A multifaceted approach to explain short- and long-term PM2.5 concentration changes in Northeast Asia in the month of January during 2016-2021

Changes in PM2.5 concentrations are influenced by interwoven impacts of key drivers (e.g., meteorology, local emis-sions, and regional emissions). However, it is challenging to quantitatively disentangle their impacts individually at once. Therefore, we introduced a multifaceted approach (i.e., meteorology vs. emissions and self-contribution vs. long-range transport) to analyze the effects of major drivers for long-and short-term PM2.5 concentration changes based on observation and simulation in the month of January during 2016-2021 in Northeast Asia. For the simula-tions, we conducted modeling with the WRF-CMAQ system. The observed PM2.5 concentrations in China and South Korea in January 2021 decreased by 13.7 and 9.8 mu g/m3, respectively, compared to those in January 2016. Emission change was the dominant factor to reduce PM2.5 concentrations in China (-115%) and South Korea (-74%) for the 6 years. However, the short-term changes in PM2.5 concentrations between January of 2020-2021 were mainly driven by meteorological conditions in China (-73%) and South Korea (-68%). At the same time, in South Korea located in downwind area, the impact of long-range transport from upwind area (LTI) decreased by 55% (9.6 mu g/m3) over the 6 years whereas the impact of local emissions increased (+2.9 mu g/m3/year) during 2016-2019 but decreased (-4.5 mu g/m3/year) during 2019-2021. Additionally, PM2.5 concentrations in the upwind area showed a positive re-lationship with LTIs. However, for the days when westerly winds became weak in the downwind area, high PM2.5 con-centrations in upwind area did not lead to high LTIs. These results imply that the decline of PM2.5 concentrations in South Korea was significantly affected by a combination of emission reduction in upwind area and meteorological con-ditions that hinder long-range transport. The proposed multifaceted approach can identify the main drivers of PM2.5 concentration change in a region by considering the regional characteristics.