Transport modelling provides a framework for comparing the effect of technological change and policy levers on energy use, activity, and greenhouse gas emissions in the sector. For road transport, we use the European Union Transport Roadmap Model (EUTRM). For aviation and shipping, we have developed modelling tools in-house.
The EUTRM was originally based on the ICCT Global Transportation Roadmap Model (GTRM). In 2017 it was adapted to include the 27 EU member states plus the United Kingdom, Switzerland and Norway, adding the functionality of second-hand sales flows between member states. The upgrade was undertaken by Cambridge Econometrics, but T&E constantly improves it. For example, the original version had a time resolution of 5 years, we upgraded it to have yearly increments between 2015 to 2030 to better model the effects of policy. The EUTRM makes use of the most recently available data as well as detailed European-specific data. These data are kept up to date and as better data become available, they are updated.
In 2018, Cambridge Econometrics was commissioned to convert the passenger cars module into a full stock model. The stock model enables much more granular outputs and has yearly resolution from the year 2000 to 2050. In 2021, T&E pythonised the spreadsheet models, extending the stock model to all road transport modes. During this process, a more accurate calibration procedure was developed. Converting the model to python allows us to develop tools based on hundreds of scenarios and to give greater flexibility for future development, for example adding vehicle segments, company cars, or second hand vehicle sales flows that are not constant in time.
The EUTRM is a demand driven model. Passenger and freight demand are based on purchasing power parity (PPP) adjusted GDP, which is determined by historical and projected gross domestic product (GDP), population, and fuel price, for each country. All transport demand is then met with the required transport capacity, whether it be through the sales of passenger cars, buses, and motor bikes for passenger transport activity, or the sale of trucks for freight or additional trains. The relationship between freight transport and GDP has been observed historically, and this assumption is carried forward in time (passenger transport demand shows a slight decoupling with GDP). Thus, an increase of per capita GDP over time will result in an increase of demand for transport and freight. In lieu of policy decisions, this new demand is only met by increasing the fleet size with new vehicle sales.
The EUTRM is initialised and calibrated with historical data, whereby for the example of trucks, the vehicle stock and number of new vehicles (both in number and in category), mileage, fuel consumption, and load factor are considered. Vehicle renewal/purchasing is based on retirement curves and freight demand. Policy levers change mode specific parameters. In the case of trucks, these can include modal shift (moving freight from road to rail), engine technology uptake (hybrid, electric, hydrogen), and fuel efficiency (through efficiency standards). Similarly for cars, passenger activity can be shifted to buses, trains, walking and cycling, and demand can be reduced through fuel or congestion taxes. Therefore, the strength of the EUTRM is in its ability to combine multiple policy decisions and show their effect on the business-as-usual (BAU) case, and to quantify the relative importance of policies on GHGs. To get more details in the model, the user guide produced by Cambridge Econometrics can be found here.
T&E has developed in-house capabilities for the analysis and projection of shipping emissions. We started by analysing automatic identification system (AIS) signals from cruise ships to determine pollution in ports. We have analysed and reported on the monitoring, reporting and verification (MRV) data. T&E has purchased vessel characteristics databases and codified the emissions calculation as used in the IMO’s Fourth Greenhouse Gas Study (2020). Combined with access to AIS data from 70,000 ships over 3 years, this capability enables us to analyse global shipping movements and their associated emissions. Finally, we have developed an in-house stock model of the European shipping fleet. This tool allows us to determine the emissions savings potential from operational and technological measures as well as the uptake of green fuels, to the end of better guiding law makers to implement the best possible policy for decarbonising the shipping sector, as we discuss in our 2021 report.
T&E has several tools at its disposal for the analysis of European aviation emissions. We have a yearly update on ETS emissions that combines databases and data filling to give an accurate picture of the intra-EU aviation sector. We have purchased aircraft AIS data from Plane Finder, which has enabled us to look at flights and their emissions to the granularity of airlines, airports, countries and individual routes and the aircraft servicing them. T&E has developed an in-house aviation model that has policy levers such as demand management, technology and e-fuel fuel uptake rates. The details and results of this model will be described in more detail in an upcoming study.