) Accounting and Reporting Standard (‘the Scope 38 3 Standard’). 12.4. These factors appear in the “Material use” and “Waste disposal” worksheets, available in both the full and condensed sets of the UK GHG Conversion factors Summary of changes since the previous update 12.5. Users wishing to quantify the impact of different waste management options may 39 wish to use WRAP Carbon Waste and Resources Metric (CarbonWARM). Note that CarbonWARM outputs cannot be used for reporting Scope 3 Greenhouse Gas emissions. The following changes have been made to the Material Use factors since the 2023 update. 12.6. Paper and board factors have been revised to remove reliance on out-of-date references and bring the values into line with the latest values in the ecoinvent lifecycle database. * * * 12.7. Plastics factors have been revised to remove reliance on out-of-date references and bring the values into line with the latest values in the ecoinvent lifecycle database. 12.8. Wood factors have been revised to remove reliance on out-of-date references and bring the values into line with the latest values in the ecoinvent lifecycle database. Closed loop factors for wood (which should cover only the use of wood as timber without remanufacture into board products) have been removed as the historical figure was not representative of closed loop recycling processes and a suitable replacement has not been sourced. All recycling processes that involve adding binders or adhesives to the wood at end of life (e.g. manufacture of fibreboard) are covered under the open loop recycling factor. 12.9. The manufacturing element of the concrete factor has been updated to reflect the latest value in the ecoinvent lifecycle database. 12.10. The steel factor has been updated based on the latest data releases from World Steel. The following changes have been made to the Waste Disposal factors since the 2023 update. 12.11. An error affecting the transport emissions for the recycling and EfW (Energy from Waste) factors has been corrected. This has had the effect of reducing the transport emissions associated with these disposal approaches. 12.12. Minor updates to the factors to account for this 2024 update of transport and UK electricity generation factors. 12.13. An error in the composting factor for books has been corrected and the results brought into line with the other factors. Emissions from Material Use and Waste Disposal 12.14. The GHG conversion factors for material consumption/use and waste disposal have been aligned with the GHG Protocol Corporate Value Chain (Scope 3) 40 Accounting and Reporting Standard (‘the Scope 3 Standard’). This sets down rules on accounting for emissions associated with material consumption and waste management. * * * 12.16. Whilst the factors are appropriate for accounting, they are therefore not appropriate for informing decision making on alternative waste management options (i.e. they do not show the impact of waste management options). 12.17. All figures expressed are kilograms of carbon dioxide equivalent (CO2e) per tonne of material. This includes the Kyoto protocol basket of greenhouse gases. Please note that biogenic41 CO2 has been excluded from these figures. 12.18. The information for material consumption presented in the conversion factors spreadsheet has been separated from the emissions associated with waste disposal to allow separate reporting of these emission sources, in compliance with the Scope 3 Standard. 12.19. Businesses must quantify emissions associated with both material use and waste management in their Scope 3 accounting, to fully capture changes due to activities such as waste reduction. 12.20. The following subsections summarise the methodology, key data sources and assumptions used to define the emission factors. Material Consumption/Use 12.21. Figure 5 shows the boundary of greenhouse gas emissions summarised in the material consumption table. Figure 5: Boundary of material consumption data sets Notes: Arrows represent transportation stages; greyed items are excluded. $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {C O} \_ {2} $$ enterprises may use these factors to estimate the impact of goods they procure. Organisations involved in manufacturing goods using these materials should note that if they separately report emissions associated with their energy use in forming products with these materials, there is potential for double counting. As many of the data sources used in preparing the tables are confidential, we cannot publish a more detailed breakdown. However, the standard assumptions made are described below. 12.23. Conversion factors are provided for both recycled and primary materials. To identify the appropriate carbon factor, an organisation should seek to identify the level of recycled content in materials and goods purchased. Under this accounting methodology, the organisation using recycled materials in place of primary materials receives the benefit of recycling in terms of reduced Scope 3 emissions. 12.24. These factors are estimates to be used in the absence of data specific to your goods and services. If you have more accurate information for your products, then please refer to the more accurate data for reporting your emissions. 12.25. Information on raw material extraction and manufacturing impacts is commonly sourced from the same reports, typically life cycle inventories published by trade associations. The sources utilised in this study are listed in Appendix 1 to this report. The stages covered include mining activities for non-renewable resources, agriculture and forestry for renewable materials, production of materials used to make the primary material (e.g. soda ash used in glass production) and primary production activities such as casting metals and producing board. Intermediate transport stages are also included. Full details are available in the referenced reports. 12.26. Conversion factors provided include emissions associated with product forming. 12.27. Table 51 identifies the transportation distances and vehicle types which have been assumed as part of the conversion factors provided. The impact of transporting the raw material (e.g. forestry products, granules, glass raw materials) is already included in the manufacturing profile for all products. The transportation tables and Greenhouse Gas Protocol guidelines on vehicle emissions have been used for most vehicle emission factors. Table 51: Distances and transportation types used in material use EF calculations | Destination/Intermediate Destination | One Way Distance | Mode of transport | Source | | --- | --- | --- | --- | | Transport of raw materials to the factory | 122km | Average, all HGVs | (DfT,2010)Based on average haulage distance for all commodities, not specific to the materials in the first column. | | Distribution to Retail Distribution Centre&to retailer | 96km | Average, all HGVs | (McKinnon,2007),(IGD,2018) | * * * 12.28. Transport of goods by consumers is excluded from the factors presented, as is the use of the product. Waste Disposal 12.29. As defined under the Scope 3 standard, emissions associated with recycling and energy recovery are attributed to the organisation which uses the recycled material or which uses the waste to generate energy. The emissions attributed to the company which generates the waste cover only the collection of waste from their site and deposit at the first point of processing (e.g. material 42 recovery facility (MRF)). This does not mean that emissions from waste management or recycling are zero or are not necessary; it simply means that, in accounting terms, these emissions are for another organisation to report. 12.30. Landfill emissions remain within the accounting Scope of the organisation producing waste materials. Factors for landfill are provided within the waste disposal sheet in the 2024 GHG Conversion Factors. These factors are drawn directly from MELMod, which contains information on landfill waste composition 43 and material properties, with the addition of collection and transport emissions. 12.31. This means that the waste disposal factors exclude the majority of emissions from waste management and cannot be used to compare the impacts of different waste management options or processes. They may be used only for the purposes of reporting Scope 3 emissions under the Greenhouse Gas protocol. 12.32. Figures for Refuse Collection Vehicles have been taken from the Environment Agency’s Waste and Resource Assessment Tool for the Environment (WRATE) (Environment Agency, 2010). 12.33. Transport distances for waste were estimated using a range of sources, principally data supplied by the Environment Agency for use in the WRATE (2005) tool (Environment Agency, 2010). The distances adopted are shown in Table 52. * * * Table 52: Distances used in the calculation of waste emission factors | Destination/Intermediate Destination | One Way Distance | Mode of transport | Source | | --- | --- | --- | --- | | Collection and transport to transfer station or MRF | 25km by Road | 26 Tonne GVW Refuse Collection Vehicle, maximum waste capacity 12 tonnes | Environment Agency(2010) | | Distance from transfer station to landfill or composting site | 10km by Road | Bulk transport | Environment Agency(2010) | | Collection and transport for inert waste recycling | 12.85km by Road | 4 axle rigid tippers and an average load of 20 tonnes, round trip of 45.7km x2,22 tonne average load) | Aggregain(2010) | | Distance to inert waste landfill | 16.1km by Road | 4 axle rigid tippers and an average load of 20 tonnes, round trip of 45.7km x2,22 tonne average load) | Aggregain(2010) | 12.34. Road vehicles are volume-limited rather than weight limited. An average loading factor (including return journeys) is used for all HGVs, based on the HGV factors provided in the 2024 Conversion factors. Waste vehicles leave a depot empty and return fully laden. A 50% loading assumption reflects the change in load over a collection round which could be expected. * * * 13. Fuel Properties Section summary 13.1. The fuel properties can be used to determine the typical calorific values / densities of most common fuels. 13.2. These factors appear in the “Fuel properties” worksheet, available in both the full and condensed sets of the UK GHG Conversion factors set. Summary of changes since the previous update 13.3. Fuel property data for the vast majority of fuels uses data from the UK GHG Inventory (GHGI) (Ricardo, 2024). The GHGI data is largely based on DUKES, but in some cases deviates, either to use data consistent with the carbon content data source (such as for power stations coal, which uses EU ETS data), or in cases where there are apparent inconsistencies in the time series, as the GHGI must present a consistent time series from 1990. This change will improve consistency between the GHGI and the Conversion Factors. General Methodology 13.4. The following standard properties for key fuels are provided in the UK GHG Conversion factors: a) Gross Calorific Value (GCV) in units of GJ/tonne, kWh/kg and kWh/litre; b) Net Calorific Value (NCV) in units of GJ/tonne, kWh/kg and kWh/litre; c) Density in units of litres/tonne and kg/m3. 13.7. Fuel properties, both density and CV, for wood chips (25% moisture content) 44 come from the Forest Research (previously Biomass Energy Centre (BEC). The density of wood logs (20% moister content), wood chips (25% moister content) * * * 2024 Government greenhouse gas conversion factors for company reporting: Methodology paper and grasses/straw (25% water content) are also sourced from the Forest Research45. * * * 14. SECR kWh Conversion factors Section summary 14.1. The new Streamlined Energy and Carbon Reporting (SECR) came into effect on the 1 April 2019. One of the requirements of the guidance is to report GHG emissions from activities for which the company is responsible. SECR obligations differ between quoted and unquoted organisations covering Scope 1, Scope 2 and some Scope 3 emissions. Most will need to calculate the GHG emissions for the combustion of fuel (including transport fuel) and the operation of any facility; together with the annual emissions from the purchase of electricity, heat, steam or cooling by the company for its own use. See the Environmental Reporting Guidelines, (BEIS, 2019), for more details. 14.2. The SECR also requires the total energy use that is used to calculate these GHG emissions to be provided in kilowatt hours (kWh). 14.3. When organisations are calculating the GHG emissions associated with fuels (Scope 1), bioenergy (Scope 1), electricity (Scope 2) and heat and steam (Scope 2), they will either already have the kWh values or will be able to convert units such as GJ, litres or tonnes using the fuel properties or conversion data provided at the end of the conversion factors spreadsheet. 14.4. For transport, companies may have two types of data which they can use to calculate vehicles emissions (cars, motorcycles, vans and HGVs owned or controlled by the company): a) Fuel consumption data in litres or kWh. In the instance of litres, this can easily be converted to kWh using the fuel properties provided at the end of the conversion factors spreadsheet. This is the preferred and more accurate method to use. b) Journey distance in km or miles. If a company does not have fuel consumption b) Journey distance in km or miles. If a company does not have fuel consumption data (option a), they may have a record of the total distance travelled, for example from expense claims. In this instance, the km or miles data will need to be converted into kWh. This will require an additional factor, which is what we have provided in the SECR factors worksheet. 14.5. SECR kWh conversion factors have been calculated for passenger and delivery vehicles including; cars, motorcycles, vans and HGVs. | Worksheet name | Full set | Condensed set | | --- | --- | --- | | SECR kWh pass & delivery vehs | Y | Y | | SECR kWh UK electricity for EV | Y | Y | 14.6. The factors are split out between two worksheets: * * * a) “SECR kWh pass & delivery vehs” worksheet contains cars, motorcycles, vans and HGVs, including electric vehicles (i.e. Plug-in Hybrid Electric Vehicles / Range-Extended Electric Vehicles and Battery Electric Vehicles) where the kWh factors presented only include the conventional fuel use (i.e. petrol or diesel) b) “SECR kWh UK electricity for EV” worksheet contains only the kWh factors for b) “SECR kWh UK electricity for EV” worksheet contains only the kWh factors for the electricity consumed by the electric vehicles. Summary of changes since the previous update 14.7. There were no major methodological changes in the 2024 update. General Methodology 14.8. The factors are calculated using a two-step approach: Step 1 - Convert km or miles data into kg CO2 using the appropriate transport GHG conversion factor. These are the factors found within the passenger and delivery vehicles worksheets. $$ \\mathrm {C O} \_ {2} $$ Step 2 ivide the kg CO – D 2 figure, from step 1, by the fuel net kWh conversion factor (e.g. diesel or petrol). These are the figures found within the fuel worksheet. 14.9. The CO2 GHG conversion factor for some vehicle types are calculated using a mixture of fuels, such as hybrid vehicles, or for those where the fuel is unknown. In these instances, the kWh conversion factor used in step 2 is calculated using the appropriate percentage fuel split used in calculating the GHG conversion factors. $$ \\mathrm {C O} \_ {2} $$ 14.10. The calculation of the SECR kWh conversion factors are based on using the CO2 (and not the CO2e) factors. This is because the CO2e factor is comprised of the CO2, CH4 and N2O factors and the CH4 and N2O emissions are not directly linked to the energy consumption but they are related to the specific (exhaust) emission after-treatment systems. For different vehicle types, the ratio is different for the same fuel type. Hence the calculation uses the ratio of CO2 with the average fuel conversion factor. $$ \\mathrm {C O} \_ {2} \\mathrm {e}) $$ $$ \\mathrm {C O} \_ {2} \\mathrm {e} $$ $$ \\mathrm {C O} \_ {2} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {N} \_ {2} \\mathrm {O} $$ $$ \\mathrm {C O} \_ {2} $$ * * * 15. Homeworking Section summary 15.1. This section describes the calculation of conversion factors for Homeworking, which should be used to report the Scope 3 emissions associated with employees working remotely from home. 15.2. These factors appear in the “Homeworking” worksheet, available only in the full set of the UK GHG Conversion factors set. 15.3. Homeworking conversion factors remain constant since the publish of 2022 GHG Conversion factors but have been updated from AR4 to AR5 GWP values. General Methodology 15.4. The methodology is based on the “Homeworking emission Whitepaper” (EcoAct, 2020). These factors estimate the incremental energy use from office equipment and home heating by homeworking employees which would not have occurred in an office-working scenario. 15.5. All the Homeworking conversion factors presented in the 2024 GHG Conversion factors are in a CO2e basis. 15.6. The Homeworking conversion factors are provided on a 'Full-time Equivalent (FTE) working hour' basis, representing the GHG emissions from one hour of work by one full-time employee. 15.7. There are several assumptions used in the estimation of the Homeworking conversion factors, as listed below. These assumptions would be updated in the future if there are data sources that are more updated or accurate. c) assumed that the energy used for lighting is 10W per homeworking employee (an assumption by EcoAct); 15.9. Home heating is an annual average of energy used for heating estimated using data from "Typical Domestic Consumption values 2020" (Ofgem, 2020) and * * * "Estimates of heat use in the United Kingdom in 2013" (DECC, 2014). GHG conversion factors for natural gas consumption come from the UK GHG Conversion factors model outputs for Fuels. There are 4 assumptions: a) assumed that all home heating in the UK is powered by natural gas (survey showed that 86% of UK homes are heated by natural gas (DLUHC, 2021); b) assumed that in the UK, heating is used 6 months per year (October to March); c) assumed that heating is used 10 hours per day during heating season; and d) assumed that one-third of the employees have at least one household member who would normally remain at home during the day (result from an internal staff survey done by NatWest Group in 2020), therefore only two-third (66.7%) of the employees moving to homeworking would result in incremental heating energy. * * * References ACEA. (2020). WLTP Facts. Retrieved from [https://wltpfacts.eu/](https://wltpfacts.eu/) AEA/Ricardo. (2011). Reduction and Testing of Greenhouse Gas (GHG) Emissions from Heavy Duty Vehicles – Lot 1: Strategy. Ricardo AEA. 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Retrieved from Vehicle Certification Agency: [https://www.vehicle-certification-agency.gov.uk/fuel-consumption-co2/averageemissions-monitoring/co2-emissions-from-new-passenger-cars/#topic-title](https://www.vehicle-certification-agency.gov.uk/fuel-consumption-co2/averageemissions-monitoring/co2-emissions-from-new-passenger-cars/#topic-title) VDA. (2014). Facts and Arguments about Fuel Consumption. Retrieved April 10, 2019, from [www.vda.de/dam/vda/publications/2014/facts-and-arguments-about-fuelconsumption.pdf](http://www.vda.de/dam/vda/publications/2014/facts-and-arguments-about-fuelconsumption.pdf) World Resources Institute. (2013). Technical Guidance for Calculating Scope 3 Emissions. Retrieved April 8, 2024, from [https://ghgprotocol.org/sites/default/files/standards/Scope3\_Calculation\_Guidance\_0.pdf](https://ghgprotocol.org/sites/default/files/standards/Scope3_Calculation_Guidance_0.pdf) WRAP. (2009). Wood Waste Market in the UK. Retrieved April 10, 2019, from [http://www.wrap.org.uk/sites/files/wrap/Wood%20waste%20market%20in%20the%20UK](http://www.wrap.org.uk/sites/files/wrap/Wood%20waste%20market%20in%20the%20UK). pdf WRAP. (2010). Environmental benefits of recycling - 2010 update. Retrieved April 10, 2019, from [http://www.wrap.org.uk/sites/files/wrap/Executive\_summary\_Environmental\_benefits\_of](http://www.wrap.org.uk/sites/files/wrap/Executive_summary_Environmental_benefits_of)\_ recycling\_-\_2010\_update.d1af1398.8671.pdf * * * Appendix 1. Additional Methodological Information on the Material Consumption/Use and Waste Disposal Factors This section explains the methodology for the choice of data used in the calculation of carbon emissions used in the “Material use” and “Waste disposal” worksheets. Section 1.1 details the indicators used to assess whether data met the data quality standards required for this project. Section 1.2 states the sources used to collect data. Finally, Section 1.3 explains and justifies the use of data which did not meet the data quality requirements. 1.1 Data Quality Requirements Table 1.1: Data Quality Indications for the waste management GHG factors Data used in this methodology should, so far as is possible, meet the data quality indicators described in Table 1.1 below. | Data Quality Indicator | Requirement | Comments | | --- | --- | --- | | Time-related coverage | Data less than 5 years' old | Ideally, data should be less than five years old. However, the secondary data in material eco-profiles is only periodically updated. In cases where no reliable data is available from within the five-year period, the most recent data available have been used.In cases where use of data over five years old creates specific issues, these are discussed below under “Use of data below the set quality standard”. All data over five years old has been marked in the references with an asterisk within the 2.0 Data Sources section. | | Geographical coverage | Data should be representative of the products placed on the market in the UK | Many datasets reflect European average production. | | Technology coverage | Average technology | A range of information is available, covering best in class, average and pending technology.Average is considered the most appropriate but may not reflect individual supply chain organisations. | | Precision/variance | No requirement | Many datasets used provide average data with no information on the range.It is therefore not possible to identify the variance. | | Completeness | All datasets must be reviewed to ensure they cover inputs and outputs pertaining to the life cycle stage | | | Representativeness | The data should represent UK conditions | This is determined by reference to the above data quality indicators. | | Consistency | The methodology has been applied consistently. | | | Reproducibility | An independent practitioner should be able to follow the method and arrive at the same results. | | | Sources of data | Data will be derived from credible sources and databases | Where possible data in public domain will be used. All data sources referenced. | | Uncertainty of the information | | Many data sources come from single sources. Uncertainty will arise from assumptions made and the setting of the system boundaries. | 1.3 Use of data below the set quality standard Every effort has been made to obtain relevant and complete data for this project. For the Every effort has been made to obtain relevant and complete data for this project. For the majority of materials and products data which fits the quality standards defined in Appendix 1.1 above are met. However, it has not always been possible to find data which meets these standards in a field which is still striving to meet the increasing data demands set by science and government. This section details data which do not meet the expected quality standard set out in the methodology of this project but were never-the-less included because they represent the best current figures available. The justification for inclusion of each dataset is explained. The most common data quality issues encountered concerned data age and availability. * * * 1.4 Wood and Paper data Data on different types of wood has been used in combination with information on the composition of wood waste in the UK (WRAP, 2009) to provide a figure which represents a best estimate of the impact of a typical tonne of wood waste. Many trade associations publish data on the impact of manufacturing 100% primary and 100% recycled materials. However, the bodies representing paper only produce industry average profile data, based on a particular recycling rate. Furthermore, paper recycling in particular is dependent on Asian export markets, for which information on environmental impacts of recycling or primary production is rare. This means that the relative impact of producing paper from virgin and recycled materials is difficult to identify. The figure for material consumption for paper represents average production, rather than 100% primary material, so already accounts for the impact of recycling. Caution should therefore be taken in using these numbers. 1.5 Excluded Materials and Products For some materials and products, such as automotive batteries and fluorescent tubes, no suitable figures have been identified to date. Table 1.2 Data Sources | Material | Reference | | --- | --- | | Aluminium cans and foil | European Aluminium Association(2018)Environmental Profile Report for the European Aluminium IndustryCE Delft(2007)Environmental Indices for the Dutch Packaging TaxDESNZ(2024)GHG Conversion factorsEnvironment Agency(2010)Waste and Resources Assessment Tool for the Environment(WRATE) | | Steel Cans | World Steel Association(2021)Life cycle inventory(LCI)study2020data releaseWorld Steel Association(2022)WorldsteelLCA eco-profileTinplateDESNZ(2024)GHG Conversion factorsSwiss Packaging Institute(1997)BUWALEnvironment Agency(2010)Waste and Resources Assessment Tool for the Environment(WRATE) | | Mixed Cans | Estimate based on aluminium and steel data,combined with data returns from Courtauld Commitment retailers(confidential,unpublished) | * * * | Glass | Ecoinvent 3(2024)Packaging glass production,white,Swiss Centre for Life Cycle Inventories | | --- | --- | | Ecoinvent 3(2024)Packaging glass production,green,Swiss Centre for Life Cycle Inventories | | | Ecoinvent 3(2024)Packaging glass production,brown,Swiss Centre for Life Cycle Inventories | | | Ecoinvent 3(2024)Packaging glass production,white,without cullet,Swiss Centre for Life Cycle Inventories | | | Ecoinvent 3(2024)Packaging glass production,green,without cullet,Swiss Centre for Life Cycle Inventories | | | Ecoinvent 3(2024)Packaging glass production,brown,without cullet,Swiss Centre for Life Cycle Inventories | | | Ecoinvent 3(2024)Market for glass cullet,sorted,Swiss Centre for Life Cycle Inventories | | | Ecoinvent 3(2024)Market for packaging glass,white,Swiss Centre for Life Cycle Inventories | | | Ecoinvent 3(2024)Market for packaging glass,green,Swiss Centre for Life Cycle Inventories | | | Glass raw material emissions for virgin glass are based on“without cullet”data,while emissions for recycled material are based on solving for emissions based on Packaging Glass production and production without cullet,accounting for the proportion of virgin and secondary material in the Packaging glass production inventories. Glass forming emissions are derived by comparison of Glass Packaging production emissions with Market emissions. | | | Pöry Forest Industry Consulting Ltd and Oxford Economics Ltd(2009)Wood Waste Market in UK | | | DESNZ(2024)GHG Conversion factors | | | Environment Agency(2010)Waste and Resources Assessment Tool for the Environment(WRATE) | | | Ecoinvent 3(2024)Sawnwood,beam,softwood,dried(u=20%),planed{CH} | market for sawnwood,beam,softwood,dried(u=20%),planed | | Ecoinvent 3(2024)Particleboard,uncoated{RER} | particle board production,uncoated, average glue mix | | Ecoinvent 3(2024)Plywood,for indoor use{RER} | production | | Ecoinvent 3(2024)Oriented strand board{RER} | production | | Ecoinvent 3(2024)Medium density fibreboard{RER} | medium density fibreboard production,uncoated | * * * | Aggregates | WRAP(2008)Lifecycle Assessment of Aggregates | | --- | --- | | Paper and board | CPI(2019)The economic value of the UK paper-based industries2019,CPIDESNZ(2024)Company GHG Reporting Guidelines,DESNZEcoinvent3(2024)Corrugated board box{RER} | | Books | Estimate based on paper | | Scrap Metal | British Metals Recycling Association(website46)Ecoinvent(2020)copper production,cathode,solvent extraction andelectrowinning processGiurco,D.,Stewart,M.,Suljada,T.,andPetrie,J.,(2006)Copper RecyclingAlternatives:An Environmental Analysis | * * * | Electrical goods | Ecoinvent(2020)market for computer,desktop,without screenEcoinvent(2020)market for computer,laptopEcoinvent(2020)market for dishwasherEcoinvent(2020)market for dryerEcoinvent(2020)market for electric kettleEcoinvent(2020)market for hair dryerEcoinvent(2020)market for microwave oven productionEcoinvent(2020)market for printer,laser,colourEcoinvent(2020)market for refrigeratorEcoinvent(2020)battery cell production,Li-ionEcoinvent(2020)battery production,NiMH,rechargeable,prismaticHamadeR.,AlAyache,R.,BouGhanem,M.andAmmouri,A.(2020)“Life Cycle Analysis of AA Alkaline Batteries”,Procedia Manufacturing,4:415-22 | | --- | --- | | Food and Drink | Tassou,S,Hadawey,A,Ge,YandMarriot,D(2008)FO405Greenhouse Gas Impacts of Food RetailingDEFRA and ONS(2009)Family food and expenditure surveyDECC(2013)Energy consumption in the UK | | Compost(food and garden) | Boldrin,A.,Hartling,K.,Laugen,M.andChristensen,T(2010)“Environmental inventory modelling of the use of compost and peat in growth media preparation” | * * * | Plastics | AMA Research (2009) Plastics Recycling Market UK 2009-2013, UK; Cheltenham | | --- | --- | | DESNZ (2024) Company GHG Reporting Guidelines, DESNZ | | | Ecoinvent 3 (2024) Extrusion, plastic film {RER} | extrusion, plastic film | | Ecoinvent 3 (2024) Packaging film, low density polyethylene {RER} | production | | Ecoinvent 3 (2024) Polyethylene terephthalate, granulate, amorphous, recycled {Europe without Switzerland} | polyethylene terephthalate production, granulate, amorphous, recycled | | Ecoinvent 3 (2024) Polyethylene terephthalate, granulate, bottle grade {RER} | production | | Ecoinvent 3 (2024) Polyethylene, high density, granulate {RER} | production | | Ecoinvent 3 (2024) Polyethylene, high density, granulate, recycled {Europe without Switzerland} | polyethylene production, high density, granulate, recycled | | Ecoinvent 3 (2024) Polystyrene, expandable {RER} | production | | Ecoinvent 3 (2024) Polystyrene, high impact {RER} | production | | Ecoinvent 3 (2024) Polyvinylchloride, bulk polymerised {RER} | polyvinylchloride production, bulk polymerisation | | Ecoinvent 3 (2024) Polyvinylchloride, emulsion polymerised {RER} | polyvinylchloride production, emulsion polymerisation | | Ecoinvent 3 (2024) Polyvinylchloride, suspension polymerised {RER} | polyvinylchloride production, suspension polymerisation | | Ecoinvent 3 (2024) Stretch blow moulding {RER} | production | | Ecoinvent 3 (2024) Thermoforming, with calendering {RER} | thermoforming, with calendering | | Environment Agency (2010) Waste and Resources Assessment Tool for the Environment (WRATE) | | | WRAP (2006) UK plastics waste: A review of supplies for recycling, global market demand, future trends and associated risks, WRAP | | | WRAP (2008) LCA of Mixed Waste Plastic Recovery Options, WRAP | | | Clothing | BIO IS (2009) Environmental Improvement Potentials of Textiles (IMPRO-Textiles), EU Joint Research Commission | * * * | Mineral Oil | IFEU(2005)Ecological and energetic assessment of re-refining used oils to base oils:Substitution of primarily produced base oils including semi-synthetic and synthetic compounds;GEIR | | --- | --- | | Plasterboard | WRAP(2008)Life Cycle Assessment of Plasterboard, prepared by ERM;WRAP;Banbury | | Concrete | Ecoinvent 3(2024)Concrete,normal{GLO} | | Bricks | Environment Agency(2011)Carbon CalculatorUSEPA(2003)Background Document for Life-Cycle Greenhouse GasConversion factors for Clay Brick Reuse and Concrete RecyclingChristopher Koroneos,Aris Dompros,“Environmental assessment of brick production in Greece”,Building and Environment,Volume42,Issue5,May2007,Pages2114-2123 | | Asphalt | Aggregain(2010)CO2calculatorMineral Products Association(2011)Sustainable Development Report | | Asbestos | Swiss Centre for Life Cycle Inventories(2014)Ecoinventv3.0 | | Insulation | Hammond,G.P.and Jones(2008)“Embodied Energy and Carbon in Construction Materials”Proceeding of the Institution of Civil EngineersWRAP(2008)Recycling of Mineral Wool Composite Panels into New Raw Materials | $$ C O \_ {2} $$ * * * 1.6 Greenhouse Gas Conversion factors Table 1.3 Greenhouse gas conversion factors | Industrial Designation or Common Name | Chemical Formula | Radiative Efficiency(Wm-2ppb-1) | Lifetime(years) | Global Warming Potential with 100 year time horizon(previous estimates for1stIPCC assessment report) | Possible source of emissions | | --- | --- | --- | --- | --- | --- | | Carbon dioxide | CO2 | 1.4x10-5 | Variable | 1 | Combustion of fossil fuels | | Methane | CH4 | 3.7x10-4 | 12 | 28(23) | Decomposition of biodegradable material, enteric emissions. | | Nitrous Oxide | N2O | 3.03x10-3 | 114 | 265(296) | N2O arises from Stationary Sources, mobile sources, manure, soil management and agricultural residue burning, sewage, combustion and bunker fuels | | Sulphur hexafluoride | SF6 | 0.52 | 3200 | 22,800(22,200) | Leakage from electricity substations,magnesium smelters,some consumer goods | | HFC134a(R134a refrigerant) | CH2FCF3 | 0.16 | 14 | 1,430(1,300) | Substitution of ozone depleting substances,refrigerant manufacture/leaks,aerosols,transmission and distribution of electricity. | | DichlorodifluoromethaneCFC12(R12 refrigerant) | CCl2F2 | 0.32 | 100 | 10,900 | | | Difluoromono-chloromethaneHCFC22(R22 refrigerant) | CHClF2 | 0.2 | 12 | 1,810 | | * * * No single lifetime can be determined for carbon dioxide because of the difference in timescales associated with long and short cycle biogenic carbon. For a calculation of lifetimes and a full list of greenhouse gases and their global warming potentials please see Table 2.14: Lifetimes, radiative efficiencies and direct (except for CH4) global warming potentials (GWP) relative to CO2 (Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Avery, M. Tignor and H.L. Miller, 2007). $$ \\mathrm {C O} \_ {2} $$ * * * Appendix 2. Updated full time series – Electricity and Heat and Steam Factors The tables below provide the fully updated and consistent time series data for electricity, heat and steam emission factors47. This is provided for organisations wishing to use fully consistent time series data for purposes OTHER than for company reporting (e.g. policy analysis). Table 1.4 Base electricity generation emissions data – most recent datasets for time series | Data Year | Electricity Generation(1)GWh | Total Grid Losses(2)% | UK electricity generation emissions(3)ktonne | | | | --- | --- | --- | --- | --- | --- | | CO2 | CH4 | N2O | | | | | 1990 | 280,236 | 8.08% | 205,809 | 2.921 | 3.737 | | 1991 | 283,203 | 8.27% | 202,382 | 2.743 | 3.680 | | 1992 | 281,225 | 7.55% | 190,374 | 2.598 | 3.455 | | 1993 | 284,352 | 7.17% | 173,950 | 2.552 | 2.943 | | 1994 | 289,128 | 9.57% | 169,531 | 2.680 | 2.810 | | 1995 | 299,197 | 9.07% | 166,629 | 2.714 | 2.699 | | 1996 | 313,072 | 8.40% | 166,528 | 2.737 | 2.519 | | 1997 | 311,220 | 7.79% | 154,163 | 2.632 | 2.168 | | 1998 | 320,740 | 8.40% | 158,998 | 2.810 | 2.233 | | 1999 | 323,871 | 8.25% | 151,177 | 2.814 | 1.947 | | 2000 | 331,553 | 8.38% | 163,331 | 2.971 | 2.174 | | 2001 | 342,686 | 8.56% | 173,749 | 3.253 | 2.415 | | 2002 | 342,339 | 8.26% | 168,338 | 3.191 | 2.275 | | 2003 | 354,223 | 8.47% | 180,576 | 3.395 | 2.512 | | 2004 | 349,312 | 8.71% | 178,536 | 3.361 | 2.417 | | 2005 | 350,778 | 7.25% | 176,753 | 3.965 | 2.553 | | 2006 | 349,211 | 7.21% | 185,644 | 4.045 | 2.752 | | 2007 | 352,778 | 7.34% | 183,367 | 4.101 | 2.568 | | 2008 | 348,876 | 7.43% | 178,628 | 4.417 | 2.431 | | 2009 | 338,983 | 7.86% | 157,349 | 4.310 | 2.099 | | 2010 | 344,127 | 7.38% | 162,267 | 4.502 | 2.191 | | 2011 | 329,792 | 7.91% | 149,467 | 4.477 | 2.218 | | 2012 | 324,823 | 8.00% | 163,589 | 4.911 | 2.813 | 47 Heat and Steam conversion factors have been held constant from the 2023 release (aligned with AR5 GWPs values). These factors are scheduled to be updated in the 2023 and 2025 Conversion Factors publications. * * * | Data Year | Electricity Generation(1) | Total Grid Losses(2) | UK electricity generation emissions(3)，ktonne | | | | --- | --- | --- | --- | --- | --- | | GWh | % | CO2 | CH4 | N2O | | | 2013 | 318,753 | 7.57% | 151,049 | 5.269 | 2.676 | | 2014 | 298,064 | 8.11% | 127,047 | 6.030 | 2.315 | | 2015 | 297,520 | 8.30% | 106,948 | 7.249 | 2.115 | | 2016 | 296,952 | 7.80% | 84,809 | 7.431 | 1.456 | | 2017 | 293,631 | 8.04% | 74,171 | 7.478 | 1.321 | | 2018 | 289,141 | 7.93% | 68,029 | 8.411 | 1.362 | | 2019 | 282,986 | 7.94% | 60,965 | 9.322 | 1.339 | | 2020 | 270,519 | 8.21% | 52,747 | 9.367 | 1.327 | | 2021 | 269,244 | 8.25% | 58,124 | 9.958 | 1.414 | | 2022 | 286,902 | 8.12% | 58,795 | 8.893 | 1.259 | Notes: (1) Based upon calculated total for all electricity generation (GWh supplied) from DUKES (2023) Table 5.5, with a reduction of the total for autogenerators based on unpublished data from the DESNZ DUKES team on the share of this that is actually exported to the grid (~20% in 2022). (2) Based upon calculated net grid losses from data in DUKES (DESNZ, 2023)Table 5.1.2 (long term trends, only available (2) Based upon calculated net grid losses from data in DUKES (DESNZ, 2023)Table 5.1.2 (long term trends, only available online). (3) Emissions from UK centralised power generation (excluding Crown Dependencies and Overseas Territories) listed under UNFCC reporting category 1A1a and autogeneration - exported to grid (UK Only) listed under UNFCC reporting category 1A2b and 1A2gviii from the UK Greenhouse Gas Inventory for 2022 (Ricardo, 2024). Also includes an accounting (estimate) for autogeneration emissions not specifically split out in the UK GHGI, consistent with the inclusion of the GWh supply for these elements also. * * * Table 1.5 Base electricity generation conversion factors (excluding imported electricity) – fully consistent time series dataset | Data Year | Emission Factor,kgCO2e/kWh | | | | | | | | | | | % Net Electricity Imports | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | For electricity GENERATED(supplied to the grid) | | | | Due to grid transmission/distribution LOSSES | | | | For electricity CONSUMED(includes grid losses) | | | | | | | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | TOTAL | | | 1990 | 0.73442 | 0.00029 | 0.00353 | 0.73824 | 0.06453 | 0.00003 | 0.00031 | 0.06486 | 0.79894 | 0.00032 | 0.00384 | 0.80311 | 4.08% | | 1991 | 0.71462 | 0.00027 | 0.00344 | 0.71833 | 0.06442 | 0.00002 | 0.00031 | 0.06476 | 0.77904 | 0.00030 | 0.00375 | 0.78309 | 5.48% | | 1992 | 0.67695 | 0.00026 | 0.00326 | 0.68046 | 0.05526 | 0.00002 | 0.00027 | 0.05554 | 0.73220 | 0.00028 | 0.00352 | 0.73601 | 5.60% | | 1993 | 0.61174 | 0.00025 | 0.00274 | 0.61474 | 0.04724 | 0.00002 | 0.00021 | 0.04747 | 0.65899 | 0.00027 | 0.00295 | 0.66221 | 5.55% | | 1994 | 0.58635 | 0.00026 | 0.00258 | 0.58919 | 0.06207 | 0.00003 | 0.00027 | 0.06237 | 0.64843 | 0.00029 | 0.00285 | 0.65156 | 5.52% | | 1995 | 0.55692 | 0.00025 | 0.00239 | 0.55956 | 0.05556 | 0.00003 | 0.00024 | 0.05582 | 0.61248 | 0.00028 | 0.00263 | 0.61539 | 5.26% | | 1996 | 0.53192 | 0.00024 | 0.00213 | 0.53429 | 0.04880 | 0.00002 | 0.00020 | 0.04901 | 0.58071 | 0.00027 | 0.00233 | 0.58331 | 5.08% | | 1997 | 0.49535 | 0.00024 | 0.00185 | 0.49743 | 0.04187 | 0.00002 | 0.00016 | 0.04205 | 0.53722 | 0.00026 | 0.00200 | 0.53948 | 5.06% | | 1998 | 0.49572 | 0.00025 | 0.00184 | 0.49781 | 0.04543 | 0.00002 | 0.00017 | 0.04562 | 0.54115 | 0.00027 | 0.00201 | 0.54344 | 3.74% | | 1999 | 0.46678 | 0.00024 | 0.00159 | 0.46862 | 0.04198 | 0.00002 | 0.00014 | 0.04214 | 0.50876 | 0.00027 | 0.00174 | 0.51076 | 4.21% | | 2000 | 0.49263 | 0.00025 | 0.00174 | 0.49461 | 0.04509 | 0.00002 | 0.00016 | 0.04527 | 0.53771 | 0.00027 | 0.00190 | 0.53988 | 4.10% | * * * 2024 Government greenhouse gas conversion factors for company reporting: Methodology paper | Data Year | Emission Factor,kgCO2e/kWh | | | | | | | | | | | % Net Electricity Imports | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | For electricity GENERATED(supplied to the grid) | | | Due to grid transmission/distribution LOSSES | | | | For electricity(includes grid losses) | | | | | | | | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | TOTAL | | | 2011 | 0.45322 | 0.00038 | 0.00178 | 0.45538 | 0.03892 | 0.00003 | 0.00015 | 0.03911 | 0.49214 | 0.00041 | 0.00194 | 0.49449 | 1.85% | | 2012 | 0.50362 | 0.00042 | 0.00229 | 0.50634 | 0.04378 | 0.00004 | 0.00020 | 0.04402 | 0.54740 | 0.00046 | 0.00249 | 0.55036 | 3.52% | | 2013 | 0.47388 | 0.00046 | 0.00222 | 0.47656 | 0.03879 | 0.00004 | 0.00018 | 0.03901 | 0.51266 | 0.00050 | 0.00241 | 0.51557 | 4.33% | | 2014 | 0.42624 | 0.00057 | 0.00206 | 0.42886 | 0.03764 | 0.00005 | 0.00018 | 0.03787 | 0.46388 | 0.00062 | 0.00224 | 0.46674 | 6.44% | | 2015 | 0.35946 | 0.00068 | 0.00188 | 0.36203 | 0.03255 | 0.00006 | 0.00017 | 0.03278 | 0.39201 | 0.00074 | 0.00205 | 0.39481 | 6.62% | | 2016 | 0.28560 | 0.00070 | 0.00130 | 0.28760 | 0.02416 | 0.00006 | 0.00011 | 0.02433 | 0.30976 | 0.00076 | 0.00141 | 0.31192 | 5.64% | | 2017 | 0.25260 | 0.00071 | 0.00119 | 0.25450 | 0.02209 | 0.00006 | 0.00010 | 0.02226 | 0.27469 | 0.00078 | 0.00130 | 0.27676 | 4.79% | | 2018 | 0.23528 | 0.00081 | 0.00125 | 0.23734 | 0.02027 | 0.00007 | 0.00011 | 0.02045 | 0.25555 | 0.00088 | 0.00136 | 0.25779 | 6.20% | | 2019 | 0.21544 | 0.00092 | 0.00125 | 0.21761 | 0.01859 | 0.00008 | 0.00011 | 0.01878 | 0.23402 | 0.00100 | 0.00136 | 0.23639 | 6.96% | | 2020 | 0.19498 | 0.00097 | 0.00130 | 0.19725 | 0.01745 | 0.00009 | 0.00012 | 0.01765 | 0.21244 | 0.00106 | 0.00142 | 0.21491 | 6.21% | | 2021 | 0.21588 | 0.00104 | 0.00139 | 0.21830 | 0.01941 | 0.00009 | 0.00013 | 0.01963 | 0.23529 | 0.00113 | 0.00152 | 0.23794 | 8.36% | Notes: \* The updated 2016 (2014 update year) methodology uses dataon the contribution of electricity from the different interconnects, hence these figures are based on a weighted average emission factor of the conversion factors for France, the Netherlands, Ireland,Belgium, and Norwaybased on the % share supplied. The dataset above uses the most recent, consistent data sources across the entire time series. Emission Factor (Electricity CONSUMED) = Emission Factor (Electricity GENERATED) / (1 %Electricity Total Grid LOSSES)- Emission Factor (Electricity LOSSES) = Emission Factor (Electricity CONSUMED) Emission Factor (Electricity GENERATED)- * * * Table 1.6 Base electricity generation emissions factors (including imported electricity) – fully consistent time series dataset | Data Year | Emission Factor,kgCO2e/kWh | | | | | | | | | | | % Net Electricity Imports | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | For electricity GENERATED(supplied to the grid,plus imports) | | | Due to grid transmission/distribution LOSSES | | | | For electricity CONSUMED(includes grid losses) | | | | | | | | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | | | | 1990 | 0.70908 | 0.00028 | 0.00341 | 0.71277 | 0.06230 | 0.00002 | 0.00030 | 0.06262 | 0.77138 | 0.00030 | 0.00372 | 0.77540 | 4.08% | | 1991 | 0.68248 | 0.00026 | 0.00329 | 0.68603 | 0.06153 | 0.00002 | 0.00029 | 0.06185 | 0.74401 | 0.00028 | 0.00358 | 0.74787 | 5.48% | | 1992 | 0.64468 | 0.00025 | 0.00310 | 0.64803 | 0.05262 | 0.00002 | 0.00025 | 0.05289 | 0.69730 | 0.00027 | 0.00335 | 0.70092 | 5.60% | | 1993 | 0.58156 | 0.00024 | 0.00261 | 0.58440 | 0.04491 | 0.00002 | 0.00020 | 0.04514 | 0.62647 | 0.00026 | 0.00281 | 0.62954 | 5.55% | | 1994 | 0.55780 | 0.00025 | 0.00245 | 0.56050 | 0.05905 | 0.00002 | 0.00026 | 0.05933 | 0.61685 | 0.00027 | 0.00271 | 0.61983 | 5.52% | | 1995 | 0.53175 | 0.00025 | 0.00229 | 0.53428 | 0.05305 | 0.00002 | 0.00023 | 0.05330 | 0.58480 | 0.00027 | 0.00252 | 0.58759 | 5.26% | | 1996 | 0.50907 | 0.00024 | 0.00204 | 0.51134 | 0.04670 | 0.00002 | 0.00019 | 0.04691 | 0.55577 | 0.00026 | 0.00222 | 0.55825 | 5.08% | | 1997 | 0.47412 | 0.00022 | 0.00177 | 0.47611 | 0.04008 | 0.00002 | 0.00015 | 0.04025 | 0.51420 | 0.00025 | 0.00192 | 0.51637 | 5.06% | | 1998 | 0.48110 | 0.00024 | 0.00179 | 0.48312 | 0.04409 | 0.00002 | 0.00016 | 0.04427 | 0.52519 | 0.00026 | 0.00195 | 0.52740 | 3.74% | | 1999 | 0.45092 | 0.00024 | 0.00154 | 0.45269 | 0.04055 | 0.00002 | 0.00014 | 0.04071 | 0.49147 | 0.00026 | 0.00168 | 0.49341 | 4.21% | | 2000 | 0.47576 | 0.00025 | 0.00168 | 0.47769 | 0.04354 | 0.00002 | 0.00015 | 0.04371 | 0.51930 | 0.00027 | 0.00183 | 0.52140 | 4.10% | * * * 2024 Government greenhouse gas conversion factors for company reporting: Methodology paper | Data Year | Emission Factor,kgCO2e/kWh | | | | | | | | | | | % Net Electricity Imports | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | For electricity GENERATED(supplied to the grid,plus imports) | | | Due to grid transmission/distribution LOSSES | | | | For electricity CONSUMED(includes grid losses) | | | | | | | | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | TOTAL | | | 2012 | 0.49496 | 0.00041 | 0.00226 | 0.49763 | 0.04303 | 0.00003 | 0.00020 | 0.04326 | 0.53799 | 0.00045 | 0.00245 | 0.54089 | 3.52% | | 2013 | 0.46307 | 0.00045 | 0.00217 | 0.46569 | 0.03790 | 0.00003 | 0.00018 | 0.03811 | 0.50097 | 0.00048 | 0.00235 | 0.50380 | 4.33% | | 2014 | 0.41177 | 0.00055 | 0.00199 | 0.41431 | 0.03636 | 0.00004 | 0.00018 | 0.03658 | 0.44813 | 0.00059 | 0.00217 | 0.45089 | 6.44% | | 2015 | 0.35054 | 0.00066 | 0.00184 | 0.35304 | 0.03174 | 0.00006 | 0.00017 | 0.03196 | 0.38228 | 0.00072 | 0.00201 | 0.38501 | 6.62% | | 2016 | 0.28393 | 0.00069 | 0.00129 | 0.28591 | 0.02402 | 0.00006 | 0.00011 | 0.02418 | 0.30795 | 0.00075 | 0.00140 | 0.31010 | 5.64% | | 2017 | 0.25296 | 0.00072 | 0.00119 | 0.25487 | 0.02212 | 0.00007 | 0.00011 | 0.02229 | 0.27508 | 0.00078 | 0.00130 | 0.27716 | 4.79% | | 2018 | 0.23096 | 0.00080 | 0.00123 | 0.23298 | 0.01990 | 0.00007 | 0.00011 | 0.02007 | 0.25086 | 0.00086 | 0.00133 | 0.25306 | 6.20% | | 2019 | 0.21119 | 0.00091 | 0.00123 | 0.21332 | 0.01822 | 0.00008 | 0.00011 | 0.01841 | 0.22941 | 0.00099 | 0.00133 | 0.23173 | 6.96% | | 2020 | 0.19105 | 0.00095 | 0.00127 | 0.19327 | 0.01710 | 0.00009 | 0.00012 | 0.01731 | 0.20815 | 0.00104 | 0.00139 | 0.21058 | 6.21% | | 2021 | 0.20612 | 0.00099 | 0.00133 | 0.20843 | 0.01854 | 0.00009 | 0.00012 | 0.01875 | 0.22466 | 0.00108 | 0.00144 | 0.22718 | 8.36% | | 2022 | 0.20493 | 0.00090 | 0.00122 | 0.20704 | 0.01811 | 0.00008 | 0.00011 | 0.01830 | 0.22304 | 0.00097 | 0.00133 | 0.22534 | 0.00% | Notes: \* The updated 2016 methodology uses data on the contribution of electricity from the different interconnects, hence these figures are based on a weighted average emission factor of the conversion factors for France, the Netherlands, Ireland,Belgium, and Norway,based on the % share supplied. The dataset above uses the most recent, consistent data sources across the entire time series. Emission Factor (Electricity CONSUMED) = Emission Factor (Electricity GENERATED) / (1 %Electricity Total Grid LOSSES)- Emission Factor (Electricity LOSSES) = Emission Factor (Electricity CONSUMED) Emission Factor (Electricity GENERATED)- ⇒ Emission Factor (Electricity CONSUMED) = Emission Factor (Electricity GENERATED) + Emission Factor (Electricity LOSSES * * * Table 1.7 Fully consistent time series for the heat/steam and supplied power carbon factors as calculated using DUKES method | Data Year | kgCO2/kWh supplied heat/steam | kgCO2/kWh supplied power | | --- | --- | --- | | Method 1(DUKES:2/3rd-1/3rd) | Method 1(DUKES:2/3rd-1/3rd) | | | 2001 | 0.238 | 0.465 | | 2002 | 0.230 | 0.449 | | 2003 | 0.234 | 0.454 | | 2004 | 0.228 | 0.440 | | 2005 | 0.221 | 0.426 | | 2006 | 0.231 | 0.442 | | 2007 | 0.231 | 0.444 | | 2008 | 0.224 | 0.433 | | 2009 | 0.222 | 0.426 | | 2010 | 0.219 | 0.419 | | 2011 | 0.215 | 0.472 | | 2012 | 0.205 | 0.385 | | 2013 | 0.208 | 0.391 | | 2014 | 0.202 | 0.384 | | 2015 | 0.196 | 0.378 | | 2016 | 0.186 | 0.366 | | 2017 | 0.174 | 0.346 | | 2018 | 0.170 | 0.339 | | 2019 | 0.171 | 0.330 | | 2020 | 0.176 | 0.335 | | 2021 | 0.178 | 0.339 | * * * If you need a version of this document in a more accessible format, please email [Greenhousegas.statistics@energysecurity.gov.uk](mailto:Greenhousegas.statistics@energysecurity.gov.uk). 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