Monitoring the distribution of atmosphere pollutants by using time series of the sulfur dioxide product of Sentinel-5P satellite (Case Study: Tehran province)

Document Type : Original Article

Authors
Nadia Abbaszadeh Tehrani 1
Kimia Khamseh 2
Seyedeh Neda Rasouli 2
Milad Janalipour 1
1 Aerospace Research Institute, Ministry of Science, Research and Technology
2 MSc Student, Department of Urban Environment, Faculty of Environment, University of Tehran
10.30487/hmes.2025.2045629.1061
Abstract
Sulfur dioxide is one of the most important pollutants in Iranian cities, especially in Tehran, which threatens the health of its citizens. The degree of damage of this pollutant depends on its temporal-spatial distribution in the atmosphere. The purpose of this research is to analyze the spatial and temporal amount of sulfur dioxide gas in Tehran province in 2023 using the time series of remote sensing products. After obtaining the sulfur dioxide product from the Sentinel-5p satellite, the relevant data analysis was performed. The presence of spatial autocorrelation and data clustering by analyzing Moran's I statistic and local Moran's index, and to determine the hot and cold spots of this pollutant, Getis-Ord Gi statistic was used in Tehran province, and finally, using the Geographic Information System, the impact of land use on the concentration of pollutants was obtained The results of zoning and local and global spatial autocorrelation along with hot spot analysis of sulfur dioxide pollutant concentration showed that the concentration of this pollutant in the south and southeast regions of the province is increasing in the cold seasons of the year. The simultaneous use of several spatial analyzes showed that Tehran province was divided into two parts, the east, which was almost unpolluted, and the west and south, which were polluted, and less pollution was seen in the central parts. Also, among the types of land use, the highest concentration of sulfur dioxide pollutant and the maximum distribution of hot spots belong to industrial use and factories.
Keywords
Moran Index
Remote Sensing
Sulfur Dioxide
Sentinel
Tehran Province
Subjects