Zhao Wenting, Li Jindong, Wu Tong, Wang Peng, Zhou Zhiqiang
Department of Applied Chemistry, China Agricultural University, Beijing, China.
J Sep Sci. 2014 Sep;37(18):2599-604. doi: 10.1002/jssc.201400156. Epub 2014 Aug 1.
A simple, rapid, efficient, and environmentally friendly pretreatment based on a low-density solvent based dispersive liquid-liquid microextraction was developed for determining trace levels of 17 organochlorine pesticides in snow. The parameters affecting the extraction efficiency, such as the type and volume of the extraction and dispersive solvents, extraction time, and salt content, were optimized. The optimized conditions yielded a good performance, with enrichment factors ranging from 271 to 474 and recoveries ranging from 71.4 to 114.5% and relative standard deviations between 1.6 and 14.8%. The detection limits, calculated as three times the signal-to-noise ratio, ranged from 0.02 to 0.11 μg/L. The validated method was used to successfully analyze 17 analytes in snow water samples, overcoming the drawbacks of some existing low-density solvent liquid microextraction methods, which require special devices, large volumes of organic solvents, or complicated operation procedures.
开发了一种基于低密度溶剂的分散液液微萃取的简单、快速、高效且环保的预处理方法，用于测定雪中痕量的17种有机氯农药。对影响萃取效率的参数进行了优化，如萃取溶剂和分散溶剂的类型及体积、萃取时间和盐含量。优化后的条件具有良好的性能，富集因子在271至474之间，回收率在71.4%至114.5%之间，相对标准偏差在1.6%至14.8%之间。以三倍信噪比计算的检测限在0.02至0.11μg/L之间。该经过验证的方法成功用于分析雪水样品中的17种分析物，克服了一些现有低密度溶剂液液微萃取方法的缺点，这些方法需要特殊装置、大量有机溶剂或复杂的操作程序。
