摘要
制备了磁性羟基磷灰石(HAP/Fe_(3)O_(4))固相萃取吸附剂,结合高效液相色谱-紫外可见检测器,建立了用于湖水和河水中3种苯甲酰脲类农药(BUs)的分析方法。采用原位生长法合成HAP/Fe_(3)O_(4),使用X射线衍射仪、扫描电子显微镜和振动样品磁强计对材料进行了表征;考察了吸附剂用量、吸附时间、溶液pH、离子强度、洗脱溶液种类和洗脱体积对BUs回收率的影响。在最优条件下,方法对湖水中氟铃脲和虱螨脲在0.80~800 ng/mL、氟啶脲在0.70~700 ng/mL线性关系良好(r=0.9996),检出限和定量限分别为0.20~0.25 ng/mL和0.70~0.80 ng/mL;回收率为81.7%~102%,日内和日间精密度(n=3)分别为1.1%~6.5%和1.2%~8.1%。当上样10 mL湖水样品时,HAP/Fe_(3)O_(4)对3种BUs的富集倍数为40.9~51.0;重复吸附-解吸10次,3种BUs回收率仍达76.7%~99.2%。本方法准确、简单且经济,可用于分析环境水样中BUs。
A method of magnetic solid-phase extraction using hydroxyapatite/magnetite(HAP/Fe_(3)O_(4))coupled with high performance liquid chromatography-UV-VIS detector was developed for the determination of three benzoylurea pesticides(BUs)in lake water and river water samples.HAP/Fe_(3)O_(4) was constructed by in-situ growth strategy and characterized by X-ray diffractometry,scanning electron microscopy and vibrating sample magnetometer.The parameters including adsorbent dosage,adsorption time,pH,ionic strength of solution,elution solvent and volume on recoveries of 3 BUs were investigated.The proposed method gave the linear ranges of 0.8-800 ng/mL(r=0.9996)for hexaflumuron and lufenuron,0.70-700 ng/mL(r=0.9996)for chlorfluazuron in lake water samples.The limits of detection and the limits of quantification in lake water samples ranged from 0.20 to 0.25 ng/mL and 0.70 to 0.80 ng/mL,respectively.The recoveries of 3 BUs in lake water samples at three spiked levels ranged from 81.7%to 102%with the intra-day and inter-day precisions of 1.1%-6.5%and 1.2%-8.1%,respectively.Besides,the enhancement factors of the analytes varied from 40.9 to 51.0 when 10 mL of lake water was loaded.The adsorbent was stable enough for ten extraction/desorption cycles with the recoveries of 76.7%-99.2%(the relative standard deviations≤12%).The method is accurate,simple and economical,and it could be used for the determination of BUs in environmental water samples.
作者
徐以恒
齐晓润
张腾
魏佳凝
李子凌
王曼曼
XU Yiheng;QI Xiaorun;ZHANG Teng;WEI Jianing;LI Ziling;WANG Manman(School of Public Health,North China University of Science and Technology,Tangshan 063210)
出处
《分析科学学报》
CAS
CSCD
北大核心
2023年第5期509-516,共8页
Journal of Analytical Science
基金
华北理工大学创新训练项目(X2022161,X2022204)
河北省自然科学基金(H2022209025)。