The activity concentration of gross alpha and gross beta particles in four samples of borehole drinking water consumed in Ibrahim Badamasi Babangida University (IBBU), Lapai, Niger State-Nigeria was measured, using a portable single channel gas free proportional counter (MPC2000B-DP) detector. This study focused on cancer related problems and the bio-data of the environment was discussed as well as the radiological effect of the water on consumers. Higher concentration of alpha and beta were observed in Hostel block A (DD) with values of 0.085 0.024 and 11.229 0.901 BqL-1, respectively. However, lower concentration of alpha and beta particles were observed in the Faculty of Management Science (AA) with values of 0.006 0.005 and 0.001 0.276 BqL-1, respectively. Out of the four sampling sites studied, only the Faculty of Management Science fall below the guideline levels of gross alpha (0.5 BqL-1) and gross beta (1.0 BqL-1) in drinking water, established by the World Health Organization. These results show that, consumption of groundwater from the other three major borehole sources, may pose significant radiological health hazards to the population.

This study was undertaken to evaluate concentration of Uranium (U) in the drinking water of the Tonk district of Rajasthan (India). The main objective of the study is to determine the distribution of Uranium concentration and the geochemical behavior of Uranium in pre-monsoon (PRM) and post-monsoon (POM) drinking water samples. Uranium was measured by LED fluorimeter. Total 318 drinking water samples were collected for both seasons. It is observed that the water quality of all the samples is within the limits prescribed by WHO (30 µg/L) except a few, and can be used for domestic purposes. The Uranium concentration was found to be in the range 0.21 to 173.72 µg/L with a mean value of 8.58 µg/L in pre-monsoon and 0.21 to 162.34 µg/L with a mean value of 11.22 µg/L in post-monsoon samples. The geochemistry of the study area shows rock-water interaction. The order of average anionic concentration is found to be HCO3 – > Cl – > SO4 2– > NO3 –. Although no definite trend of seasonal variation in the concentration of U was observed, large samples have higher Uranium concentrations in post-monsoon than pre-monsoon.

The high amount of Electrical Conductivity (EC) in the groundwater is one of the major negative Geo-environmental problems which has a considerable effect on the quality of drinking water. To address this challenging problem we proposed an intelligent Machine Learning (ML) based approach to predict EC in urban areas. We applied the deep learning technique as one of the most applicable ML techniques with high capabilities for intelligent predictions. Five different deep neural networks (Net 1 to Net 5) were developed in this study and their reliability to predict EC with an emphasis on different settings of inputs, features, functions, and the number of hidden layers was evaluated. The achieved results showed that deep neural networks can predict EC parameters using minimum and economic input parameters. Results showed parameters Cl and SO4 with a high range of correlation and pH with a low range of Pearson correlation properties are influential parameters to be used as the input of neural networks. Activation function Relu, optimization function Adam with a learning rate of 0.0005 and loss function Mean Squared Error with the minimum of two hidden dense layers from Keras laboratory of Tensor Flow developed an efficient and fast network to predict the EC parameter in urban areas. Maximum epochs for developed networks were defined up to 2000 iterations while epochs are reducible up to 200 to drive minimum loss function outcome. The maximum training and testing R2 for developed networks was 0.99 in both the training and testing parts.

In the eastern region of the Algerian Northern Sahara, the groundwater is the only resource for drinking water supply and irrigation. This study aimed to assess the physical-chemical quality of groundwater with exposition of the fluoride distribution in the eastern region of Algeria taking as case study Ouargla area. The sampling campaign was carried out in such a way to cover the exploited aquifers (Miopliocene and Senonian).  Water temperature, pH, conductivity, hardness, alkalinity, principal ions (Sodium, Potassium Calcium, Magnesium, Bicarbonates, Nitrates, Sulfates, and Chlorides) and the fluoride content in the groundwater were measured and determined. Examination and validation of obtained results were by the use ionic balance method and the hydrochemical analysis by Piper, Stabler and Richards diagrams. The obtained results of our study show that the groundwater of the Ouargla area presents a chlorinated sodium and potassium facies. Moreover, the groundwater quality in the study area is of poor quality; it is hard and characterized by very high mineralization, The Richards' diagram indicates that the groundwater of the study area are unsuitable for irrigation. The spatial distribution of fluoride ions in groundwater of the terminal complex shows that fluoride levels in Ouargla exceed the World Health Organization standard.

The article presents the results of a study of heavy metals in snow and groundwater within the industrially developed Arkhangelsk agglomeration, which is the largest among urban formations in the Arctic zone of Russia. This article describes the results of research on the territories of three suburban community garden plots used by residents of the cities of the Arkhangelsk, Severodvinsk and Novodvinsk agglomeration for recreation, growing fruits and vegetables, picking wild berries and mushrooms, and short-term residence. In groundwater samples taken from wells, the average concentrations of heavy metals decrease in the following order: Fe > Mn > Zn > Cr > Ni > Cu > Ti > V > Pb > U > As > Co > Mo > Sb > Cd. A comparison of metal concentrations in groundwater with WHO and SanPiN standards showed that only Fe and Mn exceeded the permissible limits, for the rest of the studied metals, the concentrations were significantly below the permissible limits. The study of heavy metals in the snow showed a similar order of decrease in concentrations to groundwater and total concentrations of soluble metal fractions. This fact indicates the migration of heavy metals into groundwater after the spring snowmelt and the fact the main source of groundwater pollution is the atmospheric channel. According to the values of the total areal pollution of the snow cover with heavy metals, the most polluted are suburban garden plots in the area of the Arkhangelsk city – 216.91 mg/m2. The results of the principal component analysis showed that the main sources of snow cover pollution with heavy metals in the suburban areas of the Arkhangelsk agglomeration were thermal power plants, machine-building and metallurgical plants, a solid waste landfill, and vehicles. The calculation of the heavy metal pollution index for water did not reveal a significant anthropogenic impact. However, the indices assessing the amount of metals (heavy metal evaluation index), toxicity (heavy metal toxicity load), non-carcinogenic risk (hazard index), and carcinogenic risk indicate a high level of heavy metal pollution of the studied waters, as well as the unsuitability of groundwater and melted snow as drinking water. Metals such as Fe, Mn, Ni, Cu, and Pb make the greatest contribution to the quality indices of the studied waters.

Groundwater makes up an important part of global freshwater resources, though it is often threatened by overuse of natural resources along with abundant production of wastes in modern society. This study aims to investigate the removal of three heavy metals including nickel, cadmium, and lead from groundwater via electrocoagulation, a suitable method for treatment of water-soluble compounds, dealing with the impact of this process on three major groundwater parameters, namely TDS (Total Dissolved Solid), TH, and EC at a laboratory scale. The experiments have been performed using four aluminum electrodes. In this research, the efficiency of contaminants removal and the parameters of interest have been investigated under several conditions such as the distance among the electrodes, potential difference among the electrodes, and different initial concentrations of heavy metals with a detention time of 20 min. Afterwards both results and observations have been analyzed, using diagrams and data tables. Results indicate that this method has had no significant effect on TDS and EC; however, in case of TH, the removal has increased by up to 29.17%. As for the heavy metals, all three contaminants have achieved an increase of the potential difference to 15 V, a decrease in the distance among the electrodes to 2.2 cm, as well as a removal of over 90%. Furthermore, result analysis shows that this process has had a better removal efficiency, concerning lead.

Batiaghata Upazila, Khulna District in south-west coastal region of Bangladesh is the mostly saline affected area, where agriculture activities are mainly dependent on rainfall. 23 water samples from surface water and shallow tube well (STW) were collected in the monsoon season and analyzed for physico-chemical properties to classify them according to salinity hazard. Electrical Conductivity (EC) of both surface and groundwater samples were slightly higher than that of acceptable limit ( Ca2+ > Mg2+ > K+ in both surface and groundwater while the anions trend in both surface and groundwater of the study area were Cl¯ > SO42¯ > PO43¯. EC and TDS showed high positive correlation with Na+, K+ and Ca2+ with Cl¯ as confirmed from Correlation Matrix and Principal Component Analysis (PCA). Most of the STW water samples compared to the surface water had higher Soluble Sodium Percentage (SSP) values while Sodium Adsorption Ratio (SAR) indicated the surface water and ground water with low sodium hazard. The Kelly’s ratio of STW water is more subjected to sodium hazard compared to surface water in the study area.