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Effect of Dynamic Loading on Biological Nutrient Removal in a Pilot-Scale Liquid-Solid Circulating Fluidized Bed Bioreactor

2010· article· en· W2084607236 on OpenAlexafffundabout
Nabin Chowdhury, Jesse Zhu, George Nakhla

Bibliographic record

VenueJournal of Environmental Engineering · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEffluentPhosphorusNutrientBioreactorSuspended solidsEnvironmental scienceSewage treatmentEnvironmental engineeringWastewaterSlurryFluidized bedChemistryPulp and paper industryEngineering

Abstract

fetched live from OpenAlex

A pilot-scale liquid-solid circulating fluidized bed (LSCFB) bioreactor was employed for biological nutrient removal from municipal wastewater at the Adelaide Pollution Control Plant, London, Ontario, Canada. Lava rock particles of 600 μm were used as a biomass carrier media. The system generated effluent characterized by <1.0 mg NH4N/L , <6.0 mg NO3N/L , <1.0 mg PO4P/L , <10 mg TN/L, and <10 mg SBOD/L at an influent flow of 5 m3/d , without adding any chemicals for phosphorus removal and secondary clarification for suspended solids removal. The impact of the dynamic loading on the LSCFB effluent quality and its nutrient removal efficiencies were monitored by simulating wet weather condition at a maximum peaking factor of 3 for 4 h. The achievability of effluent characteristics of 1.1 mg NH4N/L , 4.6 mg NO3N/L , 37 mg COD/L, and 0.5 mg PO4P/L after 24 h of the dynamic loading emphasize the favorable response of the LSCFB to the dynamic loadings and the sustainability of performance without loss of nutrient removal capacity.

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 score0.018
Threshold uncertainty score0.784

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.005
GPT teacher head0.209
Teacher spread0.204 · 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

Citations12
Published2010
Admission routes3
Has abstractyes

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