Methodology for Waste Forecasting and Informing an Integrated Waste Strategy at CNL - 18055
Conference
·
OSTI ID:22975275
- Canadian Nuclear Laboratories (Canada)
CNL is Canada's premier nuclear science and technology organization. CNL is a world leader in developing peaceful and innovative applications from nuclear technology through its expertise in physics, metallurgy, chemistry, biology and engineering. CNL is responsible for managing wastes from various locations across Canada. As a result of this work, legacy wastes have been generated and ongoing operations will continue to generate wastes. In order to identify gaps and ensure that paths are available to manage wastes, a waste forecast was developed. The waste forecast is intended to inform corporate strategy based on the volume of waste generated and into the future. One of the key pieces of output has been an estimate on the variability for forecasted volumes of wastes. Various sources of information were analyzed to provide a high-level summary. Many inputs were considered due to the various locations of waste generation, continuing operations, capital construction, decommissioning activities, and environmental remediation activities. In order to allow a holistic view, all waste streams were considered, including conventional industrial wastes to high-level wastes. The resulting output has mainly been used in identifying potential gaps in future storage requirements and disposition routes. It allows for the identification of the magnitude and the timing, if a gap is present. This information becomes a critical dataset to an Integrated Waste Strategy. Critical decisions regarding waste management can then be prioritized and scheduled. As the waste forecast is a living document, the existing information currently captured represents a baseline. To ensure quality management, future changes are to be documented through a change control process. Such changes can be from actual data or from updates to estimates through characterization, etc. As time progresses, comparisons between actual waste volumes versus forecasted volumes can then be used to further refine predictions on future waste generation. (authors)
- Research Organization:
- WM Symposia, Inc., PO Box 27646, 85285-7646 Tempe, AZ (United States)
- OSTI ID:
- 22975275
- Report Number(s):
- INIS-US--20-WM-18055
- Country of Publication:
- United States
- Language:
- English
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