Global Spatiotemporal Patterns and Drivers of Fire-Driven Pollutant Emissions

Biomass burning constitutes a significant source of global atmospheric pollution, profoundly impacting regional air quality and the global carbon cycle. However, current global characterizations of fire emissions rely predominantly on polar-orbiting satellite data, whose limited temporal resolution hinders the capture of rapid evolution and diurnal variations in fire emissions. To address this, we identifies global hourly fire incidents from 2015 to 2025 using active fire products from multiple geostationary satellites. By integrating ERA5 vegetation and meteorological data, we construct an Estimated Biomass Burned Index (EBBI), which enables a unified physical quantification of available fuel load across global vegetation zones. Subsequently, we evaluate the dynamic increments of multiple pollutants during fire events, quantify regional disparities in post-fire emissions, and decouple the nonlinear mechanisms by which meteorological dispersion conditions and fuel attributes drive surface pollutant concentrations. Our study effectively bridges the gap in global high-frequency fire emission monitoring, providing a critical scientific basis for understanding short-term pollutant transport mechanisms and improving emission inventories.