Uncertain numbers and uncertainty in the selection of input
distributions – Consequences for a probabilistic risk assessment of
contaminated land
Sander, P., Bergbäck, B., Öberg, T.
Risk Analysis 26, 1363-1375 (2006)
Abstract
Risks from exposure to contaminated land are often assessed with the aid of
mathematical models. The current probabilistic approach is a considerable
improvement on previous deterministic risk assessment practices, in that it
attempts to characterize uncertainty and variability. However, some inputs
continue to be assigned as precise numbers, while others are characterized as
precise probability distributions. Such precision is hard to justify, and we
show in this article how rounding errors and distribution assumptions can affect
an exposure assessment. The outcome of traditional deterministic point estimates
and Monte Carlo simulations were compared to probability bounds analyses.
Assigning all scalars as imprecise numbers (intervals prescribed by significant
digits) added uncertainty to the deterministic point estimate of about one order
of magnitude. Similarly, representing probability distributions as probability
boxes added several orders of magnitude to the uncertainty of the probabilistic
estimate. This indicates that the size of the uncertainty in such assessments is
actually much greater than currently reported. The article suggests that full
disclosure of the uncertainty may facilitate decision making in opening up a
negotiation window. In the risk analysis process, it is also an ethical
obligation to clarify the boundary between the scientific and social domains.
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