Seasonal and Spatial Variation of Polychlorinated Naphthalenes and Non-/Mono-Ortho-Substituted Polychlorinated Biphenyls in Arctic Air
Bibliographic record
Abstract
Archived extracts of weekly air samples collected at remote arctic monitoring stations at Alert and Tagish, Canada, and Dunai Island, Russia, in 1994-1995 were combined into 4-week composites and analyzed for levels and seasonal trends of polychlorinated naphthalenes (PCNs) and non- and mono-ortho-substituted polychlorinated biphenyls (PCBs). Mean annual sigmaPCN concentrations were 0.69, 0.82, and 0.38 pg/m3 at Alert, Dunai, and Tagish, respectively. PCNs exhibited a seasonal trend at Alert and Dunai, with higher levels occurring during winter when air masses originating over Eurasia influence the high arctic and coincide with the haze period. Episodic, trans-Pacific transport impacted PCN concentrations at Tagish. A seasonal trend was not evident for the non-/mono-o-PCBs. The contrary PCN and non-/mono-o-PCB trends indicate that the sources of these two compound classes to arctic air differ, and that atmospheric transport from source regions has a greater influence on PCN levels than for non-/ mono-o-PCBs. PCNs apparently originating from combustion sources contribute to levels in winter, as indicated by the presence of combustion marker congeners, but evaporative emissions from source regions are likely the dominant source. PCNs contributed 71 and 75% of dioxin toxic equivalents (TEQ) relative to the non-/mono-o-PCBs at Alert and Dunai and 30% at Tagish during the winter months, demonstrating the toxicological importance of PCNs as a compound class relative to PCBs.
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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 | 0.000 | 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".