Impact of landfill leachate on anaerobic digestion of sewage sludge
Bibliographic record
Abstract
The feasibility of mesophilic anaerobic co-digestion of landfill leachate and sewage sludge was examined in a bench-scale experiment. Three complete-mix, flow-through digesters were operated in a semi-continuous mode. During both phases of research all digesters received 500 ml d(-1) of raw sludge and Reactor 1 was always the control reactor--fed sludge only. During Phase 1, leachate volumes less than 12% of the sludge volume were fed to Reactors 2 and 3. During Phase 2 larger amounts of leachate were added, exceeding 20% of sludge volume which led to an overall decrease in the hydraulic residence time of the digesters. All reactors achieved stable operation, which indicated that the co-digestion of sewage sludge and landfill leachate is feasible During Phase 1, an increase in the average daily methane production from 2.5 l d(-1) to 3.1 l d(-1) and 3.2 l d(-1) was observed; the biomethanation production (BMP) increased from 0.46 to 0.6 m3 - 0.7 m3 CH4 (kg VS rem.)(-1). The average volatile solids reduction (VSR) increased from 46.1% to 48.6% and 49.0%. In Phase 2, the total methane production in the control reactor was significantly higher, at 4.6 l d(-1), while the addition of larger, by volume, amounts of leachate, decreased the methane production to 4.3 l d(-1) and 4.2 l d(-1), respectively. The average BMP values were 0.8, 0.87, and 0.81 m3 CH4 (kg VS rem.)(-1), respectively. In Phase 2, leachate addition decreased the average VSR from 51% to 49% and 45.6%. After calculating that leachate addition to digesters would not increase heavy metal concentrations in the produced biosolids it was concluded that mesophilic anaerobic co-digestion of sewage sludge and landfill leachate is feasible, and provides a promising alternative to aerobic co-treatment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".