Cost benefit analysis of grid-based electrolytic ammonia production across Canadian provinces
Bibliographic record
Abstract
Efforts, such as electrification, are being made to reduce the greenhouse gas emissions in ammonia production, which is traditionally a carbon-intensive process due to the use of natural gas. This research aimed to analyze the viability of electrification, i.e., grid-powered electrolytic ammonia in Canada. Using the concept of levelized cost of ammonia (LCOA), three processes were compared: The conventional process (P1), the conventional with carbon capture and storage (CCS) process (P2), and the grid electrolytic ammonia process (P3). The processes were compared across Canada's ten provinces with different forecasted grid emissions, electricity costs, and natural gas costs across 2026–2050 under two forecasted policies: Current Measures (CM) and Canada Net Zero (CNZ). Results show that CNZ policies make it more economically viable to produce grid-powered electrolytic ammonia. The findings also estimate that P3 costs 500–700 CAD more per tonne than P1, while P2 costs about 200 CAD more. However, when considering the social cost of carbon (SCC), P3 can be competitive with P1, showing the importance of considering environmental damages in the decision-making. Each province has different production costs because of varying grid emissions and power prices, with P2 being the most cost-efficient way to cut down on carbon in Canadian ammonia production for most of the provinces. Alberta and Saskatchewan are the best provinces for P2, while Manitoba and Quebec are the best for P3. Lowering grid emissions and costs is essential to the viability of electrolytic grid-based ammonia. • Blue ammonia can be more cost-effective in reducing carbon emissions. • Quebec and Manitoba are favorable provinces for electrolytic ammonia production. • Advancements in electrolytic ammonia production are required to lower its costs. • Social costs of carbon need to be considered in ammonia production.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".