4.7 Article

Retention performance of three widely used SPE sorbents for the extraction of perfluoroalkyl substances from seawater

Journal

CHEMOSPHERE
Volume 193, Issue -, Pages 259-269

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chemosphere.2017.10.174

Keywords

Per- and polyfluoroalkyl substances; Oasis (R) HLB; Oasis (R) WAX; Strata (TM)-X; Recovery; Seawater

Funding

  1. National Sustain ability Programme of the Czech Ministry of Education, Youth and Sports [LO1214]
  2. RECETOX research infrastructure [LM2015051]

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Some per- and polyfluoroalkyl substances (PFASs) have been detected ubiquitously in the environment. Owing to the polar character conferred by the presence of the carboxylic or sulfonic acid groups and their resistance to degradation, aquatic environments became their major reservoirs, including marine waters. The procedure of PFAS analysis in aqueous matrices consists usually of solid-phase extraction (SPE) followed by high-performance liquid chromatography coupled to tandem mass spectrometry. Moreover, passive sampling approach using various SPE sorbents may be applied. This study deals with the assessment of retention characteristics of a selected group of PFASs in marine water on three sorbent media widely used in SPE or passive sampling techniques. The influence of type of sorbent, matrix pH, salinity and eluent on the PFAS recovery from aquatic samples was investigated. The best overall extraction conditions were found to be at pH 8 and 50%/100% matrix seawater content using Oasis HLB/ Stratarm-X as SPE sorbents and methanol as eluent. The matrix properties found to be the most appropriate for extraction of investigated PFASs from aqueous samples (i.e., pH and salinity levels) match well the natural properties of marine and brackish waters. Acid-base behavior was found to be the main driver influencing the recovery of PFASs. These research findings can be used to optimize PFAS extraction conditions from aquatic samples and also to develop efficient extraction procedures for multiresidual analyses. (C) 2017 Elsevier Ltd. All rights reserved.

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