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Record W2151701133 · doi:10.1139/l09-144

Biofiltration of methane using an inorganic filter bed: Influence of inlet load and nitrogen concentrationThis article is one of a selection of papers published in this Special Issue on Biological Air Treatment.

2009· article· en· W2151701133 on OpenAlexafffundvenue
Josiane Nikiema, Matthieu Girard, Ryszard Brzeziński, Michèle Heitz

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2009
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiofilterInletMethaneNitrogenNitrateChemistryFilter (signal processing)Environmental scienceEnvironmental chemistryEnvironmental engineeringPulp and paper industryEngineering

Abstract

fetched live from OpenAlex

An upflow lab-scale biofilter was operated with an inorganic filter material to control methane emissions. The influence of the inlet load on methane removal was investigated and the maximum elimination capacity obtained was 36 g/(m 3 ·h) for an inlet load of 95 g/(m 3 ·h). The influence of the nitrogen concentration, which was provided in the form of nitrate through a nutrient solution, was also determined. We established that the optimum nitrogen concentration required for biofilter operation decreases with the methane inlet load. In fact, it was around 0.75 g/L for inlet loads comprised between 55 and 95 g/(m 3 ·h) and of 0.50 g/L when the inlet load was comprised between 20 and 55 g/(m 3 ·h). During this study, a nitrogen concentration of 1.00 g/L inhibited methane removal in the biofilter. In addition, the use of a nitrogen concentration superior to its optimum level can cause, in the long-term run, severe damages to the biofilter performance.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.609

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.216
Teacher spread0.202 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations32
Published2009
Admission routes3
Has abstractyes

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