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Record W2016596068 · doi:10.1002/jctb.805

Bioremediation of toluene‐contaminated air using an external loop airlift bioreactor

2003· article· en· W2016596068 on OpenAlexafffund
Rochelle C Harding, Gordon A. Hill, Yen‐Han Lin

Bibliographic record

VenueJournal of Chemical Technology & Biotechnology · 2003
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTolueneBioreactorPseudomonas putidaAirliftBiofilterSpargingBioremediationBiodegradationChemistryAerationContaminationMicrobial consortiumChromatographyBioaugmentationEnvironmental chemistryAir spargingPulp and paper industryEnvironmental engineeringEnvironmental scienceEnvironmental remediationMicroorganismOrganic chemistryBiologyBacteria

Abstract

fetched live from OpenAlex

Abstract An external loop airlift bioreactor (ELAB) has been used to capture and degrade toluene from a contaminated air stream. Using a spinning sparger, the toluene could be transferred from small, uniform bubbles into the aqueous culture media with an overall mass transfer coefficient as high as 1.1 h −1 . Due to the very volatile nature of toluene, Pseudomonas putida (ATCC 23973) was cultured and maintained on benzyl alcohol, the first intermediate compound in the metabolic degradation pathway for toluene. Consequently, before successful continuous operation of the ELAB with toluene‐contaminated air, Pseudomonas putida was acclimatized to toluene by using 30 min intermittent sparging of contaminated air into the bioreactor. Continuous sparging of toluene‐contaminated air could then be successfully carried out with 100% capture and biodegradation efficiency at a contaminated air concentration of 15 mg dm −3 and a loading rate of 35 mg dm −3 h −1 . Higher concentrations and loading rates were only partially degraded. Although this capture matches only the low rates reported earlier using biofilters to remediate toluene, the ELAB operates using submerged culture and requires no packing which can plug during biofilter operation. In this study, Pseudomonas putida grew on toluene at a maximum specific growth rate of only 0.05 h −1 . © 2003 Society of Chemical Industry

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.002
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 head0.016
GPT teacher head0.258
Teacher spread0.242 · 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 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

Citations31
Published2003
Admission routes2
Has abstractyes

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