Groundwater pollution source identification and health risk assessment in the North Anhui Plain, eastern China: Insights from positive matrix factorization and Monte Carlo simulation

Kai Chen; Qimeng Liu; Tingting Yang; Qiding Ju; Xikang Hou; Wei Gao; Shaojie Jiang

doi:10.1016/j.scitotenv.2023.165186

Groundwater pollution source identification and health risk assessment in the North Anhui Plain, eastern China: Insights from positive matrix factorization and Monte Carlo simulation

Sci Total Environ. 2023 Oct 15:895:165186. doi: 10.1016/j.scitotenv.2023.165186. Epub 2023 Jun 28.

Authors

Kai Chen¹, Qimeng Liu¹, Tingting Yang¹, Qiding Ju¹, Xikang Hou², Wei Gao³, Shaojie Jiang⁴

Affiliations

¹ School of Earth and Environment, Anhui University of Science & Technology, Huainan 232001, PR China.
² Laboratory of Aquatic Ecological Conservation and Restoration, Chinese Research Academy of Environmental Sciences, Beijing 100012, PR China. Electronic address: houxk@pku.edu.cn.
³ Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou 510006, PR China. Electronic address: gaowei21@gdut.edu.cn.
⁴ Geo-environment Monitoring Station of Anhui Province, Hefei 230001, PR China.

PMID: 37385500
DOI: 10.1016/j.scitotenv.2023.165186

Abstract

Groundwater contaminants from natural and anthropogenic sources pose a serious threat to the ecological environment and public health. In this study, 30 groundwater samples were collected from shallow wells at a large central water source in the North Anhui Plain, eastern China. Hydrogeochemical methods, positive matrix factorization (PMF) model, and Monte Carlo simulation were used to determine the characteristics, sources, and human health risks of inorganic and organic analytes in groundwater. The groundwater was weakly alkaline with high total hardness and was dominated by HCO₃-Mg·Ca, HCO₃-Ca·Mg, and HCO₃-Ca·Mg·Na hydrochemical facies. The concentration of naphthalene was at a safe level, while the concentrations of F^-, NO₃^- and Mn in 16.7 %, 26.7 % and 40 % of the samples, respectively, exceeded threshold risk-based values based on Chinese groundwater quality standards. Hydrogeochemical methods revealed that water-rock interactions (including weathering of silicate minerals, dissolution of carbonates, and cation exchange), acidity, and runoff conditions control the migration and enrichment of these analytes in groundwater. The PMF model indicated that local geogenic processes, hydrogeochemical evolution, agricultural activities, and petroleum-related industrial sources were the main factors affecting groundwater quality, with contributions of 38.2 %, 33.7 %, 17.8 %, and 10.3 %, respectively. A health risk evaluation model based on Monte Carlo simulation indicated that 77.9 % of children were exposed to a total noncarcinogenic risk above safe thresholds, about 3.4 times higher than the risk to adults. The main contributor to human health risk was F^- originating from geogenic processes; thus, F^- was identified as a priority for control. This study demonstrates the feasibility and reliability of combining source apportionment techniques and health risk assessment to evaluate groundwater quality.

Keywords: Hydrochemistry; North Anhui Plain; Saturation index; Source apportionment; Water quality.

MeSH terms

Adult
Child
China
Environmental Monitoring / methods
Groundwater*
Humans
Monte Carlo Method
Reproducibility of Results
Risk Assessment
Water
Water Pollutants, Chemical* / analysis
Water Quality

Substances

Water Pollutants, Chemical
Water