Environmental and Ecological Statistics

, Volume 11, Issue 1, pp 9–19 | Cite as

Locating major PM10 source areas in Seoul using multivariate receptor modeling

  • Eun Sug Park
  • Peter Guttorp
  • Ho Kim


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.

air pollution source spatial profile marginal likelihood posterior model probability 


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Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Eun Sug Park
    • 1
  • Peter Guttorp
    • 2
  • Ho Kim
    • 3
  1. 1.Texas Transportation InstituteCollege StationUSA
  2. 2.National Research Center for Statistics and the EnvironmentUniversity of WashingtonSeattleUSA
  3. 3.Biostatistics and Epidemiology, School of Public HealthSeoul National UniversitySeoulKorea

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