Wind‐Powered Green Urea Production for Greenhouse Agriculture: A Technoeconomic and Environmental Assessment
Bibliographic record
Abstract
This study explores the feasibility of integrating green urea production with greenhouse operations in Southern Ontario, utilizing wind energy. The technoeconomic assessment shows that the levelized cost of urea (LCOU) is USD 775 per metric ton, which is more than twice the conventional price of USD 337 per metric ton. However, when compared to the maximum historical selling price of USD 925 per metric ton, the integrated system has a payback period (PBT) of 4.2 years, a discounted payback period (DPB) is 5.7 years, and an internal rate of return (IRR) is 23.3%. These figures indicate economic viability, but sensitivity analysis highlights risk from market fluctuations. A selling price drop to USD 777 per metric ton extends PBT to 8.2 years and reduces IRR to 10.2%, while a worst‐case scenario with a price of USD 667 per metric ton renders the project financially unfeasible. Despite its higher LCOU, the system offers substantial environmental advantages, potentially lowering from 4.67 kg of CO 2 emissions kg −1 of pepper produced to zero, or even achieving a carbon‐negative footprint. By eliminating direct CO 2 emissions, this approach creates opportunities for premium pricing, carbon credit incentives, and the promotion of sustainable agriculture.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".