Uncertainty Analysis 



Sources of Uncertainty 



incidence when data are available only from less-than-lifetime 

 experiments) 



• For carcinogens, average doses are an appropriate measure of 

 exposure dose, even if dose rates vary over time 



• In the absence of pharmacokinetic data, the effective (or target 

 organ) dose is assumed to be proportional to the administered 

 dose 



• Risks from multiple exposures in time are additive 



• For each chemical, the absorption efficiency of humans is equal 

 to that of the experimental cmimal 



• If available, human data are preferable to animal data for risk 

 estimation 



• For chemical mixtures, risks for individual chemicals are addi- 

 tive. However, the total sum of individual chemical risks is not 

 necessarily the total risk associated with ingestion of con- 

 taminated fish or shellfish because some important toxic com- 

 pounds may not have been identified and quantified. 



Uncertainty analysis is an integral part of risk assessment. The EPA 

 guidelines on exposure assessment describe general approaches for 

 characterizing uncertainty (U.S. EPA 1986b). Methods for uncertainty 

 analysis are discussed by Cox and Baybutt (1981), Morgan (1984), and 

 Whitmore (1985). A detailed discussion of procedures is beyond the 

 scope of the present effort. General approaches to uncertainty analysis 

 will be described briefly after a discussion of sources of uncertainty. 



Uncertainties in the risk assessment approach presented in this manual 

 arise from the following factors: 



1. Uncertainties in the determination of the weight-of-evidence 

 classification for potential carcinogens. 



2. Uncertainties in estimating Carcinogenic Potency Factors or 

 RfDs, resulting from: 



• Uncertainties in extrapolating toxicologic data obtained 

 from laboratory animals to humans 



• Limitations in quality of animal study 



• Uncertainties in high- to low-dose extrapolation of bioas- 

 say test results, which arise from practical limitations of 

 laboratory experiments and variations in extrapolation 

 models 



3. Variance of sitespecific consumption rates and contaminant 

 concentrations 



4. Uncertainties in the selection of 6.5 g/day, 20 g/day, and 165 

 g/day as assumed consumption rates when site-specific data are 

 not available 



5. Uncertainties in the efficiency of assimilation (or absorption) 

 of contaminants by the human gastrointestinal system (assumed 



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