Investigating the Correlation Between Land Surface Temperature and Air Pollutants in Urban Environments: A Case Study of Tehran (2019–2023)

Urbanization and industrialization have intensified the interplay between land surface temperature (LST) and air pollutants, significantly influencing urban microclimates and public health. This study investigates the spatial and temporal correlations between LST and five key air pollutants, NO₂, O₃, CO, HCHO, and SO₂, across Tehran from 2019 to 2023. Using satellite-derived data from MODIS and Sentinel-5P, alongside ground-based measurements, the analysis employed geospatial techniques, Pearson correlation, and linear regression models to examine these relationships. The results reveal a strong negative correlation between LST and NO₂, suggesting that these pollutants contribute to surface cooling via aerosol formation. In contrast, CO, HCHO, and O₃ show weaker and more variable associations with LST, reflecting complex seasonal and chemical interactions. These findings highlight the multifactorial nature of urban pollution–temperature dynamics and underscore the value of integrated remote sensing and statistical modelling in environmental monitoring and climate adaptation planning.