Recent changes of surface particulate matter (PM) concentration in the Seoul Metropolitan Area (SMA), South Korea, are puzzling. The long-term trend of surface PM concentration in the SMA declined in the 2000s, but since 2012 its concentrations have tended to incline, which is coincident with frequent severe hazes in South Korea. This increase puts the Korean government’s emission reduction efforts in jeopardy. This study reports that interannual variation of surface PM concentration in South Korea is closely linked with the interannual variations of wind speed. A 12-year (2004–2015) regional air quality simulation was conducted over East Asia (27-km) and over South Korea (9-km) to assess the impact of meteorology under constant anthropogenic emissions. Simulated PM concentrations show a strong negative correlation (i.e. R = −0.86) with regional wind speed, implying that reduced regional ventilation is likely associated with more stagnant conditions that cause severe pollutant episodes in South Korea. We conclude that the current PM concentration trend in South Korea is a combination of long-term decline by emission control efforts and short-term fluctuation of regional wind speed interannual variability. When the meteorology-driven variations are removed, PM concentrations in South Korea have declined continuously even after 2012.

In January 2020, anthropogenic emissions in Northeast Asia reduced due to the COVID-19 outbreak. When outdoor activities of the public were limited, PM2.5 concentrations in China and South Korea between February and March 2020 reduced by − 16.8 μg/m3 and − 9.9 μg/m3 respectively, compared with the average over the previous three years. This study uses air quality modeling and observations over the past four years to separate the influence of reductions in anthropogenic emissions from meteorological changes and emission control policies on this PM2.5 concentration change. Here, we show that the impacts of anthropogenic pollution reduction on PM2.5 were found to be approximately − 16% in China and − 21% in South Korea, while those of meteorology and emission policies were − 7% and − 8% in China, and − 5% and − 4% in South Korea, respectively. These results show that the influence on PM2.5 concentration differs across time and region and according to meteorological conditions and emission control policies. Finally, the influence of reductions in anthropogenic emissions was greater than that of meteorological conditions and emission policies during COVID-19 period.

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We estimated long-term foreign contributions to the particulate matter of 2.5 μm or less in diameter (PM2.5) concentrations in South Korea with a set of air quality simulations. The Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Community Multiscale Air Quality (CMAQ) modeling system was used to simulate the base and sensitivity case after a 50% reduction of foreign emissions. The effects of horizontal modeling grid resolutions (27- and 9-km) was also investigated. For this study, we chose PM2.5 in South Korea during 2010–2017 for the case study and emissions from China as a representative foreign source. The 9-km simulation results show that the 8-year average contribution of the Chinese emissions in 17 provinces ranged from 40–65%, which is ~4% lower than that from the 27-km simulation for the high-tier government segments (particularly prominent in coastal areas). However, for the same comparison for low-tier government segments (i.e., 250 prefectures), the 9-km simulation presented lowered the foreign contribution by up to 10% compared to that from the 27-km simulation. Based on our study results, we recommend using high-resolution modeling results for regional contribution analyses to develop an air quality action plan as the receptor coverage decreases.

Abstract. Sixty days after the lockdown of Hubei Province, where the coronavirus was first reported, China's true recovery from the pandemic remained an outstanding question. This study investigates how human activity changed during this period using observations of surface pollutants. By combining surface data with a three-dimensional chemistry model, the impacts of meteorological variations and variations in yearly emission control are minimized, demonstrating how pollutant levels over China changed before and after the Lunar New Year from 2017 to 2020. The results show that the reduction in NO2 concentrations, an indicator of emissions in the transportation sector, was clearly greater and longer in 2020 than in normal years and started to recover after 15 February. By contrast, PM2.5 emissions had not yet recovered by the end of March, showing a reduction of around 30 % compared with normal years. SO2 emissions were not affected significantly by the pandemic. An additional model study using a top–down emission adjustment still confirms a reduction of around 25 % in unknown surface PM2.5 emissions over the same period, even after realistically updating SO2 and NOx emissions. This evidence suggests that different economic sectors in China may be recovering at different rates, with the fastest recovery in transportation and a slower recovery likely in agriculture. The apparent difference between the recovery timelines of NO2 and PM2.5 implies that monitoring a single pollutant alone (e.g., NOx emissions) is insufficient to draw conclusions on the overall recovery of the Chinese economy.