Are PCBs in the Canadian Arctic Atmosphere Declining? Evidence from 5 Years of Monitoring
Bibliographic record
Abstract
A long-term database of weekly air concentrations was examined to establish temporal trends of PCBs in the Arctic atmosphere. Several methods were employed to reduce the intra-annual variability allowing the elucidation of longterm trends for a selection of congeners at Alert located in the Canadian Arctic. These methods included temperature normalization (TN), multiple linear regression (MLR), and digital filtration (DF). Estimation of the slope (m) resulting from the linear regression between the natural logarithm of the partial pressure in air versus reciprocal temperature (In P = m/T + b), required for TN and MLR, proved difficult due to the poor correlation with temperature experienced forthe majority of congeners. Values of m were considerably lower than those obtained from temperate studies, implying that regional air-surface exchange plays a minor role in supporting the observed air concentrations in the Arctic. The lighter congeners generally showed very low slopes, and some even showed positive correlation with 1/T. This might be a result of their relatively fast reaction rates with OH radicals following the onset of 24-h sunlight in spring. Use of DF (in combination with TN and MLR) revealed declining trends for several of the lower chlorinated congeners in the high Arctic atmosphere, with estimated first-order half-lives, t1/2, ranging from approximately 3 to 20 yr. Declining trends of the lower congeners probably reflect falling levels in source regions, as a result of long-range transport to this Arctic site. There were no apparent trends for the higher chlorinated congeners (penta-substituted and above), exceptfor PCB 180, in marked contrast to temperate studies, indicating a lag time for decline between the Arctic and source regions.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".