In this study, we performed emissions adjustment of elemental carbon (EC) emissions in five sub-regions in China by adopting two approaches (i.e., annual or monthly basis) and estimated their impacts on EC concentrations in South Korea using air quality modeling and observed EC concentrations at the Baengnyeong supersite (BN). In 2016, the observed annual mean EC concentration at BN was 0.85 µg/m3, while the simulated concentration before emissions adjustment was underestimated by 0.30 µg/m3. After applying the annual- and monthly-basis emissions adjustments, Chinese EC emissions increased by 36% and 53%, respectively, compared to the emission inventory. Showing better model performance with EC concentrations observed at BN, air quality simulations with those two emissions adjustments exhibited distinct characteristics. While preserving spatiotemporal variations of EC emissions in China, the annual-basis emissions adjustment reduced model bias between observed and simulated monthly mean EC concentrations by applying one adjusting factor per sub-region. This approach helps compensate for data scarcity in specific months. Conversely, the monthly-basis approach requires data availability for each month to adjust emissions, limiting its applicability. However, the modeled results utilizing this approach more closely align with the observations by improving mean bias and correlation. While Chinses EC emission impact during 2016 was 0.25 µg/m3 before the emissions adjustment, they increased to 0.38 and 0.48 µg/m3 after the emission adjustments, showing relatively larger increases in Seoul Metropolitan Area where half of the population of South Korea live. This suggests that accurate emissions in upwind areas are essential for better understanding air quality and establishing reliable air quality improvement plans in downwind areas such as in South Korea.
