Satellite-based Emission Inventory Adjustments Improve Simulations of Long-range Transport Events

Long-range pollution transport (LRT) events have a wide impact across East Asia, but are often difficult to track due imprecise emission inventories and changing domain scales as the plume moves from source receptor locations. This study adjusts bottom-up inventory based on changes in remotely sensed NO2 column densities for region of then with CMAQv5.2.1 simulates LRT plumes Taiwan. Adjustment an emissions satellite measurements during COVID-19 lockdown China led ~59% reduction over relevant area compared base emissions. As result, PM2.5 mass concentrations were reproduced match observations (mean fractional bias, MFB -13.9% 18.5% at remote urban station) passed through northern Furthermore, OMI-adjusted simulation brought all major components within ~50% measured values. Another event 2018 more subtle OMI-adjustments was also simulated improved overall concentration tip Taiwan (MFB: -91.5%) model -102.1%), acceptable index agreement (0.78). For event, non sea-salt sulfate consistently underpredicted (0.2–0.4), while nitrate overpredicted by up factor 11. Copernicus Atmosphere Monitoring Service (CAMS) reanalysis shows high eastern areas associated 72-h back-trajectories both events, lending support future investigations production In order better these out Asia optimize OMI-adjustment methodology, it is recommended explore other satellite-based products map unaccounted SO2 sources upstream