Spatiotemporal Assessment of Atmospheric Trace Gases over Singrauli Coal-Industrial Cluster Using Sentinel-5P TROPOMI and Google Earth Engine (2019–2024)

This study presents a multi-year satellite-based assessment of atmospheric pollution over Singrauli, Madhya Pradesh, India's largest coal-industrial cluster using Sentinel-5P (TROPOMI) retrievals for 2019–2024. Concentrations of CO, NO₂, SO₂, O₃, HCHO, Cloud Fraction, UV Aerosol Absorbing Index (UV-AAI), and surface solar irradiance (NASA POWER) were analysed using Google Earth Engine (GEE), with spatial visualization performed in ArcGIS Pro. The study characterizes seasonal behaviour, identifies persistent emission hotspots, quantifies long-term pollutant trends, and explores pollutant interdependencies in a critically polluted industrial region. Results indicate strong winter and post-monsoon enhancement of CO, NO₂, and SO₂, attributed to suppressed boundary-layer mixing and intensified coal combustion, while O₃ and HCHO peaked during pre-monsoon under elevated photochemical activity driven by high solar irradiance. Industrial hotspots were consistently identified over Anpara, Vindhyachal, Renusagar, and the Mahan thermal power plant zones. Mann–Kendall trend analysis indicated gradual, non-significant directional tendencies (p > 0.05) toward increasing CO, SO₂, and O₃, alongside slight NO₂ reductions. Spearman correlation revealed strong combustion-linked coupling (CO–NO₂ ρ = 0.78; NO₂–SO₂ ρ = 0.72), photochemical associations (Solar–O₃ ρ = 0.75; Solar–HCHO ρ = 0.61), and cloud-mediated suppression of UV-AAI and O₃. The Sentinel-5P and GEE framework demonstrates a scalable, cost-effective approach applicable to data-scarce industrial regions, supporting National Clean Air Programme (NCAP)-aligned air quality management in coal-dependent clusters across India.