Quantifying uncertainty in environmental risk assessment
Environmental and human health risk assessments are frequently used to determine contaminated site clean-up levels and to predict possible health consequences. In fact, human health and environmental risk assessment knowledge have become increasingly important to most environmental professionals. The estimation of risk levels requires the estimation or assumption of several input variables. These variables include physical and chemical parameters in addition to receptor characteristics and land use classification. The risk assessment parameters and characteristics are typically variables that contain different levels of uncertainty. In order to make defensible decisions, it is necessary to have a clear knowledge of the inherent variability associated with these parameters. This knowledge, combined with statistical techniques and modern hardware and software, will enable the risk assessment professional to quantify the level of uncertainty associated with risk assessments. Such techniques include the use of Monte Carlo and Latin Hypercube simulations, which require the risk assessment professional to estimate shape, central tendency, and dispersion (probability distribution), appropriate for each variable. This process requires the risk assessment professional to treat every physical and chemical quantity or property as a random variable. One of the principal advantages of Monte Carlo and Latin Hypercube simulations is a far more realistic modeling of the risk estimate. The resulting analysis produces an output that is a probability distribution that allows the risk assessment professional to estimate the chances of exceeding or falling below acceptable critical values of risk. Thus, this result will permit a far more realistic estimate of the environmental and human health risks involved with levels of uncertainty associated with each. This paper will demonstrate the use of the Monte Carlo and Latin Hypercube uncertainty Propagation techniques to quantify the uncertainty in the estimated risk, and illustrate how to use the results to make effective and defensible decisions.
- Research Organization:
- Valparaiso Univ., IN (US)
- OSTI ID:
- 20014923
- Resource Relation:
- Conference: 1998 National Conference on Environmental Engineering, Chicago, IL (US), 06/07/1998--06/10/1998; Other Information: PBD: 1998; Related Information: In: Water resources and the urban environment--98, by Wilson, T.E. [ed.], 754 pages.
- Country of Publication:
- United States
- Language:
- English
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