Spatio-Temporal Assessment of Atmospheric Pollutants and Dispersion Mechanisms over West Bengal (2019–2024): Insights from Sentinel-5P, GEOS-CHEM, and HYSPLIT Models

Arkaprava Das 

This study delivers a thorough spatio-temporal analysis of atmospheric pollutants and their dispersion mechanisms across West Bengal (2019–2024), utilizing an integrated approach of Earth Observation and modeling techniques. We employed satellite data from Sentinel-5P alongside GEOS-Chem box modeling, HYSPLIT trajectory simulations, and AI-enhanced statistical methods to examine trends, identify hotspots, and analyze the transport dynamics of six primary atmospheric constituents—SO₂, NO₂, CO, CH₄, O₃, and HCHO. Our findings indicate a significant upward trend in CH₄ (R² = 0.92, p < 0.01) and a moderate increase in O₃ and HCHO, suggesting heightened photochemical oxidation and increased regional greenhouse forcing. In contrast, SO₂ and NO₂ displayed stabilization or slight declines, reflecting successful industrial emission regulations and monsoonal dispersion effects. Spatial hotspot analysis pinpointed the Kolkata–Howrah–Haldia–Asansol–Durgapur corridor as a continual emission zone, while trajectory assessments revealed strong seasonal transport from northern and western India. Validation of the GEOS-Chem model (AUC > 0.82 for O₃ and HCHO) demonstrated robust predictability for secondary pollutants influenced by photochemical reactions and boundary-layer changes. Collectively, these results indicate a transition toward an atmospheric regime dominated by secondary pollutants, driven by both anthropogenic activities and meteorological conditions. These insights underscore the pressing need for comprehensive mitigation strategies that prioritise methane reduction, VOC management, and coordinated regional emission control efforts. The research aligns with the UNSDGs 6, 11, 13, and 17, promoting climate-resilient air quality management and fostering sustainable environmental governance through the integration of satellite and AI technologies for atmospheric monitoring.