Techno-economic evaluation of decentralized community composting as a management model to valorize organic matter in small and medium-sized towns
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
Abstract Decentralized community composting presents a viable Techno-economic alternative to centralized industrial systems for managing 100% of the organic fraction of municipal solid waste (MSW) in rural municipalities. This study, conducted in Catalonia, Spain, evaluated a system capable of processing 90 t/y of organic matter under six scenarios, varying by mixing method (manual or mechanized) and the number of compost transfers. Mechanized mixing without transfers emerged as the most efficient approach, reducing processing time by 40% and labor demand by 50%, with annual operating costs of 15,141 €/year—14,325 €/year lower than manual methods. Payback was achieved in 10 years, supported by a canon return of 165–194 €/composter (5–7% discount rates). The resulting compost met Class A standards under Royal Decree 506/2013, ensuring high quality. This model aligns with European regulations, addressing 41% of Europe’s organic waste, while promoting a circular economy through localized waste valorization. Mechanization optimizes resource use, reduces costs, and enhances sustainability, offering a scalable solution for small-to-medium municipalities. Graphical abstract
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.002 |
| 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