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This article in JEQ

  1. Vol. 40 No. 3, p. 879-898

    * Corresponding author(s): h.vereecken@fz-juelich.de


Do Lab-Derived Distribution Coefficient Values of Pesticides Match Distribution Coefficient Values Determined from Column and Field-Scale Experiments? A Critical Analysis of Relevant Literature

  1. H. Vereecken *a,
  2. J. Vanderborghta,
  3. R. Kasteela,
  4. M. Spitellerb,
  5. A. Schäfferc and
  6. M. Closed
  1. a Agrosphere Institute, ICG-4, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
    b Institute of Environmental Research (INFU) of the Faculty of Chemistry, Chair of Environmental Chemistry and Analytical Chemistry, Dortmund Univ. of Technology, Dortmund, Germany
    c Institute for Environmental Research (Biology 5), RWTH Aachen Univ., 52074 Aachen, Germany
    d Institute of Environmental Science and Research, P.O. Box 29 181, Christchurch, New Zealand. Assigned to Associate Editor Pierre Benoit


In this study, we analyzed sorption parameters for pesticides that were derived from batch and column or batch and field experiments. The batch experiments analyzed in this study were run with the same pesticide and soil as in the column and field experiments. We analyzed the relationship between the pore water velocity of the column and field experiments, solute residence times, and sorption parameters, such as the organic carbon normalized distribution coefficient (K oc) and the mass exchange coefficient in kinetic models, as well as the predictability of sorption parameters from basic soil properties. The batch/column analysis included 38 studies with a total of 139 observations. The batch/field analysis included five studies, resulting in a dataset of 24 observations. For the batch/column data, power law relationships between pore water velocity, residence time, and sorption constants were derived. The unexplained variability in these equations was reduced, taking into account the saturation status and the packing status (disturbed-undisturbed) of the soil sample. A new regression equation was derived that allows estimating the K oc values derived from column experiments using organic matter and bulk density with an R 2 value of 0.56. Regression analysis of the batch/column data showed that the relationship between batch- and column-derived K oc values depends on the saturation status and packing of the soil column. Analysis of the batch/field data showed that as the batch-derived K oc value becomes larger, field-derived K oc values tend to be lower than the corresponding batch-derived K oc values, and vice versa. The present dataset also showed that the variability in the ratio of batch- to column-derived K oc value increases with increasing pore water velocity, with a maximum value approaching 3.5.

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Copyright © 2011. American Society of Agronomy, Crop Science Society of America, Soil Science SocietyAmerican Society of Agronomy, Crop Science Society of America, and Soil Science Society of America