Browsing by Author "David McNelis, Committee Member"

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    Greater Than Class C Low Level Radioactive Waste Management Strategies.
    (2010-10-25) Platfoot, Elizabeth; Man-Sung Yim, Committee Chair; Christine Grant, Committee Member; David McNelis, Committee Member
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    A Radioactive Waste Cleanup Decision Making Framework
    (2009-04-24) Ottinger, Keith Everette; Man-Sung Yim, Committee Chair; Peter Bloomfield, Committee Member; David McNelis, Committee Member
    Many sites in the United States and around the world are contaminated with radioactive waste. Because of the public perception of radiation, making economically feasible and socially acceptable radioactive waste cleanup decisions is often difficult. The current solution to this problem is to have the public participate in the decision making process. This allows for more disclosure to and input from the stakeholders which are supposed to make the decision more socially acceptable. The results of this approach have not always been good and meaningful public involvement takes time and resources. In this work a decision making framework is developed, which attempts to solve this problem by creating a method for quantifying the value of the public’s perception of the contamination and cleanup options. These values are then input into a multi attribute value theory analysis which includes the direct costs of the cleanup and dose, and attempts to find socially viable solutions for the decision. The framework is complete, however, more research is need for to be able to adequately quantify the public’s perception. A case study based on the contamination at the Radioactive Waste Disposal Site (RWDS) of the Kurchatov Institute (KI) in Moscow, Russia was performed to illustrate how the framework works. This case study was primarily based on published data of the contamination levels and other important parameters as of 2003. However, some of the required data was not available or very uncertain and the site has since undergone remediation so the results may not represent the actual KI RWDS. In this case study the optimum cleanup method was determined to be covering the site with clean fill for discount rates of 5 percent or less and no action for higher discount rates. This result seems reasonable but more research is needed to determine if it fully represents the public’s perception of the contamination or the cleanup alternatives and if not how to improve the model.