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Influence of SRT and HRT on Bioprocess Performance in Anaerobic Membrane Bioreactors Treating Municipal Wastewater

2016· article· en· W2417073859 on OpenAlexafffundabout
Qirong Dong, Wayne J. Parker, Martha Dagnew

Bibliographic record

VenueWater Environment Research · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsUniversity of Waterloo
FundersSolar Energy Technologies OfficeChina Scholarship CouncilUniversity of Waterloo
KeywordsMethanogenesisChemistryHydraulic retention timeWastewaterBioreactorAnaerobic digestionPulp and paper industryMembrane bioreactorBioprocessMethaneEnvironmental engineeringChromatographyEnvironmental scienceChemical engineering

Abstract

fetched live from OpenAlex

This study investigated the impact of Solid Retention Time (SRT) (40 to 100 days) and Hydraulic Retention Time (HRT) (2.5 to 8.5 hours) on the treatment of municipal wastewater in pilot and bench scale AnMBRs. The results revealed good permeate quality with respect to concentrations of COD (<40 mg/L) and BOD5 (<10 mg/L) was achieved under all conditions. Over the range of values tested SRT and HRTdid not significantly influence COD and BOD5 removal efficiencies. Extended SRTs resulted in reduced sludge production and enhanced methane production. Oversaturation of dissolved methane in permeate appears to have been responsible for a consistent lack of COD mass balance closure in all tests. After calibration of biokinetic coefficients, PetWin 4 (EnviroSim Canada) was found to effectively simulate the concentrations of particulate COD, readily biodegradable COD and acetic acid over a range of SRTs and HRTs. The calibrated saturation coefficients for hydrolysis and aceticlastic methanogenesis processes were comparable to those reported in literature. The saturation coefficient of fermentation was significantly lower than those reported in literature. The simulated methane mass flows were consistently higher than the measured values which was consistent with the lack of COD mass balance closure and was attributed to reduction of sulfate and oversaturation of the permeate with respect to Henry's Law.

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)0.001
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 score0.068
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.025
GPT teacher head0.260
Teacher spread0.236 · 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

Citations28
Published2016
Admission routes3
Has abstractyes

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