Characteristics of mercury emission and demercurization property of NID system of a 410t/h pulverized coal fired boiler
Bibliographic record
Abstract
Coal, slag, and fly ashes were sampled from a 410t/h utility boiler with the equipment of NID (Novel Integrated Desulfurization) system and mercury concentrations of these samples were determined. OntarioHydro method was applied to determine mercury speciation in flue gas before NID and after ESP. The experimental data indicate that the majority of mercury goes into fly ash. The ratio of mercury quantity in fly ash to total combustion product is about 90%, while that in flue gas is about 10%. The results also show that before NID and after ESP, the gaseous mercury concentration in the flue gas is about 21.3μg/m3~22.4μg/m3 and 1.93μg/m3~3.67μg/m3 respectively, indicating that the NID system has quite high mercury removal efficiency up to 83.6%~90.9%. The percentage of Hg2+ which is the main mercury speciation in flue gas before NID is about 67%. The percentage of Hg2+ in flue gas after ESP is about 71.8%~85.1%, while the content of Hg0 is zero, indicating that some chemical reactions have been happened to Hg0 when it passes by NID system. Hg0 becomes Hg2+ and is then adsorbed and removed.
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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) | 0.000 | 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 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".