Remote sensing of carbon monoxide vehicle emissions

Article


Muncaster, G., Hamilton, R. and Revitt, D. 1996. Remote sensing of carbon monoxide vehicle emissions. Science of the Total Environment. 189-90, pp. 149-153. https://doi.org/10.1016/0048-9697(96)05203-5
TypeArticle
TitleRemote sensing of carbon monoxide vehicle emissions
AuthorsMuncaster, G., Hamilton, R. and Revitt, D.
Abstract

The University of Denver's remote sensor for automobile exhaust emissions has been used to obtain valid model year (defined here as the year of first registration) and emissions data from roadside locations in Middlesbrough and London. Mean carbon monoxide emissions have been plotted against model year to determine if there is a relationship between mean pollutant emissions and the age of the vehicle. The results initially showed a large degree of scatter and no inference, concerning age and emissions, could be made. This can be largely attributed to the older vehicles in the fleet. Older vehicles were then omitted from an additional investigation providing a much stronger relationship with R2 values of 0.88 being calculated for London and 0.77 for Middlesbrough. Analyses of model year fleet emissions were also undertaken. It was demonstrated that old vehicles do not contribute significantly to fleet emissions. Pre-1983 registered vehicles contributed only 9% of total fleet emissions in Middlesbrough and only 21% of total fleet emissions in London. It was also shown that the vast majority of fleet emissions come from a small number of highly polluting new vehicles (quintile 5). Quintile 5 for model year 1989 represented 140 vehicles (2% of the measured fleet) which contributed to 10.6% of fleet emissions at the Middlesbrough site.

PublisherElsevier
JournalScience of the Total Environment
ISSN0048-9697
Publication dates
PrintOct 1996
Publication process dates
Deposited21 Jan 2010
Output statusPublished
Additional information

Highway and Urban Pollution

Web address (URL)http://www.sciencedirect.com/science/article/pii/0048969796052035
Digital Object Identifier (DOI)https://doi.org/10.1016/0048-9697(96)05203-5
LanguageEnglish
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