Examining the relationship of major air pollutants with land surface parameters and its monthly variation in Indian cities using satellite data

• Published in: Remote sensing applications Vol. 35; p. 101232
• Main Authors: Bala, Ruchi, Yadav, Vijay Pratap, Kumar, D. Nagesh, Prasad, Rajendra
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-08-2024
• Subjects: Air pollutants; Land surface temperature; Normalized difference built-up index; Normalized difference vegetation index; Sentinel-5P; Sentinel-5P; Normalized difference vegetation index; Land surface temperature; Air pollutants; Normalized difference built-up index
• ISSN: 2352-9385; 2352-9385
• DOI: 10.1016/j.rsase.2024.101232

The relationship of land surface parameters with the air pollutants is worth exploring. The present study investigates the relation of Land Surface Temperature (LST), Normalized Difference Built-up Index (NDBI) and Normalized Difference Vegetation Index (NDVI) with six air pollutants such as Aerosol Index (AI), Carbon monoxide (CO), formaldehyde (HCHO), Sulphur Dioxide (SO2), Nitrogen dioxide (NO2) and ozone (O3) from January to December month of year 2022 in four cities situated at varying climatic zones of India. Except for O3, which exhibits lower concentration in winter and greater in summer, the air pollutants concentration showed lower values during monsoon season and higher during summer and post-monsoon seasons. The relationship of LST, NDBI and NDVI with different air pollutants were found to vary throughout the year in the four cities. The magnitude of correlation coefficient (R) was found greater for AI and NO2 as compared to other pollutants depicting greater impact of land surface parameters on concentration of AI and NO2. The surface urban cool island effect in Bikaner showed strong negative relation of LST with NO2 with magnitude of R greater than 0.41. The surface urban heat island formation in Varanasi showed strong positive correlation with the air pollutants such as AI, CO, NO2 and O3 with magnitude of R value greater than 0.61, 0.31, 0.59 and 0.32 for AI, CO, NO2 and O3, respectively. Even though, the correlation of LST with air pollutants varied with seasons and cities, NDVI showed negative correlation with most of the air pollutants in the cities except in Bikaner where vegetation content is negligible. Thus, increasing the amount of vegetation in a city can improve the air quality by lowering the quantity of air pollutants there.