4.6 Article

Determination of six sulfonylurea herbicides in environmental water samples by magnetic solid-phase extraction using multi-walled carbon nanotubes as adsorbents coupled with high-performance liquid chromatography

期刊

JOURNAL OF CHROMATOGRAPHY A
卷 1466, 期 -, 页码 12-20

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2016.08.065

关键词

Sulfonylurea herbicides; Magnetic solid-phase extraction; Multi-walled carbon nanotubes; Water samples; High-performance liquid chromatography

资金

  1. National Natural Science Foundation of China [21547002, 51478230, 21477160]
  2. Taishan Scholar Construction Project Special Foundation [2010016010]
  3. Special Foundation of Central Financial Support to Local Colleges and Universities [201020029]

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Magnetic solid-phase extraction (MSPE) using magnetic multi-walled carbon nanotubes (mag-MWCNTs) as adsorbents, coupled with high-performance liquid chromatography-diode-array detector (HPLC-DAD), was developed for the simultaneous separation and determination of six types of sulfonylurea herbicides (SUs) in environmental water samples. Several variables affecting MSPE efficiency were systematically investigated, including the type and volume of desorption solvent, sample solution pH, salt concentration, amount of mag-MWCNTs, and extraction and desorption time. Response surface was employed to assist in the MSPE optimization. Under optimized conditions, excellent linearity was achieved in the range of 0.05-5.0 mu g/L for all six SUs, with coefficients of correlation r > 0.9994, and preconcentration factors ranging from 178 to 210. Limits of detection and quantification were 0.01-0.04 mu g/L and 0.03-0.13 mu g/L, respectively. The intra-day and inter-day precision (relative standard deviations, n = 6, %) at three spiked levels were 2.0-11.0% and 2.1-12.9% in terms of peak area, respectively. The method recoveries at three fortified concentrations were obtained within 76.7-106.9% for reservoir water samples and 78.2-105.4% for tap water samples. The developed MSPE-HPLC method demonstrated high sensitivity, repeatability, simplicity, rapidity, and excellent practical applicability. (C) 2016 Elsevier B.V. All rights reserved.

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