Springer Science and Business Media LLC

High arsenic (As) groundwater is a serious environmental problem in Yinchuan Plain, northwest China. Though some measures have been taken to alleviate it, the detection rate of high As in groundwater is still high. In order to understand the occurrence and enrichment of As in groundwater and the hydrochemical evolution, correlation analysis and interpolation approach were used to interpret the spatiotemporal variation of major ions and contaminants in phreatic groundwater at 30 sampling sites during the dry season (March) and wet season (July). Some suggestions on the treatment of groundwater As pollution in the study area were put forward. The results reveal that the predominant hydrochemical type of groundwater in the study area is SO4·Cl-Ca·Mg, followed by HCO3-Ca·Mg type, and rock weathering is the main process regulating the hydrochemical characteristics. The content of groundwater As is low in the dry season but high in the wet season. However, the difference of As concentration between the dry and wet seasons is relatively small in the areas where surface water percolation is intense. The concentrations of HCO3−, NH4+, PO43−, and Mn have a significantly positive correlation with the As enrichment in the dry season, while HCO3−, Fe, and Mn have a strongly negative correlation with As in the wet season. The content of As in surface water influences greatly to the As enrichment in groundwater. In the dry season, high arsenic is enriched in areas close to surface water, while in the wet season, the infiltration of irrigation water makes arsenic expand to the western agricultural irrigation area. The mean lung cancer risk caused by As is higher than the maximum acceptable level in the study area. As such, necessary actions such as adopting nanocomposites as As removal material are to be carried out.

In this paper, the spatial distribution of fluoride (F‒) and manganese (Mn) in groundwater was described and the overall groundwater quality was assessed with the entropy weight water quality index (EWQI) in Weining Plain, northwest China. The probabilistic health risk of F‒ and Mn in groundwater was assessed by the Monte Carlo stochastic simulation method. The results show that 50 groundwater samples (a total of 144) belong to poor and very poor quality because of agricultural activities, industrial development, and the local hydrogeological conditions. Groundwater quality in the upper reaches of the Yellow River is better than that in the lower reaches. The average health risks faced by children and adults are 4.59 and 0.62, respectively. If the uncertainty of the model parameters are considered, the mean risks faced by children and adults are 6.84 and 0.92, respectively, indicating that the health risk to residents, especially children, cannot be ignored. Compared with dermal contact, drinking water intake is the main exposure way to harm residents’ health. F‒ contributed higher to the health risk than Mn, and children face greater risk than adults. Stochastic simulation can reflect health risks more comprehensively than the deterministic methods. The study results are helpful for decision makers to take measures for the safe supply of drinking water in the study area.