Assessing complex policy problems such as those that are the target of integrated environmental health impact assessments inevitable involves major uncertainties.  Doing an assessment without considering these uncertainties is a pointless task; likewise, presenting the results of an assessment without giving information about the uncertainties involved makes the information more-or-less meaningless. Ideally, uncertainties are tracked and quantified throughout the execution phase in order to control them, and ensure that the assessment does not become too uncertain to be of value (see Managing uncertainties).  Without exception, they need to be evaluated by the end of the process and presented as part of the final assessment results.  

The dimensions of uncertainty

Uncertainties arise at every step in an assessment: from the initial formulation of the question to be addressed to the ultimate reporting and interpretation of the findings.  They also take many different forms, and are not always immediately obvious.  It is therefore helpful to apply a clear and consistent framework for identifying and classifying uncertainties, in order to ensure that key sources of uncertainty are not missed and that users can understand how they arise and what their implications might be.  In particular, it is useful to distinguish between three essential properties of uncertainty:

• location - where within the causal chain it arises
• nature - its source or cause and manner of representation 
• level - its magnitude or degree of importance

A link to a detailed explanation of this framework is given in the panel to left.

Describing uncertainties

Uncertainties can be described either quantitatively or qualitatively, and in each case using different metrics and methods.  Which is appropriate depends on the nature of the issue being assessed and the methods being used, as well as the purpose of the assessment.  In general, quantitative methods are more useful to enable comparisons between different policy options and inform decision-making; in some circumstances, however, qualitative methods may have to be used because of the limitations of the data. Many users may also find qualitative measures more easy to understand: often, therefore, both need to be presented. 

A link to some of the methods available for describing uncertainties is given in the panel to the left.