D302 EMISSIONS OF MERCURY AND OTHER TRACE ELEMENTS FROM A COAL-FIRED POWER PLANT(Environment Protection-4)
Bibliographic record
Abstract
This paper provides details concerning emissions of mercury and other trace elements conducted at a coal-fired power plant with SCR and wet FGD. Mercury emission concentration and its speciation were measured with Ontario Hydro Method (OHM) and Semi-continuous emission monitor (SCEM). The emission of trace elements was determined by EPA method 29. Mercury mass balance and partitioning of trace elements were analyzed based on the analyses of solid samples (such as: coal, bottom ash, fly ash, and flue gas desulphurization (FGD) slurry) and concentration of trace elements in the flue gas. The results indicated that total mercury (Hg^T, sum of Hg^0, Hg^<2+>, and Hg^P) remained relatively constant along the flue gas path before passing through FGD. The ratio of Hg^<2+> to Hg^ increased from 45.7% to 83.3% after flue gas passed through SCR. Hg monitoring methods of OHM and SCEM agreed that over 95% of Hg in flue gas was in oxidized form before FGD. The mercury removal efficiency of FGD was more than 96%. A better ratio of Hg output to Hg input (within the range of 0.8 to 1.2) was obtained while Hg content in ashes reached a dateable level. The emission concentration of each element was very low, and the change of the gaseous phase compositions of the selected trace elements was found insignificantly throughout the flue gas path. Mercury and Selenium are almost fully released in the gaseous phase. The main proportion of other trace elements is bound with the fly ash and collected in the electrostatic precipitator (ESP).
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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 | 0.000 | 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) | 0.002 | 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".