Closing the Mass Balance on Fluorine on Papers and Textiles.
Alix E RobelKristin MarshallMargaret DickinsonDavid LunderbergCraig ButtGraham F PeasleeHeather M StapletonJennifer A FieldPublished in: Environmental science & technology (2017)
Papers and textiles that are treated with per- and polyfluoroalkyl substances (PFASs) are sources of human and environmental exposure. Data for individual PFASs, such as perfluorooctanesulfonate (PFOS) and perfluorooctanoate (PFOA), are not placed into the context of total fluorine for papers and textiles. Gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) were used to quantify volatile and ionic PFASs, respectively, and the total oxidizable precursor (TOP) assay was used to quantify precursors that form perfluoroalkyl carboxylates. Molar sums of PFASs obtained by GC-MS, LC-MS/MS, and precursors were compared to total fluorine (nmol F/cm2) determined by particle-induced gamma ray emission (PIGE) spectroscopy, measured before and after extraction. Volatile and ionic PFASs and unknown precursors accounted for 0-2.2%, 0-0.41%, and 0.021-14%, respectively, of the total nmol F/cm2 determined by PIGE. After extraction, papers and textiles retained 64 ± 28% to 110 ± 30% of the original nmol F/cm2 as determined by PIGE, indicating that the majority of fluorine remains associated with the papers and textiles. The sum of PFASs in the volatile, ionic, and precursor fraction, and total fluorine after extraction indicate that mass balance was achieved (within analytical error) of the initial total fluorine measured by PIGE.
Keyphrases
- positron emission tomography
- liquid chromatography tandem mass spectrometry
- pet imaging
- gas chromatography mass spectrometry
- computed tomography
- gas chromatography
- ionic liquid
- solid state
- endothelial cells
- high resolution
- solid phase extraction
- electronic health record
- drinking water
- high throughput
- oxidative stress
- big data
- risk assessment
- deep learning
- high glucose
- artificial intelligence
- pet ct
- human health