Abstract
The main objectives of this study are to model, monitor and observe air quality in Greater Cairo Region (GCR) based on Landsat-8 OLI and TIRS images, HYSPLIT dispersion model, and GIS techniques to overcome the great lack of data observation and to improve data coverage and comparability. Major land covers were mapped from Landsat-8 images. Air quality map and AOT (Aerosol Optical Thickness) were derived by calculating aerosol path radiance based on exoatmospheric solar constant and atmospheric transmittance. HYSPLIT dispersion model was run to simulate the extraordinary pollution episodes (black cloud) and to determine air mass trajectories. Eventually, GIS spatial analysis was carried out based on in situ data to adjust satellite derived PM10_sat. The study deduced that concentrations of PM10 are high in GCR and exceed six times of the WHO air quality standards. It is extremely intensive in spring due to the local dusty wind “called Khamasin” and in autumn due to burning of agriculture residues. Mean annual concentrations of PM10 in GCR from 16 April 2014 to 29 January 2015 reveals that ~70% of the region is considered as unhealthy for sensitive groups (200–250 µg/m3 year).
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Moawad, M.B., Youssief, A.A., Madkour, K. (2017). Modeling and Monitoring of Air Quality in Greater Cairo Region, Egypt Using Landsat-8 Images, HYSPLIT and GIS Based Analysis. In: Leal Filho, W. (eds) Climate Change Research at Universities. Springer, Cham. https://doi.org/10.1007/978-3-319-58214-6_3
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