An Analysis of the Factors Exercising an Influence on the Morphological Transformation of Mercury in the Flue Gas of a 600 MW Coal-fired Power Plant
Bibliographic record
Abstract
Mercury emissions from coal-fired power plants are regarded as the largest pollution source of man-made mercury emissions in nature. Hence,to perform an on-the-spot testing of the mercury emission concentration in various forms from a coal-fired power plant is of vital significance for understanding and controlling the law and regularity of mercury emissions. With the internationally accepted Ontario Hydro method being adopted to sample the flue gas before and after an electrostatic precipitator (ESP) in a 600 MW coal-fired power plant,the American EPA (Environmental Protection Agency) standard method was used to determine Hg0,Hg2+and HgP concentration in the flue gas,and DMA 80 was employed to ascertain the mercury concentration in solid samples (coal,bottom ash,ESP fly ash). The testing results show that when the flue gas passes through the ESP,the morphology of the mercury contained in the flue gas will undergo a remarkable change. The percentage of Hg2+ will increase from 14.71% to 39.54%,that of Hg0 will decrease from 85.19% to 60.38% and that of HgP will drop from 0.10% to 0.08%. The chlorine in coal and NOx,SO2,HCl,Cl2 in the flue gas assume a positive correlation to the formation of oxidized mercury in the flue gas.
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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".