Risk-based imprecise post-remediation soil quality objectives

Abstract

While risk-based contaminated land management is an essential component of sustainable remediation, uncertainty is an unavoidable aspect of risk assessment, since most of the parameters that influence risk are typically affected by uncertainty. Uncertainty may be of different origins; i.e., stochastic or epistemic. Stochastic (or aleatoric) uncertainty arises from random variability related to natural processes, while epistemic uncertainty arises from the incomplete/imprecise nature of available information. But the latter is rarely considered in risk assessments, with the result that risk-based soil quality objectives are almost invariably presented as precise (unique) threshold values. In this paper it is shown: (i) how the joint treatment of stochastic and epistemic uncertainty in risk assessment can lead to soil quality objectives presented as intervals rather than precise values and (ii) how this provides an upper risk-based safeguard for post-remediation monitoring values. The proposed method is illustrated by a real case of soils contaminated by arsenic located in the North-East of France. At this site steel manufacturers have gradually filled up a small valley with slag and dust, over more than a century. These materials are enriched in various metal(loid)s, including arsenic and lead. As the environmental authority has asked for a conversion of the site to other uses that may involve access by the general public, an investigation of human health risk was performed based on a sampling campaign and chemical characterizations including various types of extractions and an analysis of bioaccessibility. While further investigations are required to improve the bioaccessibility model, the human health risk presented herein shows how partial or imprecise information can be incorporated in the analysis while taking into account underlying uncertainties.