An observation-based adjustment method of regional contribution estimation from upwind emissions to downwind PM2.5 concentrations

Back-trajectory analyses for evaluating the transboundary transport effect to the aerosol pollution in South Korea

This study performed a back-trajectory analysis to determine the influence of transboundary transport on the extent of aerosol pollution in South Korea, based on 5-year PM2.5 measurements (2015-2019) in five cities covering South Korea. A transboundary transport case was selected if a back trajectory passed over a dedicated region (BOX 1 and BOX 2) in the Yellow Sea. First, we found that the frequency of transboundary transport largely increases in the high pollution case, and this pattern is almost consistent for all months and all five cities, indicating the importance of investigating the horizontal direction of air mass movement associated with PM2.5, which has been discussed extensively in previous studies. In this study, we also examined the altitude change and straight moving distance (defined as travel distance) of back trajectories regarding the extent of local PM2.5. Consequently, we found that back trajectories in high aerosol pollution showed much lower altitudes and shorter travel differences, implying a significant contribution of surface emissions and stagnant air conditions to severe aerosol pollution. As a result, the local PM2.5 level was not significantly enhanced when the air mass passed over the Yellow Sea if transboundary transport occurred at high altitudes with rapid movement (i.e., high altitude and long travel distance back-trajectory). Based on these results, we suggest utilizing the combined information of the horizontal direction, altitude variation, and length of back trajectories to better evaluate transboundary transport.

Improvement of the anthropogenic emission rate estimate in Ulaanbaatar, Mongolia, for 2020-21 winter

Ulaanbaatar (UB), the fast-growing capital of Mongolia, is known for its world's worst level of particulate matter (PM) concentrations in winter. However, current anthropogenic emission inventories over the UB are based on data from more than fifteen years ago, and satellite observations are scarce because UB is in high latitudes. During the winter of 2020-21, the first period of the Fine Particle Research Initiative in East Asia considering the National Differences (FRIEND), several times higher concentrations of PM in UB compared to other urban sites in East Asia were observed but not reproduced with a chemical transport model mainly due to the underestimated anthropogenic emissions. Therefore, we devised a method for sequentially adjusting emissions based on the reactivity of PM precursors using ground observations. We scaled emission rates for the inert species (CO, elemental carbon (EC), and organic carbon (OC)) to reproduce their observed ambient concentrations, followed by SO2 to reproduce the concentration of SO42-, which was examined to have the least uncertainty based on the abundance of observed NH3, and finally NO and NH3 for NO3-, and NH4+. This improved estimation is compared to regional inventories for Asia and suggests more than an order of magnitude increase in anthropogenic emissions in UB. Using the improved emission inventory, we were able to successfully reproduce independent observation data on PM2.5 concentrations in UB in December 2021 from the U.S. Embassy. During the campaign period, we found more than 50% of the SO42-, NO3-, and NH4+ increased in UB due to the improvement could travel to Beijing, China (BJ), and about 20% of the SO42- could travel to Noto, Japan (NT), more than 3000 km away. Also, the anthropogenic emissions in UB can effectively increase OC, NO3-, and NH4+ concentrations in BJ when Gobi dust storms occur.

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 PM_2.5 concentrations are influenced by interwoven impacts of key drivers (e.g., meteorology, local emissions, 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 PM_2.5 concentration changes based on observation and simulation in the month of January during 2016-2021 in Northeast Asia. For the simulations, we conducted modeling with the WRF-CMAQ system. The observed PM_2.5 concentrations in China and South Korea in January 2021 decreased by 13.7 and 9.8 μg/m³, respectively, compared to those in January 2016. Emission change was the dominant factor to reduce PM_2.5 concentrations in China (-115%) and South Korea (-74%) for the 6 years. However, the short-term changes in PM_2.5 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 μg/m³) over the 6 years whereas the impact of local emissions increased (+2.9 μg/m³/year) during 2016-2019 but decreased (-4.5 μg/m³/year) during 2019-2021. Additionally, PM_2.5 concentrations in the upwind area showed a positive relationship with LTIs. However, for the days when westerly winds became weak in the downwind area, high PM_2.5 concentrations in upwind area did not lead to high LTIs. These results imply that the decline of PM_2.5 concentrations in South Korea was significantly affected by a combination of emission reduction in upwind area and meteorological conditions that hinder long-range transport. The proposed multifaceted approach can identify the main drivers of PM_2.5 concentration change in a region by considering the regional characteristics.

Factors affecting recent PM2.5 concentrations in China and South Korea from 2016 to 2020

This study used observational data and a chemical transport model to investigate the contributions of several factors to the recent change in air quality in China and South Korea from 2016 to 2020. We focused on observational data analysis, which could reflect the annual trend of emission reduction and adjust existing emission amounts to apply it into a chemical transport model. The observation data showed that the particulate matter (PM_2.5) concentrations during winter 2020 decreased by -23.4 % (-14.68 μg/m³) and - 19.5 % (-5.73 μg/m³) in China and South Korea respectively, compared with that during winter 2016. Meteorological changes, the existing national plan for a long-term emission reduction target, and unexpected events (i.e., Coronavirus disease 2019 (COVID-19) in China and South Korea and the newly introduced special winter countermeasures in South Korea from 2020) are considered major factors that may affect the recent change in air quality. The impact of different meteorological conditions on PM_2.5 concentrations was assessed by conducting model simulations by fixing the emission amounts; the results indicated changes of +7.6 % (+4.77 μg/m³) and + 9.7 % (+2.87 μg/m³) in China and South Korea, respectively, during winter 2020 compared to that during winter 2016. Due to the existing and pre-defined long-term emission control policies implemented in both countries, PM_2.5 concentration significantly decreased from winter 2016-2020 in China (-26.0 %; -16.32 μg/m³) and South Korea (-9.1 %; -2.69 μg/m³). The unexpected COVID-19 outbreak caused the PM_2.5 concentrations in China to decrease during winter 2020 by another -5.0 % (-3.13 μg/m³). In South Korea, the winter season special reduction policy, which was introduced and implemented in winter 2020, and the COVID-19 pandemic may have contributed to -19.5 % (-5.92 μg/m³) decrease in PM_2.5 concentrations.

Role of vertical advection and diffusion in long-range PM2.5 transport in Northeast Asia

This study quantitatively analyzed the role of vertical mixing in long-range transport (LRT) of PM_2.5 during its high concentration episode in Northeast Asia toward the end of February 2014. The PM_2.5 transport process from an upwind to downwind area was examined using the Community Multi-scale Air Quality (CMAQ) modeling system with its instrumented tool and certain code modifications. We identified serial distinctive roles of vertical advection (ZADV) and diffusion (VDIF) processes. The surface PM_2.5 in an upwind area became aloft by VDIF- during daytime-to the planetary boundary layer (PBL) altitude of 1 km or lower. In contrast, ZADV updraft effectively transported PM_2.5 vertically to an altitude of 2-3 km above the PBL. Furthermore, we found that the VDIF and ZADV in the upwind area synergistically promoted the vertical mixing of air pollutants up to an altitude of 1 km and higher. The aloft PM_2.5 in the upwind area was then transported to the downwind area by horizontal advection (HADV), which was faster than HADV at the surface layer. Additionally, VDIF and ZADV over the downwind area mixed down the aloft PM_2.5 on the surface. During this period, the VDIF and ZADV increased the PM_2.5 concentrations in the downwind area by up to 15 μg·m^-3 (15%) and 101 μg·m^-3 (60%), respectively. This study highlights the importance of vertical mixing on long-range PM_2.5 transport and warrants more in-depth model analysis with three-dimensional observations to enhance its comprehensive understanding.