Multi-measure pathways for achieving carbon-neutral cement production
Bibliographic record
Abstract
Greenhouse gas (GHG) emissions from cement production continue to rise, making it the second-largest source of industrial GHG emissions. In this study, we develop a framework to evaluate several decarbonization technologies and scenarios to achieve carbon-neutral cement production. A case study for Canada was conducted using this developed framework. Decarbonization technologies are grouped into six categories (energy efficiency, fuel switching, alternative raw materials, alternative binders and chemistries, carbon capture and storage, and cement carbonation) and each is evaluated using a bottom-up technology-explicit energy model. The results show that carbon-neutral cement production can be achieved before 2050 with marginal abatement costs of −17 to −34 CAD/t CO 2 e and cumulative GHG emissions reductions of 199–242 Mt. CO 2 e, based on a carbon price of 170 CAD/t CO 2 by 2030. The results are comparable to roadmaps from other jurisdictions but with some important distinctions. Canada continues to have a higher clinker/cement ratio and lower alternative fuel consumption than other jurisdictions, meaning carbon capture and storage is expected to play a larger role in reducing GHG emissions. Furthermore, carbon neutrality cannot be achieved without carbonation or a similar offset. Therefore, it is important that all cement-producing regions begin formalizing a framework to guide the calculation of carbonation impacts and compile the information to support those calculations. Finally, a sensitivity analysis concluded that carbon pricing is required in every carbon-neutral scenario to achieve negative GHG emissions abatement costs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".