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Reducing Urban Pollution Exposure from Road Transport(RUPERT)

Bell, M.C., Namdeo, A.K., Chen, H., Ashmore, M.R., Terry, A.C. and Dimitroulopoulou, S. (2004) Reducing Urban Pollution Exposure from Road Transport(RUPERT). In: Brebbia, C.A. and Wadhwa, L.C., (eds.) Urban Transport. WIT Press , Southampton, UK , pp. 829-838. ISBN 1-85312-716-7

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This paper presents the preliminary results of a two-year study on reducing urban pollution exposure from road transport (RUPERT). The main aim of this project is to develop a new modelling framework for nitrogen dioxide, carbon monoxide and particulate matter to simulate exposures of different population groups across a city, and to assess the impact of roadside concentrations on these exposures. This will be achieved by modelling the frequency distribution of personal exposures (PEFDs) as a function of urban background and roadside concentrations, under different traffic conditions. The modelling approach combines new and existing models relating traffic and air pollution data, with particular emphasis of the impact of congestion, and the probabilistic modelling framework of personal exposure. Modelling of roadside concentrations consists of two main elements, namely the analysis of concentrations patterns at different roadside sites and of the relationship between traffic conditions and added roadside pollution. Roadside concentrations are predicted using empirically derived relationships; statistical models, novel statistics and artificial neural networks namely feed forward neural network and radial basis neural network. The exposure modelling is carried out by linking two models: the INDAIR model, which is designed to simulate probabilistically diurnal profiles of air pollutant concentrations in a range of microenvironments, and the EXPAIR model, which is designed to simulate population exposure patterns based on population time-activity patterns and a library of micro-environmental concentrations derived from the INDAIR model.

Item Type: Book Section
Copyright, Publisher and Additional Information: Copyright held by the WIT Press. This version has been uploaded with their express permission.
Keywords: traffic, outdoor pollution, indoor pollution, exposure, neural network.
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)
Depositing User: Adrian May
Date Deposited: 13 Jul 2007
Last Modified: 08 Aug 2014 08:46
Published Version: http://www.witpress.com/acatalog/7167.html
Status: Published
Publisher: WIT Press
Refereed: Yes
URI: http://eprints.whiterose.ac.uk/id/eprint/2573

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