色谱

色谱 ›› 2015, Vol. 33 ›› Issue (12): 1294-1300.DOI: 10.3724/SP.J.1123.2015.08022

• 研究论文 • 上一篇    下一篇

气相色谱-质谱-自动质谱解卷积技术在沉积物和污泥中有机污染物非靶标筛查中的应用

王刚1, 马慧莲2, 王龙星2, 陈吉平1,2, 侯晓虹1   

  1. 1. 沈阳药科大学, 辽宁 沈阳 110016;
    2. 中国科学院大连化学物理研究所, 中国科学院分离分析化学重点实验室, 辽宁 大连 116023
  • 收稿日期:2015-08-13 出版日期:2015-12-08 发布日期:2012-06-21
  • 通讯作者: 陈吉平, 侯晓虹
  • 基金资助:

    国家自然基金面上项目(21277139).

Non-target screening of organic pollutants in sediments and sludges using gas chromatography-mass spectrometry and automated mass spectral deconvolution

WANG Gang1, MA Huilian2, WANG Longxing2, CHEN Jiping1,2, HOU Xiaohong1   

  1. 1. Shenyang Pharmaceutical University, Shenyang 110016, China;
    2. Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
  • Received:2015-08-13 Online:2015-12-08 Published:2012-06-21

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摘要：

以沉积物和污泥中非极性和弱极性有机污染物的非靶标筛查为目的,建立了一种超声波辅助提取-气相色谱-质谱结合自动解卷积技术的筛查方法。以二氯甲烷为溶剂超声波辅助提取样品3次,每次20 min,提取液经凝胶渗透色谱(GPC)和硅胶层析柱净化,再用3 g铜粉超声10 min除硫。前处理方法的重复性(RSD, n=5)为5.8%~14.9%。采用自动质谱解卷积软件(AMDIS)和标准谱库定性鉴别出所含的有机物。在两类样品中共鉴别出290种有机污染物,其中沉积物样品中190种,污泥样品中153种。鉴别出的污染物包括美国环境保护署(EPA)优先控制污染物、药物和除草剂等新型污染物、抗氧化剂、中间体、有机溶剂及化工原料等。该方法灵敏度高,重复性好,可用于复杂基质样品中有机污染物的非靶标筛查。

关键词: 沉积物, 非靶标筛查, 环境污染物, 气相色谱-质谱, 污泥, 自动质谱解卷积

Abstract:

A screening method in the combination of ultrasonic extraction, gas chromatography-mass spectrometry detection and automated mass spectrometry deconvolution technique was developed for non-target screening of non-polar and weak polar pollutants in sediments and sludges. The samples were extracted by ultrasonication for 20 min using dichloromethane for three times. The extraction solutions were cleaned-up by gel permeation chromatography and a silica gel column, and then 3 g of copper powder was used to remove the sulfur by ultrasonication for 10 min. Parallel experiments were carried out for 5 times and the RSDs were ranged from 5.8% to 14.9%. Automated mass spectral deconvolution & identification system (AMDIS) would improve the resolution of overlapping peaks, and identify the pure mass spectrum of the analytes in the cases of stronger background interference and co-extracted substances covering. Standard spectrum databases, such as NISTDRUG, NISTEPA, NISTFDA, Mass Spectral Library, etc, would qualitatively identify the organic pollutants in the samples. As a result, a total of 290 organic pollutants were identified, of which 190 and 153 pollutants were found in sediments and sludges, respectively. The identified pollutants included the Environmental Protection Agency (EPA) priority pollutants, pharmaceuticals, herbicides, antioxidants, intermediates, organic solvents and chemical raw materials. The proposed method is proved to be a promising one for non-target screening of complex matrix samples with the advantages of higher sensitivity and better repeatability.

Key words: automated mass spectrometry deconvolution, environmental pollutants, gas chromatography-mass spectrometry (GC-MS), non-target screening, sediments, sludges

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