# 2026 Government Greenhouse Gas

# Conversion Factors For Company Reporting

## Methodology Paper for Conversion factors Final Report

Department for Energy Security and Net Zero (2026)

* * *

© Crown copyright 2026

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 and Jason Wong (Ricardo Energy & Environment), Nina Sidhu, Nicolas Bert, Jack Bahou and Harper Robertson (Aether Ltd), and Billy Harris (WRAP) for the Department for Energy Security and Net Zero (DESNZ).

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# Contents

Glossary ... 10

1. General Introduction ... 13
   Overview of major changes since the previous update ... 15
   Conversion factors update frequency ... 15

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 ... 26
   Direct Emissions from UK Grid Electricity ... 27
   Indirect/WTT Emissions from UK Grid Electricity ... 37
   Conversion factors for the Supply of Purchased Heat or Steam ... 37
   Summary of Method 1: 1/3: 2/3 Method (DUKES) ... 38
   Calculation of CO2 Emissions Factor for CHP Fuel Input, FuelMixCO2factor ... 38
   Calculation of Non-CO2 and Indirect/WTT Emissions Factor for Heat and Steam ... 42

4. Refrigerant and Process Emission Factors ... 43
   Section summary ... 43
   Summary of changes since the previous update ... 43
   Global Warming Potentials of Greenhouse Gases ... 43
   Greenhouse Gases Listed in the Kyoto Protocol ... 43
   Other Greenhouse Gases ... 44

5. Passenger Land Transport Emission Factors ... 45
   Section summary ... 45
   Summary of changes since the previous update ... 45
   Direct Emissions from Passenger Cars ... 46
   Conversion factors for Petrol and Diesel Passenger Cars by Engine Size ... 46
   Hybrid, LPG and CNG Passenger Cars ... 52
   Plug-in Hybrid Electric and Battery Electric Passenger Cars (xEVs) ... 52
   Conversion factors by Passenger Car Market Segments ... 68


* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

Direct Emissions from Taxis ... 70
Direct Emissions from Vans/Light Goods Vehicles (LGVs) ... 70
Plug-in Hybrid Electric and Battery Electric Vans (xEVs) ... 72
Direct Emissions from Buses ... 74
Direct Emissions from Motorcycles ... 76
Direct Emissions from Passenger Rail ... 78
International Rail (Eurostar) ... 78
National Rail ... 78
Light Rail ... 78
London Underground ... 79
Indirect/WTT Emissions from Passenger Land Transport ... 80
Cars, Vans, Motorcycles, Taxis, Buses and Ferries ... 80
Rail ... 80

6. Freight Land Transport Emission Factors ... 81
   Section summary ... 81
   Summary of changes since the previous update ... 81
   Direct Emissions from Heavy Goods Vehicles (HGVs) ... 81
   Direct Emissions from Vans/Light Goods Vehicles (LGVs) ... 84
   Direct Emissions from Rail Freight ... 86
   Indirect/WTT Emissions from Freight Land Transport ... 86
   Vans and HGVs ... 86
   Rail ... 86

7. Sea Transport Emission Factors ... 87
   Section summary ... 87
   Summary of changes since the previous update ... 87
   Direct Emissions from RoPax Ferry Passenger Transport and freight ... 87
   Direct Emissions from Other Marine Freight Transport ... 89
   Indirect/WTT Emissions from Sea Transport ... 89

8. Air Transport Emission Factors ... 90
   Section summary ... 90
   Summary of changes since the previous update ... 90
   Passenger Air Transport Direct CO2 Emission Factors ... 90
   Allocating flights into short- and long-haul: ... 93
   Taking Account of Freight ... 95
   Taking Account of Seating Class Factors ... 96


* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

Freight Air Transport Direct CO2 Emission Factors ... 98
Conversion factors for Dedicated Air Cargo Services ... 98
Conversion factors for Freight on Passenger Services ... 102
Average Conversion factors for All Air Freight Services ... 102
Air Transport Direct Conversion factors for CH4 and N2O ... 103
Emissions of CH4 ... 103
Emissions of N2O ... 103
Indirect/WTT Conversion factors from Air Transport ... 105
Other Factors for the Calculation of GHG Emissions ... 105
Great Circle Flight Distances ... 105
Non-CO2 impacts and Radiative Forcing ... 105

9. Bioenergy and Water ... 110
   Section summary ... 110
   Summary of changes since the previous update ... 110
   General Methodology ... 111
   Water ... 111
   Biofuels ... 111
   Other biomass and biogas ... 113

10. Overseas Electricity Emission Factors ... 115
   Section summary ... 115
   Summary of changes since the previous update ... 115
   Direct Emissions and Emissions resulting from Transmission and Distribution Losses from
   Overseas Electricity Generation ... 115
   Indirect/WTT Emissions from Overseas Electricity Generation ... 116

11. Hotel Stay ... 118
   Section summary ... 118
   Summary of changes since the previous update ... 118
   Direct emissions from a hotel stay ... 118

12. Material Consumption/Use and Waste Disposal ... 120
   Section summary ... 120
   Summary of changes since the previous update ... 120
   Emissions from Material Use and Waste Disposal ... 121
   Material Consumption/Use ... 121
   Waste Disposal ... 123

13. Fuel Properties ... 126


* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

Section summary ... 126
Summary of changes since the previous update ... 126
General Methodology ... 126

14. SECR kWh Conversion factors ... 127
    Section summary ... 127
    Summary of changes since the previous update ... 128
    General Methodology ... 128

15. Homeworking ... 129
    Section summary ... 129
    General Methodology ... 129
    References ... 131
    Appendix 1. Additional Methodological Information on the Material Consumption/Use and
    Waste Disposal Factors ... 138


1.1 Data Quality Requirements ... 138
1.2 Data Sources ... 139
1.3 Use of data below the set quality standard ... 139
1.4 Wood and Paper data ... 140
1.5 Excluded Materials and Products ... 140
1.6 Greenhouse Gas Conversion factors ... 146
Appendix 2. Updated full time series – Electricity and Heat and Steam Factors ... 148

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# 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 ... 29

Table 8: Base electricity generation conversion factors (excluding imported electricity) ... 32

Table 9: Base electricity generation emissions factors (including imported electricity) ... 34

Table 10: Fuel types and associated emissions factors used in the determination of FuelMixCO2factor

... 39

Table 11: Heat/Steam CO2 emission factor for DUKES 1/3 2/3 method ... 41

Table 12: Related worksheets to passenger land transport emission factors ... 45

Table 15: Average CO2 conversion factors and total registrations by engine size for 2008 to 2025 (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: PHEV Cars Real-World average percentage share of Electric and Combustion Mode

kilometres, and CO2 Emissions per kilometre, based on 2024 UK fuel, electricity, and PHEV
car fleet data, per market segment ... 64

Table 20: Summary of key data elements, sources and key assumptions used in the calculation of GHG

conversion factors for electric cars and vans ... 65

Table 21: Average car CO2 conversion factors and total registrations by market segment for 2009 to

2025 (based on data sourced from SMMT) ... 68

Table 22: New conversion factors for vans for the 2026 GHG Conversion factors ... 72

Table 23: xEV van models and their allocation to different size categories ... 73

Table 24: Key assumptions used in the calculation of CO2 emissions from Urea (aka ‘AdBlue’) use75

Table 25: Conversion factors for buses for the 2026 GHG Conversion factors ... 76

Table 26: Summary dataset on CO2 emissions from motorcycles based on detailed data provided by

Clear (2008) ... 77

Table 27: GHG emission factors, electricity consumption and passenger km for different tram and light

rail services ... 79

Table 28 Related worksheets to freight land transport emission factors ... 81

Table 29: Change in CO2 emissions caused by +/- 50% change in load from the average loading factor

of 50% ... 82

Table 30: Typical van freight capacities and estimated average payload ... 84

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

Table 31: Utilisation of vehicle capacity by company-owned LGVs: annual average 2003 – 2005

(proportion of total vehicle kilometres travelled) ... 85

Table 32: Related worksheets to sea transport emission factors ... 87

Table 33: Assumptions used in the calculation of ferry emission factors ... 88

Table 34: Related worksheets to air transport emission factors ... 90

Table 35: Assumptions used in the calculation of revised average CO2 conversion factors for passenger

flights for 2025 ... 91

Table 36: Illustrative short- and long- haul flight distances from the UK ... 94

Table 37: CO2 conversion factors for alternative freight allocation options for passenger flights ... 95

Table 38: Final average CO2 conversion factors for passenger flights (excluding distance and RF uplifts)

... 96

Table 39: CO2 conversion factors by seating class for passenger flights (excluding distance and RF

uplifts) ... 97

Table 40: Revised average CO2 conversion factors for dedicated cargo flights (excluding distance and

RF uplifts) ... 98

Table 41: Assumptions used in the calculation of average CO2 conversion factors for dedicated cargo

flights ... 99

Table 42: Air freight CO2 conversion factors for alternative freight allocation options for passenger flights

(excluding distance and RF uplifts) ... 102

Table 43: Final average CO2 conversion factors for all air freight (excluding distance and RF uplifts)

... 103

Table 44: Total emissions of CO2, CH4 and N2O for domestic and international aircraft from the UK GHG

Inventory for 2023 ... 103

Table 45: Final average CO2, CH4 and N2O conversion factors for all air passenger transport (excluding

distance and RF uplifts) ... 104

Table 46: Final average CO2, CH4 and N2O conversion factors for air freight transport (excluding

distance and RF uplifts) ... 104

Table 47: Impacts of radiative forcing according to Lee et al., (2021) ... 107

Table 48: Aviation non-CO2 emissions equivalence metrics for GWP, GTP and GWP\* taken from Lee et

al. (2021) ... 108

Table 49: Related worksheets for bioenergy and water emission factors ... 110

Table 50: Fuel lifecycle GHG Conversion factors for biofuels ... 112

Table 51: Fuel sources and properties used in the calculation of biomass and biogas emission factors

... 113

Table 52: Distances and transportation types used in material use EF calculations ... 123

Table 53: Distances used in the calculation of waste emission factors ... 124

Table 54: Related worksheets to SECR kWh emissions factors ... Error! Bookmark not defined.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# Figures

Figure 1. Comparison of published UK electricity factors, before and after adjusting for the data year

... 26

Figure 2. Illustration of how UK power producers, autogenerators and imports feed into the grid electricity

mix ... 28

Figure 3: Updated GCF 'Real world' uplift values for the UK based on (ICCT, 2017) ... 50

Figure 4: Comparison of 'Real world' uplift values from various sources (ICCT, 2017) ... 51

Figure 5: Illustration of the relationship of electric range to average electric share of total km for PHEVs

assumed in the calculations ... 67

Figure 6: Boundary of material consumption data sets ... 122

* * *

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 |
| IPCC | Intergovernmental Panel on Climate Change |
| LCA | Life cycle assessment |
| LGVs | Light goods vehicles |
| LPG | Liquefied petroleum gas |
| MTBE | Methyl tert-butyl ether |
| NAEI | National Atmospheric Emissions Inventory |
| NCV | Net calorific value |
| NEDC | New European Driving Cycle |
| $N\_{2}O$ | 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) |

N{}\_{2}{}{\\cal O}

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

| Abbreviation | Definition |
| --- | --- |
| xEV | Generic term for battery electric vehicles (BEV), plug-in hybrid electric vehicles (PHEV), range-extended electric vehicles (REEV) and fuel cell electric vehicles (FCEV) |

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# 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 emissions- releasing 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 are 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 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 2026 UK Government Greenhouse Gas Conversion factors for Company Reporting2 (hereafter the 2026 UK GHG Conversion Factors) represent the current official set of UK government conversion factors. These factors are also used in a number of different policies. They are suitable for use by:
a) UK-based organisations of all sizes
1 [https://ghgprotocol.org/corporate-standard](https://ghgprotocol.org/corporate-standard)

Previously known as the ‘Guidelines to Defra/DECC’s GHG Conversion factors for Company Reporting’.

* * *

b) International organisations reporting on their UK operations.

1.5. They are relevant to Environmental Reporting Guidelines, including Streamlined
Energy and Carbon Reporting (SECR) regulations. The factors may also be used
for other purposes, but users do so at their own risk.

1.6. These conversion factors differ from the spend-based emissions multipliers
currently published by the Department for Environment, Food & Rural Affairs
(Defra) alongside the annual UK and England carbon footprint publication. Defra’s
spend-based multipliers are primarily intended to allow users to compare the
carbon intensities of different categories of final UK demand, however, they can
be used to provide an initial assessment of a user’s full supply-chain emissions
based on spending across different goods and services. Users may wish to use
spend-based methods where they do not have sufficient data to use activity-based
methods. Users should ensure they report the methods used for their emissions
accounting.

1.7. The UK GHG Conversion Factors have been developed as part of the NAEI
(National Atmospheric Emissions Inventory) contract, managed by Ricardo (now a
member of WSP), which includes the:

a) UK Air Quality Pollutant Inventory (AQPI)
b) UK Greenhouse Gas Inventory (GHGI)

b) UK Greenhouse Gas Inventory (GHGI)

1.8. Each year, the UK GHGI is published online at:
[https://naei.energysecurity.gov.uk/reports](https://naei.energysecurity.gov.uk/reports)

1.9. 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
2026 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.

\\mathrm{(C O\_{2})}

(\\mathrm{N}\_{2}\\mathrm{O})

\ \\mathrm C O\_{2}

\\tt(C O\_e

1.11. 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 2026 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

\\cdot\\mathsf{N}\_{2}\\mathsf{O}=265,

C H\_{4}=28 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.

1.12. Detailed guidance on how the conversion factors provided should be used is
contained in the “Introduction” worksheet of the 2026 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

1.13. Major changes and updates in terms of methodological approach from the 2026
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 2025
update):

• There has been a significant change to the way the electricity emission factor
is calculated. In simple terms, the change allows more up-to-date information
on energy and emissions for grid electricity production to be factored into the
calculations. This means that there is a significant drop in the electricity
conversion factor between 2026 and 2025. The change affects the main
electricity factor, as well as transmission and distribution losses. More
information is provided in Section 3 of this report.
• The above change also has knock-on effects on the conversion factors for

• The above change also has knock-on effects on the conversion factors for
other activities that use electricity, including electric vehicles, rail, and
homeworking.
Conversion factors update frequency

Conversion factors update frequency

1.14. The scope of the conversion factors has expanded over time (mainly due to the
addition of new factors and an increased 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.

{\\mathrm{c O}}\_{2}

• Fuels: natural gas, diesel, petrol, coal, CNG and LNG

* * *

• Bioenergy
• Electricity use, including T&D losses and WTT emissions

• Electricity use, including T&D losses and WTT emissions
• Passenger vehicles, delivery vehicles, and business travel: cars, HGVs, LGVs,

• Passenger vehicles, delivery vehicles, and business travel: cars, HGVs, LGVs,
xEVs & buses
• Rail

• Rail
• Material Use & Waste disposal

• Material Use & Waste disposal
• Homeworking (office equipment & main factor)

• Homeworking (office equipment & main factor)

1.16. Conversion factors that have been held constant from the 2025 release:

• Heat and Steam
• Aviation

• Aviation
• Water Supply & Water Treatment

• Water Supply & Water Treatment
• Well-to-Tank (WTT) Bioenergy

• Well-to-Tank (WTT) Bioenergy
• Outside of scopes (except UK electricity)

• Outside of scopes (except UK electricity)

1.17. Conversion factors that have been held constant from the 2024 release:

• WTT Passenger Vehicles
• WTT Business Travel - Land

• WTT Business Travel - Land
• WTT Delivery Vehicles & Freight

• WTT Delivery Vehicles & Freight

1.18. Conversion factors that have been held constant from the 2023 release:

• WTT Fuels
• WTT Electricity

• WTT Electricity
• WTT Heat & Steam

• WTT Heat & Steam
• WTT Business Travel – Air

• Refrigerants3

1.19. Conversion factors that have been held constant from the 2022 release include:

• Hotel stay
• Homeworking (heating factor)

• Homeworking (heating factor)
• Outside of Scopes UK Electricity

1.20. Conversion factors that have been held constant since the 2021 release include:

• Outside of Scopes UK Electricity

• All methane (CH4) and nitrous oxide (N2O) conversion factors, except those for
electricity which have been updated this year
• Fuels: butane, LPG, other petroleum gas, propane, aviation spirit, aviation

(\\mathrm{N}\_{2}\\mathrm{O})

• Passenger vehicles and business travel: taxis, motorcycles, shipping

* * *

• All other WTT factors4

1.21. 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 Processes5 |  | √ |
| 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 Stay6 | √ | √ |

4
WTT Bioenergy factors are still based on a AR4 basis.
5
For Refrigerants & other process gases, almost all values have been updated to use AR5 GWPs (and where AR5

5
For Refrigerants & other process gases, almost all values have been updated to use AR5 GWPs (and where AR5
values were not available, but AR6 values were, AR6 GWPs were used).

6
Hotel Stay conversion factors are not all aligned with the AR5 GWPs, because the data from Hotel Sustainability
Benchmarking Index 2021 were in CO2e with no breakdown of CH4 and N2O emissions. The conversion factors of

\ \\mathrm N{\ }O

\\mathrm{C H}\_{4}

\\mathrm{c O\_{2}e}

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

## In AR4 basis In AR5 basis

Material Use ✓ Waste Disposal ✓ Homeworking ✓

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.

* * *

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 measurement that differ from those
presented in the main UK GHG Conversion Factors tables.

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. Note that
as of 2026, the Condensed set is no longer published; however, this table has
been retained here so that users can find values from previous publication years.

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

{\\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 2026 GHG Conversion factors are based on an activity-weighted
average of all the different CH4 and N2O conversion factors from the 2024 GHGI.

2.8. There are three tables in the 2026 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
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. 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.

2.10. When using the direct conversion factor for aviation turbine fuel, applying a 1.7
multiplier to the CO2 is applicable to account for the radiative forcing effects of
emissions at altitude. Further explanation of this is provided in Section 8.39.

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

7
Gross CV or higher heating value (HHV) is the CV under laboratory conditions. Net CV or lower heating value (LHV)
is the useful calorific value in typical real-world conditions (e.g. boiler plant). The difference is essentially the latent
heat of the water vapour produced (which can be recovered in laboratory conditions).

* * *

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 where no 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 2026 GHG Conversion factors publication, 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. 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. These estimates
have also been made based on Department for Transport Renewable Fuel
Statistics.

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 | 681 | 25560 | 2.78% | 2.60% | 2.41% |
| Petrol/Bioethanol | 1500 | 15965 | 9.09% | 8.59% | 5.67% |

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 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, 2025)
is used to update the emissions for these activities estimated in Exergia.

2.17. Information on quantities and source of imported gas were taken from DUKES8
and can be used to calculate the proportion of gas in UK supply coming from each
source. These were 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.

2.18. In years when the WTT conversion factors for fuels are updated, 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.

In years when the WTT conversion factors for fuels are updated, 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% | 49.3% | 17.5% |
| 2013 | 19.1% | 51.7% | 12.1% |
| 2014 | 26.0% | 46.3% | 16.0% |
| 2015 | 30.2% | 43.4% | 18.8% |
| 2016 | 19.8% | 47.5% | 11.7% |
| 2017 | 13.0% | 46.7% | 7.8% |
| 2018 | 14.3% | 48.8% | 8.3% |
| 2019 | 36.9% | 49.0% | 21.9% |
| 2020 | 41.8% | 46.3% | 24.7% |
| 2021 | 28.5% | 57.5% | 18.8% |
| 2022 | 44.9% | 46.0% | 35.6% |
| 2023 | 42.6% | 45.5% | 30.0% |
| 2024 | 24.5% | 50.1% | 16.4% |

Source: DUKES 2025, (1) Table 4.5 - Natural gas imports and exports and (2) Table 4.1 - Commodity balances

8
From Table 4.1 Commodity balances for natural gas and Table 4.5 Natural gas imports and exports

* * *

2.19. The final combined conversion factors, presented as kilograms of carbon dioxide
equivalents per gigajoule on a net calorific value basis (kgCO2
basis), are listed in Table 5. These include WTT emissions of CO2
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 2026 GHG Conversion Factors alongside the emission factor
data tables.

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 2026 GHG Conversion Factors alongside the emission factor

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) |  |
| 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.

(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

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

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.

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.

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. Note that as of 2026, the Condensed set is no longer
published; however, this table has been retained here so that users can find
values from previous publication years.

Table 6: Related worksheets to UK electricity and heat & steam emission factors

| Worksheet name | Full set | Condensed set |
| --- | --- | --- |
| UK electricity | Y | Y |
| Transmission and distribution | Y | Y |
| WTT-UK&overseasElectricity | Y | N |
| Heat and steam | Y | N |
| WTT-heatandsteam | Y | N |

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# Summary of changes since the previous update

3.4. The 2026 iteration of the electricity conversion factor includes a significant change to the calculation methodology which has implications for all electricity-related conversion factors.
3.5. The previous approach estimated the UK electricity conversion factor (CF) per kilowatt-hour (kWh) by combining the latest information on power generation data from DUKES with the latest published emissions data from the NAEI. The core problem with this approach is the time lag imposed by the publication of the NAEI dataset, which leads to a two-year time lag between when emissions occurred and when the conversion factor is published. This point is particularly problematic given the rapid decarbonisation of the UK electricity mix in recent years, as it results in a conversion factor that does not reflect recent carbon intensity of the grid. This is illustrated in the graph below.
**Figure 1. Comparison of published UK electricity factors, before and after adjusting for**

## the data year

3.6. In light of this, the 2026 iteration of the electricity factor has been updated to utilise more recent information on fuel used for power generation, quantities of electricity generated, and imports/exports, as set out within the Energy Trends publication. This is published on a monthly and quarterly basis and therefore presents an opportunity to incorporate more up to date information when calculating the electricity factor.
3.7. For users of the GHG Conversion Factors for Company Reporting, the main implication of this methodology change is that they will be using more up-to-date conversion factors when calculating emissions from electricity, which will lead to more accurate reporting. As is the case with any significant methodological revisions, users will need to decide whether they should adjust their previous years’ estimates to use the new conversion factors so that they have a consistent time series. This is a recommendation or requirement under some GHG reporting standards, so users should refer to relevant guidance for advice on whether they
need to update previous years’ estimates.

3.8. If users do not adjust their previous years’ estimates, they should be aware that
the new methodology will result in a ‘skipping’ of the 2024 data on UK electricity
emissions intensity. This is because the 2025 publication used 2023 data, and the
2026 publication uses 2025 data. While this does not affect the use of the data by
the end user, it is an important methodological change that should be clearly
explained and to ensure transparency.

Direct Emissions from UK Grid Electricity

3.9. 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.).

3.10. 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 decade, with the
last UK coal power station having closed in September 2024.

3.11. In broad terms, the calculation divides the emissions from electricity production by
the amount of electricity that is produced, to obtain emissions per unit of
electricity. This calculation happens in several stages, as set out below.

3.13. Quantities of fuel used to generate electricity: Information on the quantities of
fuel used to generate electricity, broken down by generator type and fuel type, is
9
taken from ET 5.1, Table 5a. Values are in megatonnes oil equivalent (Mtoe);
these are converted to GWh for use in the calculations. The values are then
adjusted to remove electricity that is produced by autogenerators and consumed

Stage 1: Calculate the emissions from generating UK electricity

9
[https://www.gov.uk/government/statistics/electricity-section-5-energy-trends](https://www.gov.uk/government/statistics/electricity-section-5-energy-trends) onsite, i.e. not exported to the grid, because the CF reflects the UK grid average.
This is illustrated below using 2025 data.

Figure 2. Illustration of how UK power producers, autogenerators and imports feed into
the grid electricity mix

3.14. Emission factors per fuel type: These are taken directly from the most recent
NAEI database. In cases where there is a difference in the level of
detail/disaggregation between fuel types within the NAEI and ET or DUKES
publications, weighted average emission factors have been derived using the
NAEI activity data.

3.15. Emissions from UK electricity production: These are obtained simply by
multiplying the amount of fuel used to generate electricity) by emission factors per
fuel type. In the previous methodology, information on emissions was obtained
directly from NAEI data on total emissions from power generation.

3.16. From this point on, the new methodology follows the same calculation logic as is
used in the previous methodology.

Stage 2: Calculate the emissions per unit of grid electricity generated

3.17. This stage divides the total emissions from UK electricity production (derived in
Stage 1) by the total amount of electricity generated, to obtain an emission factor
per unit of grid electricity generated in the UK.

Stage 3: Remove emissions from electricity that is exported
1.1. This stage takes the result from Stage 2 (emission factor per unit of electricity) and
multiplies it by an adjustment factor which represents the proportion of electricity
generated in the UK that is used in the UK (rather than exported). In 2025,
approximately 94.3% of indigenous production was used in the UK, so the result
from Stage 2 is multiplied by 94.3%, i.e. it reduces slightly.

1.2. In the same way that emissions from autogeneration are excluded from the
calculations in earlier stages, this step is necessary to ensure that the final factors
are representative of the UK grid electricity mix available to UK consumers.

* * *

Stage 4: Add emissions from electricity that is imported

3.19. This stage essentially creates a weighted average of the UK electricity factor
derived in Stage 3, and an overseas emission factor for imports. The latter itself
represents the weighted average of country-specific grid emission factors.
Information on the quantity of electricity imported from different countries is taken
from ET Table 5.6, while country-specific emission factors are the same as those
used in the current methodology.

This stage essentially creates a weighted average of the UK electricity factor
derived in Stage 3, and an overseas emission factor for imports. The latter itself
represents the weighted average of country-specific grid emission factors.
Information on the quantity of electricity imported from different countries is taken
from ET Table 5.6, while country-specific emission factors are the same as those
used in the current methodology.

3.20. This stage provides average emission factors for the UK electricity grid, after
accounting for imports and exports, but before accounting for transmission and
distribution (T&D) losses.

Stage 5: Adjust the results to account for T&D losses

3.21. Grid losses are calculated from DUKES Table 5.1.2. The results from Stage 4,
which represent emissions per unit of electricity generated, are uplifted based on
grid losses. This is because the same quantity of GHG emissions occurs but less
electricity is ultimately available to the end user, so the emissions per unit of
electricity consumed are higher. This is the final step needed to calculate the
emissions per unit of UK grid electricity that is actually delivered to consumers,
which is typically reported under Scope 2.

1.3. For organisations wishing to report Scope 3 emissions associated with T&D
losses, these emission factors are simply calculated as the difference between the
‘electricity generated’ and ‘electricity consumed’ factors.

3.22. 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
users seeking a fully consistent data time series, e.g. those who are
retrospectively updating their previous years’ emissions estimates. 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 |

* * *

| Data Year | Applied to Reporting Year | Electricity Generation(1)GWh | Total Grid Losses(2)% | UK electricity generation emissions(3), ktonne |  |  |
| --- | --- | --- | --- | --- | --- | --- |
| CO2 | CH4 | N2O |  |  |  |  |
| 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 |
| 2015 | 2017 | 296,959 | 8.55% | 106,209 | 7.567 | 2.136 |
| 2016 | 2018 | 297,203 | 7.85% | 84,007 | 7.856 | 1.532 |
| 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 |

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

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 non- thermal 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.
(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** 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)** 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, 2026) for the 2022 data year.
(4) **For 2025 (data year), a new methodology was applied, using data from one year prior to the publication date of the** conversion factors compared to two years previously. This change was done to increase the accuracy of the conversion factors and explains why there is no 2024 data year.

* * *

Table 8: Base electricity generation conversion factors (excluding imported electricity)

| 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 | 0.70395 | 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% |

* * *

2026 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 interconnectors, 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 LOSSES) = Emission Factor (Electricity CONSUMED) - Emission Factor (Electricity GENERATED)

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

⇒ Emission Factor (Electricity CONSUMED) = Emission Factor (Electricity GENERATED) + Emission Factor (Electricity LOSSES),

\\*\\* In 2020, 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. For 2026, a new methodology was applied, using data from one year prior to
the publication date of the conversion factors, whereas previously there was a two-year lag. This explains why there is no 2024 data year.

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 |  |  |
| 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% |

* * *

2026 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) |  |  |  |  |  |  |
| CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | CO2 | CH4 | N2O | Total | Total |  |
| 2005 | 0.46359 | 0.00022 | 0.00291 | 0.46673 | 0.03621 | 0.00002 | 0.00023 | 0.03646 | 0.49981 | 0.00023 | 0.00314 | 0.50318 | 2.16% |
| 2006 | 0.49263 | 0.00022 | 0.00322 | 0.49608 | 0.03831 | 0.00002 | 0.00025 | 0.03857 | 0.53094 | 0.00024 | 0.00347 | 0.53465 | 1.97% |
| 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% |

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

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) Emission Factor (Electricity LOSSES) = Emission Factor (Electricity CONSUMED) – Emission Factor (Electricity GENERATED) ⇒ Emission Factor (Electricity CONSUMED) = Emission Factor (Electricity GENERATED) + Emission Factor (Electricity LOSSES) \*\* In 2020, 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.

* * *

Indirect/WTT Emissions from UK Grid Electricity

3.23. 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 WTT- Fuels 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.

3.24. The WTT conversion factor for electricity has been calculated using the data on
the total fuel consumption by type of generator from DUKES and Energy Trends
as used in the main electricity calculations (described above), and corresponding
WTT conversion factors for different fuels (see Table 5). The fuel consumption
data are used to produce a weighted average of the WTT factors.

Conversion factors for the Supply of Purchased Heat or Steam

3.25. Heat and Steam conversion factors have been held constant from the 2025
release (aligned with AR5 GWPs values).

3.26. The conversion factors for the supply of purchased heat or steam represent the
average emissions from the heat and steam supplied by the UK Combined Heat
and Power Quality Assurance (CHPQA) scheme 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.

3.27. 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.

3.28. To determine the amount of fuel attributed to CHP heat (qualifying heat output, or
‘QHO’), it is necessary to apportion the total fuel to the CHP scheme to the
separate heat and electricity outputs. This then enables the fuel, and therefore
emissions, associated with the QHO to be determined. There are three possible
methodologies for apportioning fuel to heat and power:

c) Method 3: Power Station Displacement Method

3.29. 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.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

## Summary of Method 1: 1/3: 2/3 Method (DUKES)

3.30. 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%.
3.31. Mathematically, Method 1 can be represented as follows:
 _Total Fuel Input_  _Heat \_ Energy = _  × Heat \_ Output 

# (2 × Electricit \_ Outputy) + Heat \_ Output 

 2 × Total Fuel Input  _Electricity \_ Energy = _  × Electricit \_ Outputy 

# (2 × Electricit \_ Outputy)+ Heat \_ 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.
- ‘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.
- ‘Electricity Energy’ is the fuel to the prime mover apportioned to the electricity generated.
  3.32. 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

3.33. 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.
The value for FuelMixCO2factor is determined using the following expression:

Where:

10 Climate Change Agreements (CCAs) are agreements between UK energy intensive industries and UK Government, whereby industry undertakes to make challenging, but achievable, improvements in energy efficiency in exchange for a reduction in the Climate Change Levy (CCL).

* * *

• 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.

3.34. 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. Note that these emission factors for fuels
differ from those in the 2026 publication because Heat and Steam has not been
updated in the 2026 cycle; they are presented for information purposes only.

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. Note that these emission factors for fuels
differ from those in the 2026 publication because Heat and Steam has not been
updated in the 2026 cycle; they are presented for information purposes only.

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 | - |
| VOC's | - |
| 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 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 PAS111) | - |
| Wood pellets | - |

Sources: GHG Conversion factors for Company Reporting (2025 update).

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.

3.35. The 1/3 : 2/3 method (Method 1) has been used to calculate the heat/steam
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 from the 2025 UK GHG Conversion Factors is
based on the data year of 2023 in Table 11.

Table 11: Heat/Steam CO2 emission factor for DUKES 1/3 2/3 method.

| Data Year | kgCO2/kWh supplied heat/steam |
| --- | --- |
| 2001 | 0.23770 |
| 2002 | 0.22970 |
| 2003 | 0.23393 |
| 2004 | 0.22750 |
| 2005 | 0.22105 |
| 2006 | 0.23072 |
| 2007 | 0.23118 |
| 2008 | 0.22441 |
| 2009 | 0.22196 |
| 2010 | 0.21859 |

* * *

| Data Year | kgCO2/kWh supplied heat/steam |
| --- | --- |
| 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 |
| 2022 | 0.17619 |
| 2023 | 0.17355 |

Calculation of Non-CO2 and Indirect/WTT Emissions Factor for Heat and Steam

\\mathsf{N o n C-C2}

3.36. 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.

\ \\mathrm c O\_{2}

3.37. 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 GHG Conversion Factors
publication, the value for the most similar alternative fuel was used.

3.38. The final conversion factors for supplied heat or steam utilised are presented in
the ‘Heat and Steam’ tables of the 2026 GHG Conversion Factors and are
counted as Scope 2 emissions under the GHG Protocol.

3.39. For district heating systems, the location of use of the heat will often be some
distance from the point of production and therefore there are distribution energy
losses. These losses are typically around 5% (provided by Ricardo's CHP team in
a personal communication), which need to be factored into the calculation of
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).

For district heating systems, the location of use of the heat will often be some
distance from the point of production and therefore there are distribution energy
losses. These losses are typically around 5% (provided by Ricardo's CHP team in
a personal communication), which need to be factored into the calculation of
overall GHG emissions where relevant and are counted as Scope 3 emissions
under the GHG Protocol (similar to the treatment of transmission and distribution

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# 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 the 2026 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 2026 update. Most refrigerant and process conversion factors have remained constant since the publication of 2023 GHG Conversion factors. The exception is R-511A, a refrigerant blend, which was previously reported as emitting 6.9 kgCO2e per kg and has now been corrected to 0 kgCO2e per kg. Previously, the value was calculated based on a
95.0/5.0 mix of R-290 and HFC-152a, whereas it should have been a 95.0/5.0 mix of R-290 and E-170.

## Global Warming Potentials of Greenhouse Gases

4.5. In most cases, GWP values are 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 (517/2014)
11 .

### Greenhouse Gases Listed in the Kyoto Protocol

4.6. Mixed/Blended gases: GWP values for refrigerant blends are calculated based on the percentage blend composition (e.g. the GWP for R404a that comprises of 44% HFC125
11 , 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

HFC: Hydrofluorocarbon

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

what proportion of the GWP relates specifically to Kyoto components while also presenting the total GWP.

## Other Greenhouse Gases

4.7. CFCs and HCFCs12: 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 F- gas equipment.
CFCs: Chlorofluorocarbons; HCFCs: Hydrochlorofluorocarbons

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

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.

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. The conversion factors for different vehicle types and different GHGs are updated
at different intervals; for more details, please refer to Section 1.12 of this report or
refer to the Index tab of the 2026 GHG Conversion Factors publication
spreadsheet.

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. Note that as of 2026, the Condensed set is no longer
published; however, this table has been retained here so that users can find
values from previous publication years.

\*cars and motorbikes only

| 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 |

Summary of changes since the previous update

3.1. No methodological updates have been made to the calculation of conversion
factors for road vehicles in the 2026 update.

* * *

3.2. Conversion factors for rail have been updated using new data obtained from the
Office of Rail and Road (ORR) data portal (ORR, 2025) and Transport for London
(TfL). The changes to conversion factors in the 2026 GHG Conversion Factors are
primarily due to the use of updated data for these categories rather than any
significant methodological changes.

Direct Emissions from Passenger Cars

Conversion factors for Petrol and Diesel Passenger Cars by Engine Size

5.5. 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.

5.6. The regulatory test cycle/procedure transitioned from the previous NEDC to the
new WLTP13, 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}}

5.7. SMMT14 provides numbers of registrations and average gCO2/km figures for new
15
vehicles registered from 1999 to 2025. 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.

\\mathsf{S M M T}^{14}

\\bar{2025}^{15}

\ \\mathrm c O\_{2}

\\mathrm{C O}\_{2}

13
NEDC = New European Driving Cycle, which has been the standard cycle used in the type approval of all new
passenger cars and vans historically. From 2017 there has been a phased transition in vehicle testing using the
new WLTP (Worldwide Harmonised Light Vehicle Test Procedure); from September 2018 onwards all new cars
and vans must have been tested/reported values under WLTP. More information is available on the VCA website:
[https://www.vehicle-certification-agency.gov.uk/fcb/wltp.asp](https://www.vehicle-certification-agency.gov.uk/fcb/wltp.asp)

14
SMMT is the Society of Motor Manufacturers and Traders that represents the UK auto industry.
[http://www.smmt.co.uk/](http://www.smmt.co.uk/)

15
The SMMT gCO2/km dataset for 1997 represented around 70% of total registrations, which rose to about 99% by
2000 and essentially all vehicles thereafter.

* * *

Table 13: Average CO2 conversion factors and total registrations by engine size for 2008
to 2025 (based on data sourced from SMMT)

\\mathbf{c o}}}\_{\\mathbf{2}

| Vehicle Type | Engine size | Size label | NEDC\*gCO2perkm | WLTPgCO2perkm | Total no.of registrations | % Total |
| --- | --- | --- | --- | --- | --- | --- |
| Petrol car | <1.4l | Small | 116.5 | 129.6 | 12,211,008 | 63% |
| 1.4-2.0l | Medium | 146.5 | 154.7 | 6,365,107 | 33% |  |
| >2.0l | Large | 214.9 | 245.2 | 697,568 | 4% |  |
| Average petrol car |  | All | 128.6 | 143.9 | 19,273,683 | 100% |
| Diesel car | <1.7l | Small | 108.6 | 135.6 | 4,784,081 | 39% |
| 1.7-2.0l | Medium | 130.5 | 160.2 | 5,027,246 | 41% |  |
| >2.0l | Large | 158.3 | 211.3 | 2,417,100 | 20% |  |
| Average diesel car |  | All | 126.8 | 164.1 | 12,228,427 | 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.

\\mathrm{C O\_{2}}

5.9. 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.

5.10. Counts of vehicles were extracted from the 2021 ANPR dataset and categorised
according to their engine size, fuel type and year of registration. The CO2
conversion factors for petrol and diesel passenger cars were subsequently
calculated based upon the equation below:

5.11. 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

\\mathrm{g C\_{2}/k m}=\\sum\\left(\\mathrm{g C O\_{2}/k m\_{y rmathrm,emathrm r e g}\\times\\frac{N P R\_{y r,r e g}}{A N P R\_{t omathrm a l t\ 019}}}\\right)

* * *

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.

5.12. 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.

5.13. WLTP based gCO2/km factors are used from 2020 onwards and require a different
uplift to account for the real-world effects described above. The uplifts used were
based on a report published in 2024 from the European Commission16, and the
average values are shown in Table 16. The uplift is noticeably lower due to WLTP
based factors being closer to real-world driving than NEDC based factors.

Table 14: 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 | 2024 | 2025 |
| RW uplift(%) | 38.00 | 31.50 | 31.50 | 31.50 | 22.25 | 22.48 | 22.75 | 22.95 | 22.99 | 23.01 |

Notes: 2007-2019 values applied to NEDC based factors. 2020-2025 values are an average of uplifts applied to
WLTP based factors. Uplifts in this table are only for petrol, diesel, hybrid and unknown fuel cars, not for plug-in
hybrid or battery electric cars.

5.14. The above uplifts have been applied to the ANPR weighted SMMT gCO2/km to
give the ‘Real-World’ 2026 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 61.5% petrol and 38.5% diesel, and can be
compared to the respective total registrations of the different vehicle types for
2025, which were 61.2% petrol and 38.8% diesel.

16
Available here: [https://climate.ec.europa.eu/news-your-voice/news/first-commission-report-real-world-co2-](https://climate.ec.europa.eu/news-your-voice/news/first-commission-report-real-world-co2-)
emissions-cars-and-vans-using-data-board-fuel-consumption-2024-03-
18\_en#:~:text=Since%20January%202021%2C%20all%20new,and%20the%20total%20distance%20driven

18\_en#:~:text=Since%20January%202021%2C%20all%20new,and%20the%20total%20distance%20driven

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

5.15. An adjustment factor is applied to account for the biofuel content of transportation fuels.
5.16. Conversion factors for CH4 and N2O are based on the emission factors from the UK GHGI 2019 (Ricardo Energy & Environment, 2021) and have been updated to align with AR5 GWP values. The emission factors used in the UK GHGI are based on COPERT 5 version 6 (EMISIA, 2022).
5.17. 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 2026 GHG Conversion Factors set.

* * *

Figure 3: Updated GCF 'Real world' uplift values for the UK based on (ICCT, 2017)

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

**Figure 4: Comparison of 'Real world' uplift values from various sources (ICCT, 2017)**

50% Uplift proposed WhatCar? (UK) **2** 45% ALLSTAR FUEL CARD (UK) Honestjohn.co.uk (UK) 40% TCS (Switzerland) Spiritmonitor.de (Germany) **-approval CO** 35% Travelcard (Netherlands) LeasePlan (Germany) 30% German Mobility Panel (Germany) Fiches-Auto.Fr (France) 25% Autobild (Germany) Emissions Analytics (UK) **emissions** 20% Auto Motor und Sport (Germany) Auto Motor & Sport (Sweden) 15% KM77.COM (Spain)

10% **-world' vs. manufacturers' type**

**'Real** 5%

0% 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 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.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

## Hybrid, LPG and CNG Passenger Cars

5.18. The methodology used in the 2026 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 2025. These are weighted using DfT's ANPR (Automatic Number Plate Recognition) data and an uplift applied to account for ‘real-world’ driving.
5.19. 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.
5.20. 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 2026 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:
gCO2⁄kWhCNG gCO2⁄km CNG Medium car = gCO2⁄km Petrol Medium car × gCO2⁄kWhPetrol

5.21. 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).
Plug-in Hybrid Electric and Battery Electric Passenger Cars (xEVs)

5.22. Since the number of electric vehicles (xEVs17) 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.
5.23. 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.
17 xEVs is a generic term used to refer collectively to battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), range-extended electric vehicles (REEVs, or ER-EVs, or REX) and fuel cell electric vehicles (FCEVs).

* * *

5.24. Table 17 provides an overview of the GHG Conversion Factors tables that have
been developed for the reporting of emissions from electric vehicles, which aligns
with current reporting.

Table 15: 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 | Scope 1: |  |  |
| • Passenger vehicles |  |  |  |
| • Delivery vehicles | Yes | (Zero emissions) |  |
| Emissions resulting from electricity use: |  |  |  |
| (a) Electricity Generation |  |  |  |
| (b) Electricity Transmission&Distribution losses | (a) Scope 2: |  |  |
| • UK electricity for EVs |  |  |  |
| (b) Scope 3: |  |  |  |
| • UK electricity T&D for EVs | Yes | Yes |  |
| Upstream emissions from the use of liquid fuels and electricity | Scope 3: |  |  |
| • WTT- passenger vehicles&travel-land |  |  |  |
| • WTT-delivery vehicles&freight | Yes | Yes |  |
| Total GHG emissions for all components for not directly owned /controlled assets | Scope 3: |  |  |
| • Business travel-land |  |  |  |
| • Freighting goods |  |  |  |
| • Managed assets-vehicles | Yes | Yes |  |

5.26. The calculation of UK fleet average conversion factors for electric vehicles from
2010 to 2020 were based on data obtained from the EEA CO2 monitoring
databases for cars and vans, which are publicly available (EEA, 2021a), (EEA,
2021b). These databases provide details by manufacturer and vehicle type (and
by EU member state) on the annual number of registrations and test cycle
performance for average CO2 emissions (gCO2/km) and electrical energy
consumption (Wh/km, for plug-in vehicles). This allows for the classification of vehicles into market segments and the calculation of registrations weighted
average performance figures.

5.27. 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 2026 update, the number of
new registrations of xEVs cars in the UK in 2024 have been obtained from the UK
DfT’s vehicle licensing statistics data file VEH\_0270 (DfT, 2025). 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 the previous version of VCA regulatory database,
their vehicle model specific CO2
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).

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 2026 update, the number of
new registrations of xEVs cars in the UK in 2024 have been obtained from the UK
DfT’s vehicle licensing statistics data file VEH\_0270 (DfT, 2025). Vehicle model
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 the 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}

5.28. The xEV models included in the current databases (which cover registrations up to
the end of 2024) 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 16: xEV car models and their allocation to different market segments

| MAKE | MODEL | UK Segment | UK Segment Name | BEV | PHEV |
| --- | --- | --- | --- | --- | --- |
| ALFA ROMEO | JUNIOR | C | Lower Medium | Yes | - |
| 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 | CONTINENTAL | G | Specialist Sports | - | 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 | I5 | E | Executive | Yes | - |
| BMW | I8 | G | Specialist Sports | - | Yes |
| BMW | IX | H | Dual Purpose | Yes | - |
| BMW | IX1 | C | Lower Medium | Yes | - |
| BMW | IX2 | H | Dual Purpose | Yes | - |
| BMW | IX3 | H | Dual Purpose | Yes | - |
| BMW | M5 | G | Specialist Sports | - | Yes |
| BMW | M760 | F | Luxury Saloon | - | 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 |
| BMW | XM | F | Luxury Saloon | - | Yes |
| BYD | ATTO | H | Dual Purpose | Yes | - |
| BYD | DOLPHIN | B | Supermini | Yes | - |
| BYD | E6Y | C | Lower Medium | Yes | - |
| BYD | SEAL | D | Upper Medium | Yes | Yes |
| CHEVROLET/DAEWOO | VOLT | C | Lower Medium | - | Yes |
| CITROEN | BERLINGO | I | Multi-Purpose Vehicle | Yes | - |
| CITROEN | C3 | B | Supermini | Yes | - |
| CITROEN | C4 | C | Lower Medium | Yes | - |
| CITROEN | C5 | D | Upper Medium | Yes | Yes |
| CITROEN | C-ZERO | A | Mini | Yes | - |
| CITROEN | DYANE | A | Mini | Yes | - |
| CITROEN | E-SPACETOURER | I | Multi-Purpose Vehicle | Yes | - |
| CUPRA | BORN | C | Lower Medium | Yes | - |
| CUPRA | TAVASCAN | H | Dual Purpose | Yes | - |
| DS | DS3 | B | Supermini | Yes | - |
| DS | DS4 | C | Lower Medium | - | Yes |
| DS | DS7 | H | Dual Purpose | - | Yes |
| DS | DS9 | E | Executive | - | Yes |
| DACIA | SPRING | A | Mini | Yes | - |
| FERRARI | 296 | G | Specialist Sports | - | Yes |
| FERRARI | SF90 | G | Specialist Sports | - | Yes |
| FIAT/ALFA ROMEO | 500 | A | Mini | Yes | - |
| FIAT/ALFA ROMEO | 600 | B | Supermini | Yes | - |
| FIAT/ALFA ROMEO | DUCATO | V | Van | Yes | - |
| FIAT/ALFA ROMEO | TONALE | H | Dual Purpose | - | Yes |
| FISKER | OCEAN | H | Dual Purpose | Yes | - |
| FORD | CAPRI | H | Dual Purpose | Yes | - |
| FORD | EXPLORER | H | Dual Purpose | 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 | PUMA | C | Lower Medium | Yes | - |
| FORD | TOURNEO | H | Dual Purpose | - | Yes |
| FORD | TRANSIT | V | Van | Yes | Yes |
| GENESIS | G80 | E | Executive | Yes | - |
| GENESIS | GV60 | H | Dual Purpose | Yes | - |
| GENESIS | GV70 | H | Dual Purpose | Yes | - |
| HONDA | CR-V | H | Dual Purpose | - | Yes |
| HONDA | E' | B | Supermini | Yes | - |
| HONDA | ENY1 | C | Lower Medium | 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 |
| JAECOO | 7 | H | Dual Purpose | Yes | Yes |
| JAGUAR | E-PACE | C | Lower Medium | - | Yes |
| JAGUAR | F-PACE | C | Lower Medium | - | Yes |
| JAGUAR | I-PACE | H | Dual Purpose | Yes | - |
| JEEP | AVENGER | C | Lower Medium | Yes | - |
| JEEP | COMPASS | H | Dual Purpose | - | Yes |
| JEEP | GRAND CHEROKEE | H | Dual Purpose | - | Yes |
| JEEP | RENEGADE | H | Dual Purpose | - | Yes |
| KGM | KORANDO | H | Dual Purpose | Yes | - |
| KGM | TORRES | H | Dual Purpose | Yes | - |
| KIA | CEE'D | C | Lower Medium | - | Yes |
| KIA | EV3 | H | Dual Purpose | Yes | - |
| KIA | EV6 | C | Lower Medium | Yes | - |
| KIA | EV9 | H | Dual Purpose | 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 |
| LAMBORGHINI | REVUELTO | G | Specialist Sports | - | 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 | RX | H | Dual Purpose | - | Yes |
| LEXUS | RZ | H | Dual Purpose | Yes | - |
| LEXUS | UX | H | Dual Purpose | Yes | - |
| LOTUS | ELETRE | H | Dual Purpose | Yes | - |
| MAHINDRA | E20PLUS | C | Lower Medium | Yes | - |
| MASERATI | FOLGORE | G | Specialist Sports | Yes | - |
| MAXUS | MIFA | I | Multi-Purpose Vehicle | Yes | - |
| MAZDA | 3 | C | Lower Medium | Yes | - |
| MAZDA | 5 | I | Multi-Purpose Vehicle | Yes | - |
| MAZDA | CX-60 | H | Dual Purpose | - | Yes |
| MAZDA | CX-80 | H | Dual Purpose | - | Yes |
| MAZDA | MX30 | C | Lower Medium | Yes | Yes |
| MCLAREN | ARTURA | G | Specialist Sports | - | Yes |
| MCLAREN | P1 | G | Specialist Sports | - | Yes |
| MCLAREN | SPEEDTAIL | G | Specialist Sports | - | Yes |
| MERCEDED BENZ | A CLASS | B | Supermini | Yes | - |
| MERCEDED BENZ | A CLASS (2012) | C | Lower Medium | - | Yes |
| MERCEDED BENZ | B CLASS | C | Lower Medium | Yes | Yes |
| MERCEDED BENZ | C CLASS | D | Upper Medium | - | Yes |
| MERCEDED BENZ | CLA | D | Upper Medium | - | Yes |
| MERCEDED BENZ | CL | E | Executive | - | Yes |
| MERCEDED BENZ | E CLASS | E | Executive | - | Yes |
| MERCEDED BENZ | EQA | C | Lower Medium | Yes | - |
| MERCEDED EQB | EQB | H | Dual Purpose | Yes | - |
| MERCEDED EQC | EQC | H | Dual Purpose | Yes | - |
| MERCEDED EQE | EQE | E | Executive | Yes | - |
| MERCEDED BENZ | EQS | F | Luxury Saloon | Yes | - |
| MERCEDED BENZ | EQV | I | Multi-Purpose Vehicle | Yes | - |
| MERCEDED BENZ | EVITO | I | Multi-Purpose Vehicle | Yes | - |
| MERCEDED 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 |
| MERCEDES BENZ | SPRINTER | V | Van | Yes | - |
| MG | CYBERSTER | G | Specialist Sports | 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 | ACEMAN | C | Lower Medium | Yes | - |
| MINI | COOPER | B | Supermini | Yes | - |
| MINI | COUNTRYMAN | C | Lower Medium | Yes | 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 | - |
| OMODA | E5 | H | Dual Purpose | Yes | - |
| OPEL | AMPERA | D | Upper Medium | - | Yes |
| OPEL | ASTRA | C | Lower Medium | Yes | 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 | Yes |
| OPEL | MOKKA | C | Lower Medium | Yes | - |
| OPEL | VIVARO | V | Van | Yes | - |
| ORA | 03 | B | Supermini | Yes | - |
| ORA | 07 | C | Lower Medium | Yes | Yes |
| ORA | FUNKY CAT | C | Lower Medium | Yes | - |
| PEUGEOT | 208 | B | Supermini | Yes | - |
| PEUGEOT | 308 | C | Lower Medium | Yes | Yes |
| PEUGEOT | 408 | H | Dual Purpose | - | Yes |
| PEUGEOT | 508 | D | Upper Medium | - | Yes |
| PEUGEOT | 2008 | C | Lower Medium | Yes | - |
| PEUGEOT | 3008 | H | Dual Purpose | Yes | Yes |
| PEUGEOT | 5008 | I | Multi-Purpose Vehicle | 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 | Yes |
| PORSCHE | MACAN | 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 | RAFALE | H | Dual Purpose | - | Yes |
| RENAULT | SCENIC | I | Multi-Purpose Vehicle | Yes | - |
| RENAULT | TWIZY | A | Mini | Yes | - |
| RENAULT | CAPTUR | H | Dual Purpose | - | Yes |
| RENAULT | TWINGO | A | Mini | Yes | - |
| RENAULT | ZOE | C | Lower Medium | Yes | - |
| ROLLS ROYCE | SPECTRE | F | Luxury Saloon | Yes | - |
| SEAT | FORMENTOR | H | Dual Purpose | - | Yes |
| SEAT | LEON | C | Lower Medium | - | Yes |
| SEAT | MII | A | Mini | Yes | - |
| SKYWELL | BE11 | H | Dual Purpose | Yes | - |
| SKODA | CITIGO | A | Mini | Yes | - |
| SKODA | ENYAQ | H | Dual Purpose | Yes | - |
| SKODA | KODIAQ | 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 | - |
| SMART | SMART #1 | C | Lower Medium | Yes | - |
| SMART | SMART #3 | H | Dual Purpose | 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 | C-HR | C | Lower Medium | - | Yes |
| TOYOTA | PRIUS | C | Lower Medium | - | Yes |
| TOYOTA | RAV4 | H | Dual Purpose | - | Yes |
| TOYOTA | YARIS | B | Supermini | Yes | - |
| TOYOTA | PROACE | V | Van | 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 | 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 | ID7 | E | Executive | Yes | - |
| VOLKSWAGEN | PASSAT | D | Upper Medium | - | Yes |
| VOLKSWAGEN | TIGUAN | H | Dual Purpose | - | Yes |
| VOLKSWAGEN | TOUAREG | H | Dual Purpose | - | Yes |
| VOLKSWAGEN | T-ROC | C | Lower Medium | Yes | - |
| VOLKSWAGEN | UP | A | Mini | Yes | - |
| VOLVO | C40 | C | Lower Medium | Yes | - |
| VOLVO | EX30 | C | Lower Medium | Yes | - |
| VOLVO | EX90 | H | Dual Purpose | 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 |
| VOLVO | XC60 | H | Dual Purpose | - | Yes |
| VOLVO | XC90 | H | Dual Purpose | - | Yes |
| XPENG | G6 | H | Dual Purpose | Yes | - |

Notes: Only includes models with registrations in the UK fleet up to the end of 2024 (DfT, 2025).

5.29. During the derivation of the conversion factors, some discrepancies were found in
the EEA CO2 monitoring databases for the gCO2
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). The data are
then summarised by vehicle type and year. Any remaining gaps (i.e. missing
values for specific years) are filled, either by taking the average of the two
adjacent years, or if the gap occurs at the end of a time series, using the prior
year’s value. The annual averages are then used in conjunction with vehicle
registration numbers to generate a weighted average gCO2
for each vehicle category.

During the derivation of the conversion factors, some discrepancies were found in
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). The data are
then summarised by vehicle type and year. Any remaining gaps (i.e. missing
values for specific years) are filled, either by taking the average of the two
adjacent years, or if the gap occurs at the end of a time series, using the prior
year’s value. The annual averages are then used in conjunction with vehicle
registration numbers to generate a weighted average gCO2/km and Wh/km factor adjusted ‘Real-World’ energy consumption and emission factors. These
assumptions were discussed and agreed with DfT.

5.31. 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 have been calculated
based on WLTP testing regime using real-world uplift factors for WLTP vehicles.

5.32. 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 2025 Conversion Factors
update, to better reflect the actual share of electric km in real-world. Table 19
summarises (i) the assumption of the real-world average percentage share of total
km running on electricity (battery mode) and fuel combustion mode, and (ii) the
CO2 emissions per kilometre for PHEV cars, accounting for both the real-world
percentage share of electric (battery mode) and fuel combustion mode kilometres.

5.33. The key assumptions used in the calculation of adjusted Real-World gCO2/km and
Wh/km figures are summarised in Table 20. 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 17: PHEV Cars Real-World average percentage share of Electric and Combustion
Mode kilometres, and CO2 Emissions per kilometre, based on 2024 UK fuel, electricity, and
PHEV car fleet data, per market segment

\\mathbf{c o}}}\_{2}

| PHEV Cars by Market segment | Power-train Type | % of Real-World Electric (Battery Mode)km | % of Real-World Fuel Combustion Modekm | CO2 Emissions from Battery Mode(kgCO2/km) | CO2 Emissions from Fuel Combustion Mode(kgCO2/km) |
| --- | --- | --- | --- | --- | --- |
| Mini | PHEV | 29% | 71% | - | - |
| Supermini | PHEV | 29% | 71% | 0.02 | 0.03 |
| Lower Medium | PHEV | 29% | 71% | 0.01 | 0.07 |
| Upper Medium | PHEV | 29% | 71% | 0.01 | 0.08 |
| Executive | PHEV | 22% | 78% | 0.01 | 0.08 |
| Luxury Saloon | PHEV | 22% | 78% | 0.01 | 0.11 |
| Specialist Sports | PHEV | 22% | 78% | 0.01 | 0.15 |
| Dual Purpose | PHEV | 34% | 66% | 0.01 | 0.10 |
| Multi-Purpose Vehicle | PHEV | 34% | 66% | 0.01 | 0.08 |

* * *

Table 18: 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 2024 cars and vans: |  |  |
| • UK DfT's vehicle licensing statistics data fileVEH\_0270(DfT,2025) | This data is used in conjunction withCO2/kmandWh/kmdata 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 ofkm driven in charge-sustaining mode/average liquid fuel consumption perkm. |  |  |
| Wh electricity consumption per km(test-cycle) | As for CO2 emissions | Average electricity consumption per averagekm(i.e.factoring inforPHEVs that only a fraction oftotalkmwill be in electricmode). |
| Test-Cycle to Real-World conversion forgCO2/km | Assumption based on literature,consistent with the source used forthe car EFs for conventional powertrains. | ForNEDC: |
| • An upliftof35%is applied tothe test-cycle emission component |  |  |
| ForWLTP: |  |  |
| • An upliftof23.7%is applied tothe test-cycle emission component |  |  |

\\begin array}{r}{\\operatorname{\ }}{{mathrmmathrm{E E A b}}\_{\ \ \\mathrm{a}t t a\ a a s e}}\\end{array}

\ \\mathrm C O\_{2}

* * *

| 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 $ ^{18}$ | Uses Real-World electric range in km |

18
[https://www.legislation.gov.uk/eur/2017/1151/contents](https://www.legislation.gov.uk/eur/2017/1151/contents)

* * *

| 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 generatedElectricity T&DWTT electricity generatedWTT 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 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 5 below.

\\mathrm{{C O}\_{2}}

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

5.34. For the 2026 GHG Conversion Factors, the market classification split (according
to SMMT classifications) was derived using detailed SMMT data on new car
registrations between 2006 and 2025 split by fuel (Table 21) 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.

5.35. 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).

N\\mathrm{{}}\_{2}O,,

5.36. The supplementary market segment based conversion factors for passenger cars
are presented in the ‘Passenger vehicles’ and ‘Business travel- land’ worksheets
of the 2026 GHG Conversion Factors set.

Table 19: Average car CO2 conversion factors and total registrations by market segment
for 2009 to 2025 (based on data sourced from SMMT)

\\mathbf{c o}}}\_{\\mathbf{2}}

| Fuel Type | Market Segment | Example Model | NEDC\*gCO2perkm | WLTPgCO2perkm | Registrations | % Total |
| --- | --- | --- | --- | --- | --- | --- |
| Diesel | A. Mini | Smart Fortwo | 89.3 | N/A | 7,315 | 0.1% |
| B. Super Mini | VW Polo | 103.4 | 120.5 | 1,289,204 | 10.54% |  |
| C. Lower Medium | Ford Focus | 110.6 | 130.7 | 3,385,453 | 27.69% |  |
| D. Upper Medium | Toyota Avensis | 124.2 | 146.8 | 2,072,849 | 16.95% |  |
| E. Executive | BMW 5-Series | 129.9 | 153.6 | 1,068,581 | 8.74% |  |
| F. Luxury Saloon | Bentley Continental GT | 157.0 | 175.0 | 61,506 | 0.50% |  |
| G. Specialist Sports | Mercedes CLS | 133.7 | 180.6 | 109,601 | 0.90% |  |
| H. Dual Purpose | Land Rover Discovery | 150.1 | 180.7 | 3,219,855 | 26.33% |  |
| I. Multi-Purpose | Renault Espace | 135.8 | 174.2 | 1,014,064 | 8.29% |  |
| All | Total | 126.8 | 164.1 | 12,228,428 | 100% |  |
| Petrol | A. Mini | Smart Fortwo | 106.9 | 122.4 | 769,793 | 3.99% |
| B. Super Mini | VW Polo | 117.4 | 127.6 | 9,658,141 | 50.11% |  |
| C. Lower Medium | Ford Focus | 133.7 | 141.7 | 5,155,509 | 26.75% |  |
|  | D. Upper Medium | Toyota Avensis | 156.6 | 162.8 | 723,510 | 3.75% |
| E. Executive | BMW 5-Series | 161.4 | 187.2 | 255,236 | 1.32% |  |
| F. Luxury Saloon | Bentley Continental GT | 249.7 | 275.8 | 40,122 | 0.21% |  |
| G. Specialist Sports | Mercedes CLS | 188.8 | 218.3 | 442,532 | 2.30% |  |
| H. Dual Purpose | Land Rover Discovery | 152.9 | 173.3 | 1,815,159 | 9.42% |  |
| I. Multi-Purpose | Renault Espace | 150.0 | 149.4 | 413,355 | 2.14% |  |
| All | Total | 128.6 | 143.9 | 19,273,357 | 100% |  |
| Unknown Fuel(Diesel+Petrol) | A. Mini | Smart Fortwo | 106.6 | 122.4 | 777,108 | 2.47% |
| B. Super Mini | VW Polo | 115.2 | 127.6 | 10,947,345 | 34.75% |  |
| C. Lower Medium | Ford Focus | 122.3 | 140.6 | 8,540,962 | 27.11% |  |
| D. Upper Medium | Toyota Avensis | 131.0 | 156.3 | 2,796,359 | 8.88% |  |
| E. Executive | BMW 5-Series | 136.2 | 167.1 | 1,323,817 | 4.20% |  |
| F. Luxury Saloon | Bentley Continental GT | 193.5 | 229.5 | 101,628 | 0.32% |  |
| G. Specialist Sports | Mercedes CLS | 176.9 | 217.4 | 552,133 | 1.75% |  |
| H. Dual Purpose | Land Rover Discovery | 151.7 | 176.5 | 5,035,014 | 15.98% |  |
| I. Multi-Purpose | Renault Espace | 140.0 | 167.9 | 1,427,419 | 4.53% |  |
| All | Total | 127.7 | 147.6 | 31,501,785 | 100% |  |

\*For 2019 and 2018, NEDCe (NEDC equivalent) 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 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

5.37. The conversion factors for black cabs are based on data provided by Transport for
19
London (TfL) 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).

5.38. 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).

\\mathrm{{c O}\_{2}}

5.39. Conversion factors per passenger km for taxis and black cabs are presented in
the ‘Business travel- land’ worksheet of the 2026 GHG Conversion Factors set.
The base conversion factors per vehicle km are also presented in the ‘Business
travel- land’ worksheet of the 2026 GHG Conversion Factors set.

5.40. 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 2026 GHG
Conversion Factors set.

N\_{2}O\\mathrm

5.41. 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)

Direct Emissions from Vans/Light Goods Vehicles (LGVs)

5.43. 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 2024. The
factors for each class are then calculated relative to the average from quantitative
analysis of regulatory data across the years 2012-2024. 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

\\mathrm{{C O\_{2}}}

5.42. Average conversion factors by fuel, for vans/light good vehicles (LGVs: N1
vehicles, vans up to 3.5 tonnes gross vehicle weight - GVW) and by size (Class I,
II or III) are presented in Table 22 and in the “Delivery vehicles” worksheet of the
2026 GHG Conversion Factors set.

19
The data was provided by TfL in a personal communication and is not available in a public TfL source.

* * *

by the EEA for UK vehicles, so an alternative approach was developed. Up until
the 2023 GHG Conversion Factors publication, the regulatory data was derived
from new LGV registrations from the UK DfT table VEH0160\_GB (DfT and DVLA,
2024) matched with reference weight and emissions data from the EEA database.
Responsibility for the publication of the UK vehicle regulatory data subsequently
transferred from the EEA to the UK Vehicle Certification Agency (VCA). Therefore,
vehicle registration statistics from DfT table VEH0160\_GB (DfT and DVLA, 2024)
(used in the 2025 GHG Conversion Factors publication and rolled forward to
2026) are 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.

5.44. 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 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. This dataset is also the
basis of the average van loading capacity calculations (see later section on van
freight emission factors). 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 5.21). The average van
conversion factor is calculated based on the relative UK GHGI vehicle km for
petrol and diesel vans for 2024, as presented in Table 22.

\\mathrm{{C O\_{2}}}

{\\mathrm{c O}}\_{2}

{\\mathrm{c O}}\_{2}

\\mathrm{C H}\_{4}

5.45. Conversion factors for CH4 and N2O are based on the conversion factors from the
UK GHG Inventory 2019 (Ricardo Energy & Environment, 2021) and updated to
align with AR5 GWP values.

N\_{2}O

&

5.46. As a final additional step, an accounting for biofuel use has been included in the
calculation of the final vans/LGVs emission factors.

* * *

Table 20: New conversion factors for vans for the 2026 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 | 162.5 | 0.2 | 0.5 | 163.3 | 29.5% | 0.38 |
| Petrol(Class II) | 1.305 to 1.740 tonne | 168.1 | 0.2 | 0.5 | 168.8 | 65.4% | 0.70 |
| Petrol(Class III) | Over 1.740 tonne | 272.9 | 0.2 | 0.5 | 273.6 | 5.1% | 0.98 |
| Petrol(average) | Up to 3.5 tonne | 171.8 | 0.2 | 0.5 | 172.5 | 100.0% | 0.62 |
| Diesel(Class I) | Up to 1.305 tonne | 68.1 | 0.0 | 1.9 | 70.0 | 2.4% | 0.49 |
| Diesel(Class II) | 1.305 to 1.740 tonne | 83.5 | 0.0 | 1.9 | 85.4 | 23.5% | 0.84 |
| Diesel(Class III) | Over 1.740 tonne | 121.3 | 0.0 | 1.9 | 123.1 | 74.1% | 1.08 |
| Diesel(average) | Up to 3.5 tonne | 111.1 | 0.0 | 1.9 | 113.0 | 100.0% | 1.01 |
| LPG | Up to 3.5 tonne | 120.0 | 0.0 | 0.6 | 120.6 | 100.0% | 1.00 |
| CNG | Up to 3.5 tonne | 108.6 | 1.2 | 0.6 | 110.3 | 100.0% | 1.00 |
| Average |  | 112.4 | 0.0 | 1.8 | 114.3 | 100.0% | 1.00 |

Plug-in Hybrid Electric and Battery Electric Vans (xEVs)
5.47. As outlined earlier for cars, since the number of electric cars and vans (xEVs20

5.48. 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.

20
xEVs is a generic term used to refer collectively to battery electric vehicles (BEVs), plug-in hybrid electric vehicles
(PHEVs), range-extended electric vehicles (REEVs, or ER-EVs, or REX) and fuel cell electric vehicles (FCEVs).

* * *

| 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 | EC31 | Class II | Yes | - |
| DFSK | EC35 | Class II | Yes | - |
| ETESIA | ET LANDER | Class I | 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 | - |
| MAXUS | T90 EV | Class III | Yes | - |
| MERCEDES | VITO | Class III | Yes | - |
| MERCEDES | ESPRINTER | Class III | Yes | - |
| MERCEDES | ECITAN | Class II | Yes | - |
| MERCEDES | EVITO | Class III | Yes | - |
| MIA | MIA | Class I | Yes | - |
| NISSAN | E-NV200 | Class II | Yes | - |
| NISSAN | TOWNSTAR | 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 | - |
| VOL KSWAGEN | 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 2024

5.50. All other methodological details are as already outlined for xEV passenger cars.

Direct Emissions from Buses

5.51. 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 factors21.

{\\mathrm C O}\_{2}

5.52. 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.
The conversion factors for buses account for additional direct CO2 emissions from

5.53. 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 24. These are based on assumptions in the
EMEP/EEA Emissions Inventory Guidebook (EEA, 2019).

\ \\mathrm c O\_{2}

\ \\mathrm{N O}\_{\\times}

* * *

Table 22: Key assumptions used in the calculation of CO2 emissions from Urea (aka
‘AdBlue’) use

\\mathbf{c o}}}\_{2}

|  | CO2EF for urea consumption(kgCO2/kg urea solution)\* | 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% |

Notes: \* Assumes 32.5% (by mass) aqueous solution of urea

5.54. Briefly, the main calculation for local buses can be summarised as follows:

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

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

5.55. As a final additional step, biofuel use is accounted for in the final bus emission
factors.

5.56. Conversion factors for coach services are based on information supplied by
National Express, who provide the majority of scheduled coach services in the UK.
At the time that the 2026 UK GHG Conversion Factors publication was compiled,
the most recently available data from National Express were from 2024. National
Express provided information on their total emissions and the number of
passenger km travelled, which were divided to obtain kg CO2e/pkm values.

\\mathrm{C H}\_{4}

N\\mathrm{{}}\_{2}O,,{\

5.57. 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 25.

5.58. Table 25 gives a summary of the 2026 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 23: Conversion factors for buses for the 2026 GHG Conversion Factors

| Bus type | Average passenger occupancy | kgCO2e per passenger km |  |  |  |
| --- | --- | --- | --- | --- | --- |
| Total | CO2 | CH4 | N2O |  |  |
| Local bus(not London) | 11.57 | 0.12552 | 0.12462 | 0.00002 | 0.00088 |
| Local London bus | 18.92 | 0.06360 | 0.06312 | 0.00001 | 0.00047 |
| Average local bus | 13.62 | 0.10151 | 0.10077 | 0.00001 | 0.00073 |
| Coach | 18\* | 0.03948 | 0.03899 | 0.00001 | 0.00048 |

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”.

- Estimated based on data received from a major coach operator. This information is not used in the derivation of the
  coach factors and is provided for information only.

Direct Emissions from Motorcycles

5.59. Motorcycles factors remain constant since the publication of 2021 GHG
Conversion Factors but were updated to align with AR5 instead of AR4 GWP
values in the 2023 update.

5.60. 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

b) Medium motorbikes (125-500cc); and
c) Large motorbikes (over 500cc).

5.62. The conversion factors are calculated based on a large dataset kindly provided by
22
(Clear, 2008), based on a mix of magazine road test reports and user reported
data. A summary is presented in Table 26, with the corresponding complete
conversion factors developed for motorcycles presented in the ‘Passenger
vehicles’ worksheet of the 2026 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).

c) Large motorbikes (over 500cc).

22
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.

* * *

previously used to uplift cars and vans test cycle data to real-world equivalents
(+15%).

5.64. 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

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 2026 GHG Conversion
Factors set.

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 2026 GHG Conversion

Table 24: Summary dataset on CO2 emissions from motorcycles based on detailed data
provided by Clear (2008)

\\mathbf{c o}}}\_{\\mathbf{2}

| 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 |
| 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

5.65. Conversion factors for passenger rail services have been updated and provided in
the “Business travel – land” worksheet of the 2026 GHG Conversion Factors set.
These include updates to the national rail, international rail (Eurostar), light rail
schemes and the London Underground. Conversion factors for CH4 and N2O
emissions were not updated in the 2026 update.

International Rail (Eurostar)

5.66. The international rail factor is based on passenger-km normalised CO2 e
emissions data which is obtained from the Office of Rail and Road (ORR) data
portal (ORR, 2025). This has been calculated based on total electricity consumed
on the UK side only, sourced from Eurostar by ORR. The CO2e is calculated using
conversion factors for the UK electricity grid.

5.67. CH4 and N2O conversion factors remain constant since the publication of 2021
GHG Conversion factors, but were updated to align with AR5 GWP values in
2025\. 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

5.68. The national rail factor refers to an average emission per passenger kilometre for
diesel and electric trains in 2024-25. The factor is sourced from information from
the ORR data portal (ORR, 2025). This has been calculated based on total
electricity and diesel consumed by the railway for the year sourced from
passenger operators and the total number of passenger kilometres (from the rail
industry’s central ticketing and revenue system, LENNON).

{\\mathrm N{}\_}{{2}}{\\mathrm{O}}

5.70. 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 27.

{\\mathrm{c O}}\_{2}

5.72. The factors for Glasgow Subway, Midland Metro, Tyne and Wear Metro,
Manchester Metrolink and Sheffield Supertram were calculated based on annual

{\\bf C O}\_{2} passenger km data from DfT’s Light rail and tram statistics (DfT, 2025) and the
new 2026 grid electricity CO2 emission factor.

5.73. 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 27).

5.74. CH4 and N2O conversion factors remain constant since the publication of 2021
GHG Conversion Factors but were updated to align with AR5 GWP values in
2025\. These factors in the 2021 GHG Conversion Factors were estimated from
the corresponding emissions factors for electricity generation, proportional to the
CO2 emission factors.

N{}\_{2}O{

Table 25: 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 | 0.118 | 19.32 | 0.13 | 0.21 | 19.66 | 476.10 |
| Glasgow Subway | Light Rail | 0.164 | 26.83 | 0.18 | 0.29 | 27.30 | 25.70 |
| Midland Metro | Light Rail | 0.135 | 22.09 | 0.15 | 0.24 | 22.48 | 94.60 |
| Tyne and Wear Metro | Light Rail | 0.233 | 38.03 | 0.25 | 0.42 | 38.70 | 295.80 |
| London Overground | Light Rail | 0.146 | 24.03 | 0.16 | 0.26 | 24.45 | 1,248.00 |
| London Tramlink | Tram | 0.146 | 23.87 | 0.16 | 0.26 | 24.29 | 92.00 |
| Manchester Metrolink | Tram | 0.078 | 12.81 | 0.09 | 0.14 | 13.03 | 334.90 |
| Supertram | Tram | 0.350 | 57.15 | 0.38 | 0.63 | 58.16 | 58.90 |
| Average\* | - | 0.147 | 24.02 | 0.16 | 0.26 | 24.44 | 2,626 |

London Underground

5.75. The factors for London Underground were also calculated based on annual
passenger km data from DfT’s Light rail and tram statistics (DfT, 2025) and the
new UK grid electricity CO2 emission factor.

* * *

Indirect/WTT Emissions from Passenger Land Transport
Cars, Vans, Motorcycles, Taxis, Buses and Ferries

5.77. 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 2026 GHG Conversion Factors set.

{\\bf C O}\_{2}

{\\mathrm{C O}}\_{2}

Rail

5.78. Rail passenger indirect/WTT conversion factors have not been updated in this
publication and the 2025 conversion factors are used.

5.79. In 2025 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}

\\mathrm{C O\_{2}(

5.80. 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 are relevant both for 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 28 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. Note that as of 2026, the Condensed set is no longer
published; however, this table has been retained here so that users can find
values from previous publication years.

Table 26 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 |

Summary of changes since the previous update

6.4. The HGV factors are based on road freight statistics from the Department for
Transport (DfT, 2024a) for Great Britain (GB), from a survey on different sizes of
rigid and articulated HGVs in the fleet in 2022. The 2024 figures were the most
recent ones available at the time of the 2026 UK GHG Conversion Factors being
compiled. The statistics on fuel consumption figures (in miles per gallon) were
estimated by DfT from the survey data.

Direct Emissions from Heavy Goods Vehicles (HGVs)

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
2026 GHG Conversion Factors. Table RFS0125 (DfT, 2024a) shows the percent

{\\mathfrak{g C}}{\\mathrm{O}}\_{2} loading factors are on average between c. 35-80% 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 29
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 halfload (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{{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

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).

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 27: Change in CO2 emissions caused by +/- 50% change in load from the average
loading factor of 50%

\\mathbf{c o}}}\_{\\mathbf{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

6.8. The loading factors in Table 29 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} 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
indicated in “Delivery vehicles” and “Freighting goods” worksheets of the 2026
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}

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 2026 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).

6.11. At a more aggregated level, factors for all HGVs are still representing the average
MPG for all rigid and articulated HGV classes in Table RFS0141 (DfT, 2017). This
factor should be used if the user has no knowledge of or requirement for different
classes of HGVs and may be suitable for analysis of HGV CO2 emissions in, for
example, inter-modal freight transport comparisons.

{\\mathrm C O}\_{2}

6.12. The conversion factors included in the “Delivery vehicles” worksheet of the 2026
UK 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.

6.13. For comparison with other freight transport modes (e.g. road vs. rail), the user
may require CO2 factors in tonne km (tkm) units. The “Freighting goods”
worksheet of the 2026 UK GHG Conversion Factors set also provides such factors
for 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, 2024a). Dividing the tkm by the vkm figures gives the average
tonnes of freight lifted by each HGV class. The 2026 UK GHG Conversion Factors
include factors in tonne km (tkm) for all loads (0%, 50%, 100% and average).

{\\mathrm{c O}}\_{2} 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 2026 GHG Conversion Factors for the relevant HGV class.

\ \\mathrm c O\_{2}

6.15. Conversion factors for CH4 and N2O for all HGV classes remain constant since the
publication 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
emissions are assumed to scale relative to vehicle class/CO2
These factors are presented with an overall total factor in the “Delivery vehicles”
and “Freighting goods” worksheets of the 2026 GHG Conversion Factors set.

O for all HGV classes remain constant since the
publication 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 2026 GHG Conversion Factors set.

and “Freighting goods” worksheets of the 2026 GHG Conversion Factors set.

N\_{2}O\\mathrm

N\\mathrm{{}}}\_{2}\\mathrm{{}O}

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}\_{\\times}

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 30. 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 2023 are obtained from the DfT table VEH0160\_GB (DfT and
DVLA, 2024), 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}

Table 28: Typical van freight capacities and estimated average payload

{\\bf C O}\_{2}

| Van fuel | Van size,Gross Vehicle Weight | Vkm% split | Av. Payload Capacity,tonnes | Av. Payload,tonnes |
| --- | --- | --- | --- | --- |
| Petrol(Class I) | Up to 1.305 tonne | 29.47% | 0.38 | 0.14 |
| Petrol(Class II) | 1.305 to 1.740 tonne | 65.41% | 0.70 | 0.26 |
| Petrol(Class III) | Over 1.740 tonne | 5.11% | 0.98 | 0.40 |
| Petrol(average) | Up to 3.5 tonne | 100.00% | 0.62 | 0.25 |
| Diesel(Class I) | Up to 1.305 tonne | 2.43% | 0.49 | 0.18 |
| Diesel(Class II) | 1.305 to 1.740 tonne | 23.46% | 0.84 | 0.31 |
| Diesel(Class III) | Over 1.740 tonne | 74.11% | 1.08 | 0.44 |
| Diesel(average) | Up to3.5tonne | 100.00% | 1.01 | 0.40 |
| LPG(average) | Up to3.5tonne | 100.00% | 1.00 | 0.40 |
| CNG(average) | Up to3.5tonne | 100.00% | 1.00 | 0.40 |
| Average | Up to3.5tonne | 100.00% | 1.00 | 0.40 |

6.19. The average load factors assumed for different vehicle types used to calculate the
average payloads in Table 30are summarised inTable 31, 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 202update. 6

Table 29: Utilisation of vehicle capacity by company-owned LGVs: annual average 2003 –
2005 (proportion of total vehicle kilometres travelled)

| 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% |

6.21. 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 30and the conversion factors per vehicle km in the -
“Delivery vehicles” and “Freighting goods” worksheets of the 2026 GHG
Conversion Factors set.

\\mathrm{C H}\_{4}

N\\mathrm{}O\_}\ \

* * *

Direct Emissions from Rail Freight

6.22. The data used to update the rail freight conversion factors for the 2026 GHG
Conversion Factors set is sourced from the ORR data portal (ORR, 2025). This
factor is presented in “Freighting goods” worksheet of the 2026 GHG Conversion
Factors set.

6.23. 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 98% of the total CO2 from rail freight for 2024-25 (ORR, 2025).

6.24. 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.

6.25. CH4 and N2O conversion factors remain constant since the publication of 2021
GHG Conversion Factors but were updated to align with AR5 GWP values in
2025\. These 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.

Indirect/WTT Emissions from Freight Land Transport

Vans and HGVs

Rail

6.27. Indirect/WTT rail freight conversion factors remain constant since the publication
of 2021 GHG Conversion Factors, but were updated from AR4 to AR5 GWP
values in 2025.

6.28. For 2021 the conversion factors for freight rail services were 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).

* * *

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 publication of 2021 GHG
Conversion Factors but were updated from AR4 to AR5 GWP values in the 2023
update.

7.3. Table 32 shows where the related worksheets to the sea transport conversion
factors are available in the online spreadsheets of the UK GHG Conversion
Factors set. Note that as of 2026, the Condensed set is no longer published;
however, this table has been retained here so that users can find values from
previous publication years.

Table 30: 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 2026 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 utilised for the 2026 GHG
Conversion Factors set.

* * *

7.6. The BFF study analysed data for mixed passenger and vehicle ferries (RoPax
ferries) on UK routes supplied by PSA members. Data provided by the PSA
operators included information by operating route on the route/total distance, total
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}

| 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)^{23}$ |
| 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”

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 2026 GHG Conversion Factors set. A further split has been
provided between foot-only passengers and passengers with cars, 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.

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 2026 GHG Conversion Factors set. A further split has been
provided between foot-only passengers and passengers with cars, 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}}

\\mathrm{C{O\_{2}}}

7.9. CO2 emissions are allocated to freight based on the weight of freight (including
freight vehicles/containers) relative to the total weight of passengers + luggage +
cars. For the data supplied by the 11 (out of 17) PSA operators, this equated to
just over 88% of the total emissions of the ferry operations. The emission factor for
freight was calculated from this figure and the total number of tonne km (excluding
the weight of the freight vehicle/container) and is presented in the “Freighting
goods” worksheet of the 2026 GHG Conversion Factors set.

23
This is based on a survey of actual freight weights at 6 ferry ports. Where operator-specific freight weights were
available, these were used instead of the average figure.

* * *

BFF (2007) work and at the time that the conversion factors for ferries were
developed, a suitable dataset had not been identified.

7.11. CH4 and N2O conversion factors remain constant since the publication 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 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 2026 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}}}

7.13. CH4 and N2O conversion factors remain constant since the publication 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 O

{\\bf C O}\_{2}

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# 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 CO2 and CO2e conversion factors were updated in the 2025 GHG Conversion Factors publication. CH4, N2O, and WTT Air transport factors have been constant since the publication of 2023 GHG Conversion Factors (aligned with AR5 GWPs values).
8.3. Table 34 shows where the related worksheets to the air transport conversion factors are available in the online spreadsheets of the UK GHG Conversion Factors set. Note that as of 2026, the Condensed set is no longer published; however, this table has been retained here so that users can find values from previous publication years.
**Table 32: 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

8.4. There were no major methodological changes in the 2026 update.

## Passenger Air Transport Direct CO2 Emission Factors

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.

* * *

8.6. The 2026 update of the average factors (presented at the end of this section) uses
the EUROCONTROL small emitters tool to calculate the CO2 emissions factors
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 35. 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;

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 33: Assumptions used in the calculation of revised average CO2 conversion factors
for passenger flights for 2025

|  | Av. No. Seats | Av. Load Factor | Proportion of passenger km | Emissions Factor, kgCO2/vkm | Av. flight length,km |
| --- | --- | --- | --- | --- | --- |
| Domestic Flights |  |  |  |  |  |
| AIRBUS A320neo | 184 | 75% | 13% | 13.3 | 453 |
| AIRBUS A321neo | 222 | 73% | 2% | 14.8 | 482 |
| AIRBUS A319 | 153 | 79% | 29% | 15.0 | 485 |
| AIRBUS A320-100/200 | 182 | 75% | 33% | 16.4 | 460 |
| AIRBUS A321 | 217 | 72% | 1% | 18.0 | 468 |
| ATR-42-500 | 49 | 58% | 1% | 5.2 | 369 |
| ATR72 200/500/600 | 71 | 67% | 6% | 5.6 | 310 |
| BOEING 737 MAX8 | 197 | 85% | 0% | 12.6 | 489 |
| BOEING 737-800 | 189 | 78% | 5% | 15.3 | 432 |
| BOMBARDIER DASH 8 Q400 | 78 | 45% | 0% | 7.3 | 370 |
| EMBRAER ERJ145 | 49 | 67% | 4% | 7.4 | 488 |
| EMBRAER ERJ190 | 98 | 74% | 5% | 11.6 | 547 |
| EMBRAER ERJ195 | 122 | 75% | 0% | 15.5 | 274 |
| SAAB FAIRCHILD 340 | 35 | 66% | 0% | 4.4 | 241 |
| Average | 157 | 75% | 100%\* (total) | 12.2 | 434 |

| Short-haul Flights |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- |
| AIRBUS A320neo | 183 | 79% | 10% | 9.2 | 1540 |
| AIRBUS A321neo | 226 | 82% | 9% | 10.3 | 1986 |
| AIRBUS A319 | 152 | 83% | 6% | 11.5 | 1076 |
| AIRBUS A320-100/200 | 182 | 81% | 20% | 11.6 | 1379 |
| AIRBUS A321 | 221 | 82% | 5% | 13.0 | 1692 |
| AIRBUS A330-200 | 323 | 93% | 0% | 21.9 | 2425 |
| AIRBUS A330-300 | 312 | 78% | 1% | 22.7 | 2218 |
| AIRBUS A350-900 | 326 | 75% | 0% | 22.9 | 1674 |
| ATR72 200/500/600 | 72 | 76% | 0% | 5.5 | 329 |
| BOEING 737 MAX 8 | 199 | 85% | 10% | 9.3 | 1692 |
| BOEING 737-300 | 148 | 89% | 0% | 11.6 | 1562 |
| BOEING 737-800 | 189 | 86% | 35% | 11.0 | 1645 |
| BOEING 757-200 | 235 | 90% | 1% | 14.3 | 2397 |
| BOEING 767-300ER/F | 328 | 90% | 0% | 19.5 | 2585 |
| BOEING 777-300ER | 358 | 77% | 0% | 29.6 | 2860 |
| BOEING 787-900 DREAMLINER | 323 | 76% | 0% | 20.0 | 2646 |
| AIRBUS A220-300 | 134 | 71% | 0% | 10.2 | 738 |
| AIRBUS A220-300 | 147 | 75% | 0% | 10.4 | 791 |
| EMBRAER ERJ190 | 100 | 73% | 1% | 10.5 | 758 |
| Average | 193 | 83% | 100%\* (total) | 11.0 | 1,484 |

| Long-haul Flights |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- |
| AIRBUS A320neo | 184 | 77% | 0% | 8.6 | 3650 |
| AIRBUS A321neo | 170 | 79% | 1% | 10.0 | 4865 |
| AIRBUS A330-200 | 254 | 69% | 1% | 21.0 | 6464 |
| AIRBUS A330-300 | 285 | 75% | 4% | 22.1 | 6609 |
| AIRBUS A330-900 | 272 | 73% | 2% | 19.7 | 6852 |
| AIRBUS A350-900 | 299 | 82% | 4% | 21.4 | 8634 |
| AIRBUS A350-1000 | 344 | 83% | 8% | 24.2 | 7342 |
| AIRBUS A380-800 | 505 | 82% | 14% | 46.6 | 6701 |
| BOEING 737 MAX 8 | 184 | 90% | 0% | 8.9 | 4473 |
| BOEING 757-200 | 175 | 86% | 0% | 14.1 | 5455 |
| BOEING 767-300ER/F | 187 | 76% | 2% | 18.9 | 5704 |
| BOEING 767-400 | 246 | 78% | 1% | 20.7 | 6095 |
| BOEING 777-200 | 274 | 81% | 14% | 24.8 | 6718 |
| BOEING 777-300ER | 321 | 82% | 18% | 28.8 | 7178 |
| BOEING 787-800 DREAMLINER | 248 | 86% | 9% | 18.2 | 6758 |
| BOEING 787-900 DREAMLINER | 273 | 82% | 19% | 18.8 | 7228 |
| BOEING 787-1000 DREAMLINER | 286 | 79% | 2% | 21.1 | 5867 |
| Average | 316 | 81% | 100%\* (total) | 24.0 | 6,799 |

Notes: Figures on seats, load factors, % tkm and av. flight length have been calculated from 2023 CAA statistics for UK
registered airlines for the different aircraft types. Figures of kgCO2
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.

Figures on seats, load factors, % tkm and av. flight length have been calculated from 2023 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:

8.9. 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 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 36.

Table 34: Illustrative short- and long- haul flight distances from the UK

| Area | Destination Airport | Distance,km |
| --- | --- | --- |
| Domestic |  |  |
| Average(CAA statistics) |  | 434 |
| Short-haul |  |  |
| Europe | Amsterdam，Netherlands | 400 |
| 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) |  | 1,484 |
| 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 |
| East Asia | Hong Kong | 9,700 |
| Australasia | Sydney，Australia | 17,000 |
| Average(CAA statistics) |  | 6,799 |

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 2023

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 factors24.

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 longhaul cargo services (however this is not the case when comparing individual
flights).

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 longhaul cargo services (however this is not the case when comparing individual

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 for the ‘no weighting’ option and the selected
option (described as ‘Option 2’) presented in Table 37:

a. No Freight Weighting: Assume all the CO2 is allocated to passengers on these
services.

\ \\mathrm C O\_{2}

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

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. Note, this is the preferred methodology and
therefore the option selected for use in the calculations.

therefore the option selected for use in the calculations.
Table 35: CO2 conversion factors for alternative freight allocation options for passenger
flights

8.13. The basis of the freight weighting Option 2is 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

| Freight Weighting: | None |  | Option 2: Equivalent |  |
| --- | --- | --- | --- | --- |
| Mode | Passenger tkm% of total | gCO2/pkm | Passenger tkm% of total | gCO2/pkm |
| Domestic flights | 100.00% | 124.1 | 99.97% | 124.0 |
| Short-haul flights | 100.00% | 69.5 | 99.46% | 69.1 |
| Long-haul flights | 100.00% | 99.6 | 83.04% | 82.5 |

24
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.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

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 2025 update to the 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

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. The methodology for 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).
8.17. The final average conversion factors for aviation are presented in Table 38. The figures in Table 38 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 2026 GHG Conversion Factors set.
**Table 36: Final average CO2 conversion factors for passenger flights (excluding distance**

## and RF uplifts)

## Mode Av. Load gCO2 /pkm

**Factor%**

**Domestic flights** 74.9% 124.0

**Short-haul flights** 83.3% 69.1

**Long-haul flights** 81.3% 82.5

Notes: Average load factors based on data provided by DfT that contains detailed analysis of CAA statistics for the year 2023

## 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.

{\\mathrm C O}\_}

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 39, together with additional information obtained either directly from airline
websites or from other specialist websites that had already collated such

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 39, together with additional information obtained either directly from airline
websites or from other specialist websites that had already collated such

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 times25 the
space taken up by the basic economy seating. Table 39 shows the seating classbased 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 37: CO2 conversion factors by seating class for passenger flights (excluding
distance and RF uplifts)

| Flight type | Cabin Seating Class | Av. Load Factor % | gCO2/pkm | Number of economy seats | % of average gCO2/pkm | % Total seats |
| --- | --- | --- | --- | --- | --- | --- |
| Domestic | Weighted average | 74.9% | 124.0 | 1.00 | 100.0% | 100.0% |
| Short-haul | Weighted average | 83.3% | 69.1 | 1.02 | 100.0% | 100.0% |
|  | Economy class | 83.3% | 68.0 | 1.00 | 98.4% | 96.7% |
|  | First/Business class | 83.3% | 102.0 | 1.50 | 147.5% | 3.3% |
| Long-haul | Weighted average | 81.3% | 82.5 | 1.31 | 100.0% | 100.0% |

\\mathbf{c o}}}\_{\\mathbf{2}}

* * *

| Flight type | Cabin Seating Class | Av. Load Factor % | gCO2/pkm | Number of economy seats | % of average gCO2/pkm | % Total seats |
| --- | --- | --- | --- | --- | --- | --- |
|  | Economy class | 81.3% | 63.2 | 1.00 | 76.6% | 83.0% |
|  | Economy+ class | 81.3% | 101.1 | 1.60 | 122.5% | 3.0% |
|  | Business class | 81.3% | 183.3 | 2.90 | 222.1% | 11.9% |
|  | First class | 81.3% | 252.8 | 4.00 | 306.3% | 2.0% |

Notes: Average load factors based on data provided by DfT that contains detailed analysis of CAA statistics for the year 2023

Freight Air Transport Direct CO2 Emission Factors

8.23. Freight air transport factors remain constant since the publication of 2025 GHG
Conversion Factors.

8.24. Air freight, including mail, is 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, 2023). 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 40 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 2026 GHG Conversion Factors data tables.

Table 38: Revised average CO2 conversion factors for dedicated cargo flights (excluding
distance and RF uplifts)

| Mode | Av. Load Factor% | kgCO2/tkm |
| --- | --- | --- |
| Domestic flights | 32.2% | 2.5 |
| Short-haul flights | 53.4% | 0.7 |
| Long-haul flights | 54.5% | 0.6 |

\\mathbf{c o}}}\_{\\mathbf{2}}

* * *

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, 2024). A full summary of the representative aircraft selection
and the main assumptions influencing the emission factor calculation are
presented in Table 41. The key features of the calculation methodology, data and
assumptions for the GHG Conversion Factors include:

The updated factors have been calculated in the same basic methodology as for
the passenger flights, using the EUROCONTROL small emitters tool
(EUROCONTROL, 2024). A full summary of the representative aircraft selection
and the main assumptions influencing the emission factor calculation are
presented in Table 41. 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

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 2023 (the latest
available complete dataset) (CAA, 2023).

Table 39: Assumptions used in the calculation of average CO2 conversion factors for
dedicated cargo flights

|  | Average Cargo Capacity, tonnes | Av. Load Factor | Proportion of tonne km | EF,kgCO2/vkm | Av. flight length,km |
| --- | --- | --- | --- | --- | --- |
| Domestic Flights |  |  |  |  |  |
| AIRBUS A319 | 0.0 | 0% | 0.0% | 0.00 | 0 |
| AIRBUS A320-100/200 | 0.0 | 0% | 0.0% | 0.00 | 0 |
| AIRBUS A320neo | 0.0 | 0% | 0.0% | 0.00 | 0 |
| AIRBUS A321 | 22.0 | 28% | 0.0% | 17.76 | 486 |
| AIRBUS A321neo | 0.0 | 0% | 0.0% | 0.00 | 0 |
| AIRBUS A330-300 | 39.7 | 28% | 12.8% | 24.02 | 1303 |
| AIRBUS A340-600 | 0.0 | 0% | 0.0% | 0.00 | 0 |
| AIRBUS A350-1000 | 0.0 | 0% | 0.0% | 0.00 | 0 |
| AIRBUS A380-800 | 0.0 | 0% | 0.0% | 0.00 | 0 |
| ATR72 200/500/600 | 7.0 | 29% | 10.3% | 5.88 | 263 |
| BEECH 200 | 1.7 | 10% | 0.0% | 2.04 | 421 |
| BOEING 737-300 | 17.5 | 31% | 9.4% | 15.81 | 453 |
| BOEING 737-400 | 18.9 | 31% | 28.1% | 16.32 | 408 |
| BOEING 737-800 | 22.6 | 32% | 13.7% | 14.72 | 489 |
| BOEING 747-400F | 0.0 | 0% | 0.0% | 0.00 | 0 |
| BOEING 757-200 | 14.4 | 37% | 0.6% | 55.04 | 110 |
| BOEING 767-300ER/F | 29.9 | 37% | 9.6% | 29.85 | 379 |
| BOEING 777-200 | 0.0 | 0% | 0.0% | 0.00 | 0 |

\\mathbf{c o}}}\_{\\mathbf{2}

* * *

|  | Average Cargo Capacity, tonnes | Av. Load Factor | Proportion of tonne km | EF,kgCO2/vkm | Av. flight length,km |
| --- | --- | --- | --- | --- | --- |
| BOEING 777-300ER | 0.0 | 0% | 0.0% | 0.00 | 0 |
| BOEING 777-F | 57.4 | 37% | 15.3% | 35.88 | 695 |
| BOEING 787-1000 DREAMLINER | 0.0 | 0% | 0.0% | 0.00 | 0 |
| BOEING 787-900 DREAMLINER | 0.0 | 0% | 0.0% | 0.00 | 0 |
| CESSNA F406 | 1.4 | 10% | 0.0% | 1.56 | 475 |
| Average | 27.7 | 32% | 100% | 15.21 | 372 |
| Short-haul Flights |  |  |  |  |  |
| AIRBUS A319 | 0.0 | 0% | 0.0% | 0.00 | 0 |
| AIRBUS A320-100/200 | 16.0 | 77% | 0.0% | 0.00 | 0 |
| AIRBUS A320neo | 16.1 | 77% | 0.0% | 0.00 | 0 |
| AIRBUS A321 | 35.4 | 74% | 0.0% | 15.82 | 687 |
| AIRBUS A321neo | 20.5 | 77% | 0.0% | 0.00 | 0 |
| AIRBUS A330-300 | 63.5 | 74% | 0.5% | 22.84 | 1837 |
| AIRBUS A340-600 | 70.0 | 51% | 0.0% | 0.00 | 0 |
| AIRBUS A350-1000 | 54.2 | 77% | 0.0% | 0.00 | 0 |
| AIRBUS A380-800 | 67.6 | 77% | 0.0% | 0.00 | 0 |
| ATR72 200/500/600 | 8.8 | 31% | 0.0% | 0.00 | 0 |
| BEECH 200 | 1.7 | 15% | 0.0% | 0.00 | 0 |
| BOEING 737-300 | 21.5 | 33% | 0.0% | 0.00 | 0 |
| BOEING 737-400 | 24.2 | 51% | 0.0% | 35.04 | 96 |
| BOEING 737-800 | 25.6 | 25% | 0.0% | 0.00 | 0 |
| BOEING 747-400F | 134.5 | 73% | 0.0% | 0.00 | 0 |
| BOEING 757-200 | 25.8 | 53% | 2.5% | 32.20 | 237 |
| BOEING 767-300ER/F | 53.7 | 53% | 37.4% | 23.08 | 813 |
| BOEING 777-200 | 57.5 | 77% | 0.0% | 0.00 | 0 |
| BOEING 777-300ER | 81.8 | 77% | 0.0% | 0.00 | 0 |
| BOEING 777-F | 103.1 | 53% | 59.6% | 30.27 | 1492 |
| BOEING 787-1000 DREAMLINER | 46.1 | 77% | 0.0% | 0.00 | 0 |
| BOEING 787-900 DREAMLINER | 42.7 | 77% | 0.0% | 0.00 | 0 |
| CESSNA F406 | 1.4 | 15% | 0.0% | 0.00 | 0 |
| Average | 82.5 | 53% | 100% | 26.74 | 830 |
| Long-haul Flights |  |  |  |  |  |
| AIRBUS A319 | 0.0 | 0% | 0.0% | 0.00 | 0 |
| AIRBUS A320-100/200 | 16.0 | 77% | 0.0% | 12.55 | 1001 |
| AIRBUS A320neo | 16.1 | 77% | 0.0% | 10.19 | 1001 |
| AIRBUS A321 | 35.4 | 74% | 0.0% | 16.61 | 590 |
| AIRBUS A321neo | 20.5 | 77% | 0.0% | 10.10 | 3504 |
| AIRBUS A330-300 | 63.5 | 74% | 2.9% | 20.46 | 13542 |
| AIRBUS A340-600 | 70.0 | 51% | 5.4% | 31.31 | 8383 |
| AIRBUS A350-1000 | 54.2 | 77% | 0.1% | 24.50 | 4505 |
| AIRBUS A380-800 | 67.6 | 77% | 0.1% | 46.96 | 8509 |
| ATR72 200/500/600 | 8.8 | 31% | 0.0% | 5.17 | 403 |
| BEECH 200 | 1.7 | 15% | 0.0% | 1.75 | 1151 |
| BOEING 737-300 | 21.5 | 33% | 0.0% | 13.87 | 646 |
| BOEING 737-400 | 24.2 | 51% | 0.1% | 14.11 | 664 |
| BOEING 737-800 | 25.6 | 25% | 0.3% | 11.37 | 1373 |
| BOEING 747-400F | 134.5 | 73% | 3.6% | 39.96 | 5226 |
| BOEING 757-200 | 25.8 | 53% | 2.2% | 16.71 | 1074 |
| BOEING 767-300ER/F | 53.7 | 53% | 32.8% | 19.41 | 3686 |
| BOEING 777-200 | 57.5 | 77% | 0.1% | 25.20 | 3822 |
| BOEING 777-300ER | 81.8 | 77% | 0.0% | 28.88 | 6007 |
| BOEING 777-F | 103.1 | 53% | 52.3% | 29.95 | 6766 |
| BOEING 787-1000 DREAMLINER | 46.1 | 77% | 0.0% | 21.70 | 4004 |
| BOEING 787-900 DREAMLINER | 42.7 | 77% | 0.0% | 19.28 | 4338 |
| CESSNA F406 | 1.4 | 15% | 0.0% | 1.37 | 1300 |
| Average | 82.9 | 54% | 100% | 28.09 | 3,700 |

* * *

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 2023. Figures of kgCO2/vkm were calculated using the average flight lengths in
the EUROCONTROL small emitters tool (EUROCONTROL, 2024).

Conversion factors for Freight on Passenger Services

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 42 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 2026 GHG Conversion Factors set (discussed later).

Table 40: Air freight CO2 conversion factors for alternative freight allocation options for
passenger flights (excluding distance and RF uplifts)

| 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 | 0.9% | 99.1% | 0.0% | 2.5 | 0.0% | 2.5 |
| Short-haul flights | 0.2% | 99.8% | 0.5% | 0.7 | 0.5% | 0.7 |
| Long-haul flights | 68.0% | 32.0% | 17.0% | 0.8 | 17.0% | 0.5 |

;0\_{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 air freight conversion factors for 2026.

8.32. Table 43 presents the final average air freight conversion factors for all air freight
for the 2026 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 2026
GHG Conversion Factors set (discussed later).

* * *

Table 41: Final average CO2 conversion factors for all air freight (excluding distance and
RF uplifts)

| Mode | % Total Air Freight tkm |  | All Air FreightkgCO2/tkm |
| --- | --- | --- | --- |
| Passenger Services | Cargo Services |  |  |
| Domestic flights | 0.9% | 99.1% | 2.5 |
| Short-haul flights | 0.2% | 99.8% | 0.7 |
| Long-haul flights | 68.0% | 32.0% | 0.5 |

Note: % Total Air Freight tkm based on CAA statistics for 2023 (T0.1.6 All Services)

Air Transport Direct Conversion factors for CH4 and N2O

Emissions of CH4

\\mathrm{C H}\_{4}

N\_{2}O\\mathrm

\\mathrm{C H}\_{4}

8.33. Total emissions of CO2, 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
proportions of total CO2 and CH4 emissions from the UK GHG Inventory for 2023
(see Table 44) 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 2026 GHG Conversion
Factors are presented in Table 45 for passengers and Table 46 for freight.

\\mathsf{C O\_{2},C H\_{4}}

N{\ }O

{\\mathrm{C O}}\_{2}

\\mathrm{C H}\_{4}

\ \\mathrm c O\_{2}

Table 42: Total emissions of CO2, CH4 and N2O for domestic and international aircraft from
the UK GHG Inventory for 2023

N\_{2}O

|  | CO2 |  | CH4 |  | N2O |  |
| --- | --- | --- | --- | --- | --- | --- |
| Mt CO2e | % Total CO2e | Mt CO2e | % Total CO2e | Mt CO2e | % Total CO2e |  |
| Aircraft - domestic | 1.31 | 99.03% | 0.0017 | 0.12% | 0.011 | 0.84% |
| Aircraft - international | 32.77 | 99.15% | 0.0024 | 0.01% | 0.279 | 0.84% |

8.34. Similar to those for CH4, conversion factors for N2
km were calculated on the basis of the relative proportions of total CO2
emissions from the UK GHG Inventory for 2023 (see Table 44), and the
corresponding CO2 emission factors. The resulting air transport conversion factors
for the 2026 GHG Conversion Factors are presented in Table 45 for passengers
and Table 46 for freight. The factors presented here do not include the distance or

, 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 2023 (see Table 44), and the
emission factors. The resulting air transport conversion factors
for the 2026 GHG Conversion Factors are presented in Table 45 for passengers
and Table 46 for freight. The factors presented here do not include the distance or

and Table 46 for freight. The factors presented here do not include the distance or
radiative forcing uplifts applied to the conversion factors provided in the 2026

radiative forcing uplifts applied to the conversion factors provided in the 2026
GHG Conversion Factors set (discussed later).

\\mathrm{c O2}

\ @@

\ \\mathrm N O

{\\mathrm{c O}}\_{2}

\\box{ed{\\text ircled O{}}}}boxbox{{\\texted cled{\\text}O}

* * *

Table 43: Final average CO2, CH4 and N2O conversion factors for all air passenger transport
(excluding distance and RF uplifts)

{\\bf c o}\_{2},

N\_{2}O

| Air Passenger Mode | Seating Class | CO2gCO2/pkm | CH4gCO2e/pkm | N2OgCO2e/pkm | Total GHGgCO2e/pkm |
| --- | --- | --- | --- | --- | --- |
| Domestic flights | Average | 124.0 | 0.2 | 1.1 | 125.2 |
| Short-haul flights | Average | 69.1 | 0.0 | 0.6 | 69.7 |
| Economy | 68.0 | 0.0 | 0.6 | 68.6 |  |
| First/Business | 102.0 | 0.0 | 0.9 | 102.9 |  |
| Long-haul flights | Average | 82.5 | 0.0 | 0.7 | 83.2 |
| Economy | 63.2 | 0.0 | 0.5 | 63.7 |  |
| Economy+ | 101.1 | 0.0 | 0.9 | 102.0 |  |
| Business | 183.3 | 0.0 | 1.6 | 184.9 |  |
| First | 252.8 | 0.0 | 2.1 | 255.0 |  |
| International flights(non-UK) | Average | 77.2 | 0.0 | 0.7 | 77.8 |
| Economy | 59.1 | 0.0 | 0.5 | 59.6 |  |
| Economy+ | 94.5 | 0.0 | 0.8 | 95.4 |  |
| Business | 171.4 | 0.0 | 1.5 | 172.8 |  |
| First | 236.4 | 0.0 | 2.0 | 238.4 |  |

Note: Totals may vary from the sums of the components due to rounding in the more detailed dataset.

Table 44: Final average CO2, CH4 and N2O conversion factors for air freight transport
(excluding distance and RF uplifts)

{\\bf c o}\_{2},

N\_{2}O

| Air Freight Mode | CO2kgCO2/tkm | CH4kgCO2e/tkm | N2OkgCO2e/tkm | Total GHGkgCO2e/tkm |
| --- | --- | --- | --- | --- |
| Passenger Freight |  |  |  |  |
| Domestic flights | 2.68 | 0.0034 | 0.0228 | 2.71 |
| Short-haul flights | 1.20 | 0.0001 | 0.0102 | 1.21 |
| Long-haul flights | 0.43 | 0.0000 | 0.0036 | 0.43 |
| Dedicated Cargo |  |  |  |  |
| Domestic flights | 2.49 | 0.0031 | 0.0212 | 2.52 |
| Short-haul flights | 0.69 | 0.0000 | 0.0059 | 0.70 |
| Long-haul flights | 0.62 | 0.0000 | 0.0052 | 0.62 |
| All Air Freight |  |  |  |  |

* * *

| Air Freight Mode | CO2kgCO2/tkm | CH4kgCO2e/tkm | N2OkgCO2e/tkm | Total GHGkgCO2e/tkm |
| --- | --- | --- | --- | --- |
| Domestic flights | 2.49 | 0.0031 | 0.0212 | 2.52 |
| Short-haul flights | 0.69 | 0.0000 | 0.0059 | 0.70 |
| Long-haul flights | 0.49 | 0.0000 | 0.0041 | 0.49 |

Note: Totals may vary from the sums of the components due to rounding in the more detailed dataset.

Indirect/WTT Conversion factors from Air Transport

8.35. Indirect/WTT emissions factors for air passenger and air freight services 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 aviation turbine fuel (kerosene) and the corresponding
direct CO2 conversion factors for air passenger and air freight transport in the
“Business travel – air” and “Freighting goods” worksheets.

Other Factors for the Calculation of GHG Emissions

Great Circle Flight Distances

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.

Non-CO2 impacts and Radiative Forcing

\\mathrm{-C O\_{2}}

8.39. The conversion factors provided in the 2026 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
other non-CO2 radiative forcing effects of aviation (including water vapour,

N\\mathrm{}O\_}{\ contrails, NOX, etc.) which have been indicatively accounted for by applying a
multiplier to account for CO2 equivalent emissions in some cases.

\\mathrm{N o x},

\ \\mathrm C O\_{2}

8.40. The use of CO2 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}

8.41. The application of an aggregate multiplier to take account of non-CO2 effects is a
possible way of illustratively taking account of the full climate impact of aviation. A
multiplier is not a straightforward CO2 equivalence metric. In particular, it implies
that all other emissions and effects are directly linked to production of CO2, which
is not necessarily the case. Nor does it reflect accurately the different relative
contribution of emissions to climate change over time, or reflect the potential
trade-offs between the warming and cooling effects of different emissions.

n o-{o000}

\\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 47 and the GWP100 figure
(consistent with UNFCCC reporting convention) in Table 48 below and in analysis
by Lee et al. (2021).

\ o\_n{n-C}}{O\_2{}

1.7

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
2026 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.

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 effects 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 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--mathrm{c O}\_{2}

\ 0-\\0C\_{{2}}

* * *

Table 45: Impacts of radiative forcing according to Lee et al., (2021)

| ERF(mWm-2) | 2018a | 2011a |
| --- | --- | --- |
| Contrail cirrus | 57.4(17,98) | 44.1(13,78) |
| CO2 | 34.3(28,40) | 29.0(24,36) |
| Short-termO3increase | 49.3(32,76) | 37.3(24,56) |
| Long-termO3decrease | -10.6(-20,-7.4) | -7.9(-15,-5.5) |
| CH4decrease | -21.2(-40,-15) | -15.8(-30,-11) |
| Stratosphericwater vapordecrease | -3.2(-6.0,-2.2) | -2.4(-4.4,-1.7) |
| NetNOx | 17.5(0.6,29) | 13.6(0.9,22) |
| StratosphericH2Oincrease | 2.0(0.8,3.2) | 1.5(0.6,2.2) |
| Soot(aerosolradiation) | 0.94(0.1,4.0) | 0.71(0.1,3.0) |
| Sulfate(aerosolradiation) | -7.4(-19,-2.6) | -5.6(-14,-1.9) |
| Sulfate andsoot(aerosol-cloud) | \-\-\-- | \-\-\-- |
| NetERF(onlynon-CO2terms) | 66.6(21,111) | 51.4(16,81) |
| NetaviationERF | 100.9(55,145) | 80.4(45,114) |
| Net anthropogenicERF in2011 | \-\-\-- | 2290(11303330)b |

|  | 2005a | Sensitivity to emissions | ERF/RF |
| --- | --- | --- | --- |
| (5) | 34.8(10,59) | 9.36x10-10mW m-2km-1 | 0.42 |
| (4) | 25.0(21,29) |  | 1.0 |
| (8) | 33.0(21,51) | 34.4±9.9mW m-2(Tg(N)yr-1)-1 | 1.37 |
|  | -6.7(-13,-4.7) | -9.3±3.4mW m-2(Tg(N)yr-1)-1 | 1.18 |
|  | -13.4(-25,-9.4) | -18.7±6.9mW m-2(Tg(N)yr-1)-1 | 1.18 |
|  | -2.0(-3.8,-1.4) | -2.8±1.0mW m-2(Tg(N)yr-1)-1 | 1.18 |
| (4) | 12.9(1.9,20) | 5.5±8.1mW m-2(Tg(N)yr-1)-1 |  |
|  | 1.4(0.6,2.3) | 0.0052±0.0026mW m-2(Tg(H2O)yr-1)-1 | \-\-\- |
|  | 0.67(0.1,2.8) | 100.7±165.5mW m-2(Tg(BC)yr-1)-1 | \-\-\- |
|  | -5.3(-13,-1.8) | -19.9±16.0mW m-2(Tg(SO2)yr-1)-1 | \-\-\- |
| (5) | 41.9(14,69) | \-\-\- | \-\-\- |
|  | 66.9(38,95) | \-\-\- | \-\-\- |
| (0) | \-\-\- | \-\-\- | \-\-\- |

\\begin{array}{l}{{9366\\times10^{-10},W,m}}\\end{array}

0{}\_{3}

\ up\_{3}

34.4\\pm9.9,m M m^^{{-}}}

(\\mathsf{T g},(\\mathsf{N}),\\mathsf{y r}^{-})^{-1}

-9.3\\pm3.4,m W^^{{2}}

(\\mathsf{T g}(\\mathsf{N})\\mathsf{y r}^{-})^{-1}

-18.7\\pm6.9,\\mathsf{m W}

\ mathrm N O O

^{2}\\left(\\mathsf{T g}\\left(\\mathsf{N}\\right)\\mathsf{y r}^{1}\\right)^{-1}

-.2.8\\pm1.0,m m^{-2}

(\\mathsf{T g},(\\mathsf{N}),\\mathsf{y r}^{-})^{-1}

H20

\\begin{array}{l}{0.0052\\pm0.0026}\ {\\mathsf{m W},\\mathsf{m}^{2}}\\end{array}

\ (\\mathsf{T g},(\\mathsf{H}\_{2}\\mathsf{O}),y r^{-1})^{-1}

m^{-}2\\left(g\\left\ (B\ {}C\\right)y r{{}^{-1}}\\right)^{-1}

\\mathsf{m}^{-2}\\left(\\mathsf{T g};(\\mathsf{S O}\_{2});\\mathsf{y r}^{-1}\\right)

_\\mathrm{{1O}}_{2}

a The uncertainty distributions for all forcing terms are lognormal except for CO2
and contrail cirrus (normal) and Net NOx
(discrete pdf).

\\mathrm{N O}\_{}

\\mathrm{C O\_{2}}

b Boucher et al., 2013. IPCC also separately estimated the contrail cirrus term for 2011 as 50 (20, 150) mW m-2

m N m^{-2}

* * *

Table 46: 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(Tg CO2 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 |
| Net NOx | 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{C O\_{2}}

-1
CO2-eq emissions (Tg CO2 yr) for 2018

\ \\mathrm{s O\_{2}}

| ERF term | GWP20 | GWP50 | GWP100 | GTP20 | GTP50 | GTP100 | GWP _100(E_ CO2e) |
| --- | --- | --- | --- | --- | --- | --- | --- |
| CO2 | 1034 | 1034 | 1034 | 1034 | 1034 | 1034 | 1034 |
| Contrail cirrus(Tg CO2 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 |

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

| ERF term | GWP20 | GWP50 | GWP100 | GTP20 | GTP50 | GTP100 | GWP _100(E_ co2e) |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 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 |

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 2026 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.

9.4. Table 49 shows where the related worksheets to the bioenergy and water
conversion factors are available in the online spreadsheets of the UK GHG
Conversion Factors. Note that as of 2026, the Condensed set is no longer
published; however, this table has been retained here so that users can find
values from previous publication years.

Table 47: 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. There were no major methodological changes for bioenergy or water in the 2026
update. However, 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.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# General Methodology

9.6. The 2026 GHG Conversion Factors provide tables of conversion factors for: water supply and treatment, biofuels, biomass and biogas.
9.7. 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.

# Water

9.8. The conversion factors for water supply and treatment in sections “Water supply” and “Water treatment” worksheets of the 2026 GHG Conversion Factors remain constant since the publication of the 2025 GHG Conversion Factors. Those were calculated based on 2023 data from UK water companies Carbon Accounting Workbooks (CAW). These data are used for reporting to the UK regulator (Ofwat) and all UK water companies use this common approach to reporting these data.
26

9.9. 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 dataset includes the volume of wastewater treated and of drinking water supplied by each company. 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

9.10. At the point of use, biofuels are defined as “net carbon zero” or “carbon neutral” as any CO2 expelled during the burning of the fuel is cancelled out by the CO2 absorbed by the feedstock used to produce the fuel during growth27. Therefore, all direct emissions from biofuels provided in the GHG Conversion Factors dataset are only made up of CH4 and N2O emissions.
9.11. 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 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.
9.12. The net GHG emissions for biofuels vary significantly depending on the feedstock source and production pathway. Therefore, for accuracy, it is recommended that
26 The data are not published in a suitable format for use for the GHG conversion factors. So, more suitable data were requested from, and provided by a contact at a water company in a personal communication. The individual companies' data are considered confidential, so can only be published as an aggregation. This is a convention required by international GHG Inventory guidelines and formal accounting rules.

* * *

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, 2025).

9.13. The indirect/WTT/fuel lifecycle conversion factors for biofuels were based on UK
average factors from the Quarterly Reports on the RTFO. These average factors
and the direct CH4 and N2O factors are presented in Table 50.

9.14. In addition to the direct and indirect/WTT conversion factors provided in Table 50,
conversion factors for the Out of Scope CO2 emissions have also been provided
based on data sourced from the UK GHGI and the JEC WTT v5 study (JEC WTW
v5, 2020).

Table 48: Fuel lifecycle GHG Conversion Factors for biofuels

| Biofuel | Emissions Factor,gCO2e/MJ |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- | --- |
| RTFO Lifecycle(1) | DirectCH4(2) | DirectN2O(2) | DirectCO2(2\*) | Total Lifecycle | DirectCO2 Emissions(Out of Scope(3)) |  |
| Avtur(renewable) | 15.26 | 0.04 | 0.68 | 0.00 | 15.98 | 71.74 |
| Biodiesel HVO | 16.45 | 0.01 | 1.03 | 0.00 | 17.48 | 70.83 |
| Biodiesel ME | 11.93 | 0.01 | 1.03 | 4.02 | 16.99 | 72.16 |
| Biodiesel ME(from Tallow) | 16.08 | 0.01 | 1.03 | 4.02 | 21.14 | 72.16 |
| Biodiesel ME(from used cooking oil) | 10.67 | 0.01 | 1.03 | 4.02 | 15.73 | 72.16 |
| Bioethanol | 28.91 | 0.22 | 0.20 | 0.00 | 29.33 | 71.37 |
| Biomethane(compressed) | 15.80 | 0.08 | 0.03 | 0.00 | 15.90 | 55.28 |
| Biomethane(liquified) | 23.90 | 0.08 | 0.03 | 0.00 | 24.01 | 56.80 |
| Biopropane | 6.61 | 0.05 | 0.04 | 0.00 | 6.70 | 64.51 |
| Development diesel | 23.32 | 0.01 | 1.03 | 0.00 | 24.36 | 73.54 |
| Methanol(bio) | 37.60 | 0.22 | 0.20 | 0.00 | 38.02 | 68.92 |
| Development petrol | 23.10 | 0.22 | 0.20 | 0.00 | 23.52 | 70.21 |
| Off road biodiesel | 11.93 | 0.01 | 1.03 | 4.02 | 16.99 | 72.16 |
| Notes: |  |  |  |  |  |  |

(1) Based on UK averages from the RTFO Quarterly Report from DfT (DfT, 2025).

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

(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

9.15. 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 2026 GHG Conversion Factors set.
9.16. 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.
9.17. 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).
9.18. The direct CH4 and N2O conversion factors presented in the 2026 GHG Conversion Factors are based on the conversion factors used in the UK GHG Inventory (GHGI) for 2024 (Ricardo, 2026).
9.19. In some cases, calorific values were required to convert the data into the required units. The most appropriate source was used, and this was either from the Forest Research (Forest Research, 2023), DUKES (Table A.1) or Swedish Gas Technology Centre 2012 (which is also backed up by other data sources). The values used and their associated moisture contents are provided in Table 51.
9.20. 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 2026 GHG 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). These have remained constant since the 2025 GHG Conversion Factors update.
**Table 49: Fuel sources and properties used in the calculation of biomass and biogas**

## emission factors

**Biomass Moisture content Net calorific value Source** **(GJ/tonne)**

Wood chips 25% moisture 13.6 Forestry Research

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

| Biomass | Moisture content | Net calorific value(GJ/tonne) | Source |
| --- | --- | --- | --- |
| Wood logs | Air dried 20% moisture | 14.7 | NAEI |
| Wood pellets | 10% moisture | 17.3 | DUKES |
| Grass/Straw | 10% moisture | 13.4 | NAEI |
| 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

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 UK GHG Conversion
Factors but are available for sale from the CO2 Emissions from Fuel Combustion
online data service at the International Energy Agency (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.

Summary of changes since the previous update

10.2. The related worksheet for this section is the “Overseas electricity" sheet, available
in the full set of the UK GHG Conversion Factors.

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.

10.5. However, the overseas electricity factors have not been provided after the 2015
update due to a change in the licencing conditions for the underlying International
Energy Association (IEA) dataset upon which they were based.

28
Available here: [http://data.iea.org/](http://data.iea.org/) 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 report29, 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.

{\\mathrm{C O}}\_{2}

Indirect/WTT Emissions from Overseas Electricity Generation

10.10. Since the 2024 publication of the UK GHG Conversion Factors, indirect/WTT
emission factors for overseas electricity generation have no longer been provided.
Instead, the method for calculating the factors manually is provided. The
methodology used in previous editions of the UK GHG Conversion Factors was to
take the direct emission factor for the country in question 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 GHG 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\ \ U U\\frac{W T T}{D i r e c t}R a t i o=61\ \\times\ \\frac{24.19}{100}=14.76\ g g O\_{2}e/k W k

29
Available here: [https://www.aib-net.org/facts/european-residual-mix/2021](https://www.aib-net.org/facts/european-residual-mix/2021)

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

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:
𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 𝑊𝑊𝑊𝑊𝑊𝑊 61 24.19 𝑊𝑊𝑊𝑊𝑊𝑊𝑇𝑇&𝐷𝐷= − 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 × 𝑈𝑈𝑈𝑈 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 𝑅𝑅 = − 61 × = 1.28 𝑔𝑔𝐶𝐶𝐶𝐶2𝑒𝑒 /𝑘𝑘𝑘𝑘 ℎ 1 − 𝐿𝐿𝐿𝐿 𝐿𝐿𝐿𝐿𝐿𝐿 𝐿𝐿 𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 8 100 1 − 100

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# 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 in the full set of the UK GHG Conversion Factors set.
11.3. Hotel stay conversion factors remain constant since the publication 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 2026 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 2026 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.
11.7. The following five steps were carried out in the CHSB study to arrive at the conversion factors included within the 2022 GHG Conversion Factors:
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** received.
c) **Geographic and climate zone segmentation. The data sets were grouped by** location and climate zone.
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.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

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 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.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# 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 3 Standard’)
30 .

12.4. These factors appear in the “Material use” and “Waste disposal” worksheets of the UK GHG Conversion Factors set.
12.5. Users wishing to quantify the impact of different waste management options may wish to use WRAP Carbon Waste and Resources Metric (CarbonWARM)
31 . Note that CarbonWARM outputs cannot be used for reporting Scope 3 Greenhouse Gas emissions.

## Summary of changes since the previous update

12.6. There have been no major methodological changes to the Material Use or Waste Disposal conversion factors in the 2026 publication. Changes since the 2025 publication are therefore solely due to the use of updated conversion factors for freight, as described in Section 6.
[http://www.ghgprotocol.org/standards/Scope-3-standard](http://www.ghgprotocol.org/standards/Scope-3-standard) [https://wrap.org.uk/resources/report/carbon-waste-and-resources-metric](https://wrap.org.uk/resources/report/carbon-waste-and-resources-metric)

* * *

Emissions from Material Use and Waste Disposal

12.7. The GHG Conversion Factors for material consumption/use and waste disposal
have been aligned with the GHG Protocol Corporate Value Chain (Scope 3)
32
Accounting and Reporting Standard (‘the Scope 3 Standard’). This sets down
rules on accounting for emissions associated with material consumption and
waste management.

12.8. The company sending waste for recycling does not receive any benefit to its
carbon account from recycling as the figures for waste disposal no longer include
the potential benefits where primary resource extraction is replaced by recycled
material. Under this accounting methodology, the organisation using recycled
materials will see a reduction in their account where this use is in place of higher
impact primary materials.

12.9. 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).

12.10. 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 biogenic33 CO2 has been excluded from these figures.

12.11. 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.

12.12. 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.

12.13. The following subsections summarise the methodology, key data sources and
assumptions used to define the emission factors.

Material Consumption/Use

32
[http://www.ghgprotocol.org/standards/Scope-3-standard](http://www.ghgprotocol.org/standards/Scope-3-standard)

12.14. Figure 6 shows the boundary of greenhouse gas emissions summarised in the
material consumption table.

\\mathrm{C O\_{2}}

33
Biogenic CO2 is the CO2 absorbed and released by living organisms during and at the end of their life. By
convention, this is assumed to be in balance in sustainably managed systems.

{\\mathrm C O}\_{2}

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

**Figure 6: Boundary of material consumption data sets**

Notes: Arrows represent transportation stages; greyed items are excluded.

12.15. The conversion factors presented for material consumption cover all GHG emissions from the point of raw material extraction through to the point at which a finished good is manufactured and provided for sale. Therefore, commercial 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.
12.16. 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.
12.17. 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 (for example, based on a cradle-to-gate life cycle assessment or similar method compliant with ISO14067), then please refer to the more accurate data for reporting your emissions.
12.18. 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.

12.20. Table 52 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 50: 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) |

12.21. Transport of goods by consumers is excluded from the factors presented, as is the
use of the product.

Waste Disposal

12.22. 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
34
from their site and deposit at the first point of processing (e.g. 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.

34
See, for example, notes a and b to example 5.1 (p.75) in Technical Guidance for Calculating Scope 3 Emissions
(World Resources Institute, 2013).

* * *

directly from MELMod, which contains information on landfill waste composition
35
and material properties, with the addition of collection and transport emissions.

12.24. 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.

12.25. 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).

12.26. 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 53.

Table 51: 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) |

12.27. 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 2026 UK GHG Conversion Factors. Waste vehicles leave a depot

35
MELMod accounts for biogenic methane emissions (corrected to account for capture and oxidation) but excludes
biogenic CO2 removals and emissions. For more information see Brown and Leach (2008).

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

empty and return fully laden. A 50% loading assumption reflects the change in load over a collection round which could be expected.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# 13\. Fuel Properties

## Section summary

13.1. The fuel properties can be used to determine the typical calorific values / densities of most common fuels. These factors appear in the “Fuel properties” worksheet of the UK GHG Conversion Factors set.

## Summary of changes since the previous update

13.2. Fuel property data for the vast majority of fuels uses data from the UK GHG Inventory (GHGI) (Ricardo, 2026). 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 UK GHG Conversion Factors.

## General Methodology

13.3. 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.
13.4. The standard conversion factors from the GHGI are now provided on a net energy basis. These are converted into different energy, volume and mass units for the various data tables using the information on these fuel properties (i.e. Gross and Net Calorific Values (CV), and fuel densities in litres/tonne) from UK GHGI data and in some cases from DESNZ’s Digest of UK Energy Statistics (DESNZ, 2025).
13.5. The fuel properties of most biofuels are predominantly based on data from JEC-Joint Research Centre-EUCAR-CONCAWE collaboration, “Well-to-Wheels Analysis of Future Automotive Fuels and Powertrains in the European Context” Version 5, 2020 (Report EUR 30269 EN - 2020) (JEC WTW v5, 2020). The exception is for methyl-ester based biodiesels and bioethanol, where values for NCV and GCV are taken from the UK GHGI.
13.6. Fuel properties, both density and CV, for wood chips (25% moisture content) come from the Forest Research (previously Biomass Energy Centre (BEC)
36 . The density of wood logs (20% moisture content), wood chips (25% moisture content) and grasses/straw (25% water content) are also sourced from the same Forest Research publication.

Available at: [https://www.forestry.gov.uk/fr/beeh-9ukqcn](https://www.forestry.gov.uk/fr/beeh-9ukqcn)

* * *

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 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

14.5. SECR kWh conversion factors have been calculated for passenger and delivery
vehicles including; cars, motorcycles, vans and HGVs.

b) “SECR kWh UK electricity for EV” worksheet contains only the kWh factors for
the electricity consumed by the electric vehicles.

14.6. The factors are split out between two worksheets:

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# Summary of changes since the previous update

14.7. There were no major methodological changes in the 2026 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.
- Step 2 – Divide the kg CO2 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.
  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.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# 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 in the full set of the UK GHG Conversion Factors set.
15.3. Homeworking conversion factors for office equipment have been updated in the 2026 publication to reflect the revised UK electricity factor. Conversion factors for heating remain constant since the publication 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 2026 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.
15.8. Office equipment is an estimation of energy used by a homeworking employee. Conversion factors for electricity consumption come from the UK GHG Conversion Factors model outputs for UK Electricity. There are 3 assumptions:
a) assumed that a homeworking employee only uses energy for a laptop or PC, monitor, phone, printer and lighting;
b) assumed that the energy used by a homeworking employee is 140W, same as the energy used by a workstation (a laptop or PC, monitor, phone and printer). Electricity use data for a workstation came from CIBSE Guide F (CIBSE, 2012);
c) assumed that the energy used for lighting is 10W per homeworking employee (an assumption by EcoAct);

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

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). 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.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

# 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. Retrieved from_ [https://ec.europa.eu/clima/sites/clima/files/transport/vehicles/docs/ec\_hdv\_ghg\_strategy\_](https://ec.europa.eu/clima/sites/clima/files/transport/vehicles/docs/ec_hdv_ghg_strategy_) en.pdf

AIB. (2023). European Residual Mix. Retrieved from Association of Issuing Bodies: [https://www.aib-net.org/facts/european-residual-mix](https://www.aib-net.org/facts/european-residual-mix)

Allen, J. and Browne, M. (2008). Using official data sources to analyse the light goods vehicle _fleet and operations in Britain. University of Westminster . Retrieved from_ [http://www.greenlogistics.org/SiteResources/61debf21-2b93-4082-ab15-](http://www.greenlogistics.org/SiteResources/61debf21-2b93-4082-ab15-) 84787ab75d26\_LGV%20activity%20report%20(final)%20November%202008.pdf

BEIS. (2019). Environmental reporting guidelines: including Streamlined Energy and Carbon _Reporting requirements. Retrieved from_ [https://www.gov.uk/government/publications/environmental-reporting-guidelines-](https://www.gov.uk/government/publications/environmental-reporting-guidelines-) including-mandatory-greenhouse-gas-emissions-reporting-guidance

BEIS. (2020). Government emission conversion factors for greenhouse gas company reporting. Retrieved from [https://www.gov.uk/government/collections/government-conversion-](https://www.gov.uk/government/collections/government-conversion-) factors-for-company-reporting

BFF. (2007). Carbon Emissions of Mixed Passenger and Vehicle Ferries on UK and Domestic _Routes. Best Foot Forward for the Passenger Shipping Association (PSA)._

Boldrin, Alessio, Karin R. Hartling, Maria Laugen, and Thomas H. Christensen. (2010, October). Environmental Inventory Modelling of the Use of Compost and Peat in Growth Media Preparation. Resources, Conservation and Recycling, 54(12), 1250–60. Retrieved from [https://doi.org/10.1016/j.resconrec.2010.04.003](https://doi.org/10.1016/j.resconrec.2010.04.003)

Brown, KA and Leech, A. (2008). Revision of UK model for predicting methane emissions from _landfills. Task 3 report – Review of methodology, data quality & scope for improvement._ _Final Report to Defra, October 2008._

CAA. (2023). Data and Analysis; datasets for 2023 flights from UK airports. Retrieved from Civil Aviation Authority: [https://www.caa.co.uk/data-and-analysis/uk-aviation-](https://www.caa.co.uk/data-and-analysis/uk-aviation-) market/airlines/uk-airline-data/uk-airline-data-2023/annual-2023/

CBS. (2023). Dutch Electricity Factor. Retrieved from [https://www.cbs.nl/nl-](https://www.cbs.nl/nl-) nl/achtergrond/2023/06/rendementen-en-co2-emissie-van-elektriciteitsproductie-in- nederland-update-2021

CCC. (2009). Meeting the UK aviation target-options for reducing emissions to 2050. Committee on Climate Change.

CHPQA. (2025). Combined Heat and Power Quality Assurance (CHPQA) Programme. Unpublished. Retrieved January 3, 2020

CIBSE. (2012). CIBSE Guide F. The Chartered Institution of Building Services Engineers.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

Clear. (2008). Dataset of motorcycle fuel consumption compiled by Clear for the development of _its motorcyle CO2 model used in its carbon offsetting products. Retrieved from_ [https://clear-offset.com/](https://clear-offset.com/)

CPI. (2019). The economic value of the UK paper-based industries 2019. Swindon: CPI. Retrieved from [https://thecpi.org.uk/library/PDF/Public/Publications/Reports/CPI-](https://thecpi.org.uk/library/PDF/Public/Publications/Reports/CPI-) Economic-Review-2019.pdf

DECC. (2014). Estimates of heat use in the United Kingdom in 2013. . Retrieved from Department of Energy and Climate Change: [https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment](https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment) \_data/file/386858/Estimates\_of\_heat\_use.pdf

DESNZ. (2025). Digest of UK Energy Statistics (DUKES). Retrieved from [https://www.gov.uk/government/statistics/digest-of-uk-energy-statistics-dukes-2025](https://www.gov.uk/government/statistics/digest-of-uk-energy-statistics-dukes-2025)

DfT. (2006). Average of tonnes per load to/from UK derived from Table 2.6, from Road Freight _Statistics 2005. Department for Transport ._

DfT. (2010). Transport Statistics Bulletin: Road Freight Statistics 2008 National Statistics Table

\*1.14d. Retrieved from [https://data.gov.uk/dataset/7efdee14-8cc9-406f-973e-\*](https://data.gov.uk/dataset/7efdee14-8cc9-406f-973e-*) f32ed8c28b7e/road-freight-statistics
DfT. (2017). Road Freight Statistics: Table RFS0141, July 2017. Retrieved from [https://www.gov.uk/government/collections/road-freight-domestic-and-international-](https://www.gov.uk/government/collections/road-freight-domestic-and-international-) statistics

DfT. (2019b). Passenger distance travelled (BUS03). Retrieved from [https://www.gov.uk/government/statistical-data-sets/bus03-passenger-distance-travelled](https://www.gov.uk/government/statistical-data-sets/bus03-passenger-distance-travelled)

DfT. (2023). Retrieved from Biofuels statistics: [https://www.gov.uk/government/publications/renewable-transport-fuel-obligation-rtfo-](https://www.gov.uk/government/publications/renewable-transport-fuel-obligation-rtfo-) compliance-reporting-and-verification

DfT. (2023). Department for Transport. Retrieved from Renewable Fuel Statistics: [https://www.gov.uk/government/collections/renewable-fuel-statistics](https://www.gov.uk/government/collections/renewable-fuel-statistics)

DfT. (2024a). Road freight statistics. Retrieved from [https://www.gov.uk/government/statistical-](https://www.gov.uk/government/statistical-) data-sets/rfs01-goods-lifted-and-distance-hauled

DfT. (2025). Biofuels statistics. Retrieved from [https://www.gov.uk/government/collections/renewable-fuel-statistics](https://www.gov.uk/government/collections/renewable-fuel-statistics)

DfT. (2025). df\_VEH0270: Vehicles registered for the first time by body type, make, generic model, model, fuel type and engine size: United Kingdom. [https://www.gov.uk/government/statistical-data-sets/vehicle-licensing-statistics-data-files](https://www.gov.uk/government/statistical-data-sets/vehicle-licensing-statistics-data-files).

DfT. (2025). Light rail and tram statistics. Retrieved from [https://www.gov.uk/government/collections/light-rail-and-tram-statistics](https://www.gov.uk/government/collections/light-rail-and-tram-statistics)

DfT and DVLA. (2024, September 24). Vehicle licensing statistics data files, df\_VEH0160\_GB. Retrieved from GOV.UK: [https://www.gov.uk/government/statistical-data-sets/vehicle-](https://www.gov.uk/government/statistical-data-sets/vehicle-) licensing-statistics-data-files

DLUHC. (2021). English Housing Survey 2019 to 2020: energy. Retrieved from Department for Levelling Up, Housing and Communities: [https://www.gov.uk/government/statistics/english-housing-survey-2019-to-2020-energy](https://www.gov.uk/government/statistics/english-housing-survey-2019-to-2020-energy)

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

DVLA. (2020). Vehicle statistics. Department for Transport, Driver and Vehicle Licensing Agency, and Driver and Vehicle Standards Agency. Retrieved from [https://www.gov.uk/government/collections/vehicles-statistics](https://www.gov.uk/government/collections/vehicles-statistics)

EC JRC. (2009). Environmental Impact Potentials of Textiles (IMPRO-Textiles). (E. C. Reports, Producer) Retrieved from [http://susproc.jrc.ec.europa.eu/textiles/docs/120423%20IMPRO%20Textiles\_Publication](http://susproc.jrc.ec.europa.eu/textiles/docs/120423%20IMPRO%20Textiles_Publication) %20draft%20v1.pdf

EcoAct. (2020). Homeworking emission Whitepaper. Retrieved from [https://info.eco-](https://info.eco-/) act.com/en/homeworking-emissions-whitepaper-2020

EEA. (2019). EMEP/EEA air pollutant emission inventory guidebook 2019. Retrieved from [https://www.eea.europa.eu/publications/emep-eea-guidebook-2019](https://www.eea.europa.eu/publications/emep-eea-guidebook-2019)

EEA. (2021a). Monitoring of CO2 emissions from passenger cars – Regulation (EU) 2019/631. Retrieved from [https://www.eea.europa.eu/data-and-maps/data/co2-cars-emission-20](https://www.eea.europa.eu/data-and-maps/data/co2-cars-emission-20)

EEA. (2021b). Monitoring of CO2 emissions from vans – Regulation 510/2011. Retrieved from [https://www.eea.europa.eu/data-and-maps/data/vans-16](https://www.eea.europa.eu/data-and-maps/data/vans-16)

EMISIA. (2022). COPERT 5.6. Retrieved from [https://www.emisia.com/?s=COPERT+4](https://www.emisia.com/?s=COPERT+4)

Environment Agency. (2010). Waste and Resources Assessment Tool for the Environment _(WRATE). Retrieved from_ [https://webarchive.nationalarchives.gov.uk/20140328085153/http://www2.environment-](https://webarchive.nationalarchives.gov.uk/20140328085153/http://www2.environment-) agency.gov.uk/research/commercial/102922.aspx

Environment Agency. (2020). Climate Change Agreements. Retrieved from [https://www.gov.uk/guidance/climate-change-agreements--2](https://www.gov.uk/guidance/climate-change-agreements--2)

EUROCONTROL. (2024). Small emitters tool. Retrieved from Eurocontrol: [https://www.eurocontrol.int/publication/small-emitters-tool-set-2024](https://www.eurocontrol.int/publication/small-emitters-tool-set-2024)

European Commission. (2019). 2011/877/EU: Commission Implementing Decision of 19 _December 2011establishing harmonised efficiency reference values for separate_ _production of electricity and heat in application of Directive 2004/8/EC of the European_ _Parliament and of the Council and re. (E. Commission, Producer) Retrieved from EUR-_ Lex: [https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32011D0877](https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32011D0877)

EV Database. (2023). [https://ev-database.uk/](https://ev-database.uk/). Retrieved from [https://ev-database.uk/](https://ev-database.uk/)

Exergia et al. (2015). Study on actual GHG data for diesel, petrol, kerosene and natural gas. A study by Exergia, E3 Modelling and COWI for the European Commission, DG ENER. Retrieved from [https://ec.europa.eu/energy/sites/ener/files/documents/Study%20on%20Actual%20GHG](https://ec.europa.eu/energy/sites/ener/files/documents/Study%20on%20Actual%20GHG) %20Data%20Oil%20Gas\_Project%20Interim%20Report.pdf

Forest Research. (2016). Carbon emissions of different fuels. Retrieved from [http://www.forestry.gov.uk/fr/beeh-abslby](http://www.forestry.gov.uk/fr/beeh-abslby)

Forest Research. (2016a). Biomass Environmental Assessment Tool, BEAT2. Retrieved from Forest Research: [https://www.forestry.gov.uk/fr/beeh-9uynmd](https://www.forestry.gov.uk/fr/beeh-9uynmd)

Forest Research. (2023). Carbon emissions of different fuels. Retrieved from [https://www.forestresearch.gov.uk/tools-and-resources/fthr/biomass-energy-](https://www.forestresearch.gov.uk/tools-and-resources/fthr/biomass-energy-) resources/reference-biomass/facts-figures/carbon-emissions-of-different-fuels/

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

Green Car Guide. (2023). [https://www.greencarguide.co.uk/](https://www.greencarguide.co.uk/). Retrieved from [https://www.greencarguide.co.uk/](https://www.greencarguide.co.uk/)

Greenhouse Gas Protocol. (2011). Corporate value chain (Scope 3) accounting and reporting standard. World Resources Institute and World Business Council for Sustainable _Development._

Hamade, R. A. (2020). Life Cycle Analysis of AA Alkaline Batteries. Procedia Manufacturing, 43, 415–22.

IATA. (2018). January Passenger Demand Growth Slows on Temporary Factors. Retrieved April 10, 2019, from [https://www.iata.org/pressroom/pr/Pages/2018-03-08-01.aspx](https://www.iata.org/pressroom/pr/Pages/2018-03-08-01.aspx)

ICCT. (2017). FROM LABORATORY TO ROAD: A 2017 update of official and 'real-world' fuel _consumption and CO2 values for passenger cars in Europe. International Council for_ Clean Transportation. Retrieved from [https://www.theicct.org/sites/default/files/publications/Lab-to-road-2017\_ICCT-](https://www.theicct.org/sites/default/files/publications/Lab-to-road-2017_ICCT-) white%20paper\_06112017\_vF.pdf

IGD. (2018). UK Food & Grocery Retail Logistics Overview Date. Retrieved from [http://www.igd.com/our-expertise/Supply-chain/Logistics/3457/UK-Food--Grocery-Retail-](http://www.igd.com/our-expertise/Supply-chain/Logistics/3457/UK-Food--Grocery-Retail-) Logistics-Overview/

IMO. (2009). PREVENTION OF AIR POLLUTION FROM SHIPS, Second IMO GHG Study _2009, Marine Guidance Note MGN 347 (M), . Retrieved from_ [https://www.gov.uk/government/organisations/maritime-and-coastguard-agency](https://www.gov.uk/government/organisations/maritime-and-coastguard-agency)

IPCC. (2007). Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and _III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change._ Geneva, Switzerland . Retrieved from [https://www.ipcc.ch/site/assets/uploads/2018/02/ar4\_syr\_full\_report.pdf](https://www.ipcc.ch/site/assets/uploads/2018/02/ar4_syr_full_report.pdf)

IPCC. (2014). Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and _III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change._ Geneva, Switzerland. Retrieved from [https://www.ipcc.ch/site/assets/uploads/2018/02/SYR\_AR5\_FINAL\_full.pdf](https://www.ipcc.ch/site/assets/uploads/2018/02/SYR_AR5_FINAL_full.pdf)

ITP/Greenview. (2021). Hotel Footprinting Tool. Retrieved from [https://www.hotelfootprints.org](https://www.hotelfootprints.org/)

JEC WTW v4a. (2014). WELL-TO-WHEELS ANALYSIS OF FUTURE AUTOMOTIVE FUELS _AND POWERTRAINS IN THE EUROPEAN CONTEXT. By European Commission, JRC-_ EUCAR-CONCAWE. Edwards, R; Larive, J.F; Rickeard, D; Weindorf , W. Retrieved from [https://ec.europa.eu/jrc/en/publication/eur-scientific-and-technical-research-reports/well-](https://ec.europa.eu/jrc/en/publication/eur-scientific-and-technical-research-reports/well-) tank-report-version-4a-jec-well-wheels-analysis

JEC WTW v5. (2020). JEC Well-to-Tank report v5. Luxembourg: By European Commission, JRC-EUCAR-CONCAWE. Prussi, M., Yugo, M., De Prada, L., Padella, M., Edwards, R. and Lonza, L. doi:10.2760/959137

L.E.K. Consulting. (2002). Methodology for settlements with <25k population (Appendix 10.5.1). Retrieved from [https://webarchive.nationalarchives.gov.uk/20110304135427/](https://webarchive.nationalarchives.gov.uk/20110304135427/) Lee, DS, Fahey, DW, Skowron, A et al. (2021). The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018. Atmospheric Environment, 244.117834. \*ISSN 1352-2310. [https://doi.org/10.1016/j.atmosenv.2020.117834.\*](https://doi.org/10.1016/j.atmosenv.2020.117834.*)

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

MCA. (2017). Marine Guidance Note MGN 347 (M). Retrieved from Maritime and Coastguard Agency: [http://www.dft.gov.uk/mca/mcga07-home/shipsandcargoes/mcga-](http://www.dft.gov.uk/mca/mcga07-home/shipsandcargoes/mcga-) shipsregsandguidance/marinenotices/mcga-mnotice.htm?textobjid=82A572A99504695B

McKinnon, A. (2007). Synchronised auditing of truck utilisation and energy efficiency: a review of the British Government's transport KPI programme. In proceedings of the 11th World _conference on transport research. Retrieved from_ [http://www.greenlogistics.org/SiteResources/77a765d8-b458-4e5f-b9e0-](http://www.greenlogistics.org/SiteResources/77a765d8-b458-4e5f-b9e0-) 1827e34f2f1f\_Review%20of%20Transport%20KPI%20programme%20(WCTR%202007) .pdf

National Grid. (2021). National Grid. Retrieved from [https://www.nationalgridgas.com/data-and-](https://www.nationalgridgas.com/data-and-) operations/calorific-value-cv

Ofgem. (2015). The UK Solid and Gaseous Biomass Carbon Calculator. Retrieved from [https://www.ofgem.gov.uk/publications-and-updates/uk-solid-and-gaseous-biomass-](https://www.ofgem.gov.uk/publications-and-updates/uk-solid-and-gaseous-biomass-) carbon-calculator

Ofgem. (2020). Typical Domestic Consumption values 2020. Retrieved from Office of Gas and Electricity Markets: [https://www.ofgem.gov.uk/publications/decision-typical-domestic-](https://www.ofgem.gov.uk/publications/decision-typical-domestic-) consumption-values-2020

Ofgem. (2021). The UK Bioliquid Carbon Calculator. Retrieved from [https://www.gov.uk/government/publications/biofuels-carbon-calculator-rtfo](https://www.gov.uk/government/publications/biofuels-carbon-calculator-rtfo)

Ofgem. (2021a). Biomass Sustainability Dataset 2019-20. Retrieved from [https://www.ofgem.gov.uk/publications/biomass-sustainability-dataset-2019-20](https://www.ofgem.gov.uk/publications/biomass-sustainability-dataset-2019-20)

ORR. (2021a). Estimates of passenger and freight energy consumption and carbon dioxide _equivalent (CO2e) emissions-Table 2.101 (p). Retrieved from Office of the Rail_ Regulator (ORR): [https://dataportal.orr.gov.uk/displayreport/html/html/31212a97-cf7a-](https://dataportal.orr.gov.uk/displayreport/html/html/31212a97-cf7a-) 42d5-9fe3-a134b5c08b6a

ORR. (2025). Official Statistics. Retrieved from : [http://dataportal.orr.gov.uk/browsereports/9](http://dataportal.orr.gov.uk/browsereports/9)

Pressley, P. N., & al, e. (2015). Analysis of material recovery facilities for use in life-cycle assessment. Waste Management, Vol 45, pp. 307-317.

Ricardo. (2026). UK Greenhouse Gas Inventory, 1990 to 2025: Annual Report for Submission _under the Framework Convention on Climate Change. Ricardo Energy & Environment._ Brown P, Cardenas L, Del Vento S, Karagianni E, MacCarthy J, Mullen P, Gorji, S, Richmond B, Thistlethwaite G, Thomson A, Wakeling D, Willis D. Retrieved from [https://naei.beis.gov.uk/reports/index](https://naei.beis.gov.uk/reports/index)

Ricardo Energy & Environment. (2015). UK Greenhouse Gas Inventory, 1990 to 2013: Annual _Report for Submission under the Framework Convention on Climate Change. MacCarthy_ J, Broomfield M, Brown P, Buys G, Cardenas L, Murrells T, Pang Y, Passant N, Thistlethwaite G, Watterson J. Retrieved from [https://uk-](https://uk-/) air.defra.gov.uk/assets/documents/reports/cat07/1512091113\_ukghgi-90-13\_Issue\_1.pdf

Ricardo Energy & Environment. (2018). Assessing the impacts of selected options for regulating _CO2 emissions from new passenger cars and vans after 2020. Retrieved from_ [https://ec.europa.eu/clima/sites/clima/files/transport/vehicles/docs/ldv\_post\_2020\_co2\_e](https://ec.europa.eu/clima/sites/clima/files/transport/vehicles/docs/ldv_post_2020_co2_e)

n.pdf
Ricardo Energy & Environment. (2021). UK Greenhouse Gas Inventory, 1990 to 2019: Annual _Report for submission under the Framework Convention on Climate Change. Ricardo_

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

Energy & Environment. Brown P, Cardenas L, Choudrie S, Del Vento S, Karagianni E, MacCarthy J, Mullen P, Passant N, Richmond B, Smith H, Thistlethwaite G, Thomson A, Turtle L, Wakeling D. Retrieved from [https://naei.beis.gov.uk/reports/reports?report\_id=1015](https://naei.beis.gov.uk/reports/reports?report_id=1015)

Ricardo Energy & Environment. (2022). UK Greenhouse Gas Inventory, 1990 to 2020: Annual _Report for Submission under the Framework Convention on Climate Change. Ricardo_ Energy & Environment. Brown P, Cardenas L, Choudrie S, Del Vento S, Karagianni E, MacCarthy J, Mullen P, Passant N, Richmond B, Thistlethwaite G, Thomson A, Wakeling

D. Retrieved from [https://naei.beis.gov.uk/reports/reports?report\_id=998](https://naei.beis.gov.uk/reports/reports?report_id=998)
Ricardo-AEA. (2014). UK Greenhouse Gas Inventory, 1990 to 2012: Annual Report for _Submission under the Framework. Webb N, Broomfield M, Brown P, Buys G, Cardenas_ L,. Retrieved from [https://uk-](https://uk-/) air.defra.gov.uk/assets/documents/reports/cat07/1404251327\_1404251304\_ukghgi-90- 12\_Issue1.pdf

RISE. (2019). The carbon footprint of carton packaging 2019. Zurich: Pro Carton. Retrieved from [https://www.procarton.com/wp-content/uploads/2020/03/Carbon-Footprint-Report-](https://www.procarton.com/wp-content/uploads/2020/03/Carbon-Footprint-Report-)

2019.pdf
RTE. (2022). French Electricity Factor. Retrieved from [https://www.rte-](https://www.rte-/) france.com/fr/eco2mix/eco2mix-telechargement

Sausen , R., Isaksen, I., Grewe, V., Hauglustaine, D., Lee, D., Myhre, G., . . . Zerofos, C. (2005). Aviation radiative forcing in 2000: An update on IPCC (1999). Meteorologische _Zeitschrift, 14(4), 555-561._

SEAI. (2023). Irish Electricity Factor. Retrieved from [https://www.seai.ie/data-and-insights/seai-](https://www.seai.ie/data-and-insights/seai-) statistics/key-statistics/electricity/

SMMT. (2019). Web site Homepage. Retrieved from [https://www.smmt.co.uk/](https://www.smmt.co.uk/)

Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Avery, M. Tignor and H.L. Miller. (2007). Contribution of Working Group I to the Fourth Assessment Report of the _Intergovernmental Panel on Climate Change. Cambridge, United Kingdom: Cambridge_ University Press,. Retrieved from [https://www.ipcc.ch/site/assets/uploads/2018/05/ar4\_wg1\_full\_report-1.pdf](https://www.ipcc.ch/site/assets/uploads/2018/05/ar4_wg1_full_report-1.pdf)

Tassou, S.A., et al. (2009). Food transport refrigeration-Approaches to reduce energy consumption and environmental impacts of road transport. Applied Thermal Engineering, _29(8-9), 1467-1477._

TU Graz. (2011). Reduction and testing of Greenhouse Gas Emissions from Heavy Duty _Vehicles-LOT 2; Development and testing of certification procedure CO2 and fuel_ _consumption of HDV. A report by TU Graz, TNO, VTT, AVL, LAT and TUV Nord for the_ European Commission, DG Climate Action. Retrieved from [https://ec.europa.eu/clima/sites/clima/files/transport/vehicles/heavy/docs/hdv\_2011\_01\_0](https://ec.europa.eu/clima/sites/clima/files/transport/vehicles/heavy/docs/hdv_2011_01_0) 9\_en.pdf

University of Westminster. (2008). Using official data sources to analyse the light goods vehicle _fleet and operations in Britain. Green Logistics Report, Transport Studies Group,_ University of Westminster. Allen, J; Browne, M. Retrieved from [https://westminsterresearch.westminster.ac.uk/item/91113/using-official-data-sources-to-](https://westminsterresearch.westminster.ac.uk/item/91113/using-official-data-sources-to-) analyse-the-light-goods-vehicle-fleet-and-operations-in-britain

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

VCA. (2023, July). Average Emissions Monitoring. Retrieved from Vehicle Certification Agency: [https://www.vehicle-certification-agency.gov.uk/fuel-consumption-co2/average-](https://www.vehicle-certification-agency.gov.uk/fuel-consumption-co2/average-) emissions-monitoring/co2-emissions-from-new-passenger-cars/#topic-title

VDA. (2014). Facts and Arguments about Fuel Consumption. Retrieved from [www.vda.de/dam/vda/publications/2014/facts-and-arguments-about-fuel-](http://www.vda.de/dam/vda/publications/2014/facts-and-arguments-about-fuel-) consumption.pdf

World Resources Institute. (2013). Technical Guidance for Calculating Scope 3 Emissions. Retrieved 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 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 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

Data used in this methodology should, so far as is possible, meet the data quality indicators
described in Table 1.1 below.

Table 1.1: Data Quality Indications for the material use GHG factors

| 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 | Studies are reviewed to ensure they account for the lifecycle stages covered in Figure 6. |
| 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. | Studies are reviewed for logical consistency in the use of methods and claims made. The use of publicly available studies from a wide range of sources means that it is not possible to ensure complete methodological consistency between materials, but studies are assessed to ensure all necessary lifecycle stages are included. |
| Reproducibility | An independent practitioner should be able to follow the method and arrive at the same results. | Preference is given to peer reviewed studies, though in practice most published LCA papers do not provide sufficient data(e.g. details of all lifecycle inventories) to allow reproduction, as most LCAs are based on data that are commercially confidential or provided under licence. |
| 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

Data has been taken from a combination of trade associations, who provide average
information at a UK or European level, data from the Ecoinvent database and reports/data from
third parties (e.g. academic journals, Intergovernmental Panel on Climate Change). Data on
wood and many products are taken from published life cycle assessments as no trade
association eco-profile is available. Data sources for transport are referenced in Section 12.
Data on waste management options has been modelled using Ecoinvent data and WRATE.
Some data sources used do not meet the quality criteria. The implications of this are discussed
in the following section.

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

| taken in using these numbers. Table 1.2 Data Sources | and government. This section details data which do not meet the expected quality standard set out in the methodology of this project but were nevertheless 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 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. |
| --- | --- |
| Material | Reference |
| Aluminium cans and foil | European Aluminium Association (2018) Environmental Profile Report for the European Aluminium Industry CE Delft (2007) Environmental Indices for the Dutch Packaging Tax DESNZ (2024) GHG Conversion factors Environment Agency (2010) Waste and Resources Assessment Tool for the Environment (WRATE) |
| Steel Cans | World Steel Association (2021) Life cycle inventory (LCI) study 2020 data release World Steel Association (2022) Worldsteel LCA eco-profile Tinplate DESNZ (2024) GHG Conversion factors Swiss Packaging Institute (1997) BUWAL Environment 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) |

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

| Material | Reference |
| --- | --- |
| Glass | Ecoinvent3 (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. |

* * *

| Material | Reference |
| --- | --- |
| Wood | 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) |  |
| Ecoinvent3(2024)Sawnwood,beam,softwood,dried(u=20%),planed{CH} | market for sawnwood,beam,softwood,dried(u=20%),planed |
| Ecoinvent3(2024)Particleboard,uncoated{RER} | particle board production,uncoated,average glue mix |
| Ecoinvent3(2024)Plywood,for indoor use{RER} | production |
| Ecoinvent3(2024)Oriented strand board{RER} | production |
| Ecoinvent3(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 theUKpaper-basedindustries2019,CPI |
| DESNZ(2024)Company GHG ReportingGuidelines,DESNZ |  |
| Ecoinvent3(2024)Corrugatedboardbox{RER} | production |
| Ecoinvent3(2024)Deinkedpulp,wetlap{RoW} | treatmentof waste paper to pulp,wetlap,totallychlorinefreebleached |
| Ecoinvent3(2024)Foldingboxboardcart{RER} | foldingboxboardcartonproduction |
| Ecoinvent3(2024)Paper,newsprint{RER} | paperproduction,newsprint,virgin |
| Ecoinvent3(2024)Paper,newsprint{RER} | paperproduction,newsprint, recycled |
| FEFCO(2018)EuropeandatabaseforCorrugatedBoardLifeCycleStudies,FEFCO |  |
| FEFCO(Accessed2/4/2024)CircularbyDesign(webpage),FEFCO |  |
| WRAP(2020)CompositionalanalysisofLocalAuthoritycollectedandnon-LocalAuthoritycollectednon-householdmunicipalwaste(England),WRAP |  |
| Books | Estimatebased onpaper |
| Scrap Metal | British Metals Recycling Association(website37) |
| Ecoinvent(2020)copper production,cathode, solvent extraction and electrowinning process |  |
| Giurco,D.,Stewart,M.,Suljada,T.,and Petrie,J.(2006)Copper Recycling Alternatives:An Environmental Analysis |  |
| Electrical goods | Ecoinvent(2020)market for computer,desktop without screen |
| Ecoinvent(2020)market for computer,laptop |  |
| Ecoinvent(2020)market for dishwasher |  |
| Ecoinvent(2020)market for dryer |  |
| Ecoinvent(2020)market for electric kettle |  |
| Ecoinvent(2020)market for hair dryer |  |
| Ecoinvent(2020)market for microwave oven production |  |
| Ecoinvent(2020)market for printer,laser,colour |  |
| Ecoinvent(2020)market for refrigerator |  |
| Ecoinvent(2020)battery cell production,Li-ion |  |
| Ecoinvent(2020)battery production,NiMH,rechargeable,prismatic |  |
| HamadeR.,Al Ayache,R.,Bou Ghanem,M.and Ammouri,A.(2020)“Life Cycle Analysis of AA Alkaline Batteries”,Procedia Manufacturing,4:415-22 |  |
| Food and Drink | Tassou,S,Hadawey,A,Ge,Y and Marriot,D(2008)FO405 Greenhouse Gas Impacts of Food Retailing |
| DEFRA and ONS(2009)Family food and expenditure survey |  |
| DECC(2013)Energy consumption in the UK |  |
| Compost(food and garden) | Boldrin,A.,Hartling,K.,Laugen,M.and Christensen,T(2010)“Environmental inventory modelling of the use of compost and peat in growth media preparation” |

37
[https://www.recyclemetals.org/about-metal-recycling.html](https://www.recyclemetals.org/about-metal-recycling.html).

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

| Material | Reference |
| --- | --- |
| 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} |

* * *

| Material | Reference |
| --- | --- |
| 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 | Ecoinvent3(2024)Concrete，normal{GLO} |
| Bricks | Environment Agency(2011)Carbon CalculatorUSEPA(2003)Background Document for Life-Cycle Greenhouse Gas Conversion factors for Clay Brick Reuse and Concrete RecyclingChristopher Koroneos，Aris Dompros，"Environmental assessment of brick production in Greece”，Building and Environment，Volume42，Issue5，May 2007，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.和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. |
| Dichlorodifluoro-methane CFC12(R12 refrigerant) | CCl2F2 | 0.32 | 100 | 10,900 |  |
| Difluoromono-chloromethaneHCFC22(R22 refrigerant) | CHClF2 | 0.2 | 12 | 1,810 |  |

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

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).

* * *

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 factors. This is provided for organisations wishing to use fully consistent time
series data e.g. those who are retrospectively updating their previous years’ emissions estimates.

Table 1.4 Base electricity generation emissions data – most recent datasets for time
series

| Data Year | Electricity Generation(1) | Total Grid Losses(2) | UK electricity generation emissions(3)，ktonne |  |  |
| --- | --- | --- | --- | --- | --- |
| GWh | % | CO2 | CH4 | N2O |  |
| 2010 | 344,127 | 7.4% | 175,846 | 3.740 | 2.180 |
| 2011 | 329,791 | 7.9% | 162,552 | 3.830 | 2.215 |
| 2012 | 324,827 | 8.0% | 176,864 | 4.372 | 2.874 |
| 2013 | 318,753 | 7.6% | 164,561 | 4.871 | 2.767 |
| 2014 | 298,064 | 8.1% | 137,167 | 5.403 | 2.334 |
| 2015 | 297,520 | 8.3% | 114,192 | 6.169 | 2.056 |
| 2016 | 296,952 | 7.8% | 89,146 | 6.263 | 1.317 |
| 2017 | 293,630 | 8.1% | 77,714 | 6.258 | 1.189 |
| 2018 | 289,129 | 8.1% | 70,416 | 6.677 | 1.160 |
| 2019 | 282,958 | 8.2% | 61,913 | 6.982 | 1.056 |
| 2020 | 269,904 | 8.7% | 52,148 | 6.987 | 1.029 |
| 2021 | 270,061 | 8.5% | 58,745 | 7.520 | 1.125 |
| 2022 | 284,067 | 9.1% | 57,879 | 6.491 | 0.960 |
| 2023 | 253,044 | 9.5% | 45,672 | 5.846 | 0.853 |
| 2024 | 246,899 | 9.0% | 39,151 | 7.033 | 1.005 |
| 2025 | 253,018 | 9.0% | 38,919 | 7.206 | 0.978 |

Notes:

(1) Based upon calculated total for all electricity generation (GWh supplied) from ET 5.1, Table 5a, with a reduction of the total
for autogenerators based the share of this that is actually exported to the grid. This information has historically been provided
the NAEI team directly from the DUKES team, but has been replicated in the 2026 Conversion Factors publication using
Energy Trends Tables 5.1, 5.2 and 5.4.
(2) Based upon calculated net grid losses from data in DUKES Table 5.1.2.

(3) Emissions calculated based on the methodology set out in Section 3.

* * *

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 |  |
| 2010 | 0.51099 | 0.00030 | 0.00168 | 0.51297 | 0.04071 | 0.00002 | 0.00013 | 0.04086 | 0.55170 | 0.00033 | 0.00181 | 0.55384 | 2% |
| 2011 | 0.49289 | 0.00033 | 0.00178 | 0.49500 | 0.04233 | 0.00003 | 0.00015 | 0.04251 | 0.53523 | 0.00035 | 0.00193 | 0.53751 | 3% |
| 2012 | 0.54449 | 0.00038 | 0.00234 | 0.54721 | 0.04733 | 0.00003 | 0.00020 | 0.04757 | 0.59182 | 0.00041 | 0.00255 | 0.59478 | 4% |
| 2013 | 0.51626 | 0.00043 | 0.00230 | 0.51899 | 0.04226 | 0.00004 | 0.00019 | 0.04248 | 0.55852 | 0.00046 | 0.00249 | 0.56147 | 5% |
| 2014 | 0.46019 | 0.00051 | 0.00207 | 0.46278 | 0.04064 | 0.00004 | 0.00018 | 0.04087 | 0.50084 | 0.00055 | 0.00226 | 0.50365 | 7% |
| 2015 | 0.38381 | 0.00058 | 0.00183 | 0.38622 | 0.03476 | 0.00005 | 0.00017 | 0.03497 | 0.41857 | 0.00063 | 0.00200 | 0.42120 | 7% |
| 2016 | 0.30020 | 0.00059 | 0.00118 | 0.30197 | 0.02539 | 0.00005 | 0.00010 | 0.02554 | 0.32559 | 0.00064 | 0.00128 | 0.32751 | 6% |
| 2017 | 0.26467 | 0.00060 | 0.00107 | 0.26634 | 0.02347 | 0.00005 | 0.00010 | 0.02362 | 0.28814 | 0.00065 | 0.00117 | 0.28996 | 6% |
| 2018 | 0.24355 | 0.00065 | 0.00106 | 0.24526 | 0.02133 | 0.00006 | 0.00009 | 0.02148 | 0.26488 | 0.00070 | 0.00116 | 0.26674 | 7% |
| 2019 | 0.21881 | 0.00069 | 0.00099 | 0.22049 | 0.01962 | 0.00006 | 0.00009 | 0.01977 | 0.23842 | 0.00075 | 0.00108 | 0.24025 | 8% |
| 2020 | 0.19321 | 0.00072 | 0.00101 | 0.19494 | 0.01850 | 0.00007 | 0.00010 | 0.01867 | 0.21171 | 0.00079 | 0.00111 | 0.21361 | 8% |

* * *

2026 Government greenhouse gas conversion factors for company reporting: Methodology paper

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 | TOTAL |  |
| 2010 | 0.49589 | 0.00030 | 0.00163 | 0.49782 | 0.03950 | 0.00002 | 0.00013 | 0.03966 | 0.53539 | 0.00032 | 0.00176 | 0.53747 | 2% |
| 2011 | 0.48124 | 0.00032 | 0.00174 | 0.48330 | 0.04133 | 0.00003 | 0.00015 | 0.04151 | 0.52257 | 0.00034 | 0.00189 | 0.52480 | 3% |
| 2012 | 0.52934 | 0.00037 | 0.00228 | 0.53198 | 0.04602 | 0.00003 | 0.00020 | 0.04625 | 0.57535 | 0.00040 | 0.00248 | 0.57823 | 4% |
| 2013 | 0.49616 | 0.00041 | 0.00221 | 0.49878 | 0.04061 | 0.00003 | 0.00018 | 0.04082 | 0.53677 | 0.00044 | 0.00239 | 0.53961 | 5% |
| 2014 | 0.43776 | 0.00048 | 0.00197 | 0.44022 | 0.03866 | 0.00004 | 0.00017 | 0.03888 | 0.47643 | 0.00053 | 0.00215 | 0.47910 | 7% |
| 2015 | 0.37077 | 0.00056 | 0.00177 | 0.37310 | 0.03357 | 0.00005 | 0.00016 | 0.03379 | 0.40434 | 0.00061 | 0.00193 | 0.40688 | 7% |
| 2016 | 0.29511 | 0.00058 | 0.00116 | 0.29684 | 0.02496 | 0.00005 | 0.00010 | 0.02511 | 0.32007 | 0.00063 | 0.00125 | 0.32195 | 6% |
| 2017 | 0.26073 | 0.00059 | 0.00106 | 0.26238 | 0.02313 | 0.00005 | 0.00009 | 0.02327 | 0.28386 | 0.00064 | 0.00115 | 0.28565 | 6% |
| 2018 | 0.23759 | 0.00063 | 0.00104 | 0.23926 | 0.02081 | 0.00006 | 0.00009 | 0.02096 | 0.25841 | 0.00069 | 0.00113 | 0.26022 | 7% |
| 2019 | 0.21210 | 0.00067 | 0.00096 | 0.21373 | 0.01901 | 0.00006 | 0.00009 | 0.01916 | 0.23111 | 0.00073 | 0.00105 | 0.23289 | 8% |
| 2020 | 0.18635 | 0.00070 | 0.00097 | 0.18803 | 0.01784 | 0.00007 | 0.00009 | 0.01800 | 0.20420 | 0.00077 | 0.00107 | 0.20603 | 8% |

Notes: \* The updated 2016 methodology uses data on the contribution of electricity from the different interconnect ors, 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.

\\mathsf{E m i s s i o n\ F a c t o r,i l e c t t o f y,C O N S L\ A C C D}=\\mathsf{E m i s s i o n\ F a c t o r,,,E i s e c t e t i y,,,C I S e e t t n\ C C C A A A\ C C C S S,S S\ S S\\5}.\

\\begin dmath}\ {mathrm E E e n t a t i o n ~~P amathit t o c~~(\\mathbf{E a c c h i c o l y~~L C S S}{bf}{\\bf1}}{\\bf{bf}{\\bf1

* * *

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 | 0.478 |  |
| 2002 | 0.230 | 0.457 |  |
| 2003 | 0.234 | 0.469 |  |
| 2004 | 0.228 | 0.454 |  |
| 2005 | 0.221 | 0.439 |  |
| 2006 | 0.231 | 0.459 |  |
| 2007 | 0.231 | 0.461 |  |
| 2008 | 0.224 | 0.447 |  |
| 2009 | 0.222 | 0.440 |  |
| 2010 | 0.219 | 0.431 |  |
| 2011 | 0.215 | 0.511 |  |
| 2012 | 0.205 | 0.398 |  |
| 2013 | 0.208 | 0.407 |  |
| 2014 | 0.202 | 0.400 |  |
| 2015 | 0.196 | 0.392 |  |
| 2016 | 0.186 | 0.374 |  |
| 2017 | 0.174 | 0.353 |  |
| 2018 | 0.173 | 0.345 |  |
| 2019 | 0.174 | 0.338 |  |
| 2020 | 0.178 | 0.343 |  |
| 2021 | 0.184 | 0.354 |  |
| 2022 | 0.176 | 0.338 |  |
| 2023 | 0.174 | 0.332 |  |

Note, as these factors were not updated in the 2026 publication, the 2023 data year is the most
recent one that has been used in the preparation of the UK GHG Conversion Factors, hence why
no subsequent years appear in the table.

* * *

2024 Government greenhouse gas conversion factors for company reporting: Methodology paper

This publication is available from: [https://www.gov.uk/government/collections/government-](https://www.gov.uk/government/collections/government-) conversion-factors-for-company-reporting

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). Please tell us what format you need. It will help us if you say what assistive technology you use.