Using a probabilistic model (pCNEM) to estimate personal exposure to air pollution

Zidek, James V., Shaddick, Gavin ORCID: https://orcid.org/0000-0002-4117-4264, White, Rick, Meloche, Jean and Chatfield, Chris 2005. Using a probabilistic model (pCNEM) to estimate personal exposure to air pollution. Environmetrics 16 (5) , pp. 481-493. 10.1002/env.716

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Abstract

This article describes the use of a probabilistic model to estimate personal exposure to airborne pollutants. Such estimates are important when assessing, for example, the potential effects of air pollution on health and in developing related policy. An individual's personal exposure will be determined by local pollution sources which will change throughout the day as the individual's location changes. For this reason, models have been developed that utilize ‘time activity’ patterns to compute the overall exposure to pollutants. The model described here is referred to as ‘pCNEM’ and can be accessed through the WWW. The computational platform is flexible in that it allows users to construct models defining local sources of pollution and emissions in addition to ambient levels. This article demonstrates the construction of such a model, for predicting the exposure to PM10 of random selected individuals from sub-populations of Greater London. A case study of working females in the spring and summer of 1997 is presented. Copyright © 2005 John Wiley & Sons, Ltd.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	?? VCO ??
Publisher:	Wiley
ISSN:	1180-4009
Date of Acceptance:	16 September 2004
Last Modified:	10 Sep 2024 13:00
URI:	https://orca.cardiff.ac.uk/id/eprint/170718

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