Pathway: A Dynamic Food-chain Model to Predict Radionuclide Ingestion After Fallout Deposition

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This manuscript describes the structure and basis for parameter values of a computerized food-chain transport model for radionuclides. The model, called “PATHWAY,” estimates the time-integrated ingestion intake by humans of 20 radionuclides after a single deposition from the atmosphere to the landscape. The model solves a set of linear, coupled differential equations to estimate the inventories and concentrations of radionuclides in soil, vegetation, animal tissues and animal products as a function of time following deposition. Dynamic processes in the model include foliar interception, weathering and absorption; plant growth, uptake, harvest and senescence; soil resuspension, percolation, leaching and tillage; radioactive decay; and livestock ingestion, absorption and excretion. Human dietary data are included to permit calculation of time-dependent radionuclide ingestion rates, which are then numerically integrated. The model considers seasonal changes in the biomass of vegetation and animal diets, as well as specific plowing and crop-harvest dates; thus the integrated radionuclide intakes by humans are dependent on the seasonal timing of deposition. The agricultural data base represents the arid and semi-arid regions of the western United States. The foliar deposition parameters apply to regional fallout out to a few hundred miles from nuclear detonations at the Nevada Test Site. With modification, the model could be applied to chronic or other acute releases, providing the ground deposition in Bq m−2 could be estimated. The output of PATHWAY (Bq ingested per Bq m−2 deposited) may be multiplied by the deposition and a dose conversion factor (Gy Bq−1) to yield an organ-specific dose estimate. The model may be run deterministically to yield single estimates or stochastically (“Monte-Carlo” mode) to provide distributional output that reflects uncertainty in the output due to uncertainty in parameters. Tests of the predictive accuracy are briefly described and work published to date on validation trials is cited.

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