Tier 1 qualitative uncertainty analysis

Examining the influence of the uncertainties in the key model variables (e.g. ranges of pollutant concentrations, differences in exposure durations, inhalation rates, body weights) that are used to predict high-end exposures of individuals. 

Identifying the key sources of uncertainties in food consumption rates and dietary residue data during a dietary exposure and risk analysis, and subsequently examining their respective influence on model predictions. 

Identifying and estimating the likely impact of key sources of uncertainties in conducting a 

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The framework included herein provides for both qualitative and quantitative approaches to uncertainty analysis. It includes a tiered approach to methods for uncertainty analysis, the... 

Because the objective of an exposure assessment is to characterize both the magnitude and the reliability of exposure scenarios, planning for an uncertainty analysis is a key element of an exposure assessment. The aims of the uncertainty analysis in this context are to individually and jointly characterize and quantify the exposure prediction uncertainties resulting from each step of the analysis. In performing an uncertainty analysis, typically the main sources of uncertainties are first characterized qualitatively and then quantified using a tiered approach (see chapter 4). In general, exposure uncertainty analyses attempt to differentiate between key sources of uncertainties scenario uncertainties, model uncertainties and parameter uncertainties (for definitions, see section 3.2). 

In this chapter, both qualitative and quantitative approaches for characterizing uncertainty are described. We illustrate how these approaches apply and provide insight on the different tiers of an uncertainty analysis. 

An uncertainty analysis gives the assessor the opportunity to re-evaluate the scenario, model approaches and parameters of the analysis and to consider their influence in the overall analysis. The practical impact of uncertainty analysis is illustrated within the annexed case-studies, which also clarify how uncertainty analyses follow a systematic methodology, based on a tiered approach, and consider all possible sources of uncertainty. The first step in uncertainty analysis consists of a screening, followed by a qualitative analysis and two levels of quantitative analysis, using deterministic and probabilistic data. The assessor should be aware that an uncertainty analysis cannot answer all the questions, which, moreover, may lead to new questions. 

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