Analysis of Forest Fire Emissions and Meteorological Impacts in Southwestern China Based on Multi-Source Satellite Observations

Amid the growing frequency of forest fires in southwestern China, this study aims to quantify pollutant emissions and identify key meteorological drivers using multi-source satellite data. Active fire data from Himawari-8/9, MODIS, and VIIRS were integrated to construct a top-down emission inventory for 2016–2023, while the Geodetector method was applied to evaluate meteorological influences. Results indicate mean annual emissions (×103 t·a−1) of 5623.58 (±1554.33) for CO2, 356.84 (±98.63) for CO, and substantial amounts of particulate and gaseous pollutants. Spatially, Yunnan and Sichuan were the dominant emitters; temporally, emissions peaked in January–April and November–December, with daytime levels surpassing nighttime levels. Relative humidity was identified as the dominant meteorological driver (Q = 0.1223), while the interaction between temperature and relative humidity (Q = 0.1486) further enhanced explanatory power. These findings improve the precision of emission inventories and provide essential support for regional fire management and air quality modeling in complex environments.