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

Abstract

BackgroundUrban 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). MethodThis 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. ResultThe 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.