Spatial and Temporal Trends of Chiral Organochlorine Signatures in Great Lakes Air Using Passive Air Samplers
Bibliographic record
Abstract
Passive air samples (PAS) were collected and analyzed to assess the spatial and temporal trends of chiral organochlorine signatures in the Laurentian Great Lakes. Samples were collected from 15 sites and analyzed for the concentrations and enantiomer signature of chlordanes and alpha-hexachlorocyclohexane (alpha-HCH). Levels of the chlordanes were typically 4 times higher in urban areas than what were observed at rural and remote locations, exhibiting strong urban-rural gradients. Near racemic residues were seen for the chlordane enantiomers in samples collected from sites located in Toronto and Chicago, which can be attributed to continued emissions of historical use of the technical chlordane mixture, while the chiral signature observed at sites located in rural and remote locations was indicative of an aged source. Knowledge of the spatial and temporal distribution of the enantiomer signatures of chlordane and alpha-HCH in air is useful for distinguishing sources of these compounds to ambient air. Results suggest that potential sources, such as those associated with Toronto and Chicago, have limited influence over the levels at rural and remote sites within the Great Lakes. Sources that are relatively close to sample sites, however, have a strong influence on levels observed at those sites. For instance, results indicate that Lake Superior continues to act as a source of alpha-HCH to sites located on its shores. Generally, it appears that during the warmer months, local enhanced surface-air exchange influences air concentrations and that during the cooler periods of the year, levels in the atmosphere are more strongly influenced by advective transport from 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 | 0.000 | 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".