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Title: Application of Structured Decision Making to Hanford Site Radiological Air Monitoring - 17924

Conference ·
OSTI ID:22802537

Radiological air monitoring is a component of an Environmental Surveillance (ES) program that has been in operation at the Department of Energy Hanford Site for several decades. The primary objectives of the ES program are protection of human health and the environment (on and off-site) as well as regulatory compliance. The ES program was designed decades ago when the plutonium-production reactors and related facilities at the Hanford Site were operational and air emissions were more widespread and significant than today. We employed a structured decision making (SDM) approach that integrates science with values and preferences to a Hanford Site air monitoring program decision. Specifically, a decision was necessary pertaining to the possible replacement of three air monitoring stations located in the 100 Area of the Hanford Site because the power line that supports these stations was near the end of its lifecycle. Although focused on this specific decision, the SDM model is more broadly applicable to decisions pertaining to adapting the air monitoring network to current Hanford operations. The value focused thinking approach that underlies SDM facilitates transparent and defensible decision making, and aids in communicating monitoring rationale. Some of the fundamental objectives elicited from the decision makers regarding management options for the three air monitoring stations included maximizing the ability to measure releases, minimizing environmental impacts, and maximizing social and economic sustainability. The fundamental objectives were linked to six objectives that could be measured (quantified) to allow a decision-analytic solution to the decision problem. Value functions and preference weights were developed for each of the objectives measures based on information obtained during a project workshop as well as by review and analysis of environmental data. Lastly, a set of five management options was identified that might achieve at least one of the objectives. A Bayes Network was developed as a solution to the decision problem pertaining to the three air stations (the 3 air stations decision). The Bayes Network describes the decision model graphically, and also serves as the computational engine for the decision analysis. The Bayes Network defines the relationship among the five management options and six objectives measures. In addition to the weights and value functions noted above, key inputs to the Bayes Network include a set of probabilities related to the different model states defined by the network. These include the probability of a significant release occurring, the probability that a release would be detected under each of the five management options, and the probability of achieving the other objective measures under each management option. In this manner the Bayesian Network captures the uncertainty in the components of the decision model. Replacing the three air monitoring stations with thermoluminescent dosimeters was identified as the preferred management option. A brief report was developed documenting the SDM model, including the workshop notes and analyses that were used to develop the objectives and model input variable values. This application demonstrates SDM's utility for supporting monitoring program decisions and, critically, providing a transparent and traceable basis for the decision. This relatively simple SDM model also provides a basis for an SDM model for monitoring decisions related to the more complex and holistic goal of achieving ES program objectives. (authors)

Research Organization:
WM Symposia, Inc., PO Box 27646, 85285-7646 Tempe, AZ (United States)
OSTI ID:
22802537
Report Number(s):
INIS-US-19-WM-17924; TRN: US19V0551046931
Resource Relation:
Conference: WM2017: 43. Annual Waste Management Symposium, Phoenix, AZ (United States), 5-9 Mar 2017; Other Information: Country of input: France; 4 refs.; available online at: http://archive.wmsym.org/2017/index.html
Country of Publication:
United States
Language:
English