Physicochemical characteristics and seasonal variations of PM2.5 in urban, industrial, and suburban areas in South Korea - Hwang, Kyucheol; Kim, Jeongho; Lee, Jae Young; Park, Jong Sung; Park, Sechan; Lee, Gahye; Kim, Chang Hyeok; Kim, Pilho; Shin, Su Hyun; Lee, Kwang Yul; An, Joon Young; Park, Jungmin; et al. (Asian Journal of Atmospheric Environment, 2023)
Among countries that are a part of the Organization for Economic Co-operation and Development, South Korea is the most exposed to PM2.5. Despite the country having implemented various strategies to limit PM2.5 emissions, its concentrations are still high enough to pose serious environmental and health concerns. Herein, we monitored various physiochemical properties of PM2.5 across different regions in South Korea from January 1 to December 31, 2021. Specifically, the study area consisted of the city center, industrial complexes, and suburban areas. Before analyzing dynamics of emissions specific to each site, the Clean Air Policy Support System data for the three areas were compared to elucidate their respective primary emission sources. The particle concentrations for the three areas were 21.8–26.44 µg/m3, with the highest concentrations being observed in March. All the three areas exhibited high ratios of NO3− across all seasons. The particle number concentrations in the three sites were 1.3–1.5 × 107, and the peak points of the concentrations were different in every site: city center (40 nm), industrial complexes (60 nm), and suburban areas (80 nm). We also conducted potential source contribution function and conditional bivariate probability function analyses. These analyses were conducted to determine the inflow direction of the pollution sources for high PM2.5 episodes. For the episodes that occurred in spring and winter, there were no differences in the PM2.5 concentrations between the three sites. Overall, the insights gained from this study offer a framework for developing air-quality management policies in South Korea, specifically in the context of PM2.5 emissions.
Keywords: Clean Air Policy Support System; Conditional bivariate probability function; PM2.5 concentration; Potential source contribution function; South Korea; Spatial variation