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Record W4409117928 · doi:10.31223/x5gb1k

Active Face Emissions: An Opportunity for Reducing Methane Emissions in Global Waste Management

2025· preprint· en· W4409117928 on OpenAlexaboutno aff
David Risk, Athar Omidi, Évelise Bourlon, Afshan Khaleghi, Gilles Perrine, nadia Tarakki, Rebecca Martino, Jordan Stuart

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicVehicle emissions and performance
Canadian institutionsnot available
Fundersnot available
KeywordsMethaneMethane emissionsGreenhouse gasEnvironmental scienceFace (sociological concept)Waste managementBusinessNatural resource economicsEnvironmental protectionEngineeringEconomicsChemistryEcology

Abstract

fetched live from OpenAlex

This study used mobile surveys of ten Canadian landfills to assess how methane emissions varied across different landfill sources and operational conditions. The studied landfills included two closed landfills, four open landfills equipped with Gas Collection and Control Systems (GCCS), and four open landfills operating without GCCS. We employed the Gaussian dispersion model to estimate emissions fluxes using on site and off site transect data. We observed high spatial variability of methane emissions and identified the sources that contributed significantly to overall landfill emissions, sources such as the active face, closed cells, compost areas, leachate systems, and GCCS. Overall, we found that the active face of landfills is a major emitter of methane, contributing 76% of the methane emissions for landfills with GCCS and 38% for landfills without GCCS. The results underscore the importance of improved monitoring and management strategies at landfill active faces to more effectively mitigate methane emissions from landfills.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.321
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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