Constructing Predictive Estimates for Worker Exposure to Radioactivity During Decommissioning: Analysis of Completed Decommissioning Projects

An analysis of completed decommissioning projects is used to construct predictive estimates for worker exposure to radioactivity during decommissioning activities. The preferred organizational method for the completed decommissioning project data is to divide the data by type of facility, whether decommissioning was performed on part of the facility or the complete facility, and the level of radiation within the facility prior to decommissioning (low, medium, or high). Additional data analysis shows that there is not a downward trend in worker exposure data over time. Also, the use of a standard estimate for worker exposure to radioactivity may be a best estimate for low complete storage, high partial storage, and medium reactor facilities; a conservative estimate for some low level of facility radiation facilities (reactor complete, research complete, pits/ponds, other), medium partial process facilities, and high complete research facilities; and an underestimate for the remaining facilities. Limited data are available to compare different decommissioning alternatives, so the available data are reported and no conclusions can been drawn. It is recommended that all DOE sites and the NRC use a similar method to document worker hours, worker exposure to radiation (person-rem), and standard industrial accidents, injuries, and deaths for all completed decommissioning activities

Coupled Biogeochemical Process Evaluation for Conceptualizing Trichloroethylene Co-Metabolism

Chlorinated solvent wastes (e.g., trichloroethene or TCE) often occur as diffuse subsurface plumes in complex geological environments where coupled processes must be understood in order to implement remediation strategies. Monitored natural attenuation (MNA) warrants study as a remediation technology because it minimizes worker and environment exposure to the wastes and because it costs less than other technologies. However, to be accepted MNA requires different ?lines of evidence? indicating that the wastes are effectively destroyed. We are studying the coupled biogeochemical processes that dictate the rate of TCE co-metabolism first in the medial zone (TCE concentration: 1,000 to 20,000 ?g/L) of a plume at the Idaho National Laboratory?s Test Area North (TAN) site and then at Paducah or the Savannah River Site. We will use flow-through in situ reactors (FTISR) to investigate the rate of methanotrophic co-metabolism of TCE and the coupling of the responsible biological processes with the dissolved methane flux and groundwater flow velocity. TCE co-metabolic rates at TAN are being assessed and interpreted in the context of enzyme activity, gene expression, and cellular inactivation related to intermediates of TCE co-metabolism. By determining the rate of TCE co-metabolism at different groundwater flow velocities, we will derive key modeling parameters for the computational simulations that describe the attenuation, and thereby refine such models while assessing the contribution of microbial co-metabolism relative to other natural attenuation processes. This research will strengthen our ability to forecast the viability of MNA at DOE and other sites contaminated with chlorinated hydrocarbons

A Framework for Making Sustainable Cleanup Decisions Using the KONVERGENCE Model

The effects of closure decisions for used nuclear facilities can extend centuries into the future. Yet, the longevity of decisions made over the past half century has been poor. Our goal is an improved decision framework for decommissioning, stewardship, and waste management. This paper describes our overall framework. Companion papers describe the underlying philosophy of the KONVERGENCE Model for Sustainable Decisions1 and implications for a class of intractable decision problems.2 Where knowledge, values, and resources converge (the K, V, and R in KONVERGENCE), you will find a sustainable decision – a decision that works over time. Our approach clarifies what is needed to make and keep decisions over relevant time periods. The process guides participants through establishing the real problem, understanding the universes of knowledge, values, resources, and generating alternatives. We explore three classes of alternatives – reusable (e.g. greenfield), closed (e.g. entombed structures), and adaptable. After testing for konvergence of alternatives among knowledge, values, resources, we offer suggestions to diagnose divergence, to reduce divergence by refining alternatives to address identified weaknesses, and to plan to keep konvergence over the life of the decision. We believe that decisions made via this method will better stand the test of time – because it will be either acceptable to keep them unchanged or possible to adapt them as knowledge, values, and resources change