Annual cycles of organochlorine pesticide enantiomers in Arctic air suggest changing sources and pathways
Bibliographic record
Abstract
Abstract. Air samples collected during 1994–2000 at the Canadian Arctic air monitoring station Alert (82°30' N, 62°20' W) were analysed by enantiospecific gas chromatography–mass spectrometry for α-hexachlorocyclohexane (α-HCH), trans-chlordane (TC) and cis-chlordane (CC). Results were expressed as enantiomer fractions (EF = peak areas of (+)/[(+) + (−)] enantiomers), where EFs = 0.5, < 0.5 and > 0.5 indicate racemic composition, and preferential depletion of (+) and (−) enantiomers, respectively. Long-term average EFs were close to racemic values for α -HCH (0.504 ± 0.004, n = 197) and CC (0.505 ± 0.004, n = 162), and deviated farther from racemic for TC (0.470 ± 0.013, n = 165). Digital filtration analysis revealed annual cycles of lower α-HCH EFs in summer–fall and higher EFs in winter–spring. These cycles suggest volatilization of partially degraded α-HCH with EF < 0.5 from open water and advection to Alert during the warm season, and background transport of α-HCH with EF > 0.5 during the cold season. The contribution of sea-volatilized α-HCH was only 11% at Alert, vs. 32% at Resolute Bay (74.68° N, 94.90° W) in 1999. EFs of TC also followed annual cycles of lower and higher values in the warm and cold seasons. These were in phase with low and high cycles of the TC/CC ratio (expressed as FTC = TC/(TC+CC)), which suggests greater contribution of microbially "weathered" TC in summer–fall versus winter–spring. CC was closer to racemic than TC and displayed seasonal cycles only in 1997–1998. EF profiles are likely to change with rising contribution of secondary emission sources, weathering of residues in the environment, and loss of ice cover in the Arctic. Enantiomer-specific analysis could provide added forensic capability to air monitoring programs.
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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 | 0.001 | 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".