Landfill Cover Soil, Soil Solution, and Vegetation Responses to Municipal Landfill Leachate Applications
Bibliographic record
Abstract
Municipal solid waste landfill leachate must be removed and treated to maintain landfill cover integrity and to prevent contamination of surface and ground waters. From 2003 to 2007, we studied an onsite disposal system in Ottawa County, Michigan, where leachate was spray irrigated on the vegetated landfill cover. We established six 20-m-diameter circular experimental plots on the landfill; three were spray irrigated as part of the operational system, and three remained as untreated control plots. We quantified the effects of leachate application on soil properties, soil solution chemistry, vegetative growth, and estimated solute leaching. The leachate had high mean levels of electrical conductivity (0.6-0.7 S m(-1)), Cl (760-900 mg L(-1)), and NH(4)-N (290-390 mg L(-1)) but was low in metals and volatile organic compounds. High rates of leachate application in 2003 (32 cm) increased soil electrical conductivity and NO(3)-N leaching, so a sequential rotation of spray areas was implemented to limit total leachate application to <9.6 cm yr(-1) per spray area. Concentrations of NO(3)-N and leaching losses remained higher on irrigated plots in subsequent years but were substantially reduced by spray area rotation. Leachate irrigation increased plant biomass but did not significantly affect soil metal concentrations, and plant metal concentrations remained within normal ranges. Rotating spray areas and timing irrigation to conform to seasonal capacities for evapotranspiration reduced the localized impacts of leachate application observed in 2003. Careful monitoring of undiluted leachate applications is required to avoid adverse impacts to vegetation or soils and elevated solute leaching losses.
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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 | 0.000 | 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) | 0.001 | 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".