Risk-based imprecise post-remediation soil quality objectives

Area of Science:

• Environmental Science
• Risk Assessment
• Soil Remediation

Background:

• Risk-based management of contaminated land is crucial for sustainable remediation.
• Uncertainty, both stochastic (aleatoric) and epistemic, is inherent in risk assessments.
• Epistemic uncertainty is often overlooked, leading to precise, single-value soil quality objectives.

Purpose of the Study:

• To demonstrate how joint treatment of stochastic and epistemic uncertainty can result in interval-based soil quality objectives.
• To show how interval objectives provide an improved risk-based safeguard for post-remediation monitoring.
• To apply and illustrate the proposed method using a real-world case study of arsenic-contaminated soils.

Main Methods:

• Risk assessment incorporating both stochastic and epistemic uncertainty.
• Development of interval-based soil quality objectives.
• Case study analysis of arsenic-contaminated soils in North-East France, including sampling, chemical characterization, and bioaccessibility analysis.

Main Results:

• The joint treatment of uncertainties leads to soil quality objectives presented as intervals, not precise values.
• Interval-based objectives offer a more robust safeguard for post-remediation monitoring.
• The case study successfully illustrated the incorporation of partial or imprecise information into the risk analysis.

Conclusions:

• Considering both stochastic and epistemic uncertainty provides a more realistic and protective approach to contaminated land management.
• Interval-based soil quality objectives enhance the reliability of remediation efforts.
• The method is applicable to sites with complex contamination and data limitations.