Optimization and validation of automated solid-phase microextraction arrow technique for determination of phosphorus flame retardants in water

Abstract

In the present work, a very sensitive and fully automated direct immersion PAL SPME Arrow procedure, coupled with GC-MS, has been developed and validated for determination of nine phosphorus flame retardants in different types of water samples (river, drinking and rainwater). PDMS/DVB was selected among three commercially available SPME Arrows (PDMS/DVB, DVB/PDMS/CWR and PDMS/CWR), since it resulted in the best sensitivity. The important experimental parameters were optimized via a central composite design response surface methodology and as result, extraction time of 65 min, extraction temperature of 80 degrees C and added salt concentration of 19% (w/v), were selected as the optimum values. The optimized method showed linear response over the calibration range (2 – 500 ng L-1), with R-2-values higher than 0.9937. The precision (RSD%) measured by replicate analyses (n = 7) was estimated at 2 and 100 ng L-1 and was less than 29% and 21%, respectively. The LOQ of PAL SPME Arrow, calculated as S/N = 10, was between 0.2 and 1.2 ng L-1 (for triphenyl phosphate and tris-(1-chloro-2-propyl) phosphate, respectively) with extraction efficiencies between 5.9 and 31% (for tris-(1,3-dichloro-2-propyl) phosphate and tri-n-butyl phosphate, respectively). To assess the performance of the developed technique for real samples, two river water samples, tap water from two regions and a rainwater sample were analyzed. Most of the target analytes were observed in the river samples with concentrations of 1.0 – 250 ng L-1 and the obtained recoveries at 50 ng L-1 ranged between 60 and 107%. Considering the figures of merit of the optimized method, PAL SPME Arrow-GC-MS showed to be the most sensitive analytical approach for determination of phosphorus flame retardants in water, with satisfying precision and accuracy, compared with conventional SPME-NPD, LLE-GC-MS and SPE-LC-MS/MS. (c) 2020 Elsevier B.V. All rights reserved.