Effect of recycling activities on the heating value of solid waste: case study of the Greater Vancouver Regional District (Metro Vancouver)
Bibliographic record
Abstract
Two main goals of the integrated solid waste management system (ISWMS) of Metro Vancouver (MV) include further recycling of waste and energy recovery via incineration of waste. These two very common goals, however, are not always compatible enough to fit in an ISWMS depending on waste characteristics and details of recycling programs. This study showed that recent recycling activities in MV have negatively affected the net heating value (NHV) of municipal solid waste (MSW) in this regional district. Results show that meeting MV's goal for additional recycling of MSW by 2015 will further reduce the NHV of waste, if additional recycling activities are solely focused on more extensive recycling of packaging materials (e.g. paper and plastic). It is concluded that 50% additional recycling of paper and plastic in MV will increase the overall recycling rate to 70% (as targeted by the MV for 2015) and result in more than 8% reduction in NHV of MSW. This reduction translates to up to 2.3 million Canadian dollar (CAD$) less revenue at a potential waste-to-energy (WTE) plant with 500 000 tonnes year(-1) capacity. Properly designed recycling programmes, however, can make this functional element of ISWMS compatible with green goals of energy recovery from waste. Herein an explanation of how communities can increase their recycling activities without affecting the feasibility of potential WTE projects is presented.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".