Monte Carlo Simulation Techniques:

            Human health risk assessment often has been dominated by the use of default assumptions and "worst-case" analyses. These are based on the upper bounds on the dose from exposure, deterministic (non-probabilistic) instead of distributional (probabilistic) characterizations of the dose. The National Academy of Sciences, Environmental Protection Agency, and others have recognized the need for new risk assessment methodology, which uses probabilistic techniques, Monte Carlo simulation, and distributional characterizations of dose-response, exposure, and risk.  Sielken & Associates has applied these state-of-the-art concepts to real-world situations.

            In the same way that a calculator can be used to evaluate an equation when each component of the equation is constant, Monte Carlo simulation can be used to evaluate an equation when some of the components are random variables instead of constants.

            The Monte Carlo techniques used by Sielken & Associates can simulate exposures according to any user-specified exposure equation or model and any exposure input parameter probability distributions. Thus, Sielken & Associates can estimate the likelihood of different exposures for an individual or the distribution of exposures in a population possibly involving multiple subpopulations.

            Other Sielken & Associates applications of Monte Carlo simulation techniques include ecological endangerment assessments and quantitative evaluation of the performance of proposed or alternative analytical techniques (e.g., sampling designs, estimation methods, combinations of literature and field data, fate and transport models, and alternative methods of aggregating and/or cumulating risks).