ANNEX 2 CASE-STUDY—QUANTITATIVE UNCERTAINTY ANALYSIS

ANNEX 2 CASE-STUDY—QUANTITATIVE UNCERTAINTY ANALYSIS 

This is an example exposure assessment that illustrates quantitative representations of uncertainty and variability at the higher tiers of an exposure assessment. This case-study is based on human exposures to a persistent, bioaccumulative and lipid-soluble compound through fish consumption. This compound is fictional and referred to here as PBLx, but it has properties that correspond to those of known persistent compounds. Specific goals of this case-study are to illustrate (1) the types of uncertainty and variability that arise in exposure assessments, (2) quantitative uncertainty assessment, (3) how distributions are established to represent variability and uncertainty, (4) differences among alternative variance propagation methods, (5) how to distinguish uncertainty from variability and (6) how to communicate the results of an uncertainty analysis. 

The overall process of characterizing the exposure scenario along with the magnitude, variability and uncertainty of a specific exposure includes the following steps  

Uncertainty analysis and sensitivity analysis are tools that provide insight on how model predictions are affected by data precision. One of the issues in uncertainty analysis that must be confronted is how to rank both individual inputs and groups of inputs according to their contribution to overall uncertainty. In particular, there is a need to distinguish between the relative contribution of true uncertainty versus variability (i.e. heterogeneity), as well as to distinguish model uncertainty from parameter uncertainty. This case-study illustrates methods of uncertainty representation and variance characterization. 

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ANNEX 2 CASE-STUDY—QUANTITATIVE 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. 

Each chapter builds on the previous ones, and so chapters should be read in the order given to ensure complete understanding of the text. A glossary of terms is provided at the end of the chapters, followed by two annexes with case-studies to illustrate both qualitative (Annex 1) and quantitative (Annex 2) uncertainty analysis. 

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