Integrated geochemical and magnetic potentially toxic elements assessment: a statistical solution discriminating anthropogenic and lithogenic magnetic signals in a complex area of the southeast Nile Delta.

Magnetic proxy approaches proved to be efficient for potentially toxic elements (PTEs) pollution assessment when targeting forests or areas with a homogenous background where anthropogenic magnetic signals could be easily distinguished. Here, we present a multidisciplinary approach for magnetic susceptibility ([Formula: see text]) and HM assessment in a complex area in the Nile Delta, where geogenic input, land use, and various industries with different fly ash and surface water emissions interfere. Statistical analysis discriminates between the effects of lithologic elements and the concentrations of toxic anthropogenic elements.

Unraveling the hydrogeochemical evolution and pollution sources of shallow aquifer using multivariate statistical analysis and hydrogeochemical techniques: a case study of the Quaternary aquifer in Beni Suef area, Egypt.

This study integrates multivariate statistical analysis and hydrogeochemical modeling to investigate the processes controlling the groundwater composition of a shallow aquifer where increased pumping rates and anthropogenic impacts were prevalent. Eighteen groundwater samples were collected and analyzed for major elements and selected heavy metals. The data were classified on the basis of multivariate statistical analysis into three clusters: C1 (Na-Cl facies), C2 (Ca-SO facies), and C3 (Ca-HCO facies).

Fabrication of Novel Bentonite-Anthracite@Zetag (BT-An@Zetag) Composite for the Removal of Arsenic (V) from an Aqueous Solution.

The arsenic (As) pollution of water has been eliminated via intensive scientific efforts, with the purpose of giving safe drinking water to millions of people across the world. In this study, the adsorption of As(V) from a synthetic aqueous solution was verified using a Bentonite-Anthracite@Zetag (BT-An@Zetag) composite. The SEM, FT-IR, XRD, DSC, TGA, and SBET techniques were used to characterize the (BT-An@Zetag) composite.

Predictive model for progressive salinization in a coastal aquifer using artificial intelligence and hydrogeochemical techniques: a case study of the Nile Delta aquifer, Egypt.

To monitor groundwater salinization due to seawater intrusion (SWI) in the aquifer of the eastern Nile Delta, Egypt, we developed a predictive regression model based on an innovative approach using SWI indicators and artificial intelligence (AI) methodologies. Hydrogeological and hydrogeochemical data of the groundwater wells in three periods (1996, 2007, and 2018) were used as input data for the AI methods. All the studied indicators were enrolled in feature extraction process where the most significant inputs were determined, including the studied year, the distance from the shoreline, the aquifer type, and the hydraulic head.

Hydrogeochemical evolution of inland lakes' water: A study of major element geochemistry in the Wadi El Raiyan depression, Egypt.

Wadi El Raiyan is a great depression located southwest of Cairo in the Western Desert of Egypt. Lake Qarun, located north of the study area, is a closed basin with a high evaporation rate. The source of water in the lake is agricultural and municipal drainage from the El Faiyum province.