Risk‐based environmental remediation: Decision framework and role of uncertainty

Abstract

A methodology for incorporating uncertainty in model predictions into a risk‐based decision for environmental remediation is illustrated, considering polychlorinated biphenyl (PCB) sediment contamination and uptake by winter flounder in New Bedford Harbor, Massachusetts. Sensitivity and uncertainty analyses are conducted for a model that predicts the sediment remediation volume required to meet a biota tissue concentration criterion. These evaluations help to identify the variables that most significantly contribute to uncertainty in the model prediction and allow for calculations of the expected value of including uncertainty (EVIU) and the expected value of perfect information (EVPI) for the remediation decision. The EVIU is the difference between the expected loss of a management decision based solely on a deterministic analysis and the expected loss of the optimal management decision that considers uncertainty. For the illustrative application to New Bedford Harbor, the expected loss avoided from performing an uncertainty analysis and using the resulting information to make the optimal management decision is approximately $20 million. The EVPI, the expected decrease in loss that can be achieved by having all uncertainty eliminated, is approximately $16 million.

Uncertainty analysis, Value of information, Monte Carlo analysis, Risk analysis, New Bedford Harbor

Issue Section:

Annual Review