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Record W2046787021 · doi:10.1139/s07-040

Autothermal thermophilic aerobic digestion (ATAD) — Part II: Review of research and full-scale operating experiences

2007· article· en· W2046787021 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2007
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsUniversity of British ColumbiaPrecision Nanosystems (Canada)
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnaerobic digestionDewateringWaste managementEnvironmental scienceMesophileVolume (thermodynamics)Aerobic digestionPulp and paper industryChemistryProcess engineeringEnvironmental engineeringSewage treatmentEngineeringActivated sludgeMethaneBiology

Abstract

fetched live from OpenAlex

Autothermal thermophilic aerobic digestion (ATAD) is an exothermic process where sludge is subjected to temperatures greater than 55 °C for at least 4 hours, over 6–10 days. Organic solids are degraded and the heat released during the microbial degradation is used to bring the process temperature within the thermophilic range. It produces a biologically stable product, achieving a reduction in biomass, while using smaller digesters, compared to mesophilic aerobic and anaerobic digestion. There are no regulatory requirements in North America and Europe for the reduction of the volume of total solids in sludge processing. However, a reduction in the volume of material for final disposal has cost benefits. By virtue of the residual mass, volume reductions are easily made through dewatering or dehydrating steps following ATAD. Despite the apparent advantages of ATAD, limited information on the process is available in the literature. Concerns still exist about documented cases of odour issues, problems with sludge dewaterability, foaming, excess use of polymers and high-energy consumption. This article presents some relevant bench-scale and pilot ATAD study data, with appropriate discussion. It also assembles information from a range of sources and provides an insight into actual application and experiences with full-scale ATAD.

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.

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 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 score0.418
Threshold uncertainty score0.252

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)0.0000.000

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 head0.013
GPT teacher head0.249
Teacher spread0.235 · 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