Journal Clean WAS (JCleanWAS)

Air pollution, particularly from aerosol particles, is a major issue in developing countries like India. Correlating seasonal variations between AOD, LST, NDVI, and rainfall are closely linked to regional air quality changes. This study aims to assess long-term changes in Aerosol Optical Depth (AOD), vegetation index, and land surface temperature in Singrauli, India, and investigate their interactions using remote sensing and GIS methods. This study used Google Earth Engine (GEE) to obtain Multi-Angle Implementation of Atmospheric Correction (MAIAC), a combined Aqua and Terra MODIS product for the year 2024 every month for AOD, NDVI, and LST for Singrauli district. The study found that AOD was lowest during the monsoon season and highest throughout the winter and some months of summer whereas the highest NDVI was obtained in the month after monsoon and some months of winter the lowest NDVI was recorded in the month of summer and LST shows the opposite trend of NDVI means that high LST was recorded in the month of the summer and lowest LST in the month of post-monsoon and winter season. The correlation analysis was performed from the ambient air pollutant data from 4 monitoring sites, NDVI, and LST with AOD. The Particulate matter PM10 and PM2.5 show a positive correlation with AOD with average R2 values of 0.4984 and 0.5459 respectively at all 4 locations because particulate matter directly contributes to the concentration of AOD but gaseous pollutants like NO2 and SO2 shows the very weak correlation with AOD with R2 value of 0.1393 and 0.0862 respectively as AOD only consist of particulate matters so these gaseous pollutants didn’t contribute much in AOD. Many other factors also influence the AOD and LST in the study area like wind direction, wind speed, relative humidity, and many more. The dominant wind direction in Singrauli throughout the year 2024 is North-West with an average speed of 2-3 m/s.