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Record W2417532113 · doi:10.2175/106143007x156790

Toward a High‐Rate Enhanced Biological Phosphorus Removal Process in a Membrane‐Assisted Bioreactor

2007· article· en· W2417532113 on OpenAlexafffund
Alessandro Monti, Eric R. Hall, Fred A Koch, Robert N. Dawson, Harlan G. Kelly

Bibliographic record

VenueWater Environment Research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsPrecision Nanosystems (Canada)Canadian Association of GastroenterologyStantec (Canada)University of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsHydraulic retention timePhosphorusEffluentChemical oxygen demandEnhanced biological phosphorus removalNitrificationWastewaterChemistryMembrane bioreactorPulp and paper industryBioreactorNutrientSuspended solidsNitrogenSewage treatmentEnvironmental engineeringDenitrificationEnvironmental chemistryEnvironmental scienceActivated sludge

Abstract

fetched live from OpenAlex

A membrane enhanced biological phosphorus removal (MEBPR) process was studied to determine the impact of hydraulic retention time (HRT) and solids retention time (SRT) on the removal of chemical oxygen demand (COD), nitrogen, and phosphorus from municipal wastewater. The MEBPR process was capable of delivering complete nitrification independent of the prevailing operating conditions, whereas a significant improvement in COD removal efficiency was observed at longer SRTs. In the absence of carbon-limiting conditions, the MEBPR process was able to achieve low phosphorus concentrations in the effluent at increasingly higher hydraulic loads, with the lowest HRT being 5 hours. The MEBPR process was also able to maintain optimal phosphorus removal when the SRT was increased from 12 to 20 days. However, at higher suspended solids concentrations, a substantial increase was observed in carbon utilization per unit mass of phosphorus removed from the influent. These results offer critical insights to the application of membrane technology for biological nutrient removal systems.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0010.001
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 head0.059
GPT teacher head0.301
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 source (direct Gemma or distilled Codex), 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

Citations5
Published2007
Admission routes2
Has abstractyes

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