First top-down diurnal adjustment to NOx emissions inventory in Asia informed by the Geostationary Environment Monitoring Spectrometer (GEMS) tropospheric NO2 columns

Abstract

Abstract Pioneering the use of the Geostationary Environment Monitoring Spectrometer’s (GEMS) observation data in air quality modeling, we adjusted Asia’s NOx emissions inventory by leveraging the instrument’s unprecedented sampling frequency. GEMS tropospheric NO2 columns served as top-down constraints, guiding our Bayesian inversion to constrain NOx emissions in Asia during spring 2022. This enabled the model to better capture the diurnal variation in NOx 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 NO2 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 NOx emissions, thereby more effectively improving the accuracy of air quality simulations.

Keywords

• GEMS
• Geostationary
• NOx
• Emissions inventory
• Top-down
• Inverse modeling