Issue 40, 2017

Box–Behnken design applied to optimize the ultrasound-assisted extraction of petroleum biomarkers in river sediment samples using green analytical chemistry

Abstract

In the present paper, the 33 Box–Behnken design with a triplicate central point was used to optimize the conditions for the ultrasound-assisted extraction of n-alkanes (C10–C40) and isoprenoids (phytane and pristane), which are petroleum biomarkers and their derivatives, in river sediment samples. The determination was carried out using a Gas Chromatographer/Mass Spectrometer (GC/MS). The factors studied in the Box–Behnken design were the proportion of n-hexane and acetone in the solvent mixture, the length of sonication time, and the volume of the solvent mixture. The optimized conditions were 10 minutes of sonication, 10 mL of the solvent mixture, and a n-hexane/acetone mixture composition of 25 : 75 (v/v). These conditions were validated by assessing the recovered percentage that was obtained in the studies for the spiked blank and the spiked sample. The linear range was from 1 to 10 mg L−1 and the Pearson correlations for all the compounds were above 0.995. The detection limit ranged from 1.97 to 19.01 dry weight and 6.57 to 63.37 ng g−1 dry weight for the quantification limit. The mean recoveries of the spiked samples ranged from 55.47 to 110.40% and 61.00 to 115.21% for the spiked blanks. Sediment samples were analyzed and the concentration of n-alkanes ranged from 25.80 to 511.00 ng g−1 based upon the dry weight.

Graphical abstract: Box–Behnken design applied to optimize the ultrasound-assisted extraction of petroleum biomarkers in river sediment samples using green analytical chemistry

Article information

Article type
Paper
Submitted
13 Jun 2017
Accepted
18 Sep 2017
First published
18 Sep 2017

Anal. Methods, 2017,9, 5859-5867

Box–Behnken design applied to optimize the ultrasound-assisted extraction of petroleum biomarkers in river sediment samples using green analytical chemistry

F. M. Araujo, M. D. R. Santos, M. A. L. de Oliveira, R. C. Matos and Maria. A. C. Matos, Anal. Methods, 2017, 9, 5859 DOI: 10.1039/C7AY01470H

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