Ranking Hazardous-Waste Sites for Remedial Action (1994) / Chapter Skim
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6 DOE'S PRIORITY SETTING
6 DOE'S PRIORITY SETTING
Pages 177-210
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From page 177... ...
testing grounds for the primary purpose of producing nuclear materials and weep ons for national defense. As a result of these operations, DOE facilities are now faced with contamination prob lems associated with radioactive and hazardous chemical wastes and mix lures of those wastes.
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not to use ERPS for the foreseeable future. Although it is not currently in use, ERPS provided the committee with the opportunity to assess a model clesigned to explicitly acldress social, economic, political impacts, and cost consideration in addition to health risk impacts.
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. In order to centralize and coordinate the efforts required by these statutes, DOE created the Office of Environmental Restoration and Waste Management (EM)
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to DOE waste disposal opera lions and cleanup. The DOE priority setting system discussed in this chapter was developed initially for use with the environmental restoration program only.
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From page 181... ...
A categorization system based on these four priorities was recognized as an interim approach to establishing priorities for future environmental restoration activities. In the June 1990 executive summary of the EM Five Year Plan for Fiscal Years 1992 1996, DOE reported that in consultation with interested parties, it was developing a risk teased priority setting system for its environmental restoration program.
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. Through a Federal Register announcement on September 6, 1991, DOE publicly sought comments on the priority setting system (Federal Register, 1991~.
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as an alternative for estimating population and inctiviclual risk estimates and for RIS outputs are summary risk indicators generates! using a computer model known as Multimedia Environmental Pollutant Assessment System (MEPAS)
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Role of ERPS The ERPS represents an application of multiattribute utility theory to the problem of ranking a set of alternatives for site remecliation. Details of this system are reviewed by briefly dis cussing its role in the overall process of determining priorities and funding levels for environmental restoration activities.
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an analysis of priorities cleterminecI by EM. An Overview of ERPS ERPS, a multiattribute utility moclel, is set up to allow the simultaneous evaluation of multiple objectives: Reduce health risks Recluce environmental risks Avoid adverse socioeconomic impacts Respond to regulations Reduce uncertainty .
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- ~ ~ o ~ ~ ~ I'll > m ........
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for the entire set of environmental restoration operations. Both the estimated benefits (in the form of risks reclucec!
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The Multiattribute Model The ERPS is basest on an implementation of multiattribute utility theory, an approach to ranking alternatives clescribed in Chapter 3. From a scientific standpoint, multiattribute utility theory is a prescriptive approach to decision making.
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To render more operational this list of objectives for the purposes of ERPS it was necessary to create an objectives hierarchy with these seven broad statements at the top and with more detailed objectives further clown. The lower level objectives essentially define the higher level objectives in more detail, ant!
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an c: l o so o · ,~ in o 1 _ !
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then combine them mathematically to calculate an overall utility number for each alternative. In general, the single attribute utility functions on the attributes could be combined in a variety of ways; for example, they could be added, multiplied, or combined using a complex polynomial form.
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Once the alternatives have been scored on each of the attributes, and their corresponding utility function values have been calculated from the single attribute utility functions, it is a straightforward matter to multiply these utility values times their weights ant! to sum the results to determine an overall utility function score for each alter native.
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The population health risk measures "the future expected peak annual health effects" in terms of the probability of an incidence of "a major, Diverse health consequence." For this purpose, a major adverse health consequence is clefined, in part, as a premature fatality, severe neuro toxic effect, or disabling birth defect (DOE, 199Ib)
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The next step is to use a single attribute utility function to translate these scores into measures of value. The transformation 194
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However, over the range of anticipated health impacts that is considered in this model, the assumption of linearity seems appropriate. A more subtle issue is the use of population risks and inctivic3 ual risks to estimate the health risks of budget cases.
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Thus, a number of difficult consist orations are not acIdressec! by the approach in ERPS to estimate health risks, including the need to distinguish between the impli cations of an incidence of cancer in an 80 year old indiv~clual ver sus a birth defect in a child.
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7, the same scale for the scores assigned to the health risks.
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Direct estimates of the value of the remedial efforts associates! with budget cases in alleviating environmental threats might be more accurate than these scores.
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Finally, the score for each budget case is transformed by an ex ponential single attribute utility function into a linear scale that measures the value of these socioeconomic impacts. From a scion tific point of view, this approach is crude anct again represents a tracle off between technical rigor ant!
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These estimates are basest on the scores that were developed to measure population and inctiviclual health risks.
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This scale too is bans formed by an exponential function into a linear scale that assigns value to the uncertainty reduction activities. Conceptually, the inclusion of the objective of uncertainty re Auction in the ERPS is a sound!
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Essen tially, this equation corresponds to multiplying the seriousness of the violation by its likelihood, and discounting the result at 25% per year of delay. An exponential function is then used to bans late this score into a measure of value for the multiattribute utility function.
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+ WrrUrr(Srr) where the Is are weights on the objectives, the U's are the single attribute utility functions, and the S's are the scores on the objec fives.
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and exponential single attribute utility functions (the Us) has the im plication that each of the objectives is measures!
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Factor Weight Basis Health risk Uncertain reduction Environmental risk Socioeconomic impact Regulatory compliance 36% 32% 13% 9.5% 9.5% $5M/health effect Individual weight = 1/5 of population weight Implied by weight on health and dollar tradeoffs $400M to eliminate a "7" $300M to eliminate a "7" $300M to eliminate a "7" Other: Risk urgency/timing = 5 % discount rate. Remaining and future costs = 10% discount rate.
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The mociel would help set priorities for these needs based upon a variety of social, economic, and political considerations, as well as impacts on human health and the environment. Credibility and Acceptability: The committee could not evalu ate this aspect sufficiently at this time.
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upon subjective juc3gements. It will be crucial in a broad and comprehensive model of this type to conduct a wale range of sensitivity analyses to help the model developers and others under stand the impacts of uncertainties in ciata input on the resultant relative rankings of sites.
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The multiattribute utility theory that forms the basis for ERPS is a valuable too! for organizing a complex of information for renew by others.
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provide the objective ranking of sites for remecliation that is needed, it nevertheless believes that a well cievelopec3, documented, valiciated, and comprehensive model can help greatly in making sound deci signs about what sites to remectiate first, and the degree of cleanup that is desirable.
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