Contaminated Sediments in Ports and Waterways Cleanup Strategies and Technologies (1997) / Chapter Skim
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Appendix E: Using Decision Analysis in the Management of Contaminated Sediments
Appendix E: Using Decision Analysis in the Management of Contaminated Sediments
Pages 257-284
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From page 257... ...
The management of contaminated sediments often falls into this category. Cost-benefit analysis (addressed in Appendix D)
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Decision analysis provides a way to use both factual and subjective information to evaluate the relative merits of alternative courses of action. Decision analysis does not provide absolute solutions, but it can offer valuable insights.
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Other approaches include mediation, negotiated rule making, and collaborative problem solving. These approaches may be easier to explain to stakeholders and may, therefore, be approached with less skepticism than decision analysis, which is technical in design and involves complex computations.
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frequently uses formal dispute resolution techniques, both for developing regulations and for resolving disputes in specific Superfund projects. Decision analysis is unique among the available techniques in terms of how it can improve the understanding and quality of decisions and choices.
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These developments have opened up new possibilities for applying decision analysis to a broad array of difficult problems, including environmental management problems. For example, decision modeling software enabled the committee to construct and display models as diagrams and spreadsheets, rather than as lines of computer code, and to display model output as useful graphs and diagrams (some of which are included in this appendix)
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Chevron Corporation uses decision analysis to help integrate the quantitative analysis of environmental risks into its management decisions, and DuPont Environmental Treatment has used a decision analytical approach to find costeffective, environmentally sound wastewater treatment methods (Horton, 1993)
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The data input consisted of the three dredged volumes to be evaluated, and, for each volume, the probability of not meeting the target PCB level in fish tissue (i.e., the exceedance probability) , the dredging and dredged material placement cost, and the resource damage cost.
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Paradoxically, then, the most effective modeling strategy for solving complex management problems is to build and analyze models of simpler decisions associated with the problem and then to use both direct insights from analyzing the model and indirect insights from formulating the model to make management decisions. Consensus Building The test case also suggested that decision analysis -- assuming the concept is understood and accepted by all parties -- could be useful in bringing stakeholders together to formulate and solve problems.
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Decision models can lay out the technical, scientific, and regulatory bases for decisions. In addition to fostering the sound management of contaminated sediments, decision analysis might also be used to improve government regulation.
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When applied to situations involving contaminated sediments, decision analysis can be used to integrate key assessments (e.g., site characterization, risk assessment, technical feasibility studies, and economic assessment) into explicit "decision models" that describe the management problem as it appears from the perspectives of different stakeholders.
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The effectiveness of decision analysis depends on the skill of the analyst, the effort by the decision maker to use the model and understand its results, and the quality of the information put into the model. Sometimes modeling results are counterintuitive.
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Total resource damage costs associated with PCB contamination in the harbor have been estimated on the order of $100 million to $1 trillion (Clites et al., 1991)
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. All three alternatives include a stopping rule, which states that dredged volume will not exceed the volume specified in the maximum dredged-volume alternative.
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Both sets of costs rise if the amount of sediment dredged is too low to meet the flounder body burden constraint because the need to perform additional dredging increases the cost of dredging and dredged material placement, and the extended duration of PCB contamination drives up the cost of resource damage.
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The decision also affects both dredging and placement costs and resource damage costs. Both of these cost factors also depend on whether the flounder body burden constraint is met.
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For example, dredging and placement cost data might be provided by a team of engineers, resource damage cost estimates by resource economists and local residents, and exceedance probability by a PCB bioaccumulation model. Test Case Decision Model The dredge and placement decision model developed for the demonstration project is shown in Figure E-2.
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From page 273... ...
In the test case, the 12 values of resource damage cost are calculated as the product of length of closure and annual resource damage cost. A value node with no influences has a single state; for example the node low dredged volume has one state (i.e., one volume)
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outcome i (1) where D&D cost is the cost of dredging and placement of the contaminated sediments, and resource damage cost is the cost associated with the closure of a commercial fishery (the two factors affecting the decision in this analysis)
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Thus: additional dredged volume = maximum dredged volume − dredged volume (4) Of course, if the FDA action level is not exceeded, then additional dredged volume equals zero.
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This factor was estimated as the product of two probabilistic variables, length of closure and annual resource damage cost. Length of closure represents the elapsed time (years)
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0 0.01 − exceedance probability 4 0.25 x exceedance probability 5 0.50 x exceedance probability 6 0.25 x exceedance probability Variability in annual resource damage cost due to disagreements about risks, costs, and benefits is likely to exceed variability due to uncertainty because stakeholders can have widely divergent opinions about the value of this factor. Because it reflects opinions instead of facts, variability due to disagreement should be treated parametrically rather than probabilistically.
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is much narrower than for the other two cumulative probability distribution functions. This narrow range FIGURE E-3 Expected values of alternative dredged-volume decisions.
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(In this context, value is the negative of cost; a value of −$150 million is equivalent to a cost of +$150 million.) The relatively low level of uncertainty associated with the maximum dredged-volume alternative makes sense because the low and intermediate dredged-volume alternatives involve more uncertainty about the remobilization and resource damage costs.
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From page 280... ...
As an illustration, there might be significant disagreement in the test case about the annual resource damage cost of the closure of a fishery. For example, if a substitute existed for the damaged fishery, then one might argue that the resource damage should be set at the marginal cost of the closure, rather than the total cost.
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. When annual resource damage cost exceeds $15 million, the maximum dredged volume becomes the preferred alternative (because as this cost rises, the risk associated with the exceedance probability for the intermediate dredged volume decision becomes unacceptably high)
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If this conclusion held up over a range of variations to the model, then disputes concerning the actual value of resource damage could be set aside. And, if variability in cost estimates were due to disagreements (rather than uncertainties)
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However, the model also predicts a 35 percent chance that the high dredgedvolume alternative will have the worst outcome of the three alternatives. If the model is altered slightly by increasing the uncertainty of the maximum dredged-volume alternative, then the high dredged-volume alternative becomes the model's preferred choice, demonstrating why a risk-averse decision maker might override the recommendation of the baseline analysis.
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1990. Decision Analysis and Quantitative Risk Characterization: Information-Analysis Based Risk Characterization.
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Key Terms
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