Pollution Characteristics and Health Risks of Heavy Metals in Groundwater of a Chemical Industrial Park

Technical Summary: Pollution Characteristics and Health Risks of Heavy Metals in Groundwater of a Chemical Industrial Park

Problem Statement
Chemical industrial parks pose significant risks to groundwater resources and human health due to the potential leakage of heavy metals during production and storage processes. While previous studies have utilized various statistical methods to analyze pollution characteristics and sources, traditional health risk assessments often rely on fixed exposure parameters, failing to account for the combined toxic effects of heavy metals or the uncertainty inherent in exposure scenarios. Furthermore, there is a lack of localized data regarding the dynamic evolution of pollutants and the adaptability of exposure parameters to specific regional contexts. This study addresses these gaps by investigating a chemical industrial park in southern China to systematically characterize heavy metal pollution, identify sources, and conduct a robust health risk assessment that accounts for uncertainty.

Methodology
The research was conducted in a chemical industrial park in southern China, characterized by Upper Cretaceous and Quaternary strata with groundwater flowing from west to east.

• Sampling and Analysis: A total of 127 groundwater samples were collected and analyzed for 11 heavy metals (Fe, Mn, Al, Zn, Co, Ni, Pb, Cu, Cd, As, and Tl).
• Pollution Assessment: The study employed the Single-Factor Pollution Index and the Nemerow Comprehensive Pollution Index to evaluate pollution levels against the Class III standards of GB/T 14848-2024. Spatial distribution was mapped using Inverse Distance Weighting (IDW) interpolation in ArcGIS 10.8.
• Source Identification: Pearson correlation analysis was utilized to quantify internal correlations among heavy metals, aiding in the identification of common sources or geochemical affinities.
• Health Risk Assessment: The study coupled the United States Environmental Protection Agency (USEPA) model with Monte Carlo simulation to assess non-carcinogenic and carcinogenic risks via oral ingestion. This approach constructed probability distributions for exposure parameters (e.g., water intake, body weight, exposure duration) to account for uncertainty, specifically evaluating risks for both adults and minors.

Key Results

• Pollution Characteristics: Iron (Fe) exhibited the highest mean concentration (12.16 mg/L), followed by Manganese (Mn) and Aluminum (Al). Except for Copper (Cu), the mean concentrations of all analyzed heavy metals exceeded the Class III drinking water standards. The Nemerow comprehensive pollution index for the area was 42.78, indicating severe overall pollution. Fe, Al, Tl, Pb, and Ni were classified as severely polluted, while Cd and Co showed slight pollution.
• Spatial Distribution: Fe, Mn, Al, and Tl were distributed throughout the study area with high concentrations. In contrast, Cd, Co, Ni, and Pb displayed localized hotspots in the north-central region, while the southern and eastern parts showed lower concentrations. The east-central region experienced the most severe pollution due to the superposition of multiple pollutants.
• Source Correlations: Pearson correlation analysis revealed a strongly positive correlation group comprising Zn, Al, Cd, Ni, and Co (correlation coefficients generally >0.8), suggesting a common origin or similar geochemical affinity. Mn showed significant positive correlations with most elements, acting as a "linking" factor in migration and enrichment. Lead (Pb) demonstrated weak correlations with other metals, indicating a distinct source or enrichment mechanism.
• Health Risk Assessment:
  • Non-Carcinogenic Risk: The mean Hazard Index (HI) for adults was 5.39 and for minors was 2.25, both exceeding the safety threshold of 1. Adults faced a higher risk than minors. Manganese (Mn) and Cobalt (Co) were identified as the primary drivers of non-carcinogenic risk.
  • Carcinogenic Risk: The mean Total Carcinogenic Risk (TCR) was 0.501 for adults and 0.210 for minors. While the mean values fell within the "attention-required" range (1×10⁻⁶ to 1×10⁻⁴), the maximum TCR for adults reached 1.33, exceeding the safety threshold. Aluminum (Al) was identified as the core driving factor for carcinogenic risk.

Significance and Claims
The authors state that this study provides a scientific basis for the targeted prevention, management, and remediation of regional groundwater pollution by heavy metals. By integrating Monte Carlo simulations with the USEPA model, the research addresses deficiencies in traditional assessments regarding dynamic pollution monitoring and the calibration of localized exposure parameters. The identification of specific driving factors (Mn and Co for non-carcinogenic risks; Al for carcinogenic risks) and the delineation of spatial hotspots offer precise targets for future governance. Furthermore, the correlation analysis clarifies the source characteristics of heavy metals in the study area, supporting more effective source tracing and pollution control strategies within chemical industrial parks.