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<p>The Western Dongting Lake area, a biodiversity hotspot under traditional farming, has long suffered heavy metal pollution. In this study, the concentrations of As, Cd, Cr, Hg, and Pb in agricultural soils were determined and ecological risks were evaluated using both the hazard quotient(HQ) model and the probabilistic ecological risk assessment(PERA) model. The results showed that HQ suggested slight or negligible risks, whereas PERA indicated consistently high and unacceptable risks. This discrepancy arose because HQ criteria are derived from human health thresholds and provide only deterministic estimates, whereas PERA incorporates species-specific predicted no-effect concentration(<i>P</i><sub>NEC</sub>), environmental variability, and uncertainty, thereby providing more precise and site-specific risk assessments and assigning probabilities. By applying a tiered PERA model, our study highlights its novelty and superiority in ecological risk characterization, providing critical guidance for soil management and ecological protection in contaminated farmlands.</p>

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Heavy metal concentrations in agricultural soil from the Western Dongting Lake area of Hunan province, China, and a tiered ecological risk assessment

  • 期刊论文

  • 发表日期：

    2026年3月1日

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  • Mei-hua Xia,
  • Li-li Cui,
  • Nai-liang Cao,
  • Mai Hu,
  • Zhen-yu Xu,
  • Xue-li Fan,
  • Ying-hong Yu,
  • Wen-qing Liu,
  • Rui-feng Kan,
  • Ming-dong Zhu

摘要

The Western Dongting Lake area, a biodiversity hotspot under traditional farming, has long suffered heavy metal pollution. In this study, the concentrations of As, Cd, Cr, Hg, and Pb in agricultural soils were determined and ecological risks were evaluated using both the hazard quotient(HQ) model and the probabilistic ecological risk assessment(PERA) model. The results showed that HQ suggested slight or negligible risks, whereas PERA indicated consistently high and unacceptable risks. This discrepancy arose because HQ criteria are derived from human health thresholds and provide only deterministic estimates, whereas PERA incorporates species-specific predicted no-effect concentration(PNEC), environmental variability, and uncertainty, thereby providing more precise and site-specific risk assessments and assigning probabilities. By applying a tiered PERA model, our study highlights its novelty and superiority in ecological risk characterization, providing critical guidance for soil management and ecological protection in contaminated farmlands.