Studying Effect of Climatic Variables on Temporal Distribution of Air Pollution Using Sentinel-5P Data in Mazandaran Province, Iran

Abstract

Studying air pollution distribution and factors is crucial for control. The research focused on analyzing air pollution distribution and its correlation with climatic variables in Mazandaran Province from 2018 to 2022 using Remote Sensing. Air pollution distribution analyzed with TROPOMI sensor in Google Earth Engine system. Air pollution change point analyzed with Petit's homogeneity test. Additionally, Pearson's correlation test was utilized to assess the correlation among variables. Spatial analysis of air pollution showed that the highest amount of air pollution in the period of 2018-2022 was in the east of Mazandaran and at altitudes of 0-500 m. The test results showed that the concentrations of CO, O3, and SO2 gases had a significant downward trend in some months. However, the average NO2 gas in October 2020 has been significant at the level of 5%. The seasonal air pollution concentration with NO2 gas is higher in winter and autumn. The highest concentration of O3 is in winter and spring. However, the highest concentration of SO2 is related to winter and autumn. The number of sunshine hours with a correlation coefficient between 0.5 and 0.8 has been the most effective climate component on air pollution. Meteorological factors impact temporal-spatial dispersion directly, indirectly.

Keywords

• homogeneity test
• mazandaran
• pollutant
• satellite
• sensor