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자연과학대학
통계학전공
Journal papers
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Regional source apportionment of PM2.5 in Seoul using Bayesian multivariate receptor model
Title
Regional source apportionment of PM2.5 in Seoul using Bayesian multivariate receptor model
Authors
Oh M.-S.
;
Park C.K.
Ewha Authors
오만숙
SCOPUS Author ID
오만숙
Issue Date
2022
Journal Title
Journal of Applied Statistics
ISSN
0266-4763
Citation
Journal of Applied Statistics vol. 49, no. 3, pp. 738 - 751
Keywords
air pollution
;
Bayesian analysis
;
factor analysis
;
Markov chain Monte Carlo
;
particulate matter
Publisher
Taylor and Francis Ltd.
Indexed
SCIE; SCOPUS
Document Type
Article
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. © 2020 Informa UK Limited, trading as Taylor & Francis Group.
DOI
10.1080/02664763.2020.1822305
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