Assessment of long-range transboundary aerosols in Seoul, South Korea from Geostationary Ocean Color Imager (GOCI) and ground-based observations

To better understand air quality issues in South Korea, it is essential to identify the main contributors of air pollution and to quantify the effects of transboundary transport. In this study, geostationary satellite measurements were used to assess the effects of aerosol transport on air quality in South Korea. This study proposes a method to define the long-range transport (LRT) of aerosols into the Korean Peninsula using remote sensing obervations and back-trajectories and estimates the LRT effects on air quality in Seoul using in-situ particulate matter (PM) measurements. Aerosol optical depths (AOD5) are obtained from the Geostationary Ocean Color Imager (GOCI), and the back-trajectories are from the National Ocean and Atmospheric Administration (NOAA) HYbrid Single Particle Lagrangian Integrated Trajectory (HYS-PLIT) model. For LRT events, satellite observations showed high AOD plumes over the Yellow Sea, a pathway between Eastern China and South Korea, and the movements of aerosol plumes transported to South Korea were also detected. PM2.5 concentrations, PM10 concentrations, and AOD during LRT increased by 52%, 49%, and 81%, respectively, relative to their average values for 2015-2018. To quantitatively characterize the LRT of aerosols, the effects of LRT on PM2.5 concentrations were estimated for each PM concentration category. The contribution of LRT to PM2.5 concentrations was estimated to be 33% during 2015-2018. When high concentrations of PM2.5 were observed in Seoul, they were likely to be associated with LRT events. (C) 2020 The Author(s). Published by Elsevier Ltd.

Automated summary

This study used geostationary satellite measurements and modeling to assess the impact of aerosol long-range transport (LRT) on air quality in South Korea. The findings showed that during LRT events, PM2.5 concentrations in Seoul increased by 52% to 81%, with LRT contributing up to 33% of PM2.5 concentrations.