<![CDATA[Fine particulate matter (PM2.5) estimation from satellite-derived Aerosol Optical Depth (AOD) is often biased in humid tropical environments because aerosol water uptake enhances optical extinction without a corresponding increase in dry particulate mass. This study develops a physics-informed, non-linear AOD-to-PM2.5 conversion framework that explicitly accounts for hygroscopic growth. Four years (2020–2023; N = 1.456 daily observations) of AOD, PM2.5, and relative humidity (RH) data from the Copernicus Atmosphere Monitoring Service (CAMS) global reanalysis over Jakarta, Indonesia, were used to quantify humidity-dependent bias and estimate an empirical hygroscopic exponent (gamma). The conventional linear model showed systematic overestimation under high-humidity conditions (RH > 80%), with a mean positive bias of 18.7 µgm-3. Incorporating the hygroscopic correction yielded gamma = 0.68 ± 0.04, increased R2 from 0.52 to 0.84, and reduced RMSE from 15.8 to 8.7 µgm-3. The estimated gamma remained stable across seasonal subsets, data-availability scenarios, and quality control thresholds and was consistent with reported values for urban-industrial aerosols. These results demonstrate that explicitly representing aerosol hygroscopicity can substantially improve AOD-based PM2.5 estimation in humid tropical environments. Although calibrated using CAMS reanalysis over Jakarta, the framework provides a physically interpretable and reproducible approach that can be applied to other regions after appropriate local recalibration.]]>
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