Assessing climate variability and its correlation with regional air pollution in Chhattisgarh, India utilizing Google Earth Engine (GEE)

Abstract This study investigates the spatiotemporal dynamics of key atmospheric pollutants and environmental variables in Chhattisgarh using satellite remote sensing data from 2019 to 2023. The dataset includes parameters such as Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), rainfall, and concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), methane (CH4), ozone (O3), and UV aerosol index (AI) with the help of Google Earth Engine (GEE) algorithms. Analysis revealed distinct seasonal patterns, with the highest rainfall recorded during the monsoon season, predominantly in the southern region, and elevated LST values observed in the central region during pre-monsoon months. Furthermore, CO concentrations peaked (0.057 mol/m2) during the pre-monsoon season, particularly in industrial zones, while NO2 levels were highest in the central region across all seasons. SO2 concentrations exhibited spatial variability, with peaks (0.00204 mol/m2) in the post-monsoon period, primarily attributed to industrial activities. CH4 concentrations were higher during pre-monsoon and post-monsoon seasons, with anomalies observed in 2023. O3 levels showed a seasonal variation, with higher (0.1289 mol/m2) concentrations during pre-monsoon months, especially in the northern region. The UV aerosol index was highest during the monsoon season, attributed to increased moisture and biomass burning. Correlation analysis revealed associations between pollutants and environmental variables, indicating potential sources and interactions. These findings contribute to understanding regional air quality dynamics and informing targeted mitigation strategies for sustainable environmental management in Chhattisgarh.