Briefing: Landfill mining for energy recovery in tropical developing countries
Bibliographic record
Abstract
This paper discusses landfill mining (LM) and uses data from tropical landfills in a preliminary analysis of its applicability. It is shown that there is a tendency of concentration of components with high calorific values over time, the contrary occurring with the municipal solid waste (MSW) water content, w, which is normally smaller for aged samples compared to that for fresh ones. This encourages LM adoption in various landfills since more energy can be recovered from MSW with the use of thermal recovery methods (TRMs) and less energy is necessary for MSW drying. Furthermore, it is demonstrated that 4–6 years is enough for most biological processes to occur in the field in tropical regions, making the use of LM possible in few years after landfill closing. The use of TRMs such as gasification is interesting because the produced hydrogen gas (H 2 ) can be used for electrical power generation similar to methane (CH 4 ). However, the use of thermal energy recovery methods in MSW components can result in dangerous atmospheric emissions, which must be controlled and rigorously monitored, as well as the stability of the MSW mass during the excavation process.
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.
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".