Emissions of SO<sub>2</sub> and NO<sub><i>x</i></sub> during Oxy−Fuel CFB Combustion Tests in a Mini-Circulating Fluidized Bed Combustion Reactor
Bibliographic record
Abstract
Anthropogenic CO 2 production is primarily driven by fossil fuel combustion, and the current energy demand situation gives no indication that this will change in the near future. In consequence, it is increasingly necessary to find ways to reduce these emissions when fossil fuel is used. CO 2 capture and storage (CCS) appears to be among the most promising approaches. All of the CCS technologies involve producing a nearly pure stream of CO 2, either by concentrating it in some manner from the flue gases or by using pure oxygen as the combustion gas. The latter option, oxy−fuel combustion, has now been well studied for pulverized coal combustion, but to date has received relatively little attention in the case of oxy−fuel circulating fluidized bed combustion (CFBC). Recently, oxy−fuel FBC has been examined in a 100 kW pilot plant operating with flue gas recycle at CanmetEnergy. The results strongly support the view that this technology offers all of the advantages of air-fired FBC, with one possible exception. Emissions such as CO or NO x are lower or comparable to those of air firing. It is possible to switch from air firing to oxy firing easily, with oxygen concentrations as high as 60−70%, and flue gas recycle levels of 50−60%. Only sulfation is poorer, which is not in good agreement with other studies, and the reasons for this discrepancy need further exploration. However, longer tests have confirmed these findings with two coals and a petroleum coke. It also appears that changing from direct to indirect sulfation with the petroleum coke improves the sulfation, although a similar effect could not be confirmed with coal from these results.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".