ABSTRACT: Loadings of atmospheric
Bibliographic record
Abstract
mercury to Lake Erie were numerically simulated with the use of speciated Hg emission scenarios from a coal fired power plant on the shore of Lake Erie in Ontario. Three-dimensional numerical modeling experiments were conducted using the BLFMAPS-a Mesoscale Boundary Layer forecast and Air pollution prediction system. The modeling system was utilized to simulate meteorology and the air concentration, dry deposition, wet deposition and air-water exchange of Hg species. Simulations were done for Hg containing particulates with three aerodynamic particle diameters of small (0.25μm), medium (4μm), and large (20μm). The numerical experiments exhibited the different characteristics of Hg concentration and deposition patterns of particulate Hg (P-Hg), gaseous elemental Hg (GEM) and reactive gaseous Hg (RGM). For three out of four emission scenarios RGM is found to be the dominant contributor of the three species of Hg to the Lake Erie loading. The contribution of particulate Hg to the net loading, is relatively small with coarser particles having a stronger deposition rate than finer particles. Fine particles have a longer lifetime in the atmosphere and transport over long distances. 28 % of the coarse particle and 7 % of fine particle emissions were deposited within 100 km of the power plant. Our experiments also suggest that a case with a larger GEM portion of emission (about 90 % of total Hg emission) will have the least amount of total Hg loading to the Lake Erie. Comparison of model results of surface air
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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 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".