Issue 6, 2014

Screening and quantification of 304 pesticides and related organic pollutants in surface water using dispersive liquid–liquid microextraction coupled with gas chromatography-mass spectrometry

Abstract

Dispersive liquid–liquid microextraction (DLLME) coupled with gas chromatography-mass spectrometry (GC-MS) was used to quantify and semi-quantify 304 pesticides and related organic pollutants in surface water. Extraction parameters including types and volumes of extraction solvent, disperser solvent, and the amount of salt addition were optimized to obtain highest recoveries and lowest detection limits. A mixture of 35 μL carbon tetrachloride (extraction solvent) and 1 mL acetone (disperser solvent) was added into 5 mL of water sample. After agitation and centrifugation, 20 μL of the sedimented phase was mixed with 1 μL of the internal standard solution, and 1 μL of the final solution was injected into GC-MS for separation and quantification. The enrichment factors ranging from 42- to 299-fold were obtained for all compounds. The limits of detection ranged from 0.001 to 1.125 μg L−1, and the limits of quantification ranged from 0.003 to 3.75 μg L−1. Of all 304 compounds, 90 compounds showed recoveries from 60% to 120% and RSDs lower than 20%. The proposed method is very low cost, rapid and convenient, and could be an effective method for the monitoring of multiple pesticides in surface water.

Graphical abstract: Screening and quantification of 304 pesticides and related organic pollutants in surface water using dispersive liquid–liquid microextraction coupled with gas chromatography-mass spectrometry

Supplementary files

Article information

Article type
Paper
Submitted
17 Dec 2013
Accepted
07 Jan 2014
First published
08 Jan 2014

Anal. Methods, 2014,6, 1743-1752

Author version available

Screening and quantification of 304 pesticides and related organic pollutants in surface water using dispersive liquid–liquid microextraction coupled with gas chromatography-mass spectrometry

B. Chen, B. Jin, R. Jiang, L. Xie, Y. Lin, W. Feng and G. Ouyang, Anal. Methods, 2014, 6, 1743 DOI: 10.1039/C3AY42238K

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