Protocol for the Derivation of Environmental and Human ... - CCME

Section 6
Uncertainty in Guidelines Derivation
6.1 Sources
Developing environmental soil quality guidelines requires a model that estimates (predicts) a level in soil
considered to be acceptable for given land use exposure scenarios. The models employed in the
ecological portion of this protocol are predictive in nature. Predictions based on model input
parameters or mechanisms create aggregate uncertainties when the model is applied. In most regulatory
settings, it is desirable to assess qualitatively, if not quantitatively, the level of uncertainty attached to
these predictive models. This is done so that decision-makers understand the uncertainties associated
with the scientific data on which the decision was based (Suter, 1993).
A wide spectrum of methods can assess the uncertainty associated with model predictions. In general,
the major distinction between various approaches depends on whether the cause of concern is the
propagation of error by models (sensitivity analysis methods), or the causes of prediction uncertainty
(uncertainty or error analysis methods) (Summers et al., 1993). Suter (1993) describes three basic
sources of uncertainty in ecological risk assessment:
• the inherent randomness in the world (stochasticity),
• imperfect or incomplete knowledge of things that could be known (ignorance), and
• mistakes in execution of assessment activities (error).
Finally, there is uncertainty in model error concerning the relationship between measurement endpoints
used in guidelines derivation and the actual field population response or assessment endpoint. This
uncertainty can be expressed as variance in the proportion of species to be protected at the level of the
guideline and the confidence in that degree of protection (Suter, 1993).
6.2 Use Of Uncertainty Factors in Guidelines Derivation
Traditionally, the development of environmental quality standards or guidelines, has relied on the
application of uncertainty factors (UFs) (also referred to as safety factors) to a reference toxicological
value (e.g., LOEC, LC(D) 50 , EC 50 ) to arrive at a "safe" concentration that is extrapolated to field
conditions. Uncertainty factors account for various sources of uncertainty associated with the model
input parameters, model design, and to extrapolate to field conditions. It is important to note that, in the
beginning, the use of uncertainty factors to account for model error was intuitive rather than scientific
and it was stated emphatically that:
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