Techno‐economic assessment of CO<sub>2</sub> capture from aluminum smelter emissions using PZ activated AMP solutions
Bibliographic record
Abstract
In order to reduce its greenhouse gas emissions without drastically changing currently‐used processes, the primary aluminum industry will need to consider capturing CO2 released in the electrolytic cells. In order to make the capture more economically attractive to the aluminum industry, the possibility of using a blended amine absorption solution which combines the advantages of two different amines (a fast reactivity from a cyclic polyamine, piperazine (PZ), and a high absorption capacity and low regeneration cost from a sterically‐hindered alkanolamine) is considered in this work. Specific to an aluminum plant, not only the costs and benefits of a CO2 capture facility are evaluated, but also the possibility and cost of coupling the capture process with a waste heat recovery strategy. A mixture of 0.08 g/g PZ and 0.32 g/g AMP appears to be the most appropriate, reducing the capital costs by 25 % and operating costs by 29 % compared to the use of MEA (monoethanolamine) solutions. The capture cost is evaluated to be 65.10 $/ton of CO2 avoided (without carbon tax). A thermal integration of the capture plant within the primary aluminum smelter could further reduce the cost to 57.57 $/ton of CO2 avoided, or equivalently, 69.56 $/ton of Al produced (without carbon tax).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".