Potential for Thermo-Chemical Conversion of Solid Waste in Canada to Fuel, Heat, and Electricity
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 amount of municipal solid waste (MSW) generation in Canada was 34 million tonnes in 2018. Responsible waste management is challenging, but essential to protect the environment and to prevent the contamination of the ecosystem on which we rely. Landfilling is the least desirable option, and diversion through thermo-chemical conversion to value-added products is a good option for difficult-to-recycle waste. In this study, the amounts, moisture contents, heating values, and compositions of municipally collected solid waste produced in Canada are reported, a classification that is suitable for conversion purposes is proposed, and the potential for thermo-chemical conversion is determined. Much of the waste generated in Canada is suitable for being converted, and its potential for heat or electricity generation was determined to be 193 PJ/yr and 37 TWh/y, respectively. The GHG emissions that are saved through diversion from the landfill, while assuming the generated heat or electricity offsets natural gas combustion, gives a GHG reduction of 10.6 MMTCO2E/yr or 1.6% of Canada’s GHG emissions. The blending of waste in feedstocks can have varying effects on the amount of biogenic CO2 produced per unit energy in the feedstock, which is an important consideration for new projects. Other considerations include the heating values, moisture contents, and contaminant levels in the waste.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 it