Health Risk Assessment of Heavy Metals in Groundwater of Hainan Island Using the Monte Carlo Simulation Coupled with the APCS/MLR Model

Int J Environ Res Public Health. 2022 Jun 26;19(13):7827. doi: 10.3390/ijerph19137827.

Abstract

Groundwater is a significant component of water resources, but drinking groundwater with excessive heavy metals (HMs) is harmful to human health. Currently, quantitative source apportionment and probabilistic health risk assessment of HMs in groundwater are relatively limited. In this study, 60 groundwater samples containing seven HMs were collected from Hainan Island and analyzed by the coupled absolute principal component scores/multiple linear regression (APCS/MLR), the health risk assessment (HRA) and the Monte Carlo simulation (MCS) to quantify the pollution sources of HMs and the health risks. The results show that the high-pollution-value areas of HMs are mainly located in the industry-oriented western region, but the pollution level by HMs in the groundwater in the study area is generally low. The main sources of HMs in the groundwater are found to be the mixed sources of agricultural activities and traffic emissions (39.16%), industrial activities (25.57%) and natural sources (35.27%). Although the non-carcinogenic risks for adults and children are negligible, the carcinogenic risks are at a high level. Through analyzing the relationship between HMs, pollution sources, and health risks, natural sources contribute the most to the health risks, and Cr is determined as the priority control HM. This study emphasizes the importance of quantitative evaluation of the HM pollution sources and probabilistic health risk assessment, which provides an essential basis for water pollution prevention and control in Hainan Island.

Keywords: APCS/MLR model; Monte Carlo simulation; health risk; heavy metals in groundwater; source apportionment.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Child
  • China
  • Environmental Monitoring
  • Groundwater*
  • Humans
  • Linear Models
  • Metals, Heavy* / analysis
  • Monte Carlo Method
  • Risk Assessment
  • Soil Pollutants* / analysis

Substances

  • Metals, Heavy
  • Soil Pollutants

Grants and funding

This research was funded by the National Natural Science Foundation of China (41877297) and the China Geological Survey (12120114029601).