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Record W1560510545 · doi:10.2166/wst.2004.0153

Multi-component kinetics of activated sludge treatment of bleached kraft mill effluent

2004· article· en· W1560510545 on OpenAlexaff
Steve S. Helle, Sheldon J.B. Duff

Bibliographic record

VenueWater Science & Technology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsUniversity of British Columbia Hospital
Fundersnot available
KeywordsActivated sludgeEffluentChemical oxygen demandBiodegradationKraft paperPulp and paper industryPaper millWastewaterVolatile suspended solidsBiochemical oxygen demandChemistrySequencing batch reactorMixed liquor suspended solidsWaste managementFraction (chemistry)Batch reactorDegradation (telecommunications)Sewage treatmentSubstrate (aquarium)ChromatographyOrganic chemistryCatalysisEcology

Abstract

fetched live from OpenAlex

This study investigated the discrepancies between the BOD removal rates measured during short term assays and those measured during continuous activated sludge treatment of bleached kraft mill effluent (BKME). A combination of batch tests and fed batch tests with oxygen uptake rate (OUR), chemical oxygen demand (COD), biochemical oxygen demand (BOD), and mixed liquor volatile suspended solids (MLVSS) measurements were used to characterize the degradation rates for the activated sludge treatment of BKME and to divide the soluble readily biodegradable substrate into two to five separate fractions based on biodegradation rates. The removal rates varied by over an order of magnitude between the most readily degradable substrates (1 x 10(-3) mg COD/mg MLVSS minute), and the more slowly degradable substrates (2 x 10(-5) mg COD/mg MLVSS minute). If the readily biodegradable fraction of BKME was modeled as one substrate, initial rate kinetic measurements from batch tests were heavily influenced by the fractions with the greatest degradation rates, while any remaining BOD in the treated effluent was predominantly from the slowly degradable fraction, giving inconsistent results. Taking the multi-component nature of the wastewater into account, batch test results can be used to predict fed-batch and continuous activated sludge reactor performance.

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 score0.006
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.015
GPT teacher head0.242
Teacher spread0.227 · 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

Citations6
Published2004
Admission routes1
Has abstractyes

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