Quantification and Deep Characterization of Pfass in Suspended Particulate Matter (Spm) in Timelines of German Rivers Using Comprehensive Complementary Analytical Approaches – Eof, Dtopa, (Non-)Target Hrms

Simon, Fabian; Gehrenkemper, Lennart; Becher, Susanne; Dierkes, Georg; Langhammer, Nicole; Cossmer, Antje; Au, Marcus von der; Göckener, Bernd; Fliedner, Annette; Rüdel, Heinz; Koschorreck, Jan; Meermann, Björn

doi:10.2139/ssrn.4272478

Cited by 4 publications

(3 citation statements)

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“…3 Target analysis is not feasible for a comprehensive characterization as only a few PFAS can be quantified, thereby often drastically underestimating the total PFAS burden. 4,5 Thus, current analytical trends emphasize complementary approaches based on organofluorine sum parameters and non-target screening (NTS) for a higher PFAS coverage. [6][7][8] Organofluorine sum parameters are used to determine the gap between PFAS targets and total organically bound fluorine and thereby indicate the quantity of unidentified extractable organic fluorine (EOF).…”

Section: Introductionmentioning

confidence: 99%

Can qualitative non-target data be indicative of PFAS contamination? First evidence by correlation with EOF in environmental samples

Zweigle,

Simon,

Meermann

et al. 2024

Preprint

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We combined and correlated non-target screening (NTS) features and extractable organic fluorine (EOF) data for PFAS analysis in environmental samples. Soils, sediments, and ashes from different locations (Germany, France, Lithuania) (n=34) were extracted and analyzed via liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS). NTS feature prioritization based on the mass to carbon (m/C) and mass defect to carbon (MD/C) ratio was applied to discriminate potential PFAS features from common co-extracted organic matrix. Our results show a high correlation between quantitative EOF data with the prioritized feature number (R2 = 0.87, rPearson = 0.93) as well as with the total peak area of prioritized features (R2 = 0.97, rPearson = 0.98) while commonly applied MD filtering showed no correlation with EOF. The observed highly significant correlations highlight that MD/C-m/C prioritization is associated with a good indication of the overall PFAS burden as evidenced by EOF. Also, semi-quantitative data can be extracted from PFAS-specific NTS as shown for the EOF vs. prioritized peak areas. The correlations indicate that lowly fluorinated compounds were negligible and that the EOF was mostly composed of higher fluorinated substances. We recommend further investigation of the unique complementary EOF vs. NTS combination for PFAS screening.

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Section: Introductionmentioning

confidence: 99%

Can qualitative non-target data be indicative of PFAS contamination? First evidence by correlation with EOF in environmental samples

Zweigle,

Simon,

Meermann

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

Can qualitative non-target data be indicative of PFAS contamination? First evidence by correlation with EOF in environmental samples

Zweigle,

Simon,

Meermann

et al. 2024

Preprint

View full text Add to dashboard Cite

We combined and correlated non-target screening (NTS) features and extractable organic fluorine (EOF) data for PFAS analysis in environmental samples. Soils, sediments, and ashes from different locations (Germany, France, Lithuania) (n=34) were extracted and analyzed via liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS). NTS feature prioritization based on the mass to carbon (m/C) and mass defect to carbon (MD/C) ratio was applied to discriminate potential PFAS features from common co-extracted organic matrix. Our results show a high correlation between quantitative EOF data with the prioritized feature number (R2 = 0.87, rPearson = 0.93) as well as with the total peak area of prioritized features (R2 = 0.97, rPearson = 0.98) while commonly applied MD-ranges for filtering showed much weaker correlation with EOF. The observed highly significant correlations highlight that MD/C-m/C prioritization is associated with a good indication of the overall PFAS burden as evidenced by EOF. Also, semi-quantitative data can be extracted from PFAS-specific NTS as shown for the EOF vs. prioritized peak areas. The correlations indicate that lowly fluorinated compounds were negligible and that the EOF was mostly composed of higher fluorinated substances. We recommend further investigation of the unique complementary EOF vs. NTS combination for PFAS screening.

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“…The number of available isotope labeled analytical standards -which are needed for reliable quanti cation using target MS approaches -is limited and transformation products have to be identi ed beforehand. A recently published study of our group based on PFAS sum parameter approaches revealed huge gaps between extractable organically bound uorine (EOF), PFAS total oxidizable precursor assay (TOPA) and sum of target PFAS determined by means of LC-MS/MS (17). In this work, we used molecular absorption spectrometry (MAS) to determine EOF in SPM and compared resulting data with TOPA as well as nontarget MS quali cation and target MS quanti cation.…”

Section: Introductionmentioning

confidence: 99%

Investigating the uptake and fate of per- and polyfluoroalkylated substances (PFAS) in bean plants (Phaseolus vulgaris) – Comparison between target MS and sum parameter analysis via HR-CS-GFMAS

Gehrenkemper

Ruhl

Westphalen

et al. 2023

Preprint

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In this study we present a screening method based on molecular absorption spectrometry to study PFAS uptake and fate in plants. To evaluate the suitability of this method we analyzed plant extracts with molecular absorption spectrometry (MAS) as well as liquid chromatography-tandem mass spectrometry (LC-MS/MS) for mass balance studies (w(F)). French bean plants (Phaseolus vulgaris) were grown on spiked soil using eight PFAS substances that vary in chain length and functional group composition. Specifically, these include three short-chained (C4-C5), five long-chained (C7-C10) as well as carbonic acids, one sulfonic acid and one sulfonic amid moieties. To investigate substance-specific PFAS uptake systematically, PFAS were spiked as single substance spike. Additionally, we studied one mixture of the investigated substances in equal proportions regarding w(F) and four PFAS mixtures of unknown composition. After 6 weeks plants were separated into four compartments. We analyzed the four compartments as well as soil for extractable organically bound fluorine (EOF) by HR-CS-GFMAS as well as for sum of ten target-PFAS by LC-MS/MS. All three short-chained PFAS perfluoro butanoic acid (PFBA), perfluoro butanoic sulfonic acid (PFBS) and perfluoro pentanoic acid (PFPeA) were determined in high concentrations mainly in the fruits of the investigated plants while long-chained PFAS perfluoro nonanoic acid (PFNA) and perfluoro decanoic acid (PFDA) were mainly determined in roots. PFBS was determined in remarkably high concentrations in leaves compartment by both quantification methods. Overall, comprehensive results of single substance spikes were in good agreement for both methods except for few cases. Hence, two phenomena were identified: For mixed PFAS spikes of unknown composition huge differences between EOF and sum of target PFAS were observed with systematically higher EOF values. Overall, both methods indicate comparable results with MS being more reliable for known PFAS contamination and MAS being more valuable to identify PFAS exposure of unknown composition.

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Quantification and Deep Characterization of Pfass in Suspended Particulate Matter (Spm) in Timelines of German Rivers Using Comprehensive Complementary Analytical Approaches – Eof, Dtopa, (Non-)Target Hrms

Cited by 4 publications

References 0 publications

Can qualitative non-target data be indicative of PFAS contamination? First evidence by correlation with EOF in environmental samples

Can qualitative non-target data be indicative of PFAS contamination? First evidence by correlation with EOF in environmental samples

Can qualitative non-target data be indicative of PFAS contamination? First evidence by correlation with EOF in environmental samples

Investigating the uptake and fate of per- and polyfluoroalkylated substances (PFAS) in bean plants (Phaseolus vulgaris) – Comparison between target MS and sum parameter analysis via HR-CS-GFMAS

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