<p>Chromium (Cr) contamination originating from the tanning industry presents a significant threat to soil and groundwater. Traditional static risk assessment models often lack the capacity to account for the dynamic evolution of risks due to oversights in hydrogeological processes, changes in Cr speciation, and uncertainties in parameters. In this study, an integrated analytical framework combining contaminant transport models with Bayesian networks was proposed to investigate the dynamic health risks associated with Cr exposure at 10 tannery sites in China. Key parameters were derived from laboratory experiments and field studies, enabling analysis of the dynamic changes and health risks associated with Cr pollution. By integrating solute transport with chemical equilibrium models, the dynamic changes in Cr speciation were simulated. Additionally, a Bayesian network model incorporating 43 variables was used to address multi-parameter uncertainty. Results indicated that Type III sites (Inadequate landfills) exhibited high and most persistent carcinogenic risk of Cr exposure (CR = 1.0 × 10<sup>−5</sup> at 6000&#xa0;days, 10 times above threshold), while Type II sites (legacy tanneries) had the highest short-term carcinogenic risk (CR = 1.0 × 10<sup>−2</sup> at day 100). Risk levels in Type I sites (modernized tanneries) were acceptable. Sensitivity analysis revealed that groundwater Cr(VI) concentration was the dominant driver of the human health risk, followed by groundwater flow velocity and hydraulic gradient. These findings highlight the importance of considering Cr speciation dynamics and key influencing parameters in dynamic risk management, emphasizing the need for process-based assessments to effectively manage Cr pollution at tannery sites.</p>

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Dynamic health risk assessment of chromium exposure in soil and groundwater at tannery sites: a Bayesian network perspective

  • Shan-shan Guo,
  • Yu Wang,
  • Yong qiang Tian,
  • Hao Wu,
  • Yang Li,
  • Xiao dan Jin,
  • Xin Li,
  • Ze-lin Zhou,
  • Han Zhang,
  • Jin-yan Yang

摘要

Chromium (Cr) contamination originating from the tanning industry presents a significant threat to soil and groundwater. Traditional static risk assessment models often lack the capacity to account for the dynamic evolution of risks due to oversights in hydrogeological processes, changes in Cr speciation, and uncertainties in parameters. In this study, an integrated analytical framework combining contaminant transport models with Bayesian networks was proposed to investigate the dynamic health risks associated with Cr exposure at 10 tannery sites in China. Key parameters were derived from laboratory experiments and field studies, enabling analysis of the dynamic changes and health risks associated with Cr pollution. By integrating solute transport with chemical equilibrium models, the dynamic changes in Cr speciation were simulated. Additionally, a Bayesian network model incorporating 43 variables was used to address multi-parameter uncertainty. Results indicated that Type III sites (Inadequate landfills) exhibited high and most persistent carcinogenic risk of Cr exposure (CR = 1.0 × 10−5 at 6000 days, 10 times above threshold), while Type II sites (legacy tanneries) had the highest short-term carcinogenic risk (CR = 1.0 × 10−2 at day 100). Risk levels in Type I sites (modernized tanneries) were acceptable. Sensitivity analysis revealed that groundwater Cr(VI) concentration was the dominant driver of the human health risk, followed by groundwater flow velocity and hydraulic gradient. These findings highlight the importance of considering Cr speciation dynamics and key influencing parameters in dynamic risk management, emphasizing the need for process-based assessments to effectively manage Cr pollution at tannery sites.