Influence of the SCR(Selective Catalytic Reduction)-based NO_x Removal System on Mercury Morphology in Coal-fired Flue Gas
Bibliographic record
Abstract
By adopting the standard Ontario method,measured and analyzed were the morphological distribution of mercury in flue gas before and after the selective catalytic reduction(SCR) denitrification system of a 300 MW unit.In combination with the chemical theory for SCR reactions to remove NOx,the influence of a SCR-based denitrification system on the mercury morphology of coal-fired flue gas was studied as a key problem.It has been found that the SCR catalyzer(V2O5-WO3(MoO3)/TiO2) plays a relatively small role of adsorbing the mercury in flue gas and has no influence on the total mercury concentration in flue gas.However,after a SCR,the mercury morphology in gas state underwent a relatively great change with the HgO concentration decreasing from 49.01% to 7.30% while the Hg2+ concentration increasing from 38.96% to 82.67%.The NH3 in the SCR-based denitrification system plays no role in transforming the mercury morphology.The oxidation of HgO by HCl was mainly completed through the Cl-Deacon reaction and the intermediate(HgO) under the catalytic action of the system and,eventually,HgCl2 was formed.
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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) | 0.001 | 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".