DOI 10.1016/j.envpol.2026.129391
Improving Satellite-Reanalysis Sulfate Aerosol Estimates over India Using Ground Measurements.
Аннотация
Atmospheric sulfate is a major secondary inorganic component of fine particulate matter (PM2.5) that severely degrades regional air quality and public health. As routine ground-based sulfate monitoring remains limited across India, this study evaluates uncertainties in near-surface sulfate concentrations estimated by NASA's MERRA-2 reanalysis using an extensive observational dataset. We compiled 2,583 ground-based sulfate observations from 167 monitoring sites across 37 Indian cities during 2017-2025. Of these, 2,223 daily site-level measurements from 27 cities were aggregated across multiple monitoring sites within each city to obtain 1,331 city-level daily observations for direct comparison with collocated MERRA-2 estimates, model development, and validation. Measurements reveal substantial spatial and seasonal variability, with wintertime levels peaking at 25±6 μg/m3 in Prayagraj. MERRA-2 overestimated surface sulfate across all evaluated regions, with winter NMBs (Normalized Mean Bias) of +38.35% in the Indo-Gangetic Plain (IGP), and +73.35% in Central India; corresponding post-monsoon NMBs were +68.23% and +66.94%. To improve representation, season-specific linear mixed-effects (LME) models incorporating seasonal-average fixed effects and city-specific random intercepts and slopes were developed. Seasonal relationships between ground-based sulfate and MERRA-2 sulfate yielded slopes of 0.43 (winter) and 0.28 (post-monsoon), with positive intercepts ranging from 5.0 to 6.4 μg/m3. Leave-one-city-out (LOCO) cross-validation demonstrated acceptable transferability to unseen cities during the post-monsoon ( = 0.35; NMB = +1.14%) and winter ( = 0.28; NMB = +0.53%) seasons. Applying this improved framework identified the IGP and parts of central and eastern India as major sulfate hotspots. These findings demonstrate that accounting for seasonal variability and city-level heterogeneity significantly enhances ground-level sulfate estimation, providing a robust framework for assessing regional distributions and informing target-specific SO2 emission control strategies.
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