Examining land surface temperature and relations with the major air pollutants: A remote sensing research in case of Tehran

Abstract

Background: Urban air pollution is a dynamic mixture of Land Surface Temperature (LST), gases, particulate matter with daily and seasonal changes due to anthropogenic activities, Land-use Land-cover (LULC) transformations, and climatic conditions. The relationship between urban biophysical and thermal conditions, and LULC is generally known; however, the absence of a dense network of land-based meteorological stations is an obstacle to the comparison of LST to Major Air Pollutants (MAP). Method: This research proposes investigation of the relationships between LST derived by Sentinel-3 SLSTR, MAP derived by Sentinel-5 Precursor, and air pollution monitoring system stations in Tehran province, Iran. The method is designed in a moving average model with the use of a Python application programming interface, geographical information system, and remote sensing. Result: The mean concentration of the Particulate Matter (PM), Sulfur Dioxide (SO2), and Nitrogen Dioxide (NO2) are mainly in the Tehran metropolis and the core urban area. A negative correlation was noted between the PM2.5, SO2, NO2, and altitude. Additionally, increased altitude negatively affects LST, Carbon Monoxide (CO), and Ozone (O3) values; whereas, CO and O3 have positive correlations with LST, representing the mutual impacts of LST, CO, and O3 values in Tehran province.