To comprise the future requirements to detect low levels of perfluoroalkane acids, includingbranched and linear perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA),and perfluorohexane sulfonic acid (PFHxS) in food items, here analytical methods fordetermination of PFOS, PFOA and PFHxS in six different food matrices (cow milk, butter,chicken egg, chicken meat, beef, and fish) were optimized and validated. The optimizedmethod was based on alkaline digestion and solid-liquid extraction using acetonitrile,followed by solid phase extraction (SPE) using a weak anion exchange cartridge as clean-up.In the case of milk and egg samples, an additional clean-up with graphitized carbon (ENVICarb)was applied. The separation was performed on an ultra-performance liquidchromatograph (UPLC) in negative electrospray ionization mode (MS/MS). The methodshowed an effective way to eliminate taurodeoxycholic acid (TDC), a bile acid that is anendogenous interference compound in egg sample causing ionization suppression duringelectrospray ionization. Validation was performed and resulted in recoveries for the targetanalytes at an acceptable level >70%, the limits of quantification (LOQs) in all matrices were3.1, 3.4, 4.9 pg/g for PFHxS, PFOA, and L-PFOS, respectively. The optimized method wassuccessfully applied to 53 food samples from the Swedish market (n=18) and food samplesprovided by 11 countries through the United Nations Environment Programme project, GlobalMonitoring Plan 2 on Persistent Organic Pollutants (UNEP/GMP2) (n=35). PFOS and PFOAwere detected in all samples, and PFHxS was detected in 80% of the samples. With thismethod, concentrations in the low pg/g range in food samples were quantified including thebranched PFOS isomers. This method can be applied to enforce potential future limit valuesfor PFOS and PFOA as discussed based on the recent European Food Safety Authority(EFSA) report.Further method optimization and validation is still needed for foods of plant origin such asvegetables, flour, nuts and bread.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:oru-77010 |
| Date | January 2019 |
| Creators | Sadia, Mohammad |
| Publisher | Örebro universitet, Institutionen för naturvetenskap och teknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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