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An Overview of a Multimedia Benchmarking Analysis for Three Risk Assessment Models: RESRAD, MMSOILS, and MEPAS
Authors:Gerard F Laniak  James G Droppo  Ernest R Faillace  Emmanuel K Gnanapragasam  William B Mills  Dennis L Strenge  Gene Whelan  Charley Yu
Institution:United States Environmental Protection Agency, Office of Research &Development, Ecosystem Research Division, 960 College Station Road, Athens, Georgia 30605.;Pacific Northwest National Laboratory, Richland, Washington.;Argonne National Laboratory, Argonne, Illinois.;Tetra Tech, Inc., Lafayette, California.
Abstract:Multimedia modelers from the United States Environmental Protection Agency (EPA) and the United States Department of Energy (DOE) collaborated to conduct a detailed and quantitative benchmarking analysis of three multimedia models. The three models—RESRAD (DOE), MMSOILS (EPA), and MEPAS (DOE)—represent analytically-based tools that are used by the respective agencies for performing human exposure and health risk assessments. The study is performed by individuals who participate directly in the ongoing design, development, and application of the models. Model form and function are compared by applying the models to a series of hypothetical problems, first isolating individual modules (e.g., atmospheric, surface water, groundwater) and then simulating multimedia-based risk resulting from contaminant release from a single source to multiple environmental media. Study results show that the models differ with respect to environmental processes included (i.e., model features) and the mathematical formulation and assumptions related to the implementation of solutions. Depending on the application, numerical estimates resulting from the models may vary over several orders-of-magnitude. On the other hand, two or more differences may offset each other such that model predictions are virtually equal. The conclusion from these results is that multimedia models are complex due to the integration of the many components of a risk assessment and this complexity must be fully appreciated during each step of the modeling process (i.e., model selection, problem conceptualization, model application, and interpretation of results).
Keywords:Benchmarking  model comparison  multimedia modeling  and multipathway analysis
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