This study analyzes the impact of forest and land fires on Aerosol Optical Depth (AOD) and fine particulate matter (PM₂.₅) concentrations using in-situ AERONET observations, PM₂.₅ measurements from the Sultan Thaha Meteorological Station in Jambi (2020–2023), and satellite-based AOD data from the Geostationary Environment Monitoring Spectrometer (GEMS). Linear regression and Pearson correlation analyses were applied to establish the empirical relationship between AOD and PM₂.₅, with validation against ground-based observations. The results indicate a strong correlation between AOD and PM₂.₅, with the highest values observed at 340 nm from AERONET (r = 0.7824; R² = 61.21%) and 354 nm from GEMS (r = 0.7802; R² = 60.88%). The derived regression equation was then used to convert satellite AOD into spatial estimates of PM₂.₅. The resulting distribution maps show widespread pollution, with PM₂.₅ concentrations exceeding 80 µg/m³ during the peak fire period in September 2023. This increase coincided with a rise in hotspot activity and low rainfall, while PM₂.₅ concentrations decreased following precipitation events. These findings demonstrate that satellite-derived AOD can be used to estimate PM₂.₅ concentrations and capture the temporal and spatial patterns of air pollution during fire episodes in Jambi Province. Keywords: Aerosol Optical Depth (AOD); Forest Fire; Air Quality; PM₂.₅; Remote Sensing
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