TransportEnergyandAirpollutionModel(TEAM)

The transport sector remains at the centre of any debates around energy conservation, exaggerated by the stubborn and overwhelming reliance on fossil fuels by its motorised forms, whether passenger and freight, road, rail, sea and air.

The very slow transition to alternative fuel sources to date has resulted in this sector being increasingly and convincingly held responsible for the likely failure of individual countries, including the UK, to meet their obligations under consecutive international climate change agreements.

Electrification of transport is largely expected to take us down the path to a ‘zero carbon future’ (CCC, 2019; DfT, 2018). But there are serious concerns about future technology performance, availability, costs and uptake by consumers and businesses. There are also concerns about the increasing gap between lab and ‘real world’ performance of energy use, carbon and air pollution emissions. Recently, the role of consumer ‘lifestyles’ has increased in prominence (e.g. IPCC, 2018) but, as yet, has not been taken seriously by the DfT, BEIS or even the CCC (2019).

Advancing our modelling capabilities

Societal energy consumption and pollutant emissions from transport are not only influenced by technical efficiency, mode choice and the pollutant content of energy, but also by lifestyle choices and socio-cultural factors. However, only a few attempts have been made to integrate all of these insights into systems models of future transport energy demand and supply (Creutzig et al., 2018) or narratives of low carbon transport futures (Creutzig, 2015).

Developed under the auspices of UKERC the Transport Energy Air pollution Model (TEAM) has been designed to address these concerns and uncertainties in exploring pertinent questions on the transition to a zero carbon and clean air transportation future.

TEAM is a strategic transport, energy, emissions and environmental impacts systems model, covering a range of transport-energy-environment issues from socio-economic and policy influences on energy demand reduction through to lifecycle carbon and local air pollutant emissions and external costs. It is built around exogenous and quantified scenarios, covering passenger and freight transport across all modes of transport (road, rail, shipping, air). It provides annual projections up to 2100, is technology rich with endogenous modelling of more than 1,200 vehicle technologies, and covers a wide range of output indicators, including travel demand, vehicle ownership and use, energy demand, life cycle emissions of 26 pollutants, environmental impacts, government tax revenues, and external costs.

Global relevance

The TEAM framework can be adapted to a range of geographical and administrative scales, from city to region, country and global scales. To date, two versions have been developed and used in policy analysis: a UK version, TEAM-UK; and a Scottish version, STEAM. Both were designed to explore alternative transport futures to meet UK and Scottish carbon mitigation, air quality and energy policy goals. Analysts and decision makers are able to systematically compare a wide range of scenarios and policies, including those focusing on travel behaviour and demand, vehicle ownership and use, fiscal, pricing, eco-driving, fuel obligations, speed limits, technology investment/procurement, ‘official’ vs ‘real world’ gaps, and zero or clean air zones.

TEAM has evolved from the UK Transport Carbon Model (UKTCM) that played a key role in developing the UKERC Energy2050 ‘lifestyle’ scenarios (Anable et al., 2012a; Anable et al., 2012b) and in exploring the effectiveness of low carbon car purchasing incentives in the UK (Brand et al., 2013). An overview of the model has been published in Brand et al. (2012).

A 2019 working paper provides a major update on the 2010 working paper on UKTCM.

On-going work

TEAM was recently developed, updated and recalibrated from version 2.0 (as reported in Brand et al., 2013) to the current version 3.1. We focussed our efforts on enhancing the

1. car ownership model
2. car sales, choice and use model
3. direct energy use and emissions model, and
4. the life cycle energy use and environmental impacts model

The tool was used to investigate the ‘dieselgate’ affair by exploring unaccounted and future air pollutant emissions and energy use for cars in the UK (paper under review).

In collaboration with the Scottish ClimateXChange project we are also developing a Scottish version of TEAM – STEAM. We are working with ClimateXChange and the Scottish government on developing policy scenarios to inform future policy making in the transport and energy sectors.

Publications

1. Anable, J., Brand, C., Eyre, N., Layberry, R., Bergman, N., Strachan, N., Fawcett, T., Tran, M., 2012a. Energy 2050 – WG1 Energy Demand: Lifestyle and Energy Consumption, UKERC Working Paper. UK Energy Research Centre (UKERC), Energy Demand Theme, Oxford.
2. Anable, J., Brand, C., Tran, M., Eyre, N., 2012b. Modelling transport energy demand: A socio-technical approach. Energy Policy 41, 125-138.
3. Brand, C., 2010. UK Transport Carbon Model: Reference Guide v1.0. UK Energy Research Centre, Energy Demand Theme, Oxford.
4. Brand, C., Anable, J., Tran, M., 2013. Accelerating the transformation to a low carbon passenger transport system: The role of car purchase taxes, feebates, road taxes and scrappage incentives in the UK. Transp. Res.: Part A: Pol. Practice 49, 132-148.
5. Brand, C., Tran, M., Anable, J., 2012. The UK transport carbon model: An integrated life cycle approach to explore low carbon futures. Energy Policy 41, 107-124.
6. Brand, C., 2016. Beyond Dieselgate: Implications of unaccounted and future air pollutant emissions and energy use for cars in the United Kingdom. Energy Policy 97, October 2016, 1-12.
7. Brand, C., Cluzel, C., Anable, J., 2017 Modeling the uptake of plug-in vehicles in a heterogeneous car market using a consumer segmentation approach. Transportation Research Part A: Policy & Practice 97, 121-136.

Impact

• ESRC – Supporting large-scale transition to electric cars