Ombrotrophic Peat Bogs Are Not Suited as Natural Archives To Investigate the Historical Atmospheric Deposition of Perfluoroalkyl Substances
Bibliographic record
Abstract
As ombrotrophic peat bogs receive only atmospheric input of contaminants, they have been identified as suitable natural archives for investigating historical depositions of airborne pollutants. To elucidate their suitability for determining the historical atmospheric contamination with perfluoroalkyl substances (PFAS), two peat cores were sampled at Mer Bleue, a bog located close to Ottawa, Canada. Peat cores were segmented, dried, and analyzed in duplicate for 25 PFASs (5 perfluororalkyl sulfonates (PFSAs), 13 perfluoroalkyl carboxylates (PFCAs), 7 perfluororalkyl sulfonamido substances). Peat samples were extracted by ultrasonication, cleaned up using a QuEChERS method, and PFASs were measured by HPLC-MS/MS. Twelve PFCAs and PFSAs were detected regularly in peat samples with perfluorooctane sulfonate (85-655 ng kg(-1)), perfluorooctanoate (150-390 ng kg(-1)), and perfluorononanoate (45-320 ng kg(-1)) at highest concentrations. Because of post depositional relocation processes within the peat cores, true or unbiased deposition fluxes (i.e., not affected by post depositional changes) could not be calculated. Apparent or biased deposition rates (i.e., affected by post depositional changes) were lower than measured/calculated deposition rates for similar urban or near-urban sites. Compared to PFAS production, PFAS concentration and deposition maxima were shifted about 30 years toward the past and some analytes were detected even in the oldest segments from the beginning of the 20th century. This was attributed to PFAS mobility in the peat profile. Considerable differences were observed between both peat cores and different PFASs. Overall, this study demonstrates that ombrotrophic bogs are not suited natural archives to provide authentic and reliable temporal trend data of historical atmospheric PFAS deposition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".