Stochastic environmental risk assessment considers the effects of numerous biological, chemical, physical, behavioral and physiological processes that involve elements of uncertainty and variability.
A methodology for predicting health risks to individuals from contaminated groundwater is presented that incorporates the elements of uncertainty and variability in geological heterogeneity, physiological exposure parameters, and in cancer potency.
An idealized groundwater basin is used to perform a parametric sensitivity study to assess the relative impact of (a) geologic uncertainty, (b) behavioral and physiological variability in human exposure and (c) uncertainty in cancer potency on the prediction of increased cancer risk to individuals in a population exposed to contaminants in household water supplied from groundwater.
A two-dimensional distribution (or surface) of human health risk was generated as a result of the simulations.
Cuts in this surface (fractiles of variability and percentiles of uncertainty) are then used as a measure of relative importance of various model components on total uncertainty and variability.
A case study for perchloroethylene or PCE, shows that uncertainty and variability in hydraulic conductivity play an important role in predicting human health risk that is on the same order of influence as uncertainty of cancer potenc.
Mots-clés Pascal : Tumeur maligne, Contamination, Eau potable, Pollution, Eau souterraine, Prédiction, Toxicité, Homme, Risque, Analyse risque, Carcinogène, Méthode étude, Analyse stochastique, Eau distribution, Incertitude, Géologie
Mots-clés Pascal anglais : Malignant tumor, Contamination, Drinking water, Pollution, Ground water, Prediction, Toxicity, Human, Risk, Risk analysis, Carcinogen, Investigation method, Stochastic analysis, Tap water, Uncertainty, Geology
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 99-0289127
Code Inist : 002B04B. Création : 16/11/1999.