Journey emissions comparisons: Methodology and guidance
Updated 19 October 2021
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This publication is available at https://www.gov.uk/government/publications/transport-energy-and-environment-statistics-notes-and-definitions/journey-emissions-comparisons-methodology-and-guidance
The purpose of this document is to provide further details on the methods used when producing the Department for Transport’s journey emission comparisons, and facilitate others in generating their own comparisons using this methodology.
As of May 2021, there are 2 separate publications using journey emissions comparison data:
- Transport and environment statistics 2021
- Journey emission comparisons
Journey emission comparison statistics within these publications have been designated as Experimental Statistics as the reporting of this type of data is a recent development for the Department for Transport. Additionally, there are known imprecisions within the data, and missing information that limits analysis.
As a reflection of the experimental badging being used we would welcome any feedback that readers of this publication would like to provide, via the email address provided below. All publications, tables and underlying raw data are available on our web page.
In constructing these journey emission comparisons, DfT aimed to provide a set of representative journeys a person in the UK might take, via a wide range of transport modes, and thereby demonstrate the positive contribution to overall emissions that switching to another, less-polluting mode of transport might have. We also wanted to provide members of the public and other organisations with worked-out examples of calculating journey emissions using data from government sources, so that they could do this themselves.
Data Sources
The basis for DfT’s journey emission comparisons come from BEIS’ conversion factors, published annually. Conversion factors allow organisations and individuals to calculate greenhouse gas (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. For transport, the conversion factors provide the amount of GHG kilograms emitted per mile travelled by that mode.
The UK GHG conversion factors have been developed as part of the NAEI (National Atmospheric Emissions Inventory) contract, managed by Ricardo Energy and Environment, which includes the UK Air Quality Pollutant Inventory (AQPI) and the UK Greenhouse Gas Inventory (GHGI). Further details on what data is included within the conversion factors is available in the UK GHGI Annual Report, 1990 to 2019 (BEIS/Ricardo Energy and Environment, 2021).
Conversion factors are produced by the Ricardo Consortium, which combine data on vehicle emissions with data from the Department for Transport and other sources on the population and mileage for that vehicle, to derive an average carbon output per mile for that vehicle. These data may then be selectively modified by BEIS/Ricardo to account for real-world factors that averaging from populations may not capture. More detail on how these conversion factors are determined can be found in the BEIS methodology document, published alongside the conversion factors.
The BEIS conversion factors were used as the basis for the journey emission comparisons developed by DfT, as they provided the best breadth across vehicles for comparisons and the simplest methodology for implementation in a variety of areas. To use BEIS’ conversion factors, DfT developed a series of example journeys within the UK via different vehicles, measured the distance of the journey, and combined this with the conversion factors to provide an estimated emission for the journey in carbon dioxide equivalent (CO2e). For some modes of transport, we modified the conversion factors with guidance from BEIS and Ricardo (detailed below).
Methodology
BEIS’ conversion factors offer a variety of factors for each mode of travel. The factors selected by DfT for the comparisons depended on circumstance.
For instance, most comparisons include both petrol and diesel cars, but for clarity of presentation the journey emission comparisons only include the average size car of both fuel types. Emissions can vary noticeably for large and small cars. The interactive version of the comparisons, accessible here, allows for more comparisons and includes large and small cars as comparisons.
Sometimes, the mode of travel determines the choice of factor: train travel includes national rail, international rail (for example, Eurostar), tram and London underground, so most London journeys will use the London underground factor, while other rail journeys may use the national rail factor.
Determining distance
These factors are multiplied by the distance of the journey in miles, but some modes of transport can follow a shorter path than others on the same journey. The following methods are used to measure distance.
Road vehicles - the journey emission comparisons use Open Street Map to measure the distance of given journeys via road vehicles between the origin and destination. Open Street Map was used so that routes chosen for comparison would be determined by a program accessible to members of the public. Of the routing services OSM provides (OSRM or GraphHopper), the routing that provided the shortest journey miles was chosen to represent the distance of the journey. This method was also used to provide distances measuring bicycle and walking distances, which have no carbon emissions.
Planes - calculated as a linear path, (for example, shortest distance between ports). This does not consider great circle distance or waiting for a landing slot. The conversion factors for flights already include a given ‘uplift’ to take into account these issues. We also include a journey for the origin to the nearest airport, and form the nearest landing airport to the destination. This journey to and from the airport was calculated as a petrol car journey.
Ferry journeys in the UK can be complex due to the limited number of ferry terminals and their relative inaccessibility to forms of public transport. In our journey example that uses ferries, from Leeds Town Hall to Belfast City Hall, Road vehicles use the car ferry at Larne to Cairnryan, and then travel from here to Belfast town hall. Train journeys include a bus journey from Edinburgh station to the car ferry at Larne, and then proceed as before. Foot and bicycle journeys use a foot ferry from Heysham to Douglas, on the Isle of Man, and from Douglas to Belfast. Ferry journeys are calculated as a linear path, for example, the shortest distance between ports.
Trains, tubes - railmiles.me provides accurate distances using public data on train timetables. Distances between tube stations are provided as an FOI response.
Trams, buses, coaches - for simplicity of analysis, coaches and buses are assumed to take the same journey as cars. Tram data for the journey we have provided has been published as a response to an FOI which asked the distance covered between stations:
- Wimbledon to Reeves Corner = 9.54km
- Reeves Corner to West Croydon = 0.69km
- West Croydon to Wellesley road = 0.653km
- Wellesley Road to West Croydon = 0.437km
Table 1: Example journeys provided in the comparisons, origins and destinations with co-ordinates
| Journey | Origin | Destination |
|---|---|---|
| Bristol-London | Bristol City Centre (51.4538, -2.5973) | Charing Cross station (51.508, -0.125) |
| Cardiff-Manchester | Cardiff Castle (51.481312, -3.1805) | Manchester Piccadilly Gardens (53.480759, -2.242631) |
| Croydon-Wimbledon | East Croydon station (51.3752, -0.0923) | Wimbledon station (51.4232, - 0.2043) |
| Leeds-Belfast | Leeds Town Hall (53.8003, -1.5497) | Belfast City Hall (54.5964411, -5.9302761) |
| London-Newquay | Charing Cross station (51.508, -0.125) | Newquay station (50.415, -5.075) |
| Morley-Leeds | Morley station (53.75, -1.591) | Leeds Town Hall (53.8003, -1.5497) |
| Sunderland-Newcastle | Sunderland Station 54.9055, -1.3824) | St James Park stadium (54.975556, -1.621667) |
| London-Glasgow | Charing Cross station (51.508, -0.125) | Glasgow SEC centre (55.86085, -4.28812) |
Calculating total emissions from conversion factors and distance
Our emission calculations include both ‘direct’ and ‘indirect’ emissions, as well as ‘indirect effects’ for plane travel.
Direct emissions are those that result from burning fuel during the journey (for example, tailpipe emissions).
Indirect emissions are referred to in the conversion factors as ‘well-to-tank’ (WTT) emissions and are the result of production and transport of fuel prior to its consumption.
Indirect effects are highly complex effects resulting from direct emissions interacting with the atmosphere and are only included in the calculation of air travel in our calculations. These are referred to in the conversion factors as ‘radiative forcing’ or RF.
All modes of travel that produce emissions have indirect effects, but the particular global warming impact of these emissions at high altitudes associated with air travel (for example, the production of contrails in the atmosphere which reflect sunlight) may be considerably higher than direct emissions alone. These indirect effects are still being studied, but are currently being estimated by BEIS as an additional 90% on top of existing aviation emissions.
When calculating the emissions of a given journey, the distance of the journey is multiplied by the direct emissions, and this is added to the distance multiplied by the indirect emissions.
For electric cars, there are no tailpipe emissions, but indirect emissions associated with the use of electricity to charge the car, emissions associated with the transmission and distribution loss of electricity, and emissions associated with the generation of electricity. For hybrid cars, there are emissions associated with use of petrol or diesel fuel which are added to this.
Since the conversion factors for cars assume a single passenger, and passenger vehicles other than cars and motorbikes incorporate some measure of passenger occupancy (and therefore are labelled ‘pax km’ in the conversion factors), DfT adjusted the result of these journeys to take into account the average occupancy of cars. Latest data from the National Travel Survey see (NTS0905) finds that the average occupancy of a car is 1.6 passengers, so our results divide the emissions of diesel, hybrid, electric and petrol cars by 1.6.
Table 2: Example journeys from London to Glasgow provided in the comparisons, with transport modes considered, distance of the journey by mode, conversion factor used, and emissions produced
| Transport Mode | Distance | Direct emissions per mile | Indirect emissions per mile | Total direct emissions | Total indirect emissions |
|---|---|---|---|---|---|
| Bicycle | 405 miles | 0 | 0 | 0 | 0 |
| Walking | 423 miles | 0 | 0 | 0 | 0 |
| Coach | 399 miles | 0.043 | 0.010 | 17KG | 4KG |
| Train | 393 miles | 0.057 | 0.011 | 22KG | 5KG |
| Motorbike | 399 miles | 0.183 | 0.050 | 73KG | 20KG |
| Avg. Diesel Car | 399 miles | 0.169 | 0.041 | 68KG | 16KG |
| Avg. Petrol Car | 399 miles | 0.175 | 0.049 | 70KG | 20KG |
| Plane | 345 miles | 0.209 | 0.043 | 77KG | 16KG |
Total direct emissions - Plane (77KG) - includes plus 64KG indirect effects of direct emissions
Total indirect emissions - Plane (16KG) - includes plus 6KG for travel to the airport by car
The distances for this journey were determined as expressed under the methodology, from Charing Cross station to SEC centre. Petrol, electric and diesel cars all used the ‘average’ size car under the conversion factors for ‘business travel-land’, and output factors are expressed in miles. Factors only provided in passenger miles were converted to passenger miles by multiplying the factor by (1/0.6213). For air travel, the ‘radiative forcing’ column within the conversion factors provides the estimate of emissions including indirect effects as a result of emissions. Air travel also includes the emissions resulting from travel to and from airports.
The final calculated emissions for a set of example journeys within the UK are included in data tables as part of DfT’s Transport and Environment Statistics publication, the most recent edition of which is available.
Methodological limitations
Our methodology is under continuous development to improve accuracy and utility. However, there are some areas where, due to lack of available data, we are aware of areas where estimates will be less precise. In general, the BEIS conversion factors rely on the construction of averages from regular travel patterns, and so individual behaviour is likely to vary from this central estimate. Likewise, the journeys DfT have designed may not reflect every journey.
Road travel
Car journey conversion factors include both the emissions produced by burning the fuel, but also add an additional ‘uplift factor’ (currently an additional 13.67%) to account for real-world driving conditions that affect fuel use (and therefore emissions), based on studies of real-world driving performance. This is intended to reflect driving behaviour such as acceleration and braking, use of car accessories such as air-conditioning and heating, traffic and engine idling, vehicle payload (luggage, other passengers), road gradient, weather conditions and car maintenance. This does not apply to motorcycles, which are currently tested in more representative conditions, so no uplift factor is needed.
As a result of these calculations, the calculations here may underestimate the emissions of the journey if the car is using more fuel (due to being in traffic for longer than average, for example) or conversely, overestimate the emissions if the car is using less fuel (by driving carefully and keeping tyres inflated).
Hybrid cars pose unique challenges for estimation, since they use variable amounts of fuel depending on the proportion of the journey fuelled by the battery and the proportion fuelled by petrol or diesel. If journeys in hybrid cars vary from the average conditions assumed by the conversion factor, they will misestimate the emissions produced by the journey.
In addition, as the car uses up the charge of the battery, and uses increasingly more fossil fuel instead, the additional weight of the dead battery can, on long journeys, cause a hybrid car to use more fuel per mile than a petrol car, all else being equal. Similarly to petrol and diesel cars, uplift factors are added to reflect real-world driving conditions, but on journeys longer than average this can cause the conversion factors to underestimate the amount of emissions produced.
Journey emissions from taxis assume the taxi is picked up from the origin point, and does not take into account emissions produced by moving from taxi rank to pick-up (if any).
Rail journeys
One area is in the estimation of emissions from national rail journeys. The conversion factor for national rail combines the overall emissions from both diesel and electric rail lines to provide an overall conversion factor for national rail. So, for specific journeys which may deviate from this combination of diesel and electric trains (for example, if the journey they take is mostly or entirely on trains powered by electricity), the estimation of GHG emissions will be inaccurate to an unknown degree.
Plane journeys
Plane journeys are assumed to travel in a straight line from 1 airport to another. However, the curvature of the earth means this journey is not straight but curved, and therefore longer to some degree. BEIS conversion factors handle this discrepancy by adding 8% to the emission factor to account for the curvature of the earth as well as emissions related to the plane circling awaiting to land or taxiing to the runway. This means emissions will be slightly underestimated if the journey is long, or the plane is delayed in take-off or landing, or overestimated if the journey is short, and the plane is not delayed in take-off or landing.
Classes in seating (economy, business, first class) can affect the share any given passenger has in the overall emissions of the plane journey. Larger seats mean fewer passengers overall, and a larger share of the emissions go to passengers in higher classes of seating. The conversion factors chosen in our example are domestic flights, which either do not include classes in seating, or the seating classes do not meaningfully affect the size of the seat and the number of passengers on the plane.
Plane journeys and indirect effects
While all emissions produce indirect effects, we have only included indirect effect estimates for plane journeys. This is because emissions high in the atmosphere have particular effects over and above those produced by burning fuel, principally contrail cirrus and emissions of nitrogen oxides (NOx).
In their estimation of emissions from plane journeys, BEIS conversion factors which include indirect effects (referred to in their document as ‘RF’, or ‘radiative forcing’) are supplied alongside conversion factors which do not include indirect effects. BEIS multiplier of 1.9 is used as an estimate, based on the best available scientific evidence including analysis by Lee et al. (2009) reported on by (CCC, 2009). However, these effects are extremely complex and non-linear, and it is not completely clear from current science the size of the effects, or even if they will have an overall warming or cooling effect. Recent studies have found 8 times more uncertainty in the estimate of indirect effects of emissions than the direct effects of the journey emissions, and the size of the ‘multiplier’ could be between 1 and 4 times the effect of the journey emissions, depending on time scale and metric of emissions (Lee et al., 2021).
References
CCC. (2009). Meeting the UK aviation target-options for reducing emissions to 2050. Committee on Climate Change.
Lee, D. S., Fahey, D. W., Forster, P. M., Newton, P. J., Wit, R. C., Lim, L. L., and Sausen, R. (2009). Aviation and global climate change in the 21st century. Atmospheric Environment, 43(22-23), 3520-3537.
Lee, D. S., Fahey, D. W., Skowron, A., Allen, M. R., Burkhardt, U., Chen, Q., and Wilcox, L. J. (2021). The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018. Atmospheric Environment*, 244, 117834.
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