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Prediction and Yucca Mountain

Prediction and Yucca Mountain. Jeremy Van Cleve Global Climate Change and Society Summer Program August 8 th , 2002. Prediction…who me?.

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Prediction and Yucca Mountain

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  1. Prediction and Yucca Mountain Jeremy Van Cleve Global Climate Change and Society Summer Program August 8th, 2002

  2. Prediction…who me? • Goal:“The summer project will focus on creating a WWW interface to allow for the documentation of predictions as they are made in a diverse set of policy-relevant settings, evaluation of accuracy of predictions, grades of predictive performance, and assessment of the role of predictions in the decision making process.” • Where to start? RESEARCH… • Yucca Mountain seemed like a worthwhile topic.

  3. What is Yucca Mountain? • Yucca Mountain is the chosen site in the U.S. for the disposal of spent nuclear fuel (SNF) and high-level nuclear waste (HLW). • It is a deep, geologic repository located at a depth of 300 meters in the unsaturated zone, 300 meters above the water table.

  4. Background • By the late 1970s, it became apparent that the federal government rarely stuck to any specific policy or schedule. Essentially, “states…had developed strong doubts that the Federal Government could be counted on to keep its word on waste management matters.” (OTA 1985) • Nuclear Waste Policy Act of 1982 establishes a schedule and framework for siting and building one or more geologic repositories. • 1987, the Nuclear Waste Policy Act Amendments obligated DOE to investigate only one site, Yucca Mountain.

  5. Background • 1992: Energy Policy Act (EnPA) mandated EPA to set health and safety standards for the proposed repository (specifically to “prescribe the maximum annual effective dose equivalent to individual members of the public.” (EnPA section 801(a)(1)). • Dose limit is 15 mrem/yr, which corresponds to 8.5 chances in 1,000,000 of contracting a fatal cancer per year.

  6. TSPA – Prediction in Fine Form • Total System Performance Assessment (TSPA) is a way “to provide a defensible analysis of system behavior incorporating models and parameters that are based on scientific observations in order that decision-makers can assess the ability of the repository system to comply with proposed regulations.” (TSPA-SR, 2000) • The TSPA can be conceptualized as a series of levels on a pyramid

  7. TSPA – Prediction in Fine Form • Three main elements: • The primary element is an estimate of the most likely behavior of the repository system. • The next element is a quantification of the probability of natural events that might cause a loss of waste containment. • Finally, a human intrusion component. This is the likelihood that human beings will inadvertently drill into a waste repository. • In the TSPA, the final models are probabilistic in nature

  8. Critiques of TSPA • The DOE should improve its understanding of the repository system behavior as a whole. While the TSPA-SR demonstrates regulatory compliance, it places little emphasis on contextualizing model conceptualizations and results within the body of knowledge acquired during the site investigation and repository design. • DOE has often mixed conservative assumptions and models with optimistic or realistic ones.This has left unclear the level of conservatism and uncertainty in the models • ACNW believes that motivation of the TSPA-SR is to demonstrate regulatory compliance rather than provide a risk informed assessment of repository performance.

  9. Critiques of Disposal Approach • U.S. approach to waste disposal is rife with technical optimism and as a result, DOE feels confident in setting rigid timelines and regulatory specifications. Any future problems can be solved through further engineering the solution. • TSPA methodology is heavily technical in nature. To rely on the results from TSPA model is to put a great deal of faith in the underlying scientific data and the conceptualizations of repository processes and features. Thus, the use of TSPA is contemporary instantiation of DOE’s technically optimistic approach.

  10. Critiques of Disposal Approach • NRC suggests that the biggest challenges to successful waste disposal programs are societal. In contrast, the focus of the U.S. program has been on technical issues to the exclusion of social ones. • Erosion of public trust has been and continues to be a central problem as there are few avenues for public discourse and input into decision making. • Lack of transparency in the waste disposal and management program. • Is site selection process is equitable? NWPA Amendments of 1987 limited study to Yucca Mountain and residents of Nevada felt that they had been left out of the site selection process.

  11. Alternative: Adaptive Staging • Adaptive staging is defined as “a process where the development of geologic repository for high-level waste is divided into stages that are separated by explicit decision points.” (National Research Council, 2002) • At each decision point, the results of scientific studies, site investigations, and computer models can be evaluated. The goals and work of each stage are predicated upon the outcomes of previous stages. • Key advantages to adaptive management when compared with a linear approach are that it provides greater flexibility, transparency, integrity, and responsiveness to stakeholders.

  12. The Role of Prediction • In the linear methodology, prediction is heavily used and often becomes the goal of some public policies instead of a means to study repository performance. (goal substitution…remember?) • Adaptive management uses prediction where it is applicable but acknowledges that prediction has limits and that social forces play a primary role in making policy decisions. • Bomb-pulse chlorine-36 example.

  13. Conclusions and Opinion • Over the next 4 years, the DOE and USNRC will have an opportunity to design the policy framework that will work towards permanently disposing of the glut of SNF and HLW. • If a linear methodology is continued and prediction is the only barometer for repository viability, public opposition is inevitable. • An adaptive staging approach can be adopted, which focuses on an evolving repository design and performance criteria informed through incremental learning. This could generate more trust between the DOE, the state of Nevada and other stakeholders.

  14. Reproducible? • http://sciencepolicy.colorado.edu/~jvc/

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