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Record W2163468346 · doi:10.1002/bit.21033

The effects of methanol on the biofiltration of dimethyl sulfide in inorganic biofilters

2006· article· en· W2163468346 on OpenAlexaff
Yuefeng Zhang, Steven N. Liss, D. Grant Allen

Bibliographic record

VenueBiotechnology and Bioengineering · 2006
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsBiofilterDimethyl sulfideChemistrySulfurBiodegradationMethanolEnvironmental chemistryDimethyl disulfidePulp and paper industryOrganic chemistry

Abstract

fetched live from OpenAlex

Air emissions from the pulp and paper industry frequently contain reduced sulfur compounds (RSC), such as dimethyl sulfide (DMS) mixed with volatile organic compounds (VOC) (e.g., methanol, MeOH) and it is desirable to treat either one or both of these groups of compounds. The objective of this study was to assess the effects of VOC (MeOH) on the biofiltration of DMS. Results obtained from continuous experiments using three bench-scale biofilters packed with inorganic material clearly show that MeOH has a positive effect (11-fold increase) on the biofiltration of DMS. Further experiments indicate that MeOH addition enhances biomass concentration and viability (threefold) in the biofilters. However, a suspension of MeOH addition causes a rapid significant increase (twofold) in the removal rate of DMS, suggesting that the presence of MeOH also has a competitive effect on DMS biodegradation. This negative effect was also confirmed in batch experiments. The decrease of biofilter performance with time for a long-term suspension of MeOH addition indicates that MeOH addition is necessary to sustain a high removal rate of DMS in inorganic biofilters. Results on metabolic products of DMS biodegradation demonstrate that DMS is almost completely converted to sulfate in the absence of MeOH, while it is partially oxidized to elemental sulfur in the presence of MeOH. This study suggests that there exists an optimum mix of DMS and MeOH for the treatment of DMS emissions in inorganic biofilters.

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 score0.024
Threshold uncertainty score0.301

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 head0.005
GPT teacher head0.191
Teacher spread0.187 · 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

Citations37
Published2006
Admission routes1
Has abstractyes

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