Comparison of Average Transport and Dispersion Among a Gaussian Model, a Two-Dimensional Model and a Three-Dimensional Model

摘要

The Nuclear Regulatory Commission's (NRC's) code for predicting off-site consequences, MACCS2[1] (MELCOR Accident Consequence Code System, Version 2), is used for Level 3 Probabilistic Risk Analysis Consequence analyses, planning for emergencies, and cost-benefit analyses. It uses a simplified model for atmospheric transport and dispersion (ATD), that is, a straight-line Gaussian model. This model has been criticized as being overly simplistic, even for its purpose. The justification for its use has been that only average or expected values of metrics of interest are needed for planning and that a simplified model, by averaging metrics of interest obtained using numerous weather sequences one-by-one, compensates for the loss of structure in the meteorology that occurs away from the point of release. The simple model has been retained because of the desire to have short running times on personal computers covering the entire path through the environment, including the food and water pathway, and covering essentially a lifetime of exposure to a contaminated environment. The assumption about the adequacy of averaging metrics of interest over numerous weather sequences has never been tested for the Nuclear Regulatory Commission's (NRC's) purposes. Because of an increased interest in Level-3 Probabilistic Risk Assessments (PRAs), testing of the assumption has been performed. The results from MACCS2, the simplified model; LODI[2] (Lagrangian Operational Dispersion Integrator), a state-of-the-art, 3-dimensional advection-diffusion code using a Lagrangian stochastic, Monte Carlo method; and RASCAL[4] (Radiological Assessment System for consequence analysis), which uses a Lagrangian trajectory, Gaussian puff model, have been compared. RASCAL is between MACCS2 and LODI in complexity. LODI is coupled to ADAPT[3] (Atmospheric Data Assimilation and Parameterization Technique), which provides fields of mean winds, turbulence, pressure, temperature, and precipitation based on observed or model-simulated meteorology. RASCAL uses meteorological fields generated by interpolation of surface data. The objective of this study is to see if the average ATD results from these three codes are sufficiently close that a more complex model is not required for the NRC purposes of planning and cost-benefit analysis or different enough that the NRC code should be modified to provide more rigorous ATD. It would be better if MACCS2 results could be compared with measurements over the long distances and types of terrain of interest to the NRC. However, such measurements do not exist, so the less desirable comparison with a state-of-the-art code was chosen to provide input into the decision on the adequacy of the MACCS2 ATD. Comparisons of LODI/ADAPT results with intentional and unintentional releases can be found in Foster, et al[5]. These comparisons, although over shorter ranges than those of interest to the NRC, demonstrate that LODI/ADAPT is sufficiently accurate for the purposes of this study.