Electricity Production\nfrom Anaerobic Digestion of\nHousehold Organic Waste in Ontario: Techno-Economic and GHG Emission\nAnalyses
Bibliographic record
Abstract
The first Feed-in-Tariff (FiT) program in North America\nwas recently\nimplemented in Ontario, Canada to stimulate the generation of electricity\nfrom renewable sources. The life cycle greenhouse gas (GHG) emissions\nand economics of electricity generation through anaerobic digestion\n(AD) of household source-separated organic waste (HSSOW) are investigated\nwithin the FiT program. AD can potentially provide considerable GHG\nemission reductions (up to 1 t CO<sub>2</sub>eq/t HSSOW) at relatively\nlow to moderate cost (-$35 to 160/t CO<sub>2</sub>eq) by displacing\nfossil electricity and preventing the emission of landfill gas. It\nis a cost-effective GHG mitigation option compared to some other FiT\ntechnologies (e.g., wind, solar photovoltaic) and provides unique\nadditional benefits (waste diversion, nutrient recycling). The combination\nof electricity sales at a premium rate, savings in waste management\ncosts, and economies of scale allow AD facilities processing >30,000\nt/yr to be cost-competitive against landfilling. However, the FiT\ndoes not sufficiently support smaller-scale facilities that are needed\nas a transition to larger, more economically viable facilities. Refocusing\nof the FiT program and waste policies are needed to support the adoption\nof AD of HSSOW, which has not yet been developed in the Province,\nwhile more costly technologies (e.g., photovoltaic) have been deployed.
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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 | 0.000 | 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) | 0.014 | 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".