Faculty of Art and Science, Department of Chemistry, Yildiz Technical University, 34210 Davutpasa, Esenler, Istanbul, Turkey.
Environ Monit Assess. 2020 Mar 28;192(4):253. doi: 10.1007/s10661-020-8214-5.
This study describes the development of a sensitive and accurate dispersive liquid-liquid microextraction strategy for the preconcentration and determination of selected pesticides in wastewater and lake water samples by gas chromatography-mass spectrometry. Determination of these pesticides at high accuracy and precision is important because they can be still be found in environmental samples. The type of extraction solvent and type of disperser solvent were optimized using the univariate approach. Furthermore, a Box-Behnken experimental design was used to set up a working model made up of 18 combinations of three variables, tested at three levels. The parameters fitted into the design model were volume of extraction solvent, disperser solvent volume, and mixing period. Analysis of variance was used to evaluate the experimental data to determine the significance of extraction variables and their interactions, before selecting optimum extraction conditions. The method was then applied to aqueous standard solutions between 2.0 and 500 μg L, and the limit of detection (LOD) and quantification (LOQ) values obtained for the analytes were between 0.37-2.8 and 1.2-9.4 μg L, respectively. The percent recoveries were calculated in the range of 92-114 and 96-110% for wastewater and lake water, respectively. These results validated the accuracy and applicability of the method to the selected matrices.
本研究描述了一种灵敏、准确的分散液液微萃取策略的发展,用于通过气相色谱-质谱法对废水和湖水样品中的选定农药进行预浓缩和测定。因为这些农药仍能在环境样品中被发现,所以对它们进行高精度和高精准度的测定是很重要的。采用单变量方法优化了萃取溶剂的类型和分散剂溶剂的类型。此外,还采用 Box-Behnken 实验设计建立了一个由三个变量的 18 种组合组成的工作模型,在三个水平上进行测试。拟合到设计模型中的参数是萃取溶剂的体积、分散剂溶剂的体积和混合时间。采用方差分析对实验数据进行评估,以确定萃取变量及其相互作用的显著性,然后选择最佳的萃取条件。然后将该方法应用于 2.0 至 500μg/L 的水标准溶液中,并获得了分析物的检测限 (LOD) 和定量限 (LOQ) 值分别为 0.37-2.8 和 1.2-9.4μg/L。废水和湖水的回收率分别在 92-114%和 96-110%的范围内。这些结果验证了该方法对选定基质的准确性和适用性。