Ahmed Abdelkader

Ahmed Abdelkader


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 December 2022 in Water
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Journal Article
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AAAhmed Abdelaal
Ahmed Abdelaal
AAAhmed Abdelkader
Ahmed Abdelkader
FAFahad Alshehri
Fahad Alshehri
AEAsmaa Elatiar
Asmaa Elatiar
SASattam Almadani
Sattam Almadani
This study assessed the spatiotemporal variability and pollution grades of heavy metals in water and sediments of Bahr El-Baqar drain, Eastern Nile Delta, Egypt, by integration of geochemical analysis, metal pollution indices, correlation, and multivariate statistical analyses. Twenty samples of water and sediments were collected during 2018 and analyzed for heavy metal concentrations using ICP-OES. Heavy metal contents in the water samples followed the order: Fe > Zn > Al > Pb > Mn > Cu > Ni. The drain sediments were highly contaminated with heavy metals that followed the order: Fe > Al > Mn > V > Zn > Cu > Cr > Ba > Ni > Pb > As. Spatiotemporally, most metals in the drain sediments showed a decreasing trend from upstream (south) to downstream sites (north). Results of principal component analysis (PCA) supported those from the Pearson correlation between investigated heavy metals. In water, Mn, Ni, Pb, Zn, Cu, and Fe showed highly significant correlations. In sediments, Ba, Ni, Zn, Fe, Al, Mn, and V showed strong positive correlations indicating that these metals were derived from similar anthropogenic sources. The calculated metal pollution indices: enrichment factor (EF), contamination factor (CF), pollution load index (PLI), degree of contamination (DC), and index of geo-accumulation (Igeo) indicated high loadings of heavy metals in the drain sediments. EFs revealed low, moderate to significant enrichment, whereas CFs showed low, moderate, and considerable contamination. PLI indicated low, baseline, and progressive contamination, while DC indicated low, moderate, and considerable degree of contamination. Igeo of all investigated metals (except for As; class 1) indicated extremely contaminated sediments (class 7).

3 July 2020 in Atmosphere
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Journal Article
Open access
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IEIslam Abou El-Magd
Islam Abou El-Magd
NZNaglaa Zanaty
Naglaa Zanaty
EAElham Ali
Elham Ali
HIHitoshi Irie
Hitoshi Irie
AAAhmed Abdelkader
Ahmed Abdelkader
Egypt experiences high rates of air pollution, which is a major threat to human health and the eco-environment and therefore needs to be tackled by defining major causes to hinder or mitigate their impacts. The major driving forces of air pollution are either of local and/or regional origin. In addition, seasonal aerosols may be natural, such as dust particles transported from the western desert, or anthropogenic aerosols which are transported from industrial areas and smoke particles from seasonal biomass burning. Monitoring the optical properties of aerosols and their pattern in the atmosphere on a daily basis requires a robust source of information and professional analytical tools. This research explored the potential of using time series of Moderate Resolution Imaging Spectroradiometer (MODIS) and Aerosol Robotic Network (AERONET) data to comprehensively investigate the aerosol optical depth (AOD) and variability for the period 2012–2018 on a daily basis. The data show that spring, summer and autumn seasons experienced the highest anomaly originating from regional and national sources. The high AOD in spring associated with a low Ångström exponent (AE) indicates the presence of coarse particles which naturally originate from desert dust or sea spray. In contrast, the high AE in summer and autumn demonstrated the dominance of fine anthropogenic aerosols such as smoke particles from local biomass burning. The observation of a high number of fire incidents over Egypt in October and November 2018, during the months of rice crop harvesting, showed that these incidents contribute to the presence of autumn aerosols across the country. In-situ measurements of Particulate Matter (PM10) from local stations from an environmental based network as well as the AERONET AOD were used to validate the MODIS AOD, providing a high correlation coefficient of r = 0.73.