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Stochastic Model for Estimating Personal Exposures in Contaminated Buildings at Superfund Sites

Conference ·
OSTI ID:5639217
 [1];  [1];  [2];  [2];  [2]
  1. Argonne National Laboratory (ANL), Argonne, IL (United States)
  2. Harvard Univ., Cambridge, MA (United States)
A hazardous waste site can pose threats to human health via transport of on-site contaminants through environmental media to human receptors. The US Environmental Protection Agency (EPA) has developed a framework for assessing these potential threats in order to support Superfund cleanup decisions on the basis of risk. Cleanup activities are currently being conducted by the US Department of Energy (DOE) at a contaminated site consisting of a chemical plant area that has been inactive for more than 20 years and a noncontiguous quarry that was used for waste disposal. An integral part of the CERCLA/NEPA process is the preparation of a comprehensive baseline assessment of human health and environmental impacts to support decision making for site cleanup. This paper focuses on one component of the baseline assessment prepared for the site in order to highlight the potential effects on exposure estimates that result from varying the exposure assumptions. This component is the characterization of human health risks associated with potential exposure to PCBs in one of the contaminated buildings. Because of the heterogeneous nature of the PCB contamination, a stochastic approach was used to account for the variability in possible exposures. This paper describes the mathematical model that was used to quantify human exposures and risks associated with ingestion, inhalation, and dermal absorption of PCBs in air, dust, and spills on floors and benches in the building. The model explicitly accounts for contaminant heterogeneity and simulates the movement of a person through several microenvironments within the building.
Research Organization:
Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE Office of Environmental Management (EM)
DOE Contract Number:
W-31109-ENG-38
OSTI ID:
5639217
Report Number(s):
ANL/CP--71887; CONF-910659--26; ON: DE91014019
Country of Publication:
United States
Language:
English