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Record W2810298830 · doi:10.2166/wqrj.2018.003

Recovery of particulate matter from a high-rate moving bed biofilm reactor by high-rate dissolved air flotation

2018· article· en· W2810298830 on OpenAlexafffund
Óscar J. Sánchez, Marc‐André Labelle, Alain Gadbois, Édith Laflamme, Peter Dold, Antoine Laporte, Yves Comeau

Bibliographic record

VenueWater Quality Research Journal · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsCégep de Saint-LaurentEnviroSim (Canada)Polytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsParticulatesEffluentMoving bed biofilm reactorWastewaterDissolved air flotationChemistryPulp and paper industryWaste managementEnvironmental scienceTotal suspended solidsSewage treatmentHydraulic retention timeEnvironmental engineeringBiofilmChemical oxygen demand

Abstract

fetched live from OpenAlex

Abstract High-rate biological wastewater treatment processes for carbon recovery are able to improve the energy balance and carbon footprint of water resource recovery facilities. Combination of a high-rate moving bed biofilm reactor (HR-MBBR) with a rapid flotation (HR-DAF), as a replacement for the ‘A stage’ of the A-B process, can achieve this objective. The main goal of this study was to maximize the capture of biodegradable particulate matter from an HR-MBBR effluent by an HR-DAF. A pilot-scale HR-DAF process was operated downstream of an HR-MBBR treating screened municipal wastewater. The particulate biodegradable matter recovery was evaluated by determining the total suspended solids (TSS) removal efficiency. TSS recovery in experiments without chemicals at low surface loading rates (<15 m/h) and high recycle ratio (>25%) was 94 ± 1%. By using a tannin-based polymer, the solids capture efficiency of the HR-DAF was slightly improved with TSS recovery reaching 96 ± 1% at a high SLR (at least 22 m/h) and low recycle ratio (14%). The anaerobic biodegradability of the tannin tested was determined to be 17%. The HR-DAF process downstream of an HR-MBBR gave a very good particulate matter recovery that offers a promising alternative to the A-B process for carbon recovery.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.003

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 head0.044
GPT teacher head0.314
Teacher spread0.270 · 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; both teacher heads agree on what is shown here.

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

Citations6
Published2018
Admission routes2
Has abstractyes

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