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Locating major PM10 source areas in Seoul using multivariate receptor modeling

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Abstract

Identifying the major sources contributing to air pollution is a problem of fundamental importance in developing effective air quality management plans. Multivariate receptor modeling aims to achieve this goal by unfolding the air pollution data into components associated with different sources based on factor analysis models. We analyze the PM10 data obtained from 17 monitoring sites in Seoul to locate the major source regions using multivariate receptor modeling. The model uncertainty caused by the unknown number of sources and identifiability conditions is assessed by posterior probability of each model. The estimated source spatial profiles seem to be consistent with our prior expectation about the PM10 sources in Seoul.

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Authors and Affiliations

  1. Texas Transportation Institute, 3135 TAMU, College Station, TX, 77843-3135, USA

    Eun Sug Park

  2. National Research Center for Statistics and the Environment, University of Washington, Seattle, WA, 98195, USA

    Peter Guttorp

  3. Biostatistics and Epidemiology, School of Public Health, Seoul National University, 28 Yunkeon-Dong, Chongro-Gu, Seoul, 100–799, Korea

    Ho Kim

Authors
  1. Eun Sug Park
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  2. Peter Guttorp
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  3. Ho Kim
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Park, E.S., Guttorp, P. & Kim, H. Locating major PM10 source areas in Seoul using multivariate receptor modeling. Environmental and Ecological Statistics 11, 9–19 (2004). https://doi.org/10.1023/B:EEST.0000011361.33942.be

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  • DOI: https://doi.org/10.1023/B:EEST.0000011361.33942.be

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