Pilot-Scale Investigation of Passive Methane Oxidation System Materials Performance under Seasonal Temperature Variations
Bibliographic record
Abstract
Passive methane oxidation systems (PMOSs) including biocovers and biowindows are innovative solutions to mitigate methane (CH4) emissions from landfills. In this study, the performance of different methane oxidation layer (MOL) materials including food waste compost and yard waste compost was investigated for mitigating methane emissions. Pilot-scale systems (2.7-m length, 1.45-m width, and 1-m height) were constructed on the Carleton University campus in Ottawa, where seasonal temperature variations are observed (−25°C in winter to above 30°C in summer). Two MOL thicknesses (500 and 750 mm thick) were studied in each pilot-scale system and consisted of a 70∶30 ratio by mass of compost to sand. The pilot-scale PMOSs were tested over a duration of 400 days, providing a detailed data set of the impacts of seasonal weather conditions on PMOS performance. The results demonstrate that CH4 oxidation rate in the MOLs was influenced by the seasonal temperature variations because CH4 oxidation occurred during spring, summer, and fall seasons, while it was limited during the winter season. Estimated CH4 removal efficiency in both MOL materials was between 80% and 100% in these warmer seasons. The pilot-scale results showed that increasing the thickness of the MOL to 750 mm can help offer extra buffer to mitigate overall emissions, particularly during the transition to and from colder seasons. Snow cover during winter affected gas emissions and diffusion as well as delayed cold temperature ingress and frost formation in the MOL. In addition, the pilot-scale results revealed that both yard and food waste compost acclimated quickly when the temperature changed from colder to warmer temperatures. The current study provided an enhanced understanding of yard and food waste compost MOL performance during seasonal temperature variations expected in climates such as semicontinental and continental climates and that both materials have a sufficient ability in mitigating CH4 emissions from old and small landfills under these variations.
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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 | 0.001 |
| 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 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".