The Impact of Springtime-Transported Air Pollutants on Local Air Quality With Satellite-Constrained NOx Emission Adjustments Over East Asia

To quantify the impact of transported air pollutants on local air quality, this study applies an inverse modeling technique with tropospheric nitrogen dioxide column retrievals from TROPOspheric Monitoring Instrument, and the CMAQ-ISAM model, which computes source attribution over six regions of interest in spring 2019 over East Asia. Satellite-constrained nitrogen oxides (NOx) emissions successfully improve model performance by significantly reducing the normalized mean bias of concentrations of NOx, Ozone (O-3), and PM2.5 from most regions in China and South Korea. Anticyclones over the Yellow Sea transport air pollutants and increase the contribution of emissions from adjacent regions to local air quality. Fluxes of air pollutants with posterior emissions showed notable enhancements in their magnitude by 3%-24% for NOy, O-3, and PM2.5. The contributions of emissions from neighboring regions on local NOx and O-3 budgets in the planetary boundary layer were 22.96%-35.24% and 24.23%-42.26%. The contribution of emissions from North Korea was notable despite its comparably lower emission rates. Regarding the impact of external influences on local air quality, the enhanced chemical loss of NOx compensated for increases by transport. Also, the increased vertical gradient of maximum daily 8-hr average O-3 amplified vertical transport and dry deposition processes in the opposite direction along with slight changes in the chemical net O-3 production rate. This study shows the nonlinear response of local air quality to changes in the transport of air pollutants, which could be further investigated concerning changes in emissions and climatological factors that would modify the inflow of air pollutants.

Automated summary

This study quantifies the impact of transported air pollutants on local air quality using inverse modeling technique and satellite data. The results show that using satellite-constrained emissions data can significantly improve model performance and reveal the contributions of emissions from neighboring regions to local air quality.