Use of a novel dataset to explore spatial and social variations in car type, size, usage and emissions. (August 2015)

• Record Type: Journal Article
• Authors: Chatterton, Tim; Barnes, Jo; Wilson, R. Eddie; Anable, Jillian; Cairns, Sally
• Is Part Of: Transportation research. Volume 39(2015)
• Page Start: 151
• Page End: 164
• Publication Date: 2015-08
• Subjects: Emissions -- Vehicle -- Energy -- Household -- Spatial -- Socio-demographic; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2015.06.003
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: Demonstrates the use of annual vehicle test records to investigate vehicle usage. A new owner-centred approach to emissions calculations. Spatial variations in vehicle type and use. Relationships between vehicle type and emissions. Links between vehicle type and emissions, and socio-demographic data. Abstract: The 'MOT' vehicle inspection test record dataset recently released by the UK Department for Transport (DfT) provides the ability to estimate annual mileage figures for every individual light duty vehicle greater than 3 years old within Great Britain. Vehicle age, engine size and fuel type are also provided in the dataset and these allow further estimates to be made of fuel consumption, energy use, and per vehicle emissions of both air pollutants and greenhouse gases. The use of this data permits the adoption of a new vehicle-centred approach to assessing emissions and energy use in comparison to previous road-flow and national fuel consumption based approaches. The dataset also allows a spatial attribution of each vehicle to a postcode area, through the reported location of relevant vehicle testing stations. Consequently, this new vehicle data can be linked with socio-demographic data in order to determine the potential characteristics of vehicle owners. This paper provides a broad overview of the types of analyses that are made possible by these data, with a particular focus on distance driven and pollutant emissions. The intention is to demonstrate the very broad potential for this data, and to highlight where more focused analysis could be useful. The findings from the work have important implications for understanding the distributional impacts of transport related policies and targeting messaging and interventions for the reduction of car use.