Safeguarding drinking water is a major public health and environmental concern because it is essential to human life but may contain pollutants that can cause illness or harm the environment. Therefore, continuous research is necessary to improve water treatment methods and guarantee its quality. As part of this study, the effectiveness of coagulation–flocculation treatment using aluminum sulfate (Al₂(SO₄)₃) was evaluated on a very polluted site. Samplings were taken almost every day for a month from the polluted site, and the samples were characterized by several physicochemical properties, such as hydrogen potential (pH), electrical conductivity, turbidity, organic matter, ammonium (NH⁺₄), phosphate (PO₄³⁻), nitrate (NO₃⁻), nitrite (NO₂⁻), calcium (Ca²⁺), magnesium (Mg²⁺⁾, total hardness (TH), chloride (Cl⁻⁾, bicarbonate (HCO₃⁻), sulfate (SO₄²⁻), iron (Fe³⁺), manganese (Mn²⁺), aluminum (Al³⁺), potassium (K⁺), sodium (Na⁺), complete alkalimetric titration (TAC), and dry residue (DR). Then, these samples were treated with Al₂(SO₄)₃ using the jar test method, which is a common method to determine the optimal amount of coagulant to add to the water based on its physicochemical characteristics. A mathematical model had been previously created using the support vector machine method to predict the dose of coagulant according to the parameters of temperature, pH, TAC, conductivity, and turbidity. This Al₂(SO₄)₃ treatment step was repeated at the end of each month for a year, and a second characterization of the physicochemical parameters was carried out in order to compare them with those of the raw water. The results showed a very effective elimination of the various pollutions, with a very high rate, thus demonstrating the effectiveness of the Al₂(SO₄)₃. The physicochemical parameters measured after the treatment showed a significant reduction in the majority of the physicochemical parameters. These results demonstrated that the coagulation–flocculation treatment with Al₂(SO₄)₃ was very effective in eliminating the various pollutions present in the raw water. They also stress the importance of continued research in the field of water treatment to improve the quality of drinking water and protect public health and the environment.

Monitoring stations have been established to combat water pollution, improve the ecosystem, promote human health, and facilitate drinking water production. However, continuous and extensive monitoring of water is costly and time-consuming, resulting in limited datasets and hindering water management research. This study focuses on developing an optimized K-nearest neighbor (KNN) model using the improved grey wolf optimization (I-GWO) algorithm to predict dry residue quantities. The model incorporates 20 physical and chemical parameters derived from a dataset of 400 samples. Cross-validation is employed to assess model performance, optimize parameters, and mitigate the risk of overfitting. Four folds are created, and each fold is optimized using 11 distance metrics and their corresponding weighting functions to determine the best model configuration. Among the evaluated models, the Jaccard distance metric with inverse squared weighting function consistently demonstrates the best performance in terms of statistical errors and coefficients for each fold. By averaging predictions from the models in the four folds, an estimation of the overall model performance is obtained. The resulting model exhibits high efficiency, with remarkably low errors reflected in the values of R, R², R²_ADJ, RMSE, and EPM, which are reported as 0.9979, 0.9958, 0.9956, 41.2639, and 3.1061, respectively. This study reveals a compelling non-linear correlation between physico-chemical water attributes and the content of dry tailings, indicating the ability to accurately predict dry tailing quantities. By employing the proposed methodology to enhance water quality models, it becomes possible to overcome limitations in water quality management and significantly improve the precision of predictions regarding critical water parameters.

Air gap membrane distillation (AGMD) is a widely utilized technology for producing drinking water due to its low heat loss, high thermal efficiency, and compatibility with solar energy. The application of the first and second laws of thermodynamics in energy and exergy analyses provides a comprehensive evaluation of the efficiency of thermal processes. This study aims to examine numerically the energy and exergy performance indicators of a solar AGMD system used for seawater desalination. The simulation was carried out using MATLAB 9.7 software. The total thermal efficiency and overall efficiency of each element in the AGMD system were calculated for various solar field energy outputs, and moreover, a parametric study was conducted. The results indicate that the exergetic efficiency of the AGMD system components was the lowest in the solar field, with the concentrator having the lowest energy efficiency. Additionally, the thermal and exergetic efficiency of the entire solar AGMD system decreases along with the raise of ambient temperature. An additional investigation was conducted to better apprehend the sources of exergy destruction in the solar field. The obtained results from this study can be employed as a guide to reduce exergy destruction in the whole solar AGMD desalination system with recognition of the main sources of irreversibility.

Several drinking water production techniques are being established to respond immediately to the growing needs of the population. The system of air gap membrane distillation (AGMD) is the best attractive option for the process of water desalination. This thermal process is characterized by its potential to provide drinking water at low energy costs when combined with solar energy. In this paper, the AGMD brackish water desalination unit potentialities coupled with solar energy were investigated. Ghardaïa of the south region has been considered as the field of our study. Mathematical modeling is investigated by employing MATLAB software to develop the prediction of the permeate flux related to the phenomena of heat and mass transfer. Herein, flat plate solar collectors (SFPC) were exploited as a source for heating saline water through free solar energy conversion. The further model validation of a flat solar collector made it possible for following the instantaneous evolution of the collector outlet temperature depending on the feed water temperature and the flow rate. Furthermore, it is interesting to note that the results prove the possibility to produce water by the solar AGMD process with a maximum permeate flux of 8 kg·m⁻²·h⁻¹ achieved at 68 °C, a feed temperature. Moreover, gained output ratio (GOR) of the unit of thermal solar desalination was estimated to be about 4.6, which decreases with increasing hot water flow and temperature.