Optimization of Waste Collection System Using Underground Containers with Source Separation Plan (Case Study: Zone 3 of Yazd Municipality, Iran)
Bibliographic record
Abstract
Introduction: Optimization of waste collection systems can reduce waste management costs. In this study, optimization of the waste collection system of zone 3 of Yazd municipality of Iran, has been investigated using underground containers. Materials and Methods: In this research, after collecting information and performing field inspections, the statistical and raster information obtained from the Yazd municipality and Yazd waste management organization were introduced into ArcGIS software and based on the information obtained, including population density layer and population last estimation in zone 3, per capita waste production, and then considering all the information layers obtained using the GIS software, containers were located with a source separation approach. Results: The results of this study indicate that installation of underground containers for wet waste, in addition to improving the health and environmental status, can decrease the frequency of urban waste collection from 3 days to 2 days a week. Moreover, creation of temporary storage sites for dry wastes, can also significantly decrease the route of collection, due to the reduction of the collection route from 368,000 to 180,000 meters in the new routing system, reduce the economic cost, including reducing fuel costs as 50% per day, manpower as 33%, and reduce maintenance costs. Conclusion: Optimization of urban waste collection system using underground containers for wet waste and the use of temporary stations of dry wastes, considering the significant economic, environmental and aesthetic advantages can be considered as an appropriate option in Iranian cities especially in areas with hot and humid weather such as Yazd.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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 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".