Perfluorinated chemicals (PFCs) are widely used in industrial and commercial applications, leading to their release into the environment. The rapid industrialization and growing population in India make it a suitable case study to investigate PFOS contamination in environmental matrices. The purpose of this study is to investigate PFOS concentrations in river water and groundwater from several locations along the Bharathapuzha river basin and estimate PFOS intakes through drinking water. The highest PFOS level detected in the surface water is 1.3 ng/L and groundwater is 1.0 ng/L, which is significantly lower than the level of PFOS detected in major rivers of many developed countries. It is possible to attribute the low PFOS concentration to factors such as high annual precipitation, reduced industrial and municipal wastewater discharge, and relatively low emissions per capita in a region where agriculture is a major part of the economy. In addition, the daily intake of PFOS through drinking water in all age groups was below the safety threshold for cancer risk.

A comprehensive investigation was engaged to determine the spatial distribution of Uranium (U) and the consequential chemical and radiological health risk associated due to the consumption of groundwater containing U, in Panchkula district. A well-accepted technique of fluorescence of U estimation in an aqueous medium was employed having a detection limit of 0.50 µgL-1. The chemo-radiological health risk and water quality index was computed using a standard equation of concerned agencies to determine the suitability for human health. The concentration of U was observed to vary from 1.70 – 12.28 µgL-1 with the mean value of 5.89 µgL-1 The concentration of U was far below the standard prescribed limits as per World Health Organisation, Atomic Energy Regulatory Board, and United Nation Environmental Protection Agency. Except  nitrate and total alkalinity in few samples, all water quality paramters were within the recommended limit of BIS. The annual effective dose (AED), excess cancer risk (ECR), and lifetime average daily dose (LADD) indicated no potential health issue due to the consumption of groundwater of studied locations. The correlation was computed between U and various macro-anions and cations present in water samples. U was observed to have a significant weak positive correlation with total dissolved solids (TDS), electrical conductivity (EC), and salinity.

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.