Spatial distribution, source apportionment and health risk assessment of inorganic pollutants of surface water and groundwater in the southern margin of Junggar Basin, Xinjiang, China

Surface water (SW) and groundwater (GW) are crucial water supply sources in the southern margin of Junggar Basin in Xinjiang. The sources of toxic components in SW and GW and their negative effects on human health are of great concern. A total of 40 SW and 596 GW samples were collected at the oasis belt to analyze distribution, sources and potential health risks of inorganic pollutants in SW and GW. Results revealed that SW quality was severely affected by Hg, 30.0% of which had Hg concentration greater than the national drinking water standard. High Hg SW was mainly distributed near Manas County and Urumqi City. GW quality was mostly affected by SO42-, 24.7% of which had SO42- concentration greater than the national drinking water standard. High SO42- GW primarily occurred in the northwest and middle of the study area. Source apportionment of inorganic pollutants identified geological background, municipal wastewater disposal, water-rock interaction, geological environment, geological structure and industrial emission were the prominent potential sources of inorganic pollution in SW, with contribution rates of 1.2%, 10.0%, 43.6%, 35.1%, 6.3% and 3.8%, respectively. Five potential pollution sources in GW (including geological background, municipal wastewater disposal, water-rock interaction, geological environment and aquifer burial depth) were identified, with contribution rates of 0.7%, 9.6%, 77.6%, 11.1% and 1.0%, respectively. Probabilistic health risk assessment showed that Cl- and As in SW and GW were the main inorganic pollutants threatening human health. Non-carcinogenic risks for adults and children were negligible, while carcinogenic risks cannot be negligible. Furthermore, the contribution of potential pollution sources to health risks was quantified using positive matrix factorization coupling with health risk assessment model. Based on which, we offered the suggestion that water quality improvement in contaminated areas should be implemented in combination with pollution monitoring systems.