Life-cycle assessment of solid waste management in Dhulikhel Municipality, Nepal
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
Solid waste management is becoming a major environmental and public health concern in emerging municipalities in Nepal. In this study, the life-cycle assessment (LCA) approach is used to address the environmental impacts of potential waste-treatment scenarios in Dhulikhel Municipality in Nepal. The assessment was based on four different scenarios – namely, scenario 1, landfilling; scenario 2, composting combined with landfilling; scenario 3, recycling, composting and landfilling; and scenario 4, recycling, anaerobic digestion and landfilling. The LCA methodology was developed, including the benefits and impact potentials of different unit processes in each scenario, also taking into consideration emissions from energy use. The environmental impacts from the scenarios were compared in terms of global warming potential, acidification potential and eutrophication potential. Among the four scenarios, scenario 4 (i.e. with anaerobic digestion) showed the most environmental advantage. Scenarios without biological treatment facilities are the least preferred option, as their impact is significantly greater than those of other options. Therefore, organic waste is recommended not to be disposed of in landfill sites even if the transportation activity increases, because the magnitude of methane avoidance increases with an increased amount of waste diversion to the biological treatment units.
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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 | 0.001 | 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 | 0.001 |
| 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