Regional source apportionment of PM2.5 in Seoul using Bayesian multivariate receptor model

Man Suk Oh, Chee Kyung Park

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Seoul, the capital city of Korea with over 10 million residents, has been experiencing serious air pollution problems. Previous studies on source apportionment of PM2.5 in Seoul are based on measurements of chemical compositions of PM2.5 from a single monitoring site. In this paper, we analyse PM2.5 concentration data collected from multiple sites in 24 districts of Seoul and estimate regional source profiles using Bayesian multivariate receptor model. The regional source profiles provide information for the identification of major PM2.5 sources as well as the regions relatively more seriously affected by each source than other regions. These regional characteristics relevant to PM2.5 can help establish effective, customised, region-specific PM2.5 control strategies for each region rather than general strategies that apply to every region of Seoul.

Original languageEnglish
Pages (from-to)738-751
Number of pages14
JournalJournal of Applied Statistics
Volume49
Issue number3
DOIs
StatePublished - 2022

Keywords

  • Bayesian analysis
  • Markov chain Monte Carlo
  • air pollution
  • factor analysis
  • particulate matter

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