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Record W2168793078 · doi:10.1177/0734242x14538308

Anaerobic digestion and gasification coupling for wastewater sludge treatment and recovery

2014· article· en· W2168793078 on OpenAlexaff
Nicolas Lacroix, Daniel R. Rousse, Robert Häusler

Bibliographic record

VenueWaste Management & Research The Journal for a Sustainable Circular Economy · 2014
Typearticle
Languageen
FieldEngineering
TopicAnaerobic Digestion and Biogas Production
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsAnaerobic digestionBiogasWaste managementEnergy recoverySewage sludgeEnvironmental scienceSewage treatmentSewage sludge treatmentBioenergyWastewaterPulp and paper industryChemistryBiofuelEngineeringMethaneMathematicsEnergy (signal processing)

Abstract

fetched live from OpenAlex

Sewage sludge management is an energy intensive process. Anaerobic digestion contributes to energy efficiency improvement but is limited by the biological process. A review has been conducted prior to experimentation in order to evaluate the mass and energy balances on anaerobic digestion followed by gasification of digested sludge. The purpose was to improve energy recovery and reuse. Calculations were based on design parameters and tests that are conducted with the anaerobic digester of a local wastewater treatment plant and a small commercial gasification system. Results showed a very significant potential of energy recovery. More than 90% of the energy content from sludge was extracted. Also, approximately the same amount of energy would be transferred in both directions between the digester (biogas) and the gasifier (thermal energy). This extraction resulted in the same use of biogas as the reference scenario but final product was a totally dry biochar, which represented a fraction of the initial mass. Phosphorus was concentrated and significantly preserved. This analysis suggests that anaerobic digestion followed by dehydration, drying and gasification could be a promising and viable option for energy and nutrient recovery from municipal sludge in replacement of conventional paths.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.026
GPT teacher head0.268
Teacher spread0.243 · 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 designNot applicable
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

Citations29
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueWaste Management & Research The Journal for a Sustainable Circular EconomySame topicAnaerobic Digestion and Biogas ProductionFrench-language works237,207