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Titel |
Refinement of a model for evaluating the population exposure in an urban area |
VerfasserIn |
J. Soares, A. Kousa, J. Kukkonen, L. Matilainen, L. Kangas, M. Kauhaniemi, K. Riikonen, J.-P. Jalkanen, T. Rasila, O. Hänninen, T. Koskentalo, M. A. Aarnio, C. Hendriks, A. Karppinen |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1991-959X
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Digitales Dokument |
URL |
Erschienen |
In: Geoscientific Model Development ; 7, no. 5 ; Nr. 7, no. 5 (2014-09-02), S.1855-1872 |
Datensatznummer |
250115708
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Publikation (Nr.) |
copernicus.org/gmd-7-1855-2014.pdf |
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Zusammenfassung |
A mathematical model is presented for the determination of human exposure to
ambient air pollution in an urban area; the model is a refined version of a
previously developed mathematical model EXPAND (EXposure model for
Particulate matter And Nitrogen oxiDes). The model combines predicted
concentrations, information on people's activities and location of the
population to evaluate the spatial and temporal variation of average exposure
of the urban population to ambient air pollution in different
microenvironments. The revisions of the modelling system containing the
EXPAND model include improvements of the associated urban emission and
dispersion modelling system, an improved treatment of the time use of
population, and better treatment for the infiltration coefficients from
outdoor to indoor air. The revised model version can also be used for
estimating intake fractions for various pollutants, source categories and
population subgroups. We present numerical results on annual spatial
concentration, time activity and population exposures to PM2.5 in the
Helsinki Metropolitan Area and Helsinki for 2008 and 2009, respectively.
Approximately 60% of the total exposure occurred at home, 17% at
work, 4% in traffic and 19% in other microenvironments in the
Helsinki Metropolitan Area. The population exposure originating from the long-range transported background concentrations was responsible for a major
fraction, 86%, of the total exposure in Helsinki. The largest local
contributors were vehicular emissions (12%) and shipping (2%). |
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