Spatio-Temporal Analysis of Tropospheric Atmospheric Pollution Indicators over Kolkata Municipal Corporation (KMC) Using Sentinel-5P Observations
Rimpa Patra
Annapurna Memorial College of Education, Kasinagar, South 24 Parganas-743347, India.
Subha Das
*
Department of Remote Sensing and Geoinformatics, Birla Institute of Technology, Mesra, Ranchi, Jharkhand-835215, India.
*Author to whom correspondence should be addressed.
Abstract
Rapid urbanization, industrial expansion, and increasing transportation activities have significantly influenced atmospheric pollution in major metropolitan cities of India, particularly Kolkata. The present study evaluates the spatio-temporal distribution of satellite-derived atmospheric pollution indicators, including nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), ozone (O3), and Aerosol Index (AI), over Kolkata Municipal Corporation (KMC) during 2019–2025 using Sentinel-5P observations processed within the Google Earth Engine environment. Annual mean pollutant composites were generated to assess spatial variability, concentration patterns, and long-term atmospheric changes across the metropolitan region. Descriptive statistics, trend analysis, and Pearson correlation analysis were employed to evaluate pollutant dynamics and interrelationships. The results revealed considerable spatial heterogeneity in pollutant distribution throughout the study period. Relatively higher NO2, SO2, and CO values were generally observed in the central and northern parts of KMC, whereas O3 exhibited comparatively higher concentrations in several northern and northeastern sectors. Temporal analysis indicated substantial interannual variability in NO2 and CO, while SO2 and O3 displayed relatively stronger increasing tendencies. The Aerosol Index remained predominantly negative, suggesting limited dominance of UV-absorbing aerosols and highlighting the influence of aerosol type, atmospheric humidity, cloud cover, and retrieval conditions. A noticeable decline in several pollutants was observed during 2020, corresponding to the COVID-19 lockdown period, followed by varying levels of recovery after 2021. Correlation analysis revealed the strongest positive association between O3 and AI (r = 0.74), followed by SO2 and O3 (r = 0.65), indicating potential interactions among atmospheric oxidation processes and aerosol conditions. Overall, the study demonstrates the utility of Sentinel-5P observations and cloud-based geospatial analysis as effective tools for long-term monitoring of atmospheric pollution indicators and provides valuable insights into urban atmospheric variability over Kolkata.
Keywords: Sentinel-5P, Kolkata, atmospheric pollution, google earth engine, spatio-temporal analysis