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Methane Biofiltration in the Presence of Non-Methane Organic Compounds in Solution Gas

2016· article· en· W2550825567 on OpenAlexaff
Poornima Jayasinghe, C.K. Haththotuwa, J. Patrick A. Hettiaratchi

Bibliographic record

VenueCurrent Environmental Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicUnderground infrastructure and sustainability
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMethaneBiofilterChemistryPropaneNatural gasHydrogen sulfideEnvironmental chemistryAnaerobic oxidation of methaneGreenhouse gasEnvironmental scienceEnvironmental engineeringOrganic chemistrySulfur

Abstract

fetched live from OpenAlex

Solution gas is a natural gas consisting of primarily methane and small amounts of non-methane organic compounds. When the amount of solution gas released at individual locations is relatively small and the quality is low, it is not economically feasible to recover this gas. Therefore, environmentally acceptable methods are needed for their control. This research is focused on assessing the viability of using methane biofiltration technology to control point source, low volume solution gas emissions. Unlike the systems with which methane biofilters have already been tested, solution gas contains diverse pollutants in addition to methane, particularly hydrogen sulfide and non-methane organic compounds. A comprehensive set of laboratory experiments were undertaken and the results showed that methane oxidation is not affected by the presence of low concentrations of ethane and propane that could be present in solution gas. However, in flow-through column experiments, the methane oxidation efficiency was adversely affected by increasing the inlet loading rate of ethane. Keywords: Greenhouse gas, methane biofiltration, MMO, NMOC, solution gas, trace gases.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.613
Threshold uncertainty score0.433

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)0.0000.000

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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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