INTEGRATING REACTIVE TRANSPORT, EXPOSURE, AND TOXIC POTENCY UNCERTAINTY WITH MONTE CARLO SIMULATION AND PARTITIONED MULTI-OBJECTIVE RISK MODELING

Quantifying human cancer risk arising from exposure to contaminated groundwater is particularly challenging because of the many hydrogeological, environmental, and toxicological uncertainties involved. In this study, we used Monte Carlo simulation to estimate cancer risk associated with tetrachloroethene (PCE) dissolved in groundwater by integrating three individual models for: (i) reactive transport; (ii) human exposure pathways; and (iii) the PCE cancer potency factor. The hydrogeologic model incorporates an analytical solution for a one-dimensional advective-dispersive-reactive transport equation to determine the PCE concentration in a water supply well located at a fixed distance from a continuous source. The pathway model addresses PCE exposure through ingestion, inhalation, and dermal contact. The toxicological model combines epidemiological data from eight published rodent bioassays for PCE exposure in the form of a composite cumulative distribution frequency curve of the human PCE cancer potency factor based on a linear multistage dose-response model.

We assessed the relative importance of individual model variables through their correlation with expected cancer risk calculated in 20,000 Monte Carlo simulations. For the scenario evaluated, three factors were most highly correlated with cancer risk: 1) the PCE decay constant in groundwater, 2) the cancer potency factor, and 3) the groundwater pore velocity. We then extended our analysis beyond conventional expected value risk assessment using the Partitioned Multiobjective Risk Method (PMRM) to generate expected-value functions conditional to a 1 in 100,000 increased cancer risk threshold. Rather than averaging all Monte Carlo results together, this approach accounts for potential low probability/high impact outcomes separately and can inform decision makers about the impact of decisions on worst-case scenarios. Using PMRM, we evaluated the cost-benefit relationship of implementing several hypothesized risk management alternatives intended to mitigate the expected and conditional cancer risk. Collectively, our results emphasize the importance of hydrogeologic models in risk assessment, but also illustrate the importance of integrating environmental and toxicological uncertainty.