Society of Environmental Toxicology and Chemistry Meetings

SRC scientists regularly attend the annual meetings of the Society of Toxicology (www.SETAC.org) and make presentations.

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SETAC Europe 16th Annual Meeting held May 7-11, 2006 in The Hague, The Netherlands

• Prediction of Environmental Fate and Transport Properties in Support of the Hydrocarbon Block Approach to Risk Assessment. Philip Howard, William Meylan, Dallas Aronson, Sarah Stewart, Thomas Parkerton, and Mike Comber
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SETAC North America 26th Annual Meeting held November 13-17, 2005 in Baltimore, MD

• Improved BCF Prediction for Hydrocarbons. S. Stewart, D. Aronson, W. Meylan1, P. Howard, M. Comber, and T. Parkerton
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Fourth SETAC World Congress and 25th Annual Meeting held November 14-18, 2004. Portland, OR

• Development of a Chemical Structure-Based Predictive Model for Anaerobic Biodegradation. D. Aronson, J. Tunkel, R. Boethling, W. Meylan, P. Howard
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SETAC North America 24th Annual Meeting held November 9-13, 2003 in Austin, TX

• Utility of Stochastic Weather Models for Determining Properties of Rainfall Patterns Affecting Pesticide Fate and Transport.  M. Ramsey; G. Johnson; P. Goodrum; V. Zurawski
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• Incorporating Monte-Carlo Analysis into Environmental Multi-Media Fate Models. M. Citra
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Utility of Stochastic Weather Models for Determining Properties of Rainfall Patterns Affecting Pesticide Fate and Transport

M. Ramsey, G. Johnson, P. Goodrum, V. Zurawski

Syracuse Research Corporation, Syracuse, NY; *USDA-NRCS, National Water and Climate Center, Portland, Oregon

Abstract
Pesticide fate and transport models are used by risk assessors to estimate contamination of ground and surface water and to evaluate risk management strategies in forested and agricultural ecosystems. However, a model’s ability to simulate the frequency of extreme precipitation events responsible for pesticide contamination of receiving waters is often limited to historical record of observed weather for a site. A common concern of modelers using observed weather records is the uncertainty that a relatively short record (< 100 years) represents the upper range of weather conditions that can promote pesticide transport. Stochastic weather models generate countless sequential simulations of weather data that are statistically similar to the observed weather record. The ‘GEMpro’ graphical user interface and post-processor program runs the freely-available, USDA-NRCS stochastic weather model GEM (Generation of Weather Elements for Multiple Applications) in an iterative fashion and generates meteorological files for two commonly-used pesticide exposure models - PRZM (EPA) and GLEAMS (USDA-NRCS).

Preliminary findings suggest that PRZM will estimate greater pesticide runoff fluxes with a weather file generated by GEMpro than with the observed weather record. This can be demonstrated even when the observed and simulated weather records have similar mean annual precipitation (total inches). This ability to produce varying rainfall patterns has several advantages for probabilistic exposure modeling, which yields distributions for the estimated exposure concentration (EEC). Stochastic weather models reduce the importance of the assumed pesticide application date, and may characterize variability in the rainfall patterns in a way that better represents the likelihood of conditions that yield highest pesticide runoff. We present findings from initial case studies in which the distribution of EEC is estimated from fixed meteorological records and corresponding stochastic simulations with GEMpro for different regions and sites around the United States.

Incorporating Monte-Carlo Analysis into Environmental Multi-Media Fate Models

M. Citra. Syracuse Research Corporation, Syracuse, NY

Abstract
We have incorporated a Monte Carlo module into a steady state non-equilibrium level III fugacity model in order to account for variability in degradation half-lives and observe the effects that this variability has on the model outputs. This method leads to a distribution of important output parameters such as the overall persistence time, which can be used in decision making processes or risk assessment. For herbicides such as atrazine, where the emission rate is primarily to the soil compartment, it is shown that the main contribution to the variability in overall persistence time is the soil degradation half-life.