An economic assessment of renewable natural gas (RNG) as a potential low carbon intensity fuel alternative eligible under Canada’s Clean Fuel Regulations
Bibliographic record
Abstract
The purpose of this project is to determine whether the production of renewable natural gas (RNG) using corn stover or dairy cow manure in Canada is economically feasible using a discounted cash flow analysis. Further, this work seeks to determine if there is sufficient, reliable feedstock to sustain desired production levels over the lifetime of a production facility. This project also evaluates the effect of Canada’s newly introduced Clean Fuel Regulation (CFR) and CFR credit sales on the profitability of RNG production. This work calculates that the cost to generate a credit under the CFR using manure or stover based RNG production can be as low as $315 or more than $28,000 under unfavourable circumstances. This work provides better understanding of the economic challenges of RNG, showing that feedstock acquisition and transportation costs significantly impact a projects’ ability to be profitable, leading to credit generation costs which are not competitive.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".