Geostationary observations of air pollutants from biomass burning: a synergy of GIIRS and GEMS over Southeast Asia

Biomass burning (BB) significantly disturbs ecosystems and threatens regional and global climate, air quality, and human health through the massive emission of pollutants. Carbon monoxide (CO) and nitrogen dioxide (NO₂) generated from these fires are key components in atmospheric chemistry, revealing combustion processes and efficiency. Over the past two decades, low-Earth-orbit (LEO) platforms have played a dominant role in trace gas monitoring; however, their snapshot sampling capabilities are unable to capture the rapid diurnal evolution of fire emissions, leading to systematic uncertainties in emission inventories. In this study, we integrate observations from the Geostationary Interferometric Infrared Sounder (GIIRS) onboard FY-4B and the Geostationary Environment Monitoring Spectrometer (GEMS) onboard GK-2B to monitor biomass burning over Southeast Asia. Validation against TROPOMI and ground-based networks (TCCON and Pandora) demonstrates the reliability of this combined dataset.  Time-series analysis (July 2022–June 2025) shows that regional CO and NO₂ variations exhibit high consistency with fire radiative power (FRP). Focusing on the representative fire hotspot of Northern Laos, we observe a bimodal diurnal NO₂ pattern driven by the interplay of emissions, photochemistry, and meteorology. Specifically, we identified a nonlinear response of NO₂ growth to fire intensity. Observational evidence suggests that under extreme burning conditions, the conversion of NO_x is constrained by limited atmospheric oxidative capacity. We further quantified the intraday dynamics of combustion efficiency (indicated by the enhancement ratio, ER = ΔNO₂/ΔCO), revealing significant temporal fluctuations. This pronounced diurnal variability confirms that single-overpass LEO observations introduce a systematic estimation bias in emission factors. This study provides observational constraints for refining emission inventories and demonstrates a framework for applying next-generation global geostationary satellite constellations to fire monitoring.