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doi: 10.18178/ijesd.2024.15.2.1468
Spatiotemporal Air Quality Mapping and PM10 Modelling in Abu Dhabi City, UAE
Email: g00070816@aus.edu (R.E.M.); g00074421@aus.edu (Z.A.-D.); atarig@aus.edu (T.A.)
*Corresponding author
Abstract—Air pollution is a global health concern that should
be monitored to avoid grave consequences on human health. The
rapid developments in the United Arab Emirates, in
combination with its geographic location and arid climate, make
it an area susceptible to unhealthy air quality indices,
particularly due to the high concentrations of particulate matter
in the country. Air quality can be monitored through a
combination of ground data and satellite imagery. In this study,
a numerical model was developed to estimate particulate matter
10 μm in size (PM10) concentrations in Abu Dhabi City through
linear regression analysis using data points from 2016, 2018, and
2020. The model was validated, and the data was processed to
generate PM10 concentration maps for the area of interest. The
maps show similar levels of PM10, with higher unhealthy
concentrations reported in desert and suburban areas. The
model was validated using data from 2021, and the map reveals
unhealthy concentrations across various areas in the area of
interest. This study also examines the concentrations of nitrogen
dioxide, sulfur dioxide, and formaldehyde in 2018 and 2020 for
the same area of interest using Sentinel-5P imagery. The results
show that the concentration of nitrogen dioxide decreased in
2020, likely due to imposed lockdowns and reduced industrial
activities during the COVID-19 pandemic. Overall,
formaldehyde and sulfur dioxide concentrations were relatively
low in both years, indicating that PM10 pollution is of higher
concern than other contaminants in the United Arab Emirates.
Keywords—air quality mapping, particulate matter, air
pollution
Cite: Ruba El Mootassem, Zahraa Al-Dawood, and Tarig Ali, "Spatiotemporal Air Quality Mapping and PM10 Modelling in Abu Dhabi City, UAE," International Journal of Environmental Science and Development vol. 15, no. 2, pp. 57-62, 2024.
Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).