title: A systematic uncertainty analysis of an evaluative fate and exposure model.
abstract: Multimedia fate and exposure models are widely used to regulate the release of toxic chemicals, to set cleanup standards for contaminated sites, and to evaluate emissions in life-cycle assessment. CalTOX, one of these models, is used to calculate the potential dose, an outcome that is combined with the toxicity of the chemical to determine the Human Toxicity Potential (HTP), used to aggregate and compare emissions. The comprehensive assessment of the uncertainty in the potential dose calculation in this article serves to provide the information necessary to evaluate the reliability of decisions based on the HTP A framework for uncertainty analysis in multimedia risk assessment is proposed and evaluated with four types of uncertainty. Parameter uncertainty is assessed through Monte Carlo analysis. The variability in landscape parameters is assessed through a comparison of potential dose calculations for different regions in the United States. Decision rule uncertainty is explored through a comparison of the HTP values under open and closed system boundaries. Model uncertainty is evaluated through two case studies, one using alternative formulations for calculating the plant concentration and the other testing the steady state assumption for wet deposition. This investigation shows that steady state conditions for the removal of chemicals from the atmosphere are not appropriate and result in an underestimate of the potential dose for 25% of the 336 chemicals evaluated.
authors.affiliation: Energy and Resources Group, University of California at Berkeley, USA. hertwich@design.ntnu.no
authors.forename: E G
authors.initials: EG
authors.lastname: Hertwich
authors.forename: T E
authors.initials: TE
authors.lastname: McKone
authors.forename: W S
authors.initials: WS
authors.lastname: Pease
mesh_terms: D000393:Air Pollutants / Q000633:toxicity*; D002980:Climate; D003661:Decision Support Techniques; D004305:Dose-Response Relationship, Drug; D004777:Environment; D006801:Humans; D016014:Linear Models; D008954:Models, Biological; D009010:Monte Carlo Method; D010944:Plants; D011336:Probability; D011891:Rain; D018570:Risk Assessment; D012989:Soil Pollutants / Q000633:toxicity; D013269:Stochastic Processes; D014481:United States; D014873:Water Pollutants / Q000633:toxicity
chemical_list: D000393:Air Pollutants; D012989:Soil Pollutants; D014873:Water Pollutants