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首页> 外文期刊>Environmental Science & Technology >Predicting Sorption of Pesticides and Other Multifunctional Organic Chemicals to Soil Organic Carbon
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Predicting Sorption of Pesticides and Other Multifunctional Organic Chemicals to Soil Organic Carbon

机译：预测农药和其他多功能有机化学物质对土壤有机碳的吸附

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摘要

Chemicals of current environmental concern are often multifunctional and more polar and more complex than classical pollutants such as polychlorinated biphenyls (PCB) or polycyclic aromatic hydrocarbons (PAH). Traditional models for predicting the partitioning in the environment such as group contribution methods or correlations with octanol- water partitioning cannot be expected to work well for such complex chemicals. In contrast, poly parameter Linear Free Energy Relationships (pp-LFERs) have been proven to describe partitioning of polar and nonpolar chemicals in all kinds of sorbing systems. Here, a pp-LFER model for soil-water partitioning was calibrated with data for 79 polar and nonpolar compounds that cover a very wide range of the relevant intermolecular interactions. The data set used for the model calibration in mis work is more diverse and covers a wider range of the chemical space than other pp-LFERs published so far. Subsequently, the experimental data for about 50 pesticides and pharmaceuticals -not involved in the model calibration- were used as independent validation of this new calibrated model. The model performs well with a standard error of 0.25 log units for fitting the calibration data and with a root-mean-square error of 0.4 log units for the pesticides and pharmaceuticals. The validation with the independent data set for pesticides and pharmaceuticals also shows that the pp-LFER model reported here performs better compared to earlier published pp-LFER models and to the traditional log Kow correlation.
机译：与经典污染物（如多氯联苯（PCB）或多环芳烃（PAH））相比，当前环境关注的化学品通常具有多功能，极性更强，更复杂的特点。传统的预测环境中分配的模型，例如基团贡献法或与辛醇-水分配的相关性，不能期望对这种复杂的化学药品有效。相反，多参数线性自由能关系（pp-LFERs）已被证明可描述极性和非极性化学物质在各种吸附系统中的分配。在这里，使用79种极性和非极性化合物的数据对用于土壤-水分配的pp-LFER模型进行了校准，该数据涵盖了非常广泛的相关分子间相互作用。与迄今为止发布的其他pp-LFERs相比，用于误工作的模型校准的数据集更加多样化，并且涵盖了更广阔的化学空间范围。随后，将约50种农药和药品的实验数据（不涉及模型校准）用作该新校准模型的独立验证。该模型表现良好，其标准误差为0.25 log单位以拟合校准数据，农药和药品的均方根误差为0.4 log单位。使用农药和药物的独立数据集进行的验证还表明，与较早发布的pp-LFER模型和传统的log Kow相关性相比，此处报告的pp-LFER模型的性能更好。

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  • 来源
    《Environmental Science & Technology》 |2011年第4期|p.1313-1319|共7页
  • 作者

    Guido Bronner; Kai-Uwe Goss;

  • 作者单位

    Helmholtz Centre for Environmental Research UFZ, Permoser-strasse 15, 04318 Leipzig, Germany (G.B.);

    Helmholtz Centre for Environmental Research UFZ, Permoserstrasse 15, 04318 Leipzig, Germany;

  • 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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  • 正文语种 eng
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