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印度科钦沿海海域鱼类中微污染物的大规模筛选和定量:分析方法的开发和健康风险评估。

Large scale screening and quantification of micropollutants in fish from the coastal waters of Cochin, India: Analytical method development and health risk assessment.

机构信息

National Reference Laboratory, ICAR-Central Institute of Fisheries Technology, Matsyapuri P.O., W. Island, Cochin 682029, India; Department of Chemical Oceanography, School of Marine Sciences, Cochin University of Science and Technology, Cochin 682016, India.

National Reference Laboratory, ICAR-Central Institute of Fisheries Technology, Matsyapuri P.O., W. Island, Cochin 682029, India.

出版信息

Sci Total Environ. 2024 Dec 1;954:176515. doi: 10.1016/j.scitotenv.2024.176515. Epub 2024 Sep 30.

Abstract

Urban estuarine and coastal water receive several micropollutants through industrial and agricultural influxes. The bioaccumulation of these micropollutants in fish and their entry into the coastal population's food chain raises significant food safety concerns. Hence, a comprehensive analytical method was developed for ultra-trace level quantification of 345 micropollutants in fish. The optimized sample preparation method could extract compounds suitable for both GC-MS/MS and LC-MS/MS analysis simultaneously. The target list of contaminants included 278 agricultural pesticides and also 102 endocrine disruptors covering polyaromatic hydrocarbons, polychlorinated biphenyls, organochlorines, and endocrine-disrupting pesticides. The GC-MS/MS with large volume injection (LVI) technique, and LC-MS/MS operating in MRM mode, achieved an LOQ of <2.00 ng/g for most of the analytes. The extraction strategy involved tri-phase partitioning between water, acidified acetonitrile, and hexane, followed by salting out. Dispersive solid phase cleanup (dSPE) with C18, Z-Sep+, CaCl, and MgSO was able to reduce the matrix influence, and the method achieved satisfactory recovery in the range of 70.0-120.0 % for all the target analytes. The repeatability and reproducibility relative standard deviation values of the measured analytes were <20.0 %, and the Horwitz ratio values were well below 2. The method was used to accurately measure the target micropollutants in fish from the Cochin estuary, the highly urbanized portion of the Vembanad Lake, and an important Ramsar site. At least one or more of the 41 different micropollutants were identified and quantified in about 90.7 % of the 108 samples analyzed. The importance of large-scale screening and trace-level quantification methods in environmental monitoring and risk assessment is underscored by the results. The risk assessment showed a moderate risk of exposure to the nearby coastal population through the food chain.

摘要

城市河口和沿海水域通过工业和农业的流入接收多种微量污染物。这些微量污染物在鱼类中的生物积累及其进入沿海人口食物链引起了重大的食品安全问题。因此,开发了一种用于在鱼类中对 345 种微量污染物进行超痕量定量的综合分析方法。优化的样品制备方法可以同时提取适合 GC-MS/MS 和 LC-MS/MS 分析的化合物。目标污染物清单包括 278 种农业农药,以及 102 种内分泌干扰物,涵盖多环芳烃、多氯联苯、有机氯和内分泌干扰农药。采用大体积进样 (LVI) 技术的 GC-MS/MS 和在 MRM 模式下运行的 LC-MS/MS,大多数分析物的 LOQ 均<2.00 ng/g。提取策略涉及水、酸化乙腈和正己烷之间的三相分配,然后进行盐析。通过 C18、Z-Sep+、CaCl 和 MgSO 的分散固相萃取 (dSPE) 能够降低基质的影响,该方法使所有目标分析物的回收率达到 70.0-120.0%。测量分析物的重复性和再现性相对标准偏差值<20.0%,Horwitz 比值均远低于 2。该方法用于准确测量科钦河口、高度城市化的 Vembanad 湖以及一个重要的拉姆萨尔湿地的鱼类中的目标微量污染物。在所分析的 108 个样本中,约 90.7%的样本中鉴定和定量了至少一种或多种 41 种不同的微量污染物。研究结果强调了在环境监测和风险评估中进行大规模筛选和痕量定量方法的重要性。风险评估表明,通过食物链,附近沿海人口接触这些污染物的风险处于中度水平。

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