Risk assessment at hazardous waste-contaminated sites with variability of population characteristics

Q. Zhao
J. J. Kaluarachchi, Utah State University

Abstract

Risk assessment is considered to be an effective scientific tool which enables decisionmakers to manage hazardous waste-contaminated sites in a cost-effective manner while preserving public health. However, the current risk assessment framework proposed by the US Environmental Protection Agency (US EPA) has limitations in addressing the true variability of population characteristics. This study proposed a methodology that is different from the existing framework by accounting for the true variability of population characteristics. The key differences of the proposed methodology and the existing framework are the (1) use of the transient exposure concentration; (2) use of the entire population rather than a representative ideal individual; (3) use of age- and gender-based population subgroups to represent population characteristics; (4) use of a population growth model to represent growth dynamics; and (5) presentation of risk through a risk profile with risk summarized through a single indicator, potential cancer incidences (PCI). The proposed methodology was applied in a ground water contamination scenario due to benzene to determine its applicability. The results of the study showed that age-based variability of population characteristics is important in predicting the population risk while gender played a small role. The existing US EPA methodology and its variation using age-independent variability of population characteristics overestimate the risk given by PCI substantially, and therefore, the decisions can lead to costly cleanup goals. Population risk is not a single value but a distribution due to the contribution from ditferent individuals of the exposed population. Hence, the decision criterion proposed in this study, PCI, is found to be a useful indicator to describe population carcinogenic risk to the society under a variety of conditions and scenarios.