title: Monte Carlo techniques for quantitative uncertainty analysis in public health risk assessments.
abstract: Most public health risk assessments assume and combine a series of average, conservative, and worst-case values to derive a conservative point estimate of risk. This procedure has major limitations. This paper demonstrates a new methodology for extended uncertainty analyses in public health risk assessments using Monte Carlo techniques. The extended method begins as do some conventional methods--with the preparation of a spreadsheet to estimate exposure and risk. This method, however, continues by modeling key inputs as random variables described by probability density functions (PDFs). Overall, the technique provides a quantitative way to estimate the probability distributions for exposure and health risks within the validity of the model used. As an example, this paper presents a simplified case study for children playing in soils contaminated with benzene and benzo(a)pyrene (BaP).
authors.affiliation: Alceon Corporation, Cambridge, Massachusetts 02238.
authors.forename: K M
authors.initials: KM
authors.lastname: Thompson
authors.forename: D E
authors.initials: DE
authors.lastname: Burmaster
authors.forename: E A
authors.initials: EA
authors.lastname: Crouch
mesh_terms: D002274:Carcinogens, Environmental / Q000009:adverse effects; D006256:Hazardous Waste / Q000009:adverse effects; D006801:Humans; D009010:Monte Carlo Method; D009369:Neoplasms / Q000453:epidemiology / Q000209:etiology; D011634:Public Health / Q000706:statistics & numerical data*; D012306:Risk
chemical_list: D002274:Carcinogens, Environmental; D006256:Hazardous Waste