CO2 processing and multi-pollutant control for oxy-fuel combustion systems using an advanced CO2 capture and compression unit (CO2CCU)
Bibliographic record
Abstract
Oxy-fuel combustion of fossil fuels produces a CO2-rich gas stream with some impurities, such as nitrogen, argon, oxygen, nitrogen oxides, heavy metals and sulphur oxides, whose concentrations vary based on the type of fuel, combustion conditions, plant configuration, and other process related parameters. To control the greenhouse gas (GHG) emissions from these plants and sustain their operational competitiveness in a carbon constrained world, the CO2 in the flue gas stream has to be captured, cleaned up and compressed to make it suitable for pipeline transport and permanent storage in geological formations. The flue gas CO2 capture and processing, including integrated multi-pollutant control, provides a feasible and viable technological pathway towards this goal. For oxy-fuel combustion systems, the CO2 capture is best achieved by physical gas separation through a series of compression and cooling stages to liquefy and separate CO2 from non-condensable gases in the flue gas stream. The effectiveness of the CO2 capture and compression system depends on the process design and assessed using removal efficiency, level of purification and energy demand for a unit of captured CO2. If the CO2 capture process can also simultaneously remove other pollutants in the gas stream, then the whole process becomes more efficient and cost-effective. In this case, implementing an elaborate flue gas pre-treatment system will not be necessary. Hence, CO2 capture technologies that are capable of simultaneously controlling emissions of multiple pollutants offer the potential to achieve emissions reduction at lower cost and reduced footprint, when compared to conventional emission control systems. For the new oxy-coal fired power plants, multi-pollutant control technologies can help designers of these plants select effective and less expensive compliance strategies, compared with compliance choices made when the requirements are addressed individually. CanmetENERGY has developed and successfully implemented an advanced and proprietary CO2 capture and compression unit (CO2CCU) that is capable of capturing and generating a relatively pure CO2 product stream, while simultaneously removing the pollutants such as nitrogen oxides, sulphur oxides and mercury in the process condensate streams. The pilot-scale unit is currently integrated with the existing 0.3 MWth oxy-fuel Vertical Combustor Research Facility. This advanced CO2 capture system represents an integrated approach to oxy-fuel combustion with multi-pollutant and CO2 capture and provides a unique test platform for CO2 processing. In this paper, we present and discuss the recent pilot-scale test results of CanmetENERGY’s CO2CCU. The unit was used to conduct experiments with a broad range of flue gas compositions, including different levels of CO2 concentrations and a host of impurities in the flue gas stream. The real-time measurements of CO2 product and vent stream gas compositions as well as the analysis of condensate streams provide insight into the type of chemical reactions that are taking place under different pressure, temperature, and moisture levels. The experimental results help to explain some of the chemical reactions involved in the CO2 capture and compression for better optimizing the capture process.
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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 | 0.001 | 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".