First top-down diurnal adjustment to NO emissions inventory in Asia informed by the Geostationary Environment Monitoring Spectrometer (GEMS) tropospheric NO columns.

Pioneering the use of the Geostationary Environment Monitoring Spectrometer's (GEMS) observation data in air quality modeling, we adjusted Asia's NO emissions inventory by leveraging the instrument's unprecedented sampling frequency. GEMS tropospheric NO columns served as top-down constraints, guiding our Bayesian inversion to constrain NO emissions in Asia during spring 2022. This enabled the model to better capture the diurnal variation in NO emissions, such as its morning rush hour peak, particularly when more retrievals were available each day, improving the simulation accuracy to a certain extent. The GEMS-informed adjustment reduced the extent of model underestimation of surface NO concentrations from 17.38 to 5.58% in Korea and from 13.05 to 4.54% in China, showing about 9.40% and 5.77% greater improvements, respectively, compared to the adjustment based on the sun-synchronous low earth orbit observation proxy. Our findings highlight the potential of geostationary observation data in refining the diurnal cycle of inventoried NO emissions, thereby more effectively improving the accuracy of air quality simulations.