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Record W2155359752 · doi:10.1680/jees.2013.0055

Sewage sludge treatment by a continuous microwave enhanced advanced oxidation process

2013· article· en· W2155359752 on OpenAlexafffundvenue
Yang Yu, W.I. Chan, Ing W. Lo, Ping Liao, K.V. Lo

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOrganic matterMicrowaveSewage sludgeSolubilizationMicrowave heatingChemistryMaterials scienceSewageEnvironmental scienceOrganic chemistryEnvironmental engineering

Abstract

fetched live from OpenAlex

A continuous flow mode of the microwave enhanced advanced oxidation process (MW/H2O2-AOP) was used for sludge treatment as opposed to a batch operation mode from past studies. The effects of pre-microwave heating, microwave irradiation and post-microwave holding on organic matter solubilization were studied. Pre-microwave heating did not improve the overall orthophosphate solubilization, but helped in organic matter solubilization. Nutrients and organic matter were found to have increased during the post-microwave holding period, indicating overall sludge solubilization can be more effective when maintained at a high temperature after treatment with the MW/H2O2-AOP. It was beneficial to operate a continuous mode of the MW/H2O2-AOP at a longer retention time for organic matter solubilization, and at a shorter retention time for orthophosphate solubilization. Sludge settleability was greatly improved with the microwave treatment, with or without the addition of H2O2. The pre-heating of sludge before treatment with the microwave process by the means of heat exchange can be beneficial for the overall organic matter solubilization in the MW/H2O2-AOP.

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 score0.056
Threshold uncertainty score0.470

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.002
GPT teacher head0.173
Teacher spread0.171 · 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

Citations13
Published2013
Admission routes3
Has abstractyes

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