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(60-03) An integrated exposure and effects model for probabilstic risk assessment. Gallagher, Kathryn*,1, Lin, James1, Young, Dirk1, Farrar, David1, Barry, Timothy2, Kennedy, Ian1, Bargar, Tim1, Burns, Lawrence3, Sunzenauer, Ingrid1, 1 US Environmental Protection Agency, Washington, DC2 US Environmental Protection Agency, Washington, DC3 US Environmental Protection Agency, Athens, GA ABSTRACT- For several years, the EPA's Office of Pesticide Programs has been working towards a new tiered process for conducting ecological risk assessments for pesticides, to be used under the FIFRA regulatory framework. This approach will include probabilistic tools and methods at the levels beyond the initial screening-level assessment, to provide information regarding the probability and magnitude of potential effects. A pilot model for the preliminary probabilistic analyses was released to the public in March of 2001. Since that time, the Agency has been working towards developing a user-friendly, self-contained model for conducting preliminary probabilistic risk assessments, eliminating the earlier model's need to use multiple external programs to conduct exposure and effects analyses. The newer model described here permits the user to easily conduct an exposure simulation, using an exposure module based on an abbreviated version of the Agency's PRZM/EXAMS model. The exposure module has the capability to use distributions of selected input parameters, and provides an output of predictions of pond concentrations and associated uncertainty. Inherent in the model is also a toxicity data analysis module. The effects and exposure data are integrated using Monte Carlo methods in the probabilistic risk estimate module, yielding estimates of the probability and magnitude of risk to aquatic organisms, as well as estimates of uncertainty associated with those predictions. The results of analyses performed using this model will be used by risk management divisions in decision-making. General examples of the application of the model will be provided. Key words: probabilistic risk assessment, pesticides, Monte Carlo, US EPA |
