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Record W2339177931 · doi:10.2166/wst.2004.0290

Batch experiment on H2S degradation by bacteria immobilised on activated carbons

2004· article· en· W2339177931 on OpenAlexaff
Ran Yan, Yuen Ling Ng, Xiaojing Chen, Anli Geng, W. Douglas Gould, Huiqi Duan, D.T. Liang, Lawrence C. C. Koe

Bibliographic record

VenueWater Science & Technology · 2004
Typearticle
Languageen
FieldChemical Engineering
TopicOdor and Emission Control Technologies
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsBiofilterBiodegradationActivated carbonPulp and paper industryAdsorptionWaste managementChemistryDegradation (telecommunications)Activated sludgeBioreactorChemical engineeringEnvironmental scienceEnvironmental engineeringSewage treatmentOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Biological treatments of odorous compounds, as compared to chemical or physical technologies, are in general ecologically and environmentally favourable. However, there are some inefficiencies relative to the media used in biofiltration processes, such as the need for an adequate residence time; the limited lifetime, and pore blockage of media, which at present render the technology economically non-viable. The aim of the study is to develop novel active media to be used in performance-enhanced biofiltration processes, by achieving an optimum balance and combination of the media adsorption capacity with the biodegradation of H2S through the bacteria immobilised on the media. An enrichment culture was obtained from activated sludges in order to metabolise thiosulphate. Batch-wise experiments were conducted to optimise the bacteria immobilisation on activated carbon, so as to develop a novel "biocarbon". Biofilm was mostly developed through culturing the bacteria with the presence of carbons in mineral media. SEM and BET tests of the carbon along with the culturing process were used to identify, respectively, the biofilm development and biocarbon porosity. Breakthrough tests evaluated the biocarbon performance with varying gas resistance time, inlet H2S concentration, and type of support materials. Fundamental issues were discussed, including type of support material, mode of bacteria immobilisation, pore blockages, and biodegradation kinetics, etc. This batch-wise study provides a basis for our future research on optimisation of the biofiltration process using a bio-trickling reactor.

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 score0.008
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.240
Teacher spread0.231 · 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

Citations8
Published2004
Admission routes1
Has abstractyes

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