Spatial prediction of armed conflicts from the perspective of political geography using bivariate frequency ratio method (FR) in East African States.

Armed conflicts, as significant human phenomena, profoundly impact populations and reflect a state's capacity to fulfill its responsibilities. These conflicts arise from various causes, necessitating robust predictive models to understand their spatial distribution. This study employs the Bivariate Frequency Ratio (FR) method to spatially predict the occurrence of armed conflicts across the East African States, drawing on 42 political geography-related criteria.

Comprehensive evaluation and prediction of groundwater quality and risk indices using quantitative approaches, multivariate analysis, and machine learning models: An exploratory study.

Assessing and predicting quality of groundwater is crucial in managing groundwater availability effectively. In the current study, groundwater quality was thoroughly appraised using various indexing methods, including the drinking water quality index (DWQI), pollution index of heavy metals (HPI), pollution index (PI), metal index (MI), degree of contamination (C), and risk indicators, like hazard quotient (HQ) and total hazard indicator (HI). The assessments were augmented through multivariate analytical techniques, models based on recurrent neural networks (RNNs), and integration of geographic information system (GIS) technology.

Comprehensive approach integrating water quality index and toxic element analysis for environmental and health risk assessment enhanced by simulation techniques.

Due to water shortages and the potential impact of Ethiopia's new dam on the Nile River, Egypt is seeking new water resources. This study assesses the drinking water quality and associated risks from potentially toxic elements (PTEs) in the Quaternary aquifer (QA) in Beni-Suef, Egypt. Using a comprehensive approach, including PHREEQC geochemical modeling, ionic ratios, multivariate statistical analyses, and the integrated weight water quality index (WQI), the study evaluated the sources of ion contamination and the mixing of Nile water with QA.

Assessing surface water quality in Hungary's Danube basin using geochemical modeling, multivariate analysis, irrigation indices, and Monte Carlo simulation.

Evaluation of water quality is crucial for managing surface water effectively, ensuring its suitability for human use, and sustaining the environment. In the lower Danube River basin, various methods were employed to assess surface water quality for irrigation, drinking, human health risk purposes and the main mechanism control the surface water chemistry. These methods included water quality indicators (WQIs), complex statistical analyses, geographic information systems (GIS), Monte Carlo simulation, and geochemical modeling.

Advanced approach combines integrated weight water quality index and potential toxic elements for environmental and health risk assessment supported by simulation technique in Oued Souf, Algeria.

The current research study evaluated the health and environmental risks issues associated with potentially toxic elements (PTEs) in the complex terminal aquifer located in the Algerian desert. The methods used included principal component and cluster (dendrogram) analysis to estimate source of ions and contamination. Various indices such as the Heavy Metal Pollution Index (HPI), Metal Index, hazard quotient, hazard index (HI), and cancer risk (CR) were applied to assess both environmental and human health risks.

Comprehensive approach integrating remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems.

The current study integrates remote sensing, machine learning, and physicochemical parameters to detect hydrodynamic conditions and groundwater quality deterioration in non-rechargeable aquifer systems. Fifty-two water samples were collected from all water resources in Siwa Oasis and analyzed for physical (pH, T°C, EC, and TDS) chemical (SO , HCO , NO , Cl, CO , SiO, Mg, Na, Ca, and K), and trace metals (AL, Fe, Sr, Ba, B, and Mn). A digital elevation model supported by machine learning was used to predict the change in the land cover (surface lake area, soil salinity, and water logging) and its effect on water quality deterioration.

Hydrogeochemical characteristics and air quality risks associated with gold mining operations in Egypt using geochemical modeling and risk indices.

The success of industrial operations depends on the effective identification, appraisal, and mitigation of possible hazards and associated environmental concerns. This report provides a complete review of environmental management techniques at the Sukari Gold Mine (SGM), located in the southeastern desert of Egypt. Extensive environmental measurements were taken to assess air and water quality, identify hazards, and analyze risks on the SGM premises.

New approach into human health risk assessment associated with heavy metals in surface water and groundwater using Monte Carlo Method.

This study assessed the environmental and health risks associated with heavy metals in the water resources of Egypt's northwestern desert. The current approaches included the Spearman correlation matrix, principal component analysis, and cluster analysis to identify pollution sources and quality-controlling factors. Various indices (HPI, MI, HQ, HI, and CR) were applied to evaluate environmental and human health risks.

Investigating the impacts of heavy metal(loid)s on ecology and human health in the lower basin of Hungary's Danube River: A Python and Monte Carlo simulation-based study.

This study aimed to determine the environmental and health risks of the heavy metal levels in the Danube River in Hungary. The metals, including Fe, Mn, Zn, Cu, Ni, Cr, Pb, and As, were measured in the period from 2013 to 2019. The Spearman correlation and heatmap cluster analysis were utilized to determine the origin of pollution and the factors that control surface water quality.

Effective desalination of brackish groundwater using zeolitized diatomite/kaolinite geopolymer as low-cost inorganic membrane; Siwa Oasis in Egypt as a realistic case study.

The salinization of the groundwater wells in Siwa oasis, Egypt represents a critical environmental and economic issue. Developing low-cost, effective, and self-supported inorganic membranes were suggested as suitable desalination techniques. Zeolite/geopolymer (Z/GP) membrane was synthesized as a potential low-cost membrane for effective desalination of brackish groundwater in Siwa Oasis, Egypt.

Effective decontamination of Ca and Mg hardness from groundwater using innovative muscovite based sodalite in batch and fixed-bed column studies; dynamic and equilibrium studies.

A novel form of sodalite was synthesized from muscovite (M.SD) as low-cost softening material for both Ca and Mg ions from real groundwater in batch and column studies. The sodalite sample showed significant surface area (105 m/g) and ion exchange capacity (87.