Air pollution is reported as one of the most severe environmental problems in the Middle East and North Africa (MENA) region. Remotely sensed data from newly available TROPOMI - TROPOspheric Monitoring Instrument on board Sentinel-5 Precursor, shows an annual mean of high-resolution maps of selected air quality indicators (NO2, CO, O3, and UVAI) of the MENA countries for the first time. The correlation analysis among the aforementioned indicators show the coherency of the air pollutants in urban areas. Multi-year data from the Aerosol Robotic Network (AERONET) stations from nine MENA countries are utilized here to study the aerosol optical depth (AOD) and Ångström exponent (AE) with other available observations. Additionally, a total of 65 different machine learning models of four categories, namely: linear regression, ensemble, decision tree, and deep neural network (DNN), were built from multiple data sources (MODIS, MISR, OMI, and MERRA-2) to predict the best usable AOD product as compared to AERONET data. DNN validates well against AERONET data and proves to be the best model to generate optimized aerosol products when the ground observations are insufficient. This approach can improve the knowledge of air pollutant variability and intensity in the MENA region for decision makers to operate proper mitigation strategies.

The present study aims at describing and analysing the floristic composition and vegetation types, as well as determining the effect of recent land uses on the vegetation structure. It aims also at identifying the alien plants species and elucidating the impact of these species on the plant diversity and community structure of the study area. One hundred and ninety stands were selected monthly for this study, 145 species were recorded (69 perennials and 76 annuals) related to 83 genera, 40 families in 9 identified habitats in El-Omayed Biosphere Reserve (coastal sand dunes, salt marshes, saline depression, non-saline depression, inland ridges, inland plateau, irrigation canals, road sides and cultivated lands). Therophytes were the most represented life form. Three habitat groups resulted after the application of TWINSPAN and DCA as classification and ordination techniques: 2 represented the natural habitats and one represented the urban and cultivated habitats. Group I represented coastal dunes and salt marshes GII: saline depressions, non-saline depressions, inland plateau and inland ridges and GIII: irrigation canals, road sides and cultivated lands. Coastal dunes had the highest species richness (α-diversity), followed by cultivated lands, while inland plateau had the lowest; but saline depressions had the highest species turnover (β-diversity). Non-saline depressions had the highest relative evenness, while saline depressions had the highest relative concentration of dominance. Coastal dunes had highest values of calcium carbonates and calcium ions, and salt marshes had the highest salinity, pH, potassium and sodium contents, but cultivated lands had the highest values of silt, clay and organic matter. The diagram resulting from CCA showed an influence of most soil variables, except nitrogen, calcium and potassium. Twenty two species were recorded for the first time in the study area. The recent land use (overgrazing, wood cutting and collecting, construction of summer resorts and irrigation canals and agricultures) led to the emergence of new invasive species, which may severely affect the plant diversity and community structure of this hot spot of biodiversity in Egypt