Revised framework for pesticide aquatic environmental exposure assessment that accounts for vegetative filter strips.
For pesticides that do not pass higher-level environmental exposure assessments, vegetated filter strips (VFS) are often mandated for use of the compound. However, VFS physiographic characteristics (i.e., width) are not currently specified based on predictive modeling of VFS performance. This has been due to the lack of predictive tools that can explain the wide range of field-reported efficacies. This research hypothesizes that mechanistic modeling of VFS runoff and sediment trapping, integrated with an empirical, regression-based pesticide trapping equation and the U.S. Environmental Protection Agency's (EPA) exposure framework, is able to effectively derive these VFS characteristics. To test this hypothesis, a well-tested process-based model for VFS (VFSMOD) was coupled with the pesticide trapping equation and integrated with EPA's PRZM/EXAMS exposure package. The revised framework was applied to a prescribed U.S. EPA assessment scenario for four hypothetical pesticides: more mobile (i.e., organic carbon (OC) sorption coefficients, K(oc), of 100 L/kg OC) and less mobile (2000 L/kg OC) pesticides that are fast degrading or stable (i.e., 10 or 10,000 d aquatic dissipation half-lives). A nonlinear and complex relationship was observed between pesticide reduction, VFS length, and rainfall plus runon event size. The impact of VFS on environmental exposure concentrations (EECs) was found to be dependent on the pesticide sorption and dissipation half-life and whether calculating an acute or chronic EEC. While acute and chronic EECs were equivalent for stable pesticides, for fast degrading pesticides the acute EEC depended on specific loading events. Therefore, while VFS may reduce the cumulative pesticide loading, a corresponding reduction in the acute EEC may not always be observed. Such results emphasize the need to incorporate physically based modeling of VFS reductions for pesticides that do not pass the current U.S. EPA exposure assessment framework.
Sabbagh
George J
GJ
Bayer CropScience, Stilwell, Kansas 66085, USA. george.sabbagh@bayercropscience.com
Fox
Garey A
GA
Muñoz-Carpena
Rafael
R
Lenz
Mark F
MF
D004781:Environmental Exposure; D008962:Models, Theoretical; D010575:Pesticides / Q000633:toxicity*; D010944:Plants; D014874:Water Pollutants, Chemical / Q000633:toxicity*
D010575:Pesticides; D014874:Water Pollutants, Chemical