Natural background levels, source apportionment and health risks of potentially toxic elements in groundwater of highly urbanized area.

Identifying the natural background levels (NBLs), threshold values (TVs), sources and health risks of potentially toxic elements in groundwater is crucial for ensuring the water security of residents in highly urbanized areas. In this study, 96 groundwater samples were collected in urban area of Sichuan Basin, SW China. The concentrations of potentially toxic elements (Li, Fe, Cu, Zn, Al, Pb, B, Ba and Ni) were analyzed for investigating the NBLs, TVs, sources and health risks. The potentially toxic elements followed the concentration order of Fe > Ba > B > Al > Zn > Li > Cu > Ni > Pb. The NBLs and TVs indicated the contamination of potentially toxic elements mainly occurred in the northern and central parts of the study area. The Positive Matrix Factorization (PMF) model identified elevated concentrations of Fe, Al, Li, and B were found to determine groundwater quality. The primary sources of Fe, Al, Pb, and Ni were attributed to the dissolution of oxidation products, with Fe additionally affected by anthropogenic reduction environments. Li and B were determined to be originated from the weathering of tourmaline. High levels of Ni and Cu concentrations were derived from electronic waste leakage, while excessive Ba and Zn were linked to factory emissions and tire wear. The reasonable maximum exposure (RME) of hazard index (HI) was higher than safety standard and reveal the potential health risks in the southwestern study area. Sensitivity analysis demonstrated the Li concentrations possessed the highest weight contributing to health risk. This study provides a valuable information for source-specific risk assessments of potentially toxic elements in groundwater associated with urban areas.

Identification and apportionment of shallow groundwater nitrate pollution in Weining Plain, northwest China, using hydrochemical indices, nitrate stable isotopes, and the new Bayesian stable isotope mixing model (MixSIAR).

Groundwater nitrate (NO3-) pollution is a worldwide environmental problem. Therefore, identification and partitioning of its potential sources are of great importance for effective control of groundwater quality. The current study was carried out to identify the potential sources of groundwater NO3- pollution and determine their apportionment in different land use/land cover (LULC) types in a traditional agricultural area, Weining Plain, in Northwest China. Multiple hydrochemical indices, as well as dual NO3- isotopes (δ15N-NO3 and δ18O-NO3), were used to investigate the groundwater quality and its influencing factors. LULC patterns of the study area were first determined by interpreting remote sensing image data collected from the Sentinel-2 satellite, then the Bayesian stable isotope mixing model (MixSIAR) was used to estimate proportional contributions of the potential sources to groundwater NO3- concentrations. Groundwater quality in the study area was influenced by both natural and anthropogenic factors, with anthropological impact being more important. The results of LULC revealed that the irrigated land is the dominant LULC type in the plain, covering an area of 576.6 km2 (57.18% of the total surface study area of the plain). On the other hand, the results of the NO3- isotopes suggested that manure and sewage (M&S), as well as soil nitrogen (SN), were the major contributors to groundwater NO3-. Moreover, the results obtained from the MixSIAR model showed that the mean proportional contributions of M&S to groundwater NO3- were 55.5, 43.4, 21.4, and 78.7% in the forest, irrigated, paddy, and urban lands, respectively. While SN showed mean proportional contributions of 29.9, 43.4, 61.5, and 12.7% in the forest, irrigated, paddy, and urban lands, respectively. The current study provides valuable information for local authorities to support sustainable groundwater management in the study region.

Source Identification and Apportionment of Trace Elements in Soils in the Yangtze River Delta, China.

Trace elements pollution has attracted a lot of attention worldwide. However, it is difficult to identify and apportion the sources of multiple element pollutants over large areas because of the considerable spatial complexity and variability in the distribution of trace elements in soil. In this study, we collected total of 2051 topsoil (0⁻20 cm) samples, and analyzed the general pollution status of soils from the Yangtze River Delta, Southeast China. We applied principal component analysis (PCA), a finite mixture distribution model (FMDM), and geostatistical tools to identify and quantitatively apportion the sources of seven kinds of trace elements (chromium (Cr), cadmium (Cd), mercury (Hg), copper (Cu), zinc (Zn), nickel (Ni), and arsenic (As)) in soil. The PCA results indicated that the trace elements in soil in the study area were mainly from natural, multi-pollutant and industrial sources. The FMDM also fitted three sub log-normal distributions. The results from the two models were quite similar: Cr, As, and Ni were mainly from natural sources caused by parent material weathering; Cd, Cu, and Zu were mainly from mixed sources, with a considerable portion from anthropogenic activities such as traffic pollutants, domestic garbage, and agricultural inputs, and Hg was mainly from industrial wastes and pollutants.