Comparative Study on the Characteristics of Mercury Emission from Coal-Fired Plants before and after Ultra-Low Emission Retrofitting
Bibliographic record
Abstract
In this paper, with the aid of Ontario Hydro Method (OHM), the mercury emissions from the two units with ultra-low emission retrofit are sampled and tested, then the testing data are compared and analyzed with those before the retrofitting. The testing results show that the mercury emission concentrations from the two units are 2.31 and 4.22 μg/m3 respectively, far below the limit value in the current domestic national standard. The mercury emission factors are reduced from 1.76 and 3.13 g/TJ to 0.83 and 2.17 g/TJ correspondingly, 52.84% and 30.67% of decrease. And the total mercury removal efficiencies of the retrofitted air pollution control devices with the combination of SCR+DESP+WFGD+WESP are 87.91% and 82.27%, respectively, 18.34% and 16.66% of increase compared with the efficiency of 69.57% and 65.61% of the combination of SCR+DESP+WFGD before the retrofit. These data indicate that the ultra-low emission retrofit has improved the oxidation rate of SCR to elemental mercury, and enhanced the capability of WFGD to capture mercury oxide and particulate mercury. Besides, the newly added WESP also displays a synergistic removal capability of both mercury oxide and elemental mercury. Furthermore, by improving the uniformity of SCR flow field, strengthening the maintenance of catalyst and inhibiting the reduction of mercury oxide in WFGD, the synergistic mercury removal capacity can be effectively guaranteed for the present air pollution control devices.
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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 | 0.000 |
| 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".