Fate and Transport of Perfluoroalkyl Substances from Snowpacks into a Lake in the High Arctic of Canada
Bibliographic record
Abstract
The delivery of perfluoroalkyl substances (PFAS) from snowpacks into Lake Hazen, located on Ellesmere Island (Nunavut, Canada, 82° N) indicates that annual atmospheric deposition is a major source of PFAS that undergo complex cycling in the High Arctic. Perfluoroalkyl carboxylic acids (PFCA) in snowpacks display odd-even concentration ratios characteristic of long-range atmospheric transport and oxidation of volatile precursors. Major ion analysis in snowpacks suggests that sea spray, mineral dust, and combustion aerosol are all relevant to the fate of PFAS in the Lake Hazen watershed. Distinct drifts of light and dark snow (enriched with light absorbing particles, LAPs) facilitate the study of particle loads on the fate of PFAS in the snowpack. Total PFAS (ΣPFAS, ng m –2 ) loads are lower in snowpacks enriched with LAPs and are attributed to reductions in snowpack albedo combined with enhanced post-depositional melting. Elevated concentrations of PFCA are observed in the top 5 m of the water column during snowmelt periods compared to ice-covered or ice-free periods. PFAS concentrations in deep waters of the Lake Hazen water column were consistent between snowmelt, ice-free, and ice-covered periods, which is ascribed to the delivery of dense and turbid glacier meltwaters mixing PFAS throughout the Lake Hazen water column. These observations highlight the underlying mechanisms in PFAS cycling in High Arctic Lakes particularly in the context of increased particle loads and melting.
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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 | 0.003 | 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) | 0.001 | 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".