Fabric phase sorptive extraction: Two practical sample pretreatment techniques for brominated flame retardants in water

摘要

Sample pretreatment is the critical section for residue monitoring of hazardous pollutants. In this paper, using the cellulose fabric as host matrix, three extraction sorbents such as poly (tetrahydrofuran) (PTHF), poly (ethylene glycol) (PEG) and poly (dimethyldiphenylsiloxane) (PDMDPS), were prepared on the surface of the cellulose fabric. Two practical extraction techniques including stir bar fabric phase sorptive extraction (stir bar-FPSE) and magnetic stir fabric phase sorptive extraction (magnetic stir-FPSE) have been designed, which allow stirring of fabric phase sorbent during the whole extraction process. In the meantime, three brominated flame retardants (13FR5) [tetrabromobisphenol A (TBBPA), tetrabromobisphenol A bisallylether (TBBPA-BAE), tetrabromobisphenol A bis(2,3-dibromopropyl)ether (TBBPA-BDBPE)] in the water sample were selected as model analytes for the practical evaluation of the proposed two techniques using high-performance liquid chromatography (HPLC). Moreover, various experimental conditions affecting extraction process such as the type of fabric phase, extraction time, the amount of salt and elution conditions were also investigated. Due to the large sorbent loading capacity and unique stirring performance, both techniques possessed high extraction capability and fast extraction equilibrium. Under the optimized conditions, high recoveries (90-99%) and low limits of detection (LODs) (0.01 -0.05 mu g L-1) were achieved. In addition, the reproducibility was obtained by evaluating the intraday and interday precisions with relative standard deviations (RSDs) less than 5.1% and 6.8%, respectively. The results indicated that two pretreatment techniques were promising and practical for monitoring of hazardous pollutants in the water sample. Due to low solvent consumption and high repeated use performance, proposed techniques also could meet green analytical criteria. (C) 2016 Elsevier Ltd. All rights reserved.