title: Extended sorption partitioning models for pesticide leaching risk assessments: Can we improve upon the koc concept?
abstract: Models used to assess leaching of pesticides to groundwater still rely on the sorption koc value, even though its limitations have been known for several decades, especially for soils of low organic carbon content (i.e. subsoils). This is mainly because the general applicability of any improved model approach that is also simple enough to use for regulatory purposes has not been demonstrated. The objective of this study was to test and compare alternative models of sorption that could be useful in pesticide risk assessment and management. To this end, a database containing the results of batch sorption experiments for pesticides was compiled from published studies in the literature, which placed at least as much emphasis on measurements in subsoil horizons as in topsoil. The database includes 785 data entries from 34 different published studies and for 21 different active substances. Overall, the apparent koc value, koc(app), roughly doubled as the soil organic carbon content decreased by a factor of ten. Nevertheless, in nearly half of the individual datasets, a constant koc value proved to be an adequate model. Further analysis showed that significant increases in koc(app) in subsoil were found primarily for the more weakly adsorbing compounds (koc values<ca. 100-200Lkg(-1)) and that sorption to clay in loamy and clayey-textured subsoil horizons was the main cause. Tests with the MACRO model demonstrated that sorption to clay minerals may significantly affect the outcome of regulatory exposure and risk assessments for leaching to groundwater. The koc concept currently used in leaching models should therefore be replaced by an alternative approach that gives a more realistic representation of pesticide sorption in subsoil. The two alternative models tested in this study appear to have widespread applicability and are also simple enough to parameterize for this purpose.
authors.affiliation: Department of Soil and Environment, Swedish University of Agricultural Sciences, Box 7014, 750 07 Uppsala, Sweden. Electronic address: nicholas.jarvis@slu.se.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Jarvis
mesh_terms: D000327:Adsorption; D000538:Aluminum Silicates; D000077215:Clay; D008956:Models, Chemical; D010575:Pesticides / Q000032:analysis*; D018570:Risk Assessment; D012987:Soil / Q000737:chemistry*; D012989:Soil Pollutants / Q000032:analysis*
chemical_list: D000538:Aluminum Silicates; D010575:Pesticides; D012987:Soil; D012989:Soil Pollutants; D000077215:Clay
keywords: Modelling; Pesticide; Risk assessment; Sorption; Subsoil; k(oc)