UNCERTAINTY AND SENSITIVITY ANALYSIS OF EARLY EXPOSURE RESULTS WITH THE MACCS REACTOR ACCIDENT CONSEQUENCE MODEL

Uncertainty and sensitivity analysis techniques based on Latin hypercu be sampling, partial correlation analysis and stepwise regression anal ysis are used in an investigation with the MACCS model of the early he alth effects associated with a severe accident at a nuclear power stat ion. The primary purpose of this study is to provide guidance on the v ariables to be considered in future review work to reduce the uncertai nty in the important variables used in the calculation of reactor acci dent consequences. The effects of 34 imprecisely-known input variables on the following reactor accident consequences are studied: Dumber of early fatalities, number of cases prodromal vomiting, population dose within 10 mi of the reactor, population dose within 1000 mi of the re actor, individual early fatality probability within 1 mi of the reacto r, and maximum early fatality distance. When the predicted variables a re considered collectively, the following input variables were found t o be the dominant contributors to uncertainty: scaling factor for hori zontal dispersion, dry deposition velocity, inhalation protection fact or for nonevacuees, ground-shine shielding factor for nonevacuees, ear ly fatality hazard function alpha value for bone marrow exposure, and scaling factor for vertical dispersion.