Summary of Conceptual Models and Data Needs to Support the INL Remote-Handled Low-Level Waste Disposal Facility Performance Assessment and Composite Analysis

An overview of the technical approach and data required to support development of the performance assessment, and composite analysis are presented for the remote handled low-level waste disposal facility on-site alternative being considered at Idaho National Laboratory. Previous analyses and available data that meet requirements are identified and discussed. Outstanding data and analysis needs are also identified and summarized. The on-site disposal facility is being evaluated in anticipation of the closure of the Radioactive Waste Management Complex at the INL. An assessment of facility performance and of the composite performance are required to meet the Department of Energy’s Low-Level Waste requirements (DOE Order 435.1, 2001) which stipulate that operation and closure of the disposal facility will be managed in a manner that is protective of worker and public health and safety, and the environment. The corresponding established procedures to ensure these protections are contained in DOE Manual 435.1-1, Radioactive Waste Management Manual (DOE M 435.1-1 2001). Requirements include assessment of (1) all-exposure pathways, (2) air pathway, (3) radon, and (4) groundwater pathway doses. Doses are computed from radionuclide concentrations in the environment. The performance assessment and composite analysis are being prepared to assess compliance with performance objectives and to establish limits on concentrations and inventories of radionuclides at the facility and to support specification of design, construction, operation and closure requirements. Technical objectives of the PA and CA are primarily accomplished through the development of an establish inventory, and through the use of predictive environmental transport models implementing an overarching conceptual framework. This document reviews the conceptual model, inherent assumptions, and data required to implement the conceptual model in a numerical framework. Available site-specific data and data sources are then addressed. Differences in required analyses and data are captured as outstanding data needs