The Estimated Six-Year Mercury Dry Deposition Across North America
Bibliographic record
Abstract
Dry deposition of atmospheric mercury (Hg) to various land covers surrounding 24 sites in North America was estimated for the years 2009 to 2014. Depending on location, multiyear mean annual Hg dry deposition was estimated to range from 5.1 to 23.8 μg m –2 yr –1 to forested canopies, 2.6 to 20.8 μg m –2 yr –1 to nonforest vegetated canopies, 2.4 to 11.2 μg m –2 yr –1 to urban and built up land covers, and 1.0 to 3.2 μg m –2 yr –1 to water surfaces. In the rural or remote environment in North America, annual Hg dry deposition to vegetated surfaces is dominated by leaf uptake of gaseous elemental mercury (GEM), contrary to what was commonly assumed in earlier studies which frequently omitted GEM dry deposition as an important process. Dry deposition exceeded wet deposition by a large margin in all of the seasons except in the summer at the majority of the sites. GEM dry deposition over vegetated surfaces will not decrease at the same pace, and sometimes may even increase with decreasing anthropogenic emissions, suggesting that Hg emission reductions should be a long-term policy sustained by global cooperation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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; both teacher heads agree on what is shown here.
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".