Use of Monte Carlo Simulation for Human Exposure Assessment at a Superfund Site

TLDR

The study compares probabilistic and deterministic health risk estimates for an industrial Superfund site in the northeastern United States. The authors assessed volatile solvent exposure through drinking water and showering, using probability densities for concentrations, contact rates, and exposure frequencies, and calculated deterministic risks via the EPA’s reasonable maximum exposure (RME) method. The probabilistic and deterministic estimates were consistent, the EPA RME approach was protective, and Monte Carlo software successfully generated the required risk estimates.

Abstract

This work presents a comparison of probabilistic and deterministic health risk estimates based on data from an industrial site in the northeastern United States. The risk assessment considered exposures to volatile solvents by drinking water ingestion and showering. Probability densities used as inputs included concentrations, contact rates, and exposure frequencies; dose‐response inputs were single values. Deterministic risk estimates were calculated by the “reasonable maximum exposure” (RME) approach recommended by the EPA Superfund program. The RME non‐carcinogenic risk fell between the 90th and the 95th percentile of the probability density; the RME cancer risk fell between the 95th percentile and the maximum. These results suggest that in this case (1) EPA's deterministic RME risk was reasonably protective, (2) results of probabilistic and deterministic calculations were consistent, and (3) commercially available software Monte Carlo software effectively provided multiple risk estimates recommended by recent EPA guidance.