Effect of Leachate Recirculation on Enhancement of Biological Degradation of Solid Waste: Case Study
Bibliographic record
Abstract
This paper presents a case study of leachate recirculation at the Trail Road landfill site, located in Nepean, Ontario, Canada. The leachate collected from the landfill leachate collection system is pumped into infiltration lagoons that were built on the working face of the landfilled waste. The locations of these infiltration lagoons are constantly changing to accommodate the landfilling of the municipal solid waste in Stage 3, which has a composite liner consisting of 600 mm of compacted clay and an 80 mil high-density polyethylene geomembrane. The initial estimation of the leachate generation rates in 1991, using the Hydrological Evaluation of Landfill Performance model indicated that leachate recirculation into the landfill could be feasible for a period of 5 to 6 years, after which time a substantial amount of leachate would have to be removed from the system. The average pH of the leachate in the early stage of recirculation was on the acidic side of the pH scale; however, the pH value was in the range of 7 to 8 after 2 years of leachate recirculation. The leachate recirculation accelerated the reduction of organic load, measured as BOD and COD. The concentration of chloride remained fairly constant at about 1,000 mg/L during the leachate recirculation period. The recovery of landfill air space was also noted as a during active periods of landfilling as an added benefit due to the enhanced subsidence of the solid waste.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 source (direct Gemma or distilled Codex), 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".