The adaptation of waste-to-energy technologies: towards the conversion of municipal solid waste into a renewable energy resource
Bibliographic record
Abstract
Currently, there are an estimated 1.3 billion tonnes of municipal solid waste (MSW) generated per year globally, and this quantity is predicted to increase to 2.2 billion tonnes annually by 2025. If not well treated, this rapid growth of waste products can lead to socio-economic and environmental problems. Waste is potentially a misplaced valuable resource that can be converted and utilized in different ways such as renewable energy resources for the realization of sustainable development. Presently, waste-to-energy technologies (WtETs) are considered to be an encouraging advanced technology that is applied to convert MSW into a renewable energy resource (methane, biogas, biofuels or biodiesel, ethanol, syngas, or alcohol). WtETs can be biochemical (fermentation, anaerobic digestion, landfill with gas capture, and microbial fuel cell), thermochemical (incineration, thermal gasification, and pyrolysis), or chemical (esterification). This review mainly aims to provide an overview of the applications of these technologies by focusing on anaerobic digestion as biological (nonthermal) treatment technologies, and incineration, pyrolysis, and gasification processes as thermal treatment processes. Landfill gas utilization technologies, biological hydrogen production processes, and microbial fuel cells also are assessed. In addition, the contemporary risks and challenges of WtETs are reviewed.
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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) | 0.000 | 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 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".