Evolution of GEMS Level-2 Algorithms for Atmospheric Composition Retrievals and Their Impacts on Air Quality Monitoring

Since the launch of the Geostationary Environment Monitoring Spectrometer (GEMS) in 2020, the Level-2 (L2) algorithms for atmospheric pollutant retrievals—such as nitrogen dioxide (NO₂), ozone, and aerosols—as well as for the generation of a priori data, including cloud and surface reflectance products, have been continuously improved on an annual basis. Through successive algorithm updates, the GEMS NO₂ product has shown reduced overestimation and improved representation of the stratospheric contribution, while the formaldehyde (HCHO) product has mitigated the excessive influence of chemical transport model (CTM) a priori information on the retrieval results. This study presents the major updates and changes implemented in key GEMS L2 products over the past five years and evaluates their impacts through comparisons with other satellite observations and ground-based remote-sensing measurements. These results provide a comprehensive overview of the evolution of the GEMS L2 algorithms and demonstrate their applicability for long-term air-quality monitoring.