Document ID: chunk:federal_register_of_legislation:F2013C00288:reg:6:p11
Version: federal_register_of_legislation:F2013C00288
Segment Type: reg
Provision Reference: reg 6 (pt 11/12)
Character Range: 1079416–1082491

although a number of usable methodologies are provided, it is unclear what level of detail is required to capture and communicate key uncertainties. A further comment is that quantitative methods suffer from the difficulty in sensibly quantifying all uncertainties, and that the apparent precision of quantitative analysis for some uncertainties may distract attention from other, possibly equally important but unquantifiable, uncertainties.

In most health risk assessments for contaminated land projects, it is unlikely that quantitative uncertainty analysis (for example, US EPA 2001) will provide value given the effort required to undertake it. A clear qualitative analysis is considered sufficient in most cases to provide the communication of the effects of uncertainty that is necessary.

Further discussion and guidance regarding uncertainty is provided in enHealth (2012a). A useful example of an uncertainty analysis table is also provided in enHealth (2012a). NRC (2008) and WHO (2008) provide useful guidance on the principles to be adopted for uncertainty analysis; these have been adapted for specific relevance to contaminated land risk assessment herein:
    * Risk assessments should provide qualitative (as a minimum) or quantitative description of uncertainty and variability consistent with available data. The information required to conduct detailed uncertainty analysis may not be available in many situations.
    * Sensitive populations should be considered to the extent that they are not covered by the selected toxicity criteria (generally they will be).
    * The uncertainty analysis should seek to communicate which uncertainties are most important to the conclusions of the risk assessment.
    * The level of detail of the uncertainty analysis should be commensurate with the scope of the risk assessment.
    * Uncertainty analysis should be expressed in terms that can be understood by the risk manager and other stakeholders.
    * Uncertainty and variability should be kept conceptually separate.
The combination of uncertainty in the scientific data and assumptions (the 'inputs') and inability to validate assessment results directly or to isolate and evaluate the impact of a resulting decision (the 'outputs') creates a situation in which decision-makers, the scientific community, the public, industry and other stakeholders have little choice but to rely on the overall quality of the many processes used in the conduct of risk assessment to provide some assurance that the assessment is aligned with societal goals (NRC 2008).

    6.6.2          Sensitivity analysis
Sensitivity analysis provides a quantitative estimate of the effect of uncertainty and/or variability in the input parameters on the results of the risk assessment.

Sensitivity analysis should be undertaken when a risk assessment is conducted using a deterministic exposure model. While a single value should be entered for each parameter in a deterministic model, it is unlikely that reasonable inputs for each parameter can be limited to a single value. This