Journal of Spatial Analysis

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Application of Sentinel 5 satellite imagery in identifying air pollutants Hotspots in Iran
 
Shiva Gharibi¹, Kamran Shayesteh²
1- PhD Student of Environmental Science, Malayer University, Malayer, Iran.
2-Assistant professor, Department of Environmental Sciences, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran
 
k.shayesteh@malayeru.ac.ir
Extended abstract
1- Introduction
Today, poor air quality is one of the most important environmental problems in many cities around the world. Air pollution can have a devastating effect on humans, plants, organisms, and human assets, and efforts are being made to anticipate and analyze the amount of distribution and transmission of air pollutants in order to minimize the adverse effects on air quality and climate. Among the most important air pollutants are (CO), (SO2), (NO2), (O3) and aerosols (AI). Numerous studies have been conducted on the monitoring of these pollutants based on information and statistics from pollution monitoring devices, but the use of satellite images in the field of monitoring and measuring pollutants has been limited. Due to the increasing growth of these pollutants, in this study, an attempt has been made to identify the average spatial concentration of the most important air pollutants as the actual sources of pollution on the scale of Iran from October 2018 to December 2019. Also, identifying the most polluted centers in Iran based on the average of 5 pollutants is another goal of this study. Therefore, the aim of this study is to demonstrate the ability of Sentinel satellite to monitor air pollutants, and the ability of GPW images to produce a population density map for the first time on an Iranian scale.
 
2- Methodology
 Using the Python programming language in the Google Earth Engine program environment, various products related to CO, SO2, NO2, O3 and AI pollutant images, obtained from Sentinel-5 satellite images during the study period and in the scale of Iran, were obtained for monitoring of air pollutants and determination of pollutants focuses. The output variable is defined as a set of images based on the time filter (2019) and the spatial filter (Iran borders). The output of the average concentration of pollutants for each month is calculated separately and annually in these filters. Then, the spatial map of the average concentration of pollutants in the Arc map software was analyzed and statistical information related to the average concentration of these pollutants was processed by SPSS statistical software. To determine the hotspots in terms of all pollutants, the raster location map of each pollutant was classified using the Jenks algorithm. In order to identify the share of provinces and counties, the amount of pollutants was also analyzed by spatial statistics in GIS environment and using the Zonal Statistics command based on the defined administrative boundaries. The G statistic was used for Cluster analysis, and in order to identify Hot Spots and Cold Spots, Getis-Ord Gi statistic (Gi) was used in GIS environment.To determine the population of each province, the latest census information of Iran as well as satellite images related to the fourth version of Gridded Population of World (GPW) product were used. Finally, The Moran index was used to determine the pattern of pollutants distribution and the spatial autocorrelation.
 
3- Results
 Spatial output from the processing of Sentinel-5 satellite images during the study period for identifying air pollution centers in Iran showed that the highest levels of nitrogen dioxide were recorded in the majority of cities in Tehran and Alborz provinces and then in the centers of other provinces. In the case of carbon monoxide, the highest rate is in Tehran and the coasts of the Caspian Sea and Khuzestan, and coastal areas of Bushehr and Hormozgan provinces. The highest amount of ozone is in the northern parts of the provinces of West and East Azerbaijan, Ardabil, Gilan, Mazandaran, Golestan and Northern Khorasan. Most of the dust was in the southern, eastern, southeastern and central provinces of Iran. The highest amount of sulfur dioxide pollutants is recorded in Tehran and then in the provinces of Khuzestan, Kerman, Hormozgan, Bushehr, Markazi, Qom, Isfahan and Khorasan Razavi. Provincially, the highest share of nitrogen dioxide is in the provinces of Tehran, Alborz, Qazvin and Qom. The highest provincial share of carbon monoxide is in Khuzestan, Gilan and Mazandaran provinces. The highest share of dust is in the southeastern provinces, including Sistan and Baluchestan, the highest share of sulfur dioxide is in Khuzestan province, and the highest share of ozone pollution is in the coastal provinces of Caspian Sea. Compliance of the average 5 pollutants with Google Earth images showed that the contaminated areas are located in the cities of Abadan, Imam Khomeini Port, Mahshahr Port and Ahvaz (Khuzestan Province), Tehran, Pakdasht (Tehran Province) and Assaluyeh Port (Bushehr Province). The results of comparing the average concentrations of pollutants in different seasons showed that there was no significant difference between CO, NO2 and O3 pollutants in different seasons, but suspended particles and aerosols in winter and autumn seasons have a significant difference with the amount of this pollutant in spring and autumn. Also, SO2 pollutant in autumn had lower concentrations than other seasons. The results of clustering analysis to determine the status of significant spatial clusters showed that the data are in the confidence range and have spatial auto-correlation and cluster distribution pattern.
 
4- Discussion & Conclusions
 According to Sentinel-5 satellite images, most of the pollution centers in Iran are related to petrochemical industries and refineries, which are located in the cities of Abadan, Imam Khomeini port, Mahshahr port and Ahvaz (Khuzestan province), Assaluyeh port (Bushehr province) and common pollutants. By these centers are NOX, SO2, CO, suspended particles and aerosols. Also, other centers (Tehran, Pakdasht in Tehran province) are located in the most populous urban areas of, which have been identified as hotspots in high production of NO2 and CO, due to high population and urban traffic.  Due to the higher population density of Tehran and Pakdasht than other cities in Iran, air pollution can be more important in these cities. Therefore, the use of satellite imagery to monitor Iran's air pollutants and the location of hotspots can be very cost-effective and time-consuming.
 
Keywords: Air Pollution Monitoring, Sentinel, Satellite Imagery, Polluted Hotspot, Moran’s Index.