Concentrations, Trends, and Air–Water Exchange of PAHs and PBDEs Derived from Passive Samplers in Lake Superior in 2011
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) and polybrominated diphenylethers (PBDEs) are both currently released into the environment from anthropogenic activity. Both are hence primarily associated with populated or industrial areas, although wildfires can be an important source of PAHs, as well. Polyethylene passive samplers (PEs) were simultaneously deployed in surface water and near surface atmosphere to determine spatial trends and air-water gaseous exchange of 21 PAHs and 11 PBDEs at 19 sites across Lake Superior in 2011. Surface water and atmospheric PAH concentrations were greatest at urban sites (up to 65 ng L(-1) and 140 ng m(-3), respectively, averaged from June to October). Near populated regions, PAHs displayed net air-to-water deposition, but were near equilibrium off-shore. Retene, probably depositing following major wildfires in the region, dominated dissolved PAH concentrations at most Lake Superior sites. Atmospheric and dissolved PBDEs were greatest near urban and populated sites (up to 6.8 pg L(-1) and 15 pg m(-3), respectively, averaged from June to October), dominated by BDE-47. At most coastal sites, there was net gaseous deposition of BDE-47, with less brominated congeners contributing to Sault Ste. Marie and eastern open lake fluxes. Conversely, the central open lake and Eagle Harbor sites generally displayed volatilization of PBDEs into the atmosphere, mainly BDE-47.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".