Electricity Production from Anaerobic Digestion of Household Organic Waste in Ontario: Techno-Economic and GHG Emission Analyses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The first Feed-in-Tariff (FiT) program in North America was recently implemented in Ontario, Canada to stimulate the generation of electricity from renewable sources. The life cycle greenhouse gas (GHG) emissions and economics of electricity generation through anaerobic digestion (AD) of household source-separated organic waste (HSSOW) are investigated within the FiT program. AD can potentially provide considerable GHG emission reductions (up to 1 t CO(2)eq/t HSSOW) at relatively low to moderate cost (-$35 to 160/t CO(2)eq) by displacing fossil electricity and preventing the emission of landfill gas. It is a cost-effective GHG mitigation option compared to some other FiT technologies (e.g., wind, solar photovoltaic) and provides unique additional benefits (waste diversion, nutrient recycling). The combination of electricity sales at a premium rate, savings in waste management costs, and economies of scale allow AD facilities processing >30,000 t/yr to be cost-competitive against landfilling. However, the FiT does not sufficiently support smaller-scale facilities that are needed as a transition to larger, more economically viable facilities. Refocusing of the FiT program and waste policies are needed to support the adoption of AD of HSSOW, which has not yet been developed in the Province, while more costly technologies (e.g., photovoltaic) have been deployed.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 it