Cost-effectiveness, cost–benefit analysis, and multiattribute utility analysis developed using statistical methods can be useful for assessing costs and benefits.
• When assessing model and parameter uncertainty:
Expert elicitation and the analysis of probability distributions, including extreme value analyses, can be useful for assessing health effects. Safety or default factors developed using expert judgments can also be helpful.
Formal expert elicitation to assess technology availability, as well as technology choice and risk analysis using expert judgment, can be helpful in assessing technology factors.
Cost-effectiveness, cost–benefit analysis, and multiattribute utility analysis developed using expert judgments can be useful for assessing costs and benefits.
• When assessing deep uncertainty:
Scenario analysis and robust decision-making methods can be helpful for assessing health effects, technology factors, and costs and benefits.
• The interpretation and incorporation of uncertainty into environmental decisions will depend on a number of characteristics of the risks and the decision. Those characteristics include the distribution of the risks, the decision makers’ risk aversion, and the potential consequences of the decision.
• The quality of the analysis and recommendations following from the analysis will depend on the relationship between analyst and the decision maker. The planning, conduct, and results of uncertainty analysis should not be isolated from the individuals who will eventually make the decisions. The success of a decision in the face of uncertainty depends on the analysts having a good understanding of the context of the decision and the information needed by the decision makers, and the decision makers having a good understanding of the evidence on which the decision is based, including an understanding of the uncertainty in that evidence.
Although some analysis and description of uncertainty is always important, how many and what types of uncertainty analyses are carried out should depend on the specific decision problem at hand. The effort to analyze specific uncertainties through probabilistic risk assessment or quantitative uncertainty analysis should be guided by the ability of those analyses to affect the environmental decision.