Temporal pattern classification of PM2.5 chemical compositions in Seoul, Korea using K-means clustering analysis

Woosuk Choi, Chang Hoi Ho, Yoojin Lee

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1 Scopus citations

Abstract

Particulate matter with a diameter ≤ 2.5 μm (PM2.5) is a complex mixture of particles with a variety of compositions potentially including sulfate ions (SO42−), nitrate ions (NO3), ammonium ions (NH4+), organic and inorganic elemental carbon, and metals. Here, the temporal composition evolution of PM2.5 was analyzed to characterize its emission source, origin, and external influences. The concentrations of wintertime PM2.5 chemical compositions in Seoul, Korea during the period of 2012–2021 were classified into four representative clusters using a K-means cluster analysis method. Cluster 1 exhibited high concentrations of NO3 and NH4+ ions mainly due to the prevalence of emissions from domestic manure and fertilizer sources in the northeast. High concentrations of these two ions are conducive to generation of ammonium nitrate (NH4NO3) through atmospheric chemical reactions, resulting in relatively long-lasting high PM2.5 concentrations in Seoul. In cluster 2, high concentrations of SO42−, vanadium, and nickel were observed in frequent south-westerly winds, indicating the domestic influence of industrial facilities. Cluster 3 showed high concentrations of potassium ions and organic carbon, highlighting a pronounced external influence transported from China via prevailing westerly winds. Cluster 4 showed low PM2.5 concentrations accompanied by strong winds in warm environments, which are uncommon in winter. This study revealed that the air quality in Seoul, which was influenced by many factors, could be classified into four representative patterns. Our results provide insights into the emission sources, major influences, and responsible mechanisms of high PM2.5 concentrations in Seoul, which can help with air quality policies.

Original languageEnglish
Article number172157
JournalScience of the Total Environment
Volume927
DOIs
StatePublished - Jun 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors

Keywords

  • Air quality patterns
  • Chemical composition
  • K-means cluster analysis
  • PM
  • Seoul

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