Vertical distribution of gaseous elemental mercury in Canada
Bibliographic record
Abstract
Measurements of gaseous elemental mercury (GEM) were made in three locations in Canada at altitudes from 0.1 to 7 km. In the summer in southeastern Canada, northwesterly winds bring air with a constant mixing ratio of GEM at altitudes up to 7 km, with a concentration near 1.5 nanograms per standard cubic meter of air (ng sm−3). In the winter in southern and central Ontario the mixing ratio is still approximately constant with altitude, but the concentration is 1.7 ng sm−3. In the spring in the Arctic the concentration of gaseous elemental mercury at altitudes above 1 km is near 1.7 ng sm−3; however, there is evidence of episodic depletion of elemental mercury near the surface with mixing of depleted air to altitudes of 1 km. Measurements of GEM in cloud interstitial air and of mercury in cloud water indicate that the influence of a single cycling of air through cloud has little effect on the concentration of GEM. The GEM in air masses transported over the relatively unpopulated terrain of northern Canada during the summer indicates a lower limit of 5000 ng m−2 for an atmospheric column from the surface to 5 km. This gives a global burden of at least 2500 t for that altitude range. These data demonstrate the existence of a vast pool of mercury aloft, provide evidence for a long atmospheric lifetime, and illustrate the potential for long‐range atmospheric transport of this metal at altitudes up to at least 7 km.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".