Alceon has pioneered the use of Monte Carlo simulations and other probabilistic techniques in human health risk assessments. These techniques overcome important limitations in older, deterministic risk assessment methods. Deterministic risk assessments combine a set of average, conservative, high, and worst-case assumptions to derive "conservative" point estimates for exposure and risk. The major drawback of this approach is that no one can say how conservative these estimates are. Risk managers have no way of knowing if the estimated risk represents the 90th, 99th, 99.99th, or some higher percentile of risk.
In the Monte Carlo method -- now 50 years old and widely used throughout science and engineering -- input variables are treated as random variables described by probability distributions (i.e., not as point values). With appropriate precautions to consider correlations, dependencies, and other pitfalls, Monte Carlo techniques give risk assessors the proper tools to estimate full distributions of risks in a population and, as appropriate, full distributions for cleanup targets (acceptable exposure point concentrations).
Alceon staff members have:
Since publishing its exposure assessment guidelines in 1992, the US Environmental Protection Agency has repeatedly recognized the validity and power of Monte Carlo techniques in refining human health risk assessments. Several of the Agency's regional offices and leading states (MA, CA) now accept probabilistic techniques in risk assessments. As Monte Carlo techniques become the tool of choice in risk assessment, Alceon will work closely with private and public clients to apply these techniques and to provide formal estimation of distributions needed for such assessments.