Application of quantitative uncertainty analysis for human health risk assessment at Rocky Flats

The characterization of uncertainty is an important component of the risk assessment process. According to the U.S. Environmental Protection Agency's (EPA's) open-quotes Guidance on Risk Characterization for Risk Managers and Risk Assessors,close quotes point estimates of risk open-quotes do not fully convey the range of information considered and used in developing the assessment.close quotes Furthermore, the guidance states that the Monte Carlo simulation may be used to estimate descriptive risk percentiles. To provide information about the uncertainties associated with the reasonable maximum exposure (RME) estimate and the relation of the RME to other percentiles of the risk distribution for Operable Unit 1 (OU-1) at Rocky Flats, uncertainties were identified and quantitatively evaluated. Monte Carlo simulation is a technique that can be used to provide a probability function of estimated risk using random values of exposure factors and toxicity values in an exposure scenario. The Monte Carlo simulation involves assigning a joint probability distribution to the input variables (i.e., exposure factors) of an exposure scenario. Next, a large number of independent samples from the assigned joint distribution are taken and the corresponding outputs calculated. Methods of statistical inference are used to estimate, from the output sample, some parameters of the output distribution, such as percentiles and the expected value