Mercury speciation in a coal‐fired power plant plume: An aircraft‐based study of emissions from the 3640 MW Nanticoke Generating Station, Ontario, Canada
Bibliographic record
Abstract
Abstract Coal‐fired power plants are one of the principal sources of mercury to the atmosphere. The form this mercury takes is the predominant factor determining its fate after emission. Recent ground‐level field and modeling studies suggest that oxidized mercury in stack emissions is converted into elemental mercury in the plume. We present here aircraft‐based plume mercury measurements taken by Environment Canada in 2000 at the Nanticoke Generating Station as part of the Health Canada Toxic Substances Research Initiative Metals in the Environment Research Network. Although the average mercury speciation observed in the Nanticoke plume (82% Hg0, 13% Hg(II)(g), 5% Hg(P), by mass) appears to be distinct from the average mercury speciation in the Nanticoke stacks (53% Hg0, 43% Hg(II)(g), 4% Hg(P)), we find that the in‐plume elemental mercury concentrations as a whole can be explained by plume dilution after emission. The discrepancy between in‐stack and in‐plume Hg(II) concentrations is statistically significant, yet is not associated with a transformation of Hg(II) to Hg0. Sampling biases associated with the differing techniques used to measure Hg(II) in‐stack and in‐plume may reconcile the concentration discrepancy without invoking novel chemical reactions or physical processes. Although the mercury speciation of the Nanticoke plume influences local mercury deposition, the majority of the mercury emitted is transported out of the surrounding area.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".