Air Quality Assessment Before and During COVID-19 Using Sentinel-5P Satellite and Ground Station Data in Ahvaz, Bushehr, and Bandar Abbas

Introduction: The current study investigated temporal variations in six air pollutants: PM2.5 , PM10 , SO2 , NO3 , O3 , CO in the cities of Ahvaz, Bandar Abbas, and Bushehr during 2018–2022, with a focus on the pre- and during-COVID-19 periods. Methods: SO2 , NO2 , CO, and O3 data were obtained from the TROPOMI sensor onboard Sentinel-5P (7 × 7 km resolution) using Google Earth Engine (GEE). PM2.5 and PM10 concentrations were estimated from Aerosol Optical Depth (AOD) data derived from MODIS MCD19A2 (1 km resolution) using a regression model calibrated with ground-based monitoring data. Records with > 30% cloud cover or missing values were excluded, and monthly and annual means were calculated. Satellite observations were bias-corrected via linear regression against ground-based data and downscaled using bilinear interpolation. Inter-city comparisons were conducted using independent t-tests, while pre- vs. during-pandemic differences were assessed using paired t-tests. Results: Ahvaz recorded the highest mean concentrations of PM2.5 , PM10 , SO2 , and CO. In most cases, pollutant concentrations were higher before the COVID-19 pandemic, particularly for PM2.5 and PM10 in Ahvaz and Bushehr (P < 0.05). Correlations between satellite-derived and ground-based measurements of PM2.5 and PM10 were strong and statistically significant in Ahvaz and Bushehr, but weak or non-significant for SO2 , NO2 , and O3 . Conclusion: The integration of satellite observations with ground-based monitoring systems provides a reliable and cost-efficient approach to air quality assessment. Reductions in certain pollutants, especially particulate matter, were associated with decreased industrial activity and transportation during the pandemic.