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Record W2921650390 · doi:10.2166/wqrj.2000.007

Performance of UASB Reactors at 6 to 32°C in Municipal Wastewater Treatment

2000· article· en· W2921650390 on OpenAlexaff
Kripa Shankar Singh, T. Viraraghavan

Bibliographic record

VenueWater Quality Research Journal · 2000
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsBiogasMethaneWastewaterBiogas productionChemistrySewage treatmentBiomass (ecology)Volume (thermodynamics)Pulp and paper industryAnaerobic digestionEnvironmental scienceWaste managementEnvironmental engineeringEcology

Abstract

fetched live from OpenAlex

Abstract The feasibility of using a high-rate upflow anaerobic sludge blanket (UASB) system for the treatment of low-strength municipal wastewater at 6 to 32°C was investigated for temperate climate applications. UASB reactors could be started up successfully in about 60 days at 20°C. Under stable conditions, the removal of COD, BOD and SS ranged from 38 to 90%, 47 to 91% and 50 to 92%, respectively, for a temperature range of 6 to 32°C. Sulfate reduction ranged from 10 to 90%, showing a decreasing trend with a decrease in temperature at each HRT. The average biogas production and methane content ranged from 167 to 199 mL CH4/g-CODremoved and 65 to 86%, respectively. The recovery of methane in the gas phase was very low compared with soluble COD removals, especially during operation at lower temperatures (6 to 15°C). Digital image analysis and scanning electron microscopy results indicated the aggregation of biomass in the form of flocs and small granules. The mean size of aggregated sludge particles increased from 0.2 to 3.0 mm, with a sludge volume index of 18 ± 2 mL/g during the operation.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.207
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0010.000

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 head0.100
GPT teacher head0.358
Teacher spread0.259 · 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.

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

Citations7
Published2000
Admission routes1
Has abstractyes

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