Perfluorinated Acids in Arctic Snow: New Evidence for Atmospheric Formation
Bibliographic record
Abstract
Perfluorinated acids (PFAs) are ubiquitously found in water and biota, including remote regions such as the High Arctic. Under environmental conditions, PFAs exist mainly as anions and are not expected to be subject to long-range atmospheric transport in the gas phase. Fluorinated telomer alcohols (FTOHs) are volatile and can be atmospherically oxidized to form perfluorocarboxylic acids. Analogously, fluorosulfamido alcohols can be oxidized to form perfluorooctane sulfonate (PFOS). High Arctic ice caps experience contamination solely from atmospheric sources. By examining concentrations of PFAs in ice cap samples, it is possible to determine atmospheric fluxes to the Arctic. Ice samples were collected from high Arctic ice caps in the spring of 2005 and 2006. Samples were concentrated using solid-phase extraction and analyzed by LC-MS-MS. PFAs were observed in all samples, dating from 1996 to 2005. Concentrations were in the low-mid pg L(-1) range and exhibited seasonality, with maximum concentrations in the spring-summer. The presence of perfluorodecanoic acid (PFDA) and perfluoroundecanoic acid (PFUnA) on the ice cap was indicative of atmospheric oxidation as a source. Ratios of PFAs to sodium concentrations were highly variable, signifying PFA concentrations on the ice cap were unrelated to marine chemistry. Fluxes of the PFAs were estimated to the area north of 65 degrees N for the 2005 season, which ranged from 114 to 587 kg year(-1) for perfluorooctanoic acid (PFOA), 73 to 860 kg year(-1) for perfluorononanoic acid (PFNA), 16 to 84 kg year(-1) for PFDA, 26 to 62 kg year(-1) for PFUnA, and 18 to 48 kg year(-1) for PFOS. The PFOA and PFNA fluxes agreed with FTOH modeling estimations. A decrease in PFOS concentrations through time was observed, suggesting a fast response to changes in production. These data suggest that atmospheric oxidation of volatile precursors is a primary source of PFAs to the Arctic.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".