Document ID: chunk:federal_register_of_legislation:F2013C00288:reg:2:p9
Version: federal_register_of_legislation:F2013C00288
Segment Type: reg
Provision Reference: reg 2 (pt 9/9)
Character Range: 918084–920406

this approach is that it is simple and easily understood. Its potential disadvantage is that selection of many point estimates at the upper end of their likely ranges leads to compounding of the uncertainty. Sensitivity and uncertainty analysis are used to overcome this disadvantage and provide increased understanding and clarity on which values are risk-driving; this is itself a useful part of the risk assessment.

Probabilistic techniques can be used to overcome the potential for compounding conservatism and may provide increased understanding of the uncertainty inherent in the assessment results. Monte Carlo analysis and other probabilistic statistical techniques rely on the use of probability distribution functions instead of point estimates to represent the values of variables. A probabilistic exposure model is run over several thousand iterations, and values for each parameter are selected randomly from each distribution at each iteration. The output is also expressed as a probability distribution function.

The advantage of probabilistic methods is that it becomes possible to express the range of potential exposure and risk outcomes. This can aid decision-making by increasing the level of understanding around how likely different risk outcomes may be. The disadvantage is that in order to generate meaningful output, a high level of data and information on the shape of the probability distribution inputs is required. Often this information is not available, and in this case incorrect selection of a probability distribution can introduce error. Some variables are linked (for example, body weight and skin surface area) and if not carefully constructed, probabilistic models may be capable of generating some results that are physically impossible. Another disadvantage of probabilistic risk assessments is the difficulty in explaining this complex approach to the stakeholders who are involved in a site.

In summary, probabilistic techniques are generally not practicable for the majority of assessments at Tier 2, on the basis that there is often insufficient data to support the method. When probabilistic techniques are used, the justification for the probability distribution functions selected as inputs should be clearly given, and dependent variables should be identified and linked.