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Parameterization Models for Pesticide Exposure via Crop Consumption

机译：通过作物消费的农药暴露参数化模型

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摘要

An approach for estimating human exposure to pesticides via consumption of six important food crops is presented that can be used to extend multimedia models applied in health risk and life cycle impact assessment. We first assessed the variation of model output (pesticide residues per kg applied) as a function of model input variables (substance, crop, and environmental properties) including their possible correlations using matrix algebra. We identified five key parameters responsible for between 80% and 93% of the variation in pesticide residues, namely time between substance application and crop harvest, degradation half-lives in crops and on crop surfaces overall residence times in soil, and substance molecular weight. Partition coefficients also play an important role tor truit trees and tomato (Kow), potato (Koc), and lettuce (Kaw, Kow). Focusing on these parameters, we develop crop-specific models by parametrizing a complex fate and exposure assessment framework. The parametric models thereby reflect the frameworks physical and chemical mechanisms and predict pesticide residues in harvest using linear combinations of crop, crop surface, and soil compartments. Parametric model results correspond well with results from the complex framework for 1540 substance-crop combinations with total deviations between a factor 4 (potato) and a factor 66 (lettuce). Predicted residues also correspond well with experimental data previously used to evaluate the complex framework. Pesticide mass in harvest can finally be combined with reduction factors accounting for food processing to estimate human exposure from crop consumption All parametric models can be easily implemented into existing assessment frameworks.
机译：提出了一种通过食用六种重要粮食作物来估计人类接触农药的方法，该方法可用于扩展应用于健康风险和生命周期影响评估的多媒体模型。我们首先根据模型输入变量（物质，作物和环境特性）评估模型输出（每千克施用的农药残留量）的函数变化，包括使用矩阵代数的可能相关性。我们确定了造成农药残留变化80％至93％的五个关键参数，即物质施用与作物收割之间的时间，作物的降解半衰期以及作物表面在土壤中的总体停留时间以及物质的分子量。分配系数在金枪鱼树和番茄（Kow），马铃薯（Koc）和生菜（Kaw，Kow）中也起着重要作用。着眼于这些参数，我们通过参数化复杂的命运和暴露评估框架来开发特定于作物的模型。参数模型从而反映了框架的物理和化学机制，并使用作物，作物表面和土壤区室的线性组合来预测收获时的农药残留。参数模型的结果与1540种物质-作物组合的复杂框架的结果非常吻合，总偏差介于4（马铃薯）和66（生菜）之间。预测的残基也与先前用于评估复杂框架的实验数据非常吻合。最终，收获中的农药量可以与减少因素结合起来，这些减少因素可以说明食品加工过程，从而从农作物消费中估计人体暴露量。所有参数模型都可以轻松地应用于现有的评估框架中。

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  • 来源
    《Environmental Science & Technology》 |2012年第23期|12864-12872|共9页
  • 作者

    Peter Fantke; Peter Wieland; Ronnie Juraske; Gavin Shaddick; Eva Sevigne Itoiz; Rainer Friedrich; Olivier Jolliet;

  • 作者单位

    Institute of Energy Exonomics and the Rational Use of Energy, University of Stuttgart, Hessbruehlstrasse 49a, 70565 Stuttgart, Germany;

    Institute for Systems Theory and Automatic Control, University of Stuttgart, 70550 Stuttgart, Germany,osch Power Tec GmbH, Herrenberger Str. 130, 71034 Boeblingen, Germany;

    Institute of Environmental Engineering, Swiss Federal Institute of Technology Zurich, CH-8093 Zurich, Switzerland;

    Department of Mathematical Sciences, University of Bath, Bath BA2 7AY, United Kingdom;

    Institute of Agriculture and Food Research and Technology, 08348 Cabrils, Barcelona, Spain;

    Institute of Energy Exonomics and the Rational Use of Energy, University of Stuttgart, Hessbruehlstrasse 49a, 70565 Stuttgart, Germany;

    Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109-2029, United States,Quantis, EPFL Science Park (PSE-D), University of Stuttgart, CH-1015 Uusanne, Switzerland;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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