Principles of Good Practice for the Use of Monte Carlo Techniques in Human Health and Ecological Risk Assessments

Abstract

We propose 14 principles of good practice to assist people in performing and reviewing probabilistic or Monte Carlo risk assessments, especially in the context of the federal and state statutes concerning chemicals in the environment. Monte Carlo risk assessments for hazardous waste sites that follow these principles will be easier to understand, will explicitly distinguish assumptions from data, and will consider and quantify effects that could otherwise lead to misinterpretation of the results. The proposed principles are neither mutually exclusive nor collectively exhaustive. We think and hope that these principles will evolve as new ideas arise and come into practice.

Uncertainty and variability in environmental life-cycle assessment

“…To save time and money in collecting data for defining density distributions, only the most important parameters are to be considered in detail (Burmaster and Anderson, 1994;USEPA, 1997a). Those parameters were identified by a preliminary uncertainty importance analysis.…”

Military Ecological Risk Assessment Framework (MERAF) for Assessment of Risks of Military Training and Testing to Natural Resources

“…Body weights, feeding rates, and water consumption rates, for example, are all highly correlated. If correlations are believed to occur but cannot be estimated from available data, perform Monte Carlo simulations with correlations set to zero and set to high, but plausible, values to determine their importance and presence (Burmaster and Anderson 1994).…”

“…If the expert judgments of individuals are used to derive distributions, any information or logic that went into the judgment should be described as fully as possible. Burmaster and Anderson (1994) indicate that a typical justification for a distribution would require five to ten pages.…”

Guidance for treatment of variability and uncertainty in ecological risk assessments of contaminated sites

“…These exposures are estimated through the use of simple mathematical models that are subject to Monte Carlo analysis . The reader is referred to the many guidance documents for probabilistic analysis in risk assessment concerned with this sort of analysis (Burmaster and Anderson 1994;Hammonds et al 1994;Hansen 1997;Risk Assessment Forum 1997).…”

“…Fourteen principles of good practice for Monte Carlo analyses proposed by Burmaster and Anderson (1994) are often cited and reproduced (Risk Assessment Forum 1996). They are all reasonable and sound but are seldom implemented.…”