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• W2080597643 abstract "Decision analysis in subsurface contamination management is generally carried out through a traditional engineering economic viewpoint. However, new advances in human health risk assessment, namely, the probabilistic risk assessment, and the growing awareness of the importance of soft data in the decision-making process, require decision analysis methodologies that are capable of accommodating non-technical and politically biased qualitative information. In this work, we discuss the major limitations of the currently practiced decision analysis framework, which evolves around the definition of risk and cost of risk, and its poor ability to communicate risk-related information. A demonstration using a numerical example was conducted to provide insight on these limitations of the current decision analysis framework. The results from this simple ground water contamination and remediation scenario were identical to those obtained from studies carried out on existing Superfund sites, which suggests serious flaws in the current risk management framework. In order to provide a perspective on how these limitations may be avoided in future formulation of the management framework, more matured and well-accepted approaches to decision analysis in dam safety and the utility industry, where public health and public investment are of great concern, are presented and their applicability in subsurface remediation management is discussed. Finally, in light of the success of the application of risk-based decision analysis in dam safety and the utility industry, potential options for decision analysis in subsurface contamination management are discussed." @default.
• W2080597643 created "2016-06-24" @default.
• W2080597643 creator A5046105312 @default.
• W2080597643 creator A5088443301 @default.
• W2080597643 date "2003-07-01" @default.
• W2080597643 modified "2023-09-27" @default.
• W2080597643 title "Applicability of risk-based management and the need for risk-based economic decision analysis at hazardous waste contaminated sites" @default.
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• W2080597643 doi "https://doi.org/10.1016/s0160-4120(03)00009-6" @default.
• W2080597643 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/12705948" @default.
• W2080597643 hasPublicationYear "2003" @default.
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