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Evaluation of Secondary Organic Aerosol (SOA) Simulations for Seoul, Korea

Cited 11 time in Web of Science Cited 10 time in Scopus

Oak, Yujin J.; Park, Rokjin J.; Jo, Duseong S.; Hodzic, Alma; Jimenez, Jose L.; Campuzano-Jost, Pedro; Nault, Benjamin A.; Kim, Hwajin; Kim, Hyeonmin; Ha, Eunjo S.; Song, Chang-Keun; Yi, Seung Muk; Diskin, Glenn S.; Weinheimer, Andrew J.; Blake, Donald R.; Wisthaler, Armin; Shim, Mihee; Shin, Yoonmi

Issue Date
American Geophysical Union
Journal of Advances in Modeling Earth Systems, Vol.14 No.2, p. e2021MS002760
Organic aerosols (OA) represent a significant fraction of total submicron particulate matter (PM1) concentrations globally, including densely populated megacities such as Seoul. However, scientific understanding of the atmospheric formation and removal processes of OA, especially for secondary organic aerosols (SOA), is still highly uncertain. In this study, we examine the characteristics of SOA formation in Seoul during spring-summer 2016 and fall-winter 2017/2018, using airborne and ground observations along with a 3-D global chemical transport model, GEOS-Chem. We use four different SOA schemes in the model, including simplified and complex volatility-based frameworks, and evaluate them by comparing the simulations with the observations to examine how our scientific understanding embedded in each SOA scheme affects the observed biases. Our analysis of the model performance of each scheme also provides the most suitable approach in simulating SOA in a typical urban environment. Comparisons of the simulated versus observed OA concentrations show that model biases range from -72% to +118%, with considerable variability among different schemes and seasons. We find that the inclusion of semi/intermediate volatile precursors, in addition to the traditional precursors, and chemical aging (functionalization) are important factors to simulate surface SOA concentrations in Seoul. However, a comparison of observed and simulated SOA/ increment CO enhancement ratios suggests that most schemes underpredict SOA aging in upper levels in the boundary layer. We also find that the simplified SOA scheme can reproduce observed OA but often shows overestimation in surface air, indicating that uncertainties exist in bottom-up emissions and precursor parameterization in Seoul.
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  • Graduate School of Public Health
  • Department of Environmental Health Sciences
Research Area Aerosol Health Effect, Atmospheric chemistry monitoring and modeling, Chemistry and life cycles of aerosol, 대기화학 모니터링 및 모델링, 대기환경 오염원 및 특성 규명


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