Abstract

Air pollution is a global health concern that shouldbe monitored to avoid grave consequences on human health. Therapid developments in the United Arab Emirates, incombination with its geographic location and arid climate, makeit an area susceptible to unhealthy air quality indices,particularly due to the high concentrations of particulate matterin the country. Air quality can be monitored through acombination of ground data and satellite imagery. In this study,a numerical model was developed to estimate particulate matter10 μm in size (PM10) concentrations in Abu Dhabi City throughlinear regression analysis using data points from 2016, 2018, and2020. The model was validated, and the data was processed togenerate PM10 concentration maps for the area of interest. Themaps show similar levels of PM10, with higher unhealthyconcentrations reported in desert and suburban areas. Themodel was validated using data from 2021, and the map revealsunhealthy concentrations across various areas in the area ofinterest. This study also examines the concentrations of nitrogendioxide, sulfur dioxide, and formaldehyde in 2018 and 2020 forthe same area of interest using Sentinel-5P imagery. The resultsshow that the concentration of nitrogen dioxide decreased in2020, likely due to imposed lockdowns and reduced industrialactivities during the COVID-19 pandemic. Overall,formaldehyde and sulfur dioxide concentrations were relativelylow in both years, indicating that PM10 pollution is of higherconcern than other contaminants in the United Arab Emirates.