Local and regional factors affecting atmospheric mercury speciation at a remote location
Bibliographic record
Abstract
Atmospheric concentrations of elemental (Hg0), reactive gaseous (RGM), and particulate (PHg) mercury were measured at two remote sites in the midwestern United States. Concurrent measurements of Hg0, PHg, and RGM obtained at Devil’s Lake and Mt. Horeb, located approximately 65 km apart, showed that Hg0 and PHg concentrations were affected by regional, as well as local sources, while RGM was mainly impacted by local sources. Plumes reaching the Devil’s Lake site from a nearby coal-fired power plant significantly impacted SO2 and RGM concentrations at Devil’s Lake, but had little impact on Hg0. Our findings suggest that traditional modeling approaches to assess sources of mercury deposited that utilize source emissions and large-scale grids may not be sufficient to predict mercury deposition at sensitive locations due to the importance of small-scale sources and processes. We suggest the use of a receptor-based monitoring to better understand mercury source–receptor relationships.
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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 | 0.001 |
| 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) | 0.000 | 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".