Assessing the Shifts in Atmospheric Per- and Polyfluoroalkyl Substances (PFAS) Levels in the Great Lakes and Implications for the Environmental Transport and Fate
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide This study presents the first multiyear investigation of per- and polyfluoroalkyl substances (PFAS) in the atmosphere over the Great Lakes. The levels of ∑PFAS exhibit a broad range from 2.9 to 280 pg/m 3 . Higher concentrations of PFAS at the urban-influenced site compared to the rural site signified spatial variability between the two sampling locations. Despite the absence of a consistent seasonal pattern, concentrations of perfluorooctanoic acid (PFOA) and neutral PFAS (nPFAS) tend to be higher during the summer months. This pattern appears to be influenced by the seasonal variations of air back trajectories and potential influences from south of the sampling site. The study elucidates potential shifts in atmospheric PFAS dynamics during the COVID-19 pandemic. Applying a modified model with a probabilistic approach, we investigated the transport and fate of PFOA and perfluorooctanesulfonic acid (PFOS) within Lake Ontario. The estimated loadings of PFOA and PFOS from air-to-water were 9.5 ± 3.6 and 17 ± 6.6 kg/y, respectively, close to the values from wet deposition (10 ± 3.9 and 31 ± 12 kg/y, respectively) but much lower than those from inflow and all other sources. The primary output pathways for PFOA and PFOS were from water outflow.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".