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An Improved Description of Pesticide Volatilization
Author(s) -
Wolters André,
Klein Michael,
Vereecken Harry
Publication year - 2004
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.2134/jeq2004.1629
Subject(s) - volatilisation , soil water , sorption , soil science , pesticide , environmental science , leaching (pedology) , water content , environmental chemistry , chemistry , geology , agronomy , geotechnical engineering , biology , organic chemistry , adsorption
ABSTRACT The consideration of pesticide volatilization from soil surfaces as an integral component of pesticide fate models is of importance, especially as part of the Predicted Environmental Concentrations (PEC) models used in the registration procedures for pesticides. The Pesticide Leaching Model (PELMO), which is used in the European registration process, was modified to allow for a reliable prediction of volatilization from soil. The previous PELMO version was upgraded by improving the spatiotemporal discretization at the soil surface, improving the empirical description of temperature dependence of Henry's law constants and including increased sorption of pesticides in dry soils. Comparison of predictions with experimental findings revealed the improvements of PELMO to contribute to a more realistic reflection of measurements, particularly at initial stages of the studies. The broad range of literature values of Henry's law constants was shown to have a significant effect on predicted volatilization fluxes. As a main refinement, the tendency of pesticides toward enhanced volatilization under moist conditions was correctly calculated by the improved model. Variations between model predictions and measurements were due to a lack of experimental data on soil sorption under dry conditions and indicated the need for further calibration of the model. The description of water content in the top layer was subject to uncertainty, which was exemplified by an overestimation of soil moisture during the last days of the field study. Thus, future model improvement will be dependent on experimental support to obtain more detailed information on soil–air–water partitioning of pesticides in the top soil layer.