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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/∆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. Plain Language Summary: We compare four different modeling approaches for simulating secondary organic aerosol (SOA) formation, accounting for a significant fraction of total fine particulate matter concentrations in Seoul, Korea. Using GEOS‐Chem, a chemical transport model, we find that current SOA schemes show large variabilities. Including an additional precursor species and further oxidation (i.e., chemical aging) of simulated SOA improves model performance. We also find that a simplified scheme with less computational cost can reproduce observed values but generally shows an overestimation in Seoul, indicating uncertainties in parameterization. Key Points: Model evaluation of simulated organic aerosols (OA) using different secondary organic aerosols (SOA) schemes in Seoul shows large variabilityThe inclusion of semi/intermediate volatile precursors and chemical aging are important factors in reducing model biasesThe simplified SOA scheme can reproduce observed OA, but uncertainties exist in precursor parameterization in Seoul [ABSTRACT FROM AUTHOR]

Two approaches were applied for characterization of organic compounds in the atmospheric aerosols. These were chemical and statistical grouping analysis. We applied chemical group analysis as a new approach using the GC×GC data. Based on the principle of GC×GC, analytes in two dimensional data were divided into 6 chemical group depending on their volatility and polarity. Using this classification standards, all analytes were classified as one of 6 chemical groups, HP-VOC, LP-VOC, HP-SVOC, LP-SVOC, HPNVOC and LP-NVOC. The relationship between the sum of the peak areas of each chemical group with other variables such as the concentrations of OC, EC, OCPOC, OC/EC and OCSOC were studied. However, no apparent relationship was observed. The principle component analysis (PCA) was carried out to find out the relationship among the analytes based on their sources. The OVOCs were dominant compounds in 3 out of 4 factors in summer. In winter, factor 1 was related to secondary organic aerosol and factor 3 was related to primary emission sources. The proposed approach looks promising in characterization of chemical groups but have limitations at current stage which are discussed. [ABSTRACT FROM AUTHOR]

Seventy three individual organic compounds in the atmospheric particulate matter with an aerodynamic diameter of less than or equal to a nominal 10 μm (PM 10 ) over Seoul were identified and quantified from April 2010 to April 2011 using gas chromatography/mass spectrometry (GC/MS). These organic compounds were classified into five groups, n-alkanes, polycyclic aromatic hydrocarbons (PAHs), mono-carboxylic acids, di-carboxylic acids (DCAs), and sugars based on their chemical structures and properties. The organic compounds showed higher seasonal average concentrations from fall to winter than from spring to summer due to source strength, except some organic compounds among mono-carboxylic acids, DCAs, sugars such as undecanoic acid, methylmalonic acid, and fructose. Through qualitative data analysis using seasonal concentration variations and relevant diagnostic parameters, it was found that (1) anthropogenic sources such as combustion of fossil fuel and biomass burning attributed more to the formation of the organic aerosols than biogenic sources, and (2) the ambient level of n-alkanes, PAHs, and some compounds of DCAs and sugars was elevated in winter due to the increased primary emissions and larger transport from outside of the organic compounds in winter. [ABSTRACT FROM AUTHOR]