tracking air pollution changes using sentinel-5p data in khuzestan

Air pollution represents a significant challenge in middle eastern countries and has notably impacted the western regions of iran, specifically the province of khuzestan. the identification of pollution production centers and the spatial distribution and patterns of pollution are crucial for effective management. limited synoptic ground stations and challenging data accessibility make it difficult to precisely monitor air pollution across various regions. remote sensing, however, offers a viable solution for obtaining reliable air pollution information through time series analysis. this study utilized sentinel-5p satellite image products and data from synoptic stations in khuzestan province. leveraging the google earth engine system, the research identified atmospheric pollutants including no2, co, uv-aerosol, and so2 over a period of one year from january 2022 to january 2023. subsequently, maps displaying the concentration of atmospheric pollutants were generated, visually representing pollutant concentrations through color-coded layers. monthly fluctuations in no2, co, uv-aerosol, and so2 levels were graphed, revealing seasonal variations in pollutant concentration. the results indicated that no and co showed higher concentrations during spring and summer, while uv-aerosol exhibited peak concentrations in spring. additionally, the months of september and october highlighted the highest concentration of so2 in the central and southwest regions of khuzestan province. the research findings further illustrated an increase in pollutant levels from central areas to the south and southwest regions of the province. finally, ground data from synoptic stations were utilized to validate the results.