Efficiency of planted and unplanted vertical flow aerated filters in treatment of young landfill leachate
Bibliographic record
Abstract
Young landfill leachate, produced by the passage of water through operating sites at a municipal landfill, is highly concentrated in organic matter, ammonia and metals, and is typically treated using intensive, conventional systems. Studies have demonstrated efficient treatment of low-strength old leachate, produced by capped sites at a landfill, by nature-based systems such as treatment wetlands. Few studies have investigated the use of similar systems to treat young leachate. The objectives of this study were to 1) determine if vertical flow planted and unplanted aerated filters could efficiently treat young leachate COD, BOD 5 , TSS, NH 4 and p -cresol; 2) determine the suitability and effect of two plant species on treatment efficiency; 3) quantify the denitrification capacity achieved in pre-anoxic filters; and 4) determine full-scale design criteria (hydraulic and organic loading rates and space requirements) for 1500 m 3 /d of young leachate. Five 430 L water-saturated vertical flow pilot-scale filters with forced aeration and 10 to 20 mm granite gravel media were operated in parallel in a greenhouse for 42 weeks total during fall 2020 and spring through fall 2021. Each filter was fed with an average of 16.4 L m −2 d −1 of anaerobically pretreated young leachate spiked with 3340 μg/L of p -cresol for an organic loading rate of 3.5 g BOD 5 m −3 d −1 to each filter. Two filters were planted with Salix miyabeana ‘SX67’, two were planted with Sporobolus michauxianus and one was left unplanted. Two planted filters (one with each plant species) had pre-anoxic filters for denitrification. Results indicated that planted and unplanted filters offered similar treatment, with average removal efficiencies of 74 % for COD, 98 % for BOD 5 , 96 % for TSS, 100 % for NH 4 and 100 % for p -cresol. Young leachate treatment negatively impacted plant health and their chlorophyll fluorescence. Systems with pre-anoxic filters were able to achieve a higher total nitrogen removal efficiency of 70 % compared to 60 % on average for systems without pre-anoxic filters. The high removal efficiency achieved suggests that filter systems were operated below the treatment capacity of the microorganisms. Unplanted aerated filters are a promising technology for treatment of young landfill leachate and p -cresol. • Efficient undiluted mostly young leachate treatment by vertical flow aerated filter • Very high organic matter, solids, ammonium and p-cresol removal with aerated filter • Higher total nitrogen removal efficiency of systems with preanoxic filters • Salix miyabeana ‘SX67’ and Sporobolus michauxianus not tolerant to young leachate
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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".