Human and Ecological Risk Assessment - Earthjustice

Section 4.0Risk CharacterizationWaterbodies Intercepting the Groundwater Plume. As discussed in Section 3.7, massis not actually removed from the groundwater when the plume is intercepted by a surfacewaterbody. Therefore, in cases where wells are located beyond an intersecting surface waterbody, the draft risk assessment may not account for interactions between surface water andgroundwater. Examining the input database, EPA notes that approximately two-thirds (69%) ofthe Monte Carlo runs contained such an intersecting surface waterbody. Thus, the 50th percentileresults may overestimate groundwater risks to these receptors. However, because the WMUswith closer receptor wells exhibited higher risks on average, the 90th percentile results are notlikely to be significantly affected.Environmental Parameters. Uncertainties related to environmental parameters (soil,aquifer, surface water, climate data) have already been mentioned. The parameters with thelargest impact on results are aquifer hydraulic conductivity and gradient, which were selectedfrom a national database of aquifer properties.Fish Bioconcentration and Bioaccumulation Factors. For fish consumption, exposuredose was calculated using BCFs to estimate the transfer of pollutants from environmental mediainto fish. Uncertainty is associated with models used to estimate BCFs for aquatic biota. AquaticBCFs are developed by dividing measured concentrations in aquatic biota by total surface waterconcentrations. Appendix J lists the bioconcentration and bioaccumulation parameters used inthe risk assessment, along with their sources.4.4.3.4 Exposure and Risk Modeling VariablesExposure parameters and benchmarks for human and ecological risk also contribute toparameter variability and uncertainty.Human Exposure Factors. Individual physical characteristics, activities, and behaviorare quite different, and thus the exposure factors that influence the exposure of an individual,including ingestion rate, body weight, and exposure duration, are quite variable. Exposuremodeling relies heavily on default assumptions concerning population activity patterns, mobility,dietary habits, body weights, and other factors. The probabilistic assessment for the adult andchild exposure scenario addressed the possible variability in the exposure modeling by usingstatistical distributions for these variables for each receptor in the assessment: adult and childresident and adult and child recreational fisher. Data on fish consumption rates were notavailable for children of recreational anglers; thus the adult recreational angler data were usedfor children in this analysis, which could overestimate risk from this pathway for children. Forall exposure factors varied, a single exposure factor distribution was used for adults for bothmales and females. For child exposures, one age (age 1) was used to represent the age at the startof exposure, because this age group was considered to be most sensitive for most health effects.The Exposure Factors Handbook (U.S. EPA, 1997c,d,e) provides the current state of thescience concerning exposure assumptions and represents EPA’s current guidance on exposuredata, and it was used throughout this assessment to establish statistical distributions of values foreach exposure parameter for each receptor. The Exposure Factors Handbook has been carefullyreviewed and evaluated for quality. EPA’s evaluation criteria included peer review,reproducibility, pertinence to the United States, currency, adequacy of the data collection period,April 2010–Draft EPA document. 4-53