Development of surface observation-based two-step emissions adjustment and its application on CO, NO_x, and SO₂...

It is challenging to estimate local emission conditions of a downwind area solely based on concentrations in the downwind area. This is because air pollutants that have a long residence time in the atmosphere can be transported over long distances and influence air quality in downwind areas. In this study, a Two-step Emissions Adjustment (TEA) approach was developed to adjust downwind emissions of target air pollutants with surface observations, considering their long-range transported emission impacts from upwind areas calculated from air quality simulations. Using the TEA approach, CO, NO_x, and SO₂ emissions were adjusted in China and South Korea between 2016 and 2021 based on existing bottom-up emissions inventories. Simulations with the adjusted emissions showed that the 6-year average normalized mean biases of the monthly mean concentrations of CO, NO_x, and SO₂ improved to 0.3 %, -2 %, and 2 %, respectively, in China, and to 5 %, 7 %, and 4 %, respectively, in South Korea. When analyzing the emission trends, it was estimated that the annual emissions of CO, NO_x, and SO₂ in China decreased at a rate of 7.2 %, 4.5 %, and 10.6 % per year, respectively. The decrease rate of emissions for each of these pollutants was similar to that of ambient concentrations. When considering upwind emission impacts in the emissions adjustment, CO emissions increased by 1.3 %/year in South Korea, despite CO concentrations in the country decreasing during the study period. During the study period, NO_x and SO₂ emissions in South Korea decreased by 3.9 % and 0.5 %/year, respectively. Moreover, the TEA approach can account for drastic short-term emission changes (e.g., social distancing due to COVID-19). Therefore, the TEA approach can be used to adjust emissions and improve reproducibility of concentrations of air pollutants suitable for health studies for areas where upwind emission impacts are significant.