In order to evaluate the impact on water quality of the abandoned Sidi Kamber mine in Skikda, NE Algeria, Pb, Zn, Cd, Fe, Cu, Mn and Ni metals were collected at surface water and groundwater, from twenty eight sites located near the mine. Conventional hydrochemical methods, heavy metal pollution index (HPI) and multivariate statistical analysis techniques: correlation matrix (CM), principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used. Surface water results show that El-Souk River has a high level of pollution, but Guenitra dam water is less contaminated. Regarding the groundwater results, the wells and springs are not suitable for drinking. The overall quality estimated by HPI values of surface and groundwater are poor; they may pose a potential health risk to the local population. The PCA and HCA suggest that surface water and groundwater are contaminated by two sources: anthropogenic and natural. According to the obtained results, surface water and groundwater pollution state of this area raises serious concerns about health and environment.

This study derives an analytical solution of a one-dimensional (1-D) Advection-Dispersion Equation (ADE) for solute transport with two contaminant sources incorporating the source term. Groundwater velocity is considered as a linear function of space while the dispersion as a nth power of velocity and analytical solutions are obtained for , and . The solution is derived using the Generalized Integral Transform Technique (GITT) with a new regular Sturm-Liouville Problem (SLP). Analytical solutions are compared with numerical solutions obtained in MATLAB pedpe solver and are found to be in good agreement. The obtained solutions are illustrated for linear combination of exponential input distribution and its particular cases. The dispersion coefficient and temporal variation of the source term on the solute distribution are demonstrated graphically for the set of input data based on similar data available in the literature. As an illustration, model predictions are used to estimate the time histories of the radiological doses of uranium at different distances from the sources boundary in order to understand the potential radiological impact on the general public for such problem.

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.