Monitoring Air Pollution Using Sentinel-5 Satellite Imagery: A Case Study of Razavi and South Khorasan Provinces

Document Type : Original Research Article

Authors

1 Department of Environmental Engineering, Faculty of Natural Resources and Environment, University of Birjand, Birjand, Iran

2 Department of Environmental Engineering, Faculty of Natural Resources and Environment, University of Birjand, Birjand, Iran. Research Group of Drought and Climate Change, University of Birjand, Birjand, Iran

3 Department of Water Engineering, Faculty of Civil Engineering, Semnan University, Semnan, Iran

4 Department of Environmental Engineering, Faculty of Environment, University of Tehran, Tehran, Iran

Abstract

One of the significant challenges facing developing countries is combating air pollution and improving air quality. Therefore, analyzing changes in air pollutants can provide valuable information for experts to analyze air quality. The TROPOMI sensor on the Sentinel-5 satellite enables the tracking of gaseous pollutants. In this study, using GEE (Google Earth Engine), the products of CO, O3, NO2, and SO2 pollutants were retrieved, and their average concentrations were mapped at the spatial scale of Razavi and South Khorasan Provinces in the period 2018-2023. Additionally, the inverse distance weighting (IDW) method was used for annual data from five air quality monitoring stations. The results of this research showed that the spatial distribution of the concentration of these pollutants increased from Razavi and South Khorasan Provinces, with the highest values recorded in the north, northeast, and center of Khorasan Razavi province. Also, the spatial distribution of the concentration of measured pollutants using the IDW model showed that the highest concentration dispersion of pollutants was recorded at the Mashin Abzar, Khiam, Sajad, and Tarog stations. To investigate the overall ability of the TRPOPMI sensor to estimate atmospheric pollutants, the coefficient of determination (R²) was used. The results showed that the monitoring values using Sentinel-5 satellite images correlate at least 0.76% for CO, 0.85% for O3, 0.79% for NO2, and 0.78% for SO2 with the values monitored by air quality monitoring stations.

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References

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