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Record W2129521985 · doi:10.1139/l10-029

Anaerobic treatment of concentrated latex processing wastewater in two-stage upflow anaerobic sludge blanketA paper submitted to the Journal of Environmental Engineering and Science.

2010· article· en· W2129521985 on OpenAlexvenueno aff
Siriuma Jawjit, Winai Liengcharernsit

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMesophileEffluentWastewaterChemical oxygen demandPulp and paper industryHydraulic retention timeWaste managementEnvironmental scienceAerationAnaerobic exerciseSewage treatmentEnvironmental engineeringEngineeringBiology

Abstract

fetched live from OpenAlex

This study aims to investigate treatment performance of the two-stage upflow anaerobic sludge blanket (UASB) applied to concentrated latex processing wastewater in Thailand. First, optimal conditions including the hydraulic retention time (HRT) in the acid tank and the UASB tank, pH, and temperature (mesophilic and thermophilic) were determined. It was found that the HRT at 24 h and 48 h were the optimal HRT for the acid tank and the UASB tank, respectively. The pH of the system should be controlled at 7 to prevent rubber coagulation and to achieve high treatment performance, and the mesophilic condition (35°C) was found to be the optimal temperature. Second, the two-stage UASB was applied with the optimal conditions mentioned earlier with real wastewater at a latex mill. It was found that methane production was about 0.116 L CH 4 /g COD removed (16.3–22.8 m 3 CH 4 /d), and average chemical oxygen demand (COD) and suspended solids (SS) removal efficiency were about 82% and 92%, respectively. In case of SS removal, the results revealed that the two-stage UASB was capable of overcoming the limitations of the single-stage UASB in treating concentrated latex effluent. The results indicated that application of the two-stage UASB to concentrated latex processing wastewater is feasible. Nevertheless, combination with other treatment systems (e.g., oxidation pond, aerated lagoon) is necessary to meet Thailand's industrial effluent standards (in the case of COD).

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 score0.297
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.195
Teacher spread0.189 · 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

Citations10
Published2010
Admission routes1
Has abstractyes

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