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Insecticide Risk in US Surface Waters: Drivers and Spatiotemporal Modeling

机译:美国地表水的杀虫剂风险:驱动因素和时空模型

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摘要

Although pesticide contamination in agricultural surface waters is a common phenomenon, large-scale studies dealing with the responsible drivers are rare. We used data from 259 publications reporting 5830 individual water or sediment concentrations of 32 insecticides and their metabolites in 644 US surface waters to determine the factors driving insecticide risks, that is, exceedance of regulatory threshold levels (RTLs). Multiple linear regressions (R-2 adj. = 49.6-76.5) revealed that toxicity-normalized agricultural insecticide use (i.e. use divided by toxicity) was the most important driver. Burst rainfall erosivity and irrigation practices also had risk-promoting effects, whereas time, catchment size, and sampling interval had risk-demoting effects. A regression model (R-2 adj. = 62.2, n = 1833) for small, medium, and large running waters was validated and used for risk mapping at the national scale, highlighting multiple regions, where the comparison of predicted insecticide concentrations with their RTLs indicate adverse conditions for aquatic organisms. Particularly in smaller streams, risks were most pronounced with an average RTL exceedance frequency of 27.7% in all grid cells (n = 9968). Finally, mixture toxicity was mainly (about 76.7%) explained by the most toxic compound in the mixture, causing similar to 95.7% of RTL exceedances. Identifying the factors, which drive exposure for all relevant insecticide classes, and subsequently mapping these risks for surface waters of various sizes across the U.S., will support future risk management.
机译:尽管农业地表水中的农药污染是一种普遍现象,但是涉及负责任驱动因素的大规模研究却很少。我们使用了259家出版物的数据,这些出版物报告了644种美国地表水中5830种32种杀虫剂及其代谢物的单独水或沉积物浓度,以确定驱动杀虫剂风险的因素,即超过监管阈值水平(RTLs)。多元线性回归(R-2调整= 49.6-76.5)显示,毒性标准化农用杀虫剂的使用(即除以毒性的使用)是最重要的驱动因素。突发降雨侵蚀力和灌溉习惯也具有促进风险的作用,而时间,集水区大小和采样间隔则具有降低风险的作用。验证了小,中和大自来水的回归模型(R-2调整为62.2,n = 1833),并已在全国范围内用于风险绘图,突出显示了多个区域,在该区域比较了预测杀虫剂浓度与杀虫剂浓度RTL指示了水生生物的不利条件。特别是在较小的流中,所有网格单元中的平均RTL超出频率为27.7%(n = 9968),风险最为明显。最后,混合物毒性主要由混合物中毒性最高的化合物解释(约占76.7%),造成超过RTL的95.7%。确定导致所有相关杀虫剂类别暴露的因素,然后绘制全美各种规模地表水的这些风险,将有助于未来的风险管理。

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  • 来源
    《Environmental Science & Technology》 |2019年第20期|12071-12080|共10页
  • 作者单位

    Univ Koblenz Landau Inst Environm Sci IES Landau Ft Str 7 D-76829 Landau Germany;

    Univ Koblenz Landau Inst Environm Sci IES Landau Ft Str 7 D-76829 Landau Germany|Univ Koblenz Landau Eusserthal Ecosyst Res Stn Birkenthalstr 13 D-76857 Eusserthal 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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