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LC- and GC-QTOF-MS as Complementary Tools for a Comprehensive Micropollutant Analysis in Aquatic Systems

机译:LC-和GC-QTOF-MS作为水生系统中全面微量污染物分析的补充工具

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摘要

Efficient strategies are required to implement comprehensive suspect screening methods using high-resolution mass spectrometry within environmental monitoring campaigns. In this study, both liquid and gas chromatography time-of-flight mass spectrometry (LC-QTOF-MS and GC-QTOF-MS) were used to screen for >5000 target and suspect compounds in the Sacramento-San Joaquin River Delta in Northern California. LC-QTOF-MS data were acquired in All-Ions fragmentation mode in both positive and negative electrospray ionization (ESI). LC suspects were identified using two accurate mass LC-QTOF-MS/MS libraries containing pesticides, pharmaceuticals, and other environmental contaminants and a custom exact mass database with predicted transformation products (TPs). The additional fragment information from the All-Ions acquisition improved the confirmation of the compound identity, with a low false positive rate (9%). Overall, 25 targets, 73 suspects, and 5 TPs were detected. GC-QTOF-MS extracts were run in negative chemical ionization (NCI) for 21 targets (mainly pyrethroids) at sub-ng/L levels. For suspect screening, extracts were rerun in electron ionization (EI) mode with a retention time locked method using a GC-QTOF-MS pesticide library (containing exact mass fragments and retention times). Sixteen targets and 42 suspects were detected, of which 12 and 17, respectively, were not identified by LC-ESI-QTOF-MS. The results highlight the importance of analyzing water samples using multiple separation techniques and in multiple ionization modes to obtain a comprehensive chemical contaminant profile. The investigated river delta experiences significant pesticide inputs, leading to environmentally critical concentrations during rain events.
机译:需要有效的策略来在环境监测活动中使用高分辨率质谱法实施全面的可疑物筛查方法。在这项研究中,液相色谱和气相色谱飞行时间质谱(LC-QTOF-MS和GC-QTOF-MS)均用于筛查北部萨克拉曼多-圣华金河三角洲的> 5000种目标化合物和可疑化合物加利福尼亚LC-QTOF-MS数据以全离子裂解模式在正电喷雾电离电离和负电喷雾电离(ESI)中获取。使用两个包含农药,药物和其他环境污染物的精确质量数LC-QTOF-MS / MS库和定制的精确质量数据库(带有预测的转化产物(TP)),可以识别LC嫌疑人。来自全离子采集的其他碎片信息改善了化合物身份的确认,假阳性率低(9%)。总体上,检测到25个目标,73个可疑对象和5个TP。 GC-QTOF-MS提取物在负ng / L浓度下以负化学电离(NCI)处理了21个目标(主要是拟除虫菊酯)。为了进行可疑筛查,使用GC-QTOF-MS农药库(包含确切的质量碎片和保留时间),使用保留时间锁定方法以电子电离(EI)模式重新运行提取物。 LC-ESI-QTOF-MS未检测到16个目标和42个嫌疑人,其中分别识别了12个和17个。结果强调了使用多种分离技术和多种电离模式分析水样以获得全面的化学污染物特征的重要性。被调查的三角洲经历了大量农药投入,导致降雨事件中对环境至关重要的浓度。

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  • 来源
    《Environmental Science & Technology》 |2017年第3期|1537-1561|共25页
  • 作者单位

    Department of Civil and Environmental Engineering, University of California, One Shields Avenue, Davis, California 95616, United States;

    Department of Civil and Environmental Engineering, University of California, One Shields Avenue, Davis, California 95616, United States;

    Department of Civil and Environmental Engineering, University of California, One Shields Avenue, Davis, California 95616, United States;

    Agilent Technologies Inc., 2850 Centerville Road, Wilmington, Delaware 19808, United States;

    Department of Civil and Environmental Engineering, University of California, One Shields Avenue, Davis, California 95616, United States;

  • 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);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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  • 入库时间 2022-08-17 13:57:31

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