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London Hybrid Exposure Model: Improving Human Exposure Estimates to NO2 and PM2.5 in an Urban Setting.

Smith, JD; Mitsakou, C; Kitwiroon, N; Barratt, BM; Walton, HA; Taylor, JG; Anderson, HR; Kelly, FJ; Beevers, SD (2016) London Hybrid Exposure Model: Improving Human Exposure Estimates to NO2 and PM2.5 in an Urban Setting. Environ Sci Technol, 50 (21). pp. 11760-11768. ISSN 1520-5851 https://doi.org/10.1021/acs.est.6b01817
SGUL Authors: Anderson, Hugh Ross

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Abstract

Here we describe the development of the London Hybrid Exposure Model (LHEM), which calculates exposure of the Greater London population to outdoor air pollution sources, in-buildings, in-vehicles, and outdoors, using survey data of when and where people spend their time. For comparison and to estimate exposure misclassification we compared Londoners LHEM exposure with exposure at the residential address, a commonly used exposure metric in epidemiological research. In 2011, the mean annual LHEM exposure to outdoor sources was estimated to be 37% lower for PM2.5 and 63% lower for NO2 than at the residential address. These decreased estimates reflect the effects of reduced exposure indoors, the amount of time spent indoors (∼95%), and the mode and duration of travel in London. We find that an individual's exposure to PM2.5 and NO2 outside their residential address is highly correlated (Pearson's R of 0.9). In contrast, LHEM exposure estimates for PM2.5 and NO2 suggest that the degree of correlation is influenced by their exposure in different transport modes. Further development of the LHEM has the potential to increase the understanding of exposure error and bias in time-series and cohort studies and thus better distinguish the independent effects of NO2 and PM2.5.

Item Type: Article
Additional Information: This is an open access article published under a Creative Commons Attribution (CC-BY) License, https://creativecommons.org/licenses/by/4.0/ which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
Keywords: Environmental Sciences, MD Multidisciplinary
SGUL Research Institute / Research Centre: Academic Structure > Population Health Research Institute (INPH)
Journal or Publication Title: Environ Sci Technol
ISSN: 1520-5851
Language: eng
Dates:
DateEvent
1 November 2016Published
6 October 2016Published Online
6 October 2016Accepted
Publisher License: Creative Commons: Attribution 4.0
PubMed ID: 27706935
Web of Science ID: WOS:000386991100038
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/108637
Publisher's version: https://doi.org/10.1021/acs.est.6b01817

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