Introducing an Integrated Municipal Solid Waste Management System: Assessment in Jordan
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
<p class="Body-Masterspaper">Municipal solid waste management (MSWM) is considered one of the challenging environmental problems in the Middle East and North Africa (MENA) region. Municipal solid waste increased significantly due to rapid population growth and fast urbanization, change in lifestyles and consumption patterns. Major problems associated with MSWM are poor collection rates, open dumping, and improper recycling that pose environmental damages. An environmental impact analysis of Jordan’s MSWM was required to look into opportunities for bringing in an integrated solid waste management (ISWM). In this paper, we analyzed the country’s MSWM as a case study in the MENA region. Our goal was to identify the most environmentally-friendly and economically-viable alternative to the current situation. Based on the Life Cycle Assessment (LCA), we evaluated the potential environmental and economic impacts of 10 MSWM scenarios adopting different waste treatment technologies. Indicators of the environmental performance used were four impact categories of EDIP 2003 assessment method: Climate Change (GWP 100a), Acidification Potential, Eutrophication Potential and Human Toxicity. The results showed that improving the current MSWM with 72% of sanitary landfills with energy recovery and 28% of dry recyclable materials was the best scenario in terms of environmental impacts and economic cost. The cost recovery of this scenario was 155% compared to an average of 55.5% of the current cost recovery. The study also revealed that the materials recycled could be increased by 33.5% if the waste separation was applied at the source of generation.</p>
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it