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From comparative risk assessment to multi-criteria decision analysis and adaptive management: recent developments and applications.

Abstract：

:Environmental risk assessment and decision-making strategies over the last several decades have become increasingly more sophisticated, information-intensive, and complex, including such approaches as expert judgment, cost-benefit analysis, and toxicological risk assessment. One tool that has been used to support environmental decision-making is comparative risk assessment (CRA), but CRA lacks a structured method for arriving at an optimal project alternative. Multi-criteria decision analysis (MCDA) provides better-supported techniques for the comparison of project alternatives based on decision matrices, and it also provides structured methods for the incorporation of project stakeholders' opinions in the ranking of alternatives. We argue that the inherent uncertainty in our ability to predict ecosystem evolution and response to different management policies requires shifting from optimization-based management to an adaptive management paradigm. This paper brings together a multidisciplinary review of existing decision-making approaches at regulatory agencies in the United States and Europe and synthesizes state-of-the-art research in CRA, MCDA, and adaptive management methods applicable to environmental remediation and restoration projects. We propose a basic decision analytic framework that couples MCDA with adaptive management and its public participation and stakeholder value elicitation methods, and we demonstrate application of the framework to a realistic case study based on contaminated sediment management issues in the New York/New Jersey Harbor.

journal_name

Environ Int

journal_title

Environment international

authors

Linkov I,Satterstrom FK,Kiker G,Batchelor C,Bridges T,Ferguson E

doi

10.1016/j.envint.2006.06.013

subject

Has Abstract

pub_date

2006-12-01 00:00:00

pages

1072-93

issue

8

eissn

0160-4120

issn

1873-6750

pii

S0160-4120(06)00083-3

journal_volume

32

pub_type

杂志文章,评审

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