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

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  • Roy L. Smith

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.

Suggested Citation

  • Roy L. Smith, 1994. "Use of Monte Carlo Simulation for Human Exposure Assessment at a Superfund Site," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 433-439, August.
    • Handle: RePEc:wly:riskan:v:14:y:1994:i:4:p:433-439
    DOI: 10.1111/j.1539-6924.1994.tb00261.x
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    References listed on IDEAS

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    1. Andrew E. Smith & P. Barry Ryan & John S. Evans, 1992. "The Effect of Neglecting Correlations When Propagating Uncertainty and Estimating the Population Distribution of Risk," Risk Analysis, John Wiley & Sons, vol. 12(4), pages 467-474, December.
    2. Ann M. Roseberry & David E. Burmaster, 1992. "Lognormal Distributions for Water Intake by Children and Adults," Risk Analysis, John Wiley & Sons, vol. 12(1), pages 99-104, March.
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    2. Charles N. Haas, 1997. "Importance of Distributional Form in Characterizing Inputs to Monte Carlo Risk Assessments," Risk Analysis, John Wiley & Sons, vol. 17(1), pages 107-113, February.
    3. Qin, X.S. & Huang, G.H. & Zeng, G.M. & Chakma, A. & Huang, Y.F., 2007. "An interval-parameter fuzzy nonlinear optimization model for stream water quality management under uncertainty," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1331-1357, August.
    4. Martí Nadal & Vikas Kumar & Marta Schuhmacher & José L. Domingo, 2008. "Applicability of a Neuroprobabilistic Integral Risk Index for the Environmental Management of Polluted Areas: A Case Study," Risk Analysis, John Wiley & Sons, vol. 28(2), pages 271-286, April.
    5. Arkadiy Larionov & Ekaterina Nezhnikova & Elena Smirnova, 2021. "Risk Assessment Models to Improve Environmental Safety in the Field of the Economy and Organization of Construction: A Case Study of Russia," Sustainability, MDPI, vol. 13(24), pages 1-37, December.
    6. Viscusi, W. Kip & Hamilton, James T. & Dockins, P. Christen, 1997. "Conservative versus Mean Risk Assessments: Implications for Superfund Policies," Journal of Environmental Economics and Management, Elsevier, vol. 34(3), pages 187-206, November.
    7. Guido Sassi & Bernardo Ruggeri, 2008. "Uncertainty Evaluation of Human Risk Analysis (HRA) of Chemicals by Multiple Exposure Routes," Risk Analysis, John Wiley & Sons, vol. 28(5), pages 1343-1356, October.
    8. Allison C. Reilly & Andrea Staid & Michael Gao & Seth D. Guikema, 2016. "Tutorial: Parallel Computing of Simulation Models for Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 36(10), pages 1844-1854, October.
    9. Maged M. Hamed, 1997. "First‐Order Reliability Analysis of Public Health Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 17(2), pages 177-185, April.
    10. Tanu Altomare & Patrick M. Tarwater & Alesia C. Ferguson & Helena M. Solo-Gabriele & Kristina D. Mena, 2020. "Estimating Health Risks to Children Associated with Recreational Play on Oil Spill-Contaminated Beaches," IJERPH, MDPI, vol. 18(1), pages 1-10, December.

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