D. Rayfield
A methodology for estimation of vehicle emissions in an urban environment: An example from Greater Manchester
Rayfield, D.; Longhurst, James; Watson, A. F R; Hewison, T.; Raper, D. W.; Conlon, D.E.; Owen, B.
Authors
Assistant Vice Chancellor, Environment and Sustainability Jim Longhurst James.Longhurst@uwe.ac.uk
Professor
A. F R Watson
T. Hewison
D. W. Raper
D.E. Conlon
B. Owen
Abstract
Road transport is a major contributor to urban air pollution. The introduction of local air quality management in the UK will require objective test procedures to evaluate and prioritise the air pollution benefits of existing transport systems and proposed developments. This methodology has been developed to assist the land use and transport planning professionals in evaluating current and potential future impacts on air quality. The method couples an emissions estimation procedure to a traffic flow database. It requires data on emission factors, the composition of the vehicle fleet, vehicle control technologies and the daily traffic flow profile. With these data, it is possible to generate emission estimates per kilometre, link or road as selected by the user. Forecasts can be made by varying input variables. The current methodology allows prediction of five or more pollutant species/classes, limited only by availability of emission factors. The method utilises a commercially available personal computer based spreadsheet. Further coupling of the method to a geographical information system will improve the decision support capability of the method.
Journal Article Type | Article |
---|---|
Publication Date | Dec 1, 1998 |
Journal | Environmentalist |
Print ISSN | 0251-1088 |
Electronic ISSN | 1573-2991 |
Publisher | Springer Verlag |
Peer Reviewed | Peer Reviewed |
Volume | 18 |
Issue | 3 |
Pages | 175-182 |
DOI | https://doi.org/10.1023/A%3A1006602217842 |
Keywords | methodology, estimationm vehicle emissions, urban, Greater Manchester |
Public URL | https://uwe-repository.worktribe.com/output/1101484 |
Publisher URL | http://dx.doi.org/10.1023/A:1006602217842 |
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