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Record W2767389688 · doi:10.1186/s13036-017-0085-0

Treatment of old landfill leachate with high ammonium content using aerobic granular sludge

2017· article· en· W2767389688 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.

Bibliographic record

VenueJournal of Biological Engineering · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsLeachateSequencing batch reactorChemistryAmmoniumChemical oxygen demandSettlingWastewaterPulp and paper industryAmmoniaActivated sludgeSewage treatmentNitrificationBioreactorWaste managementNitrogenEnvironmental chemistryEnvironmental scienceEnvironmental engineeringBiochemistry

Abstract

fetched live from OpenAlex

Aerobic granular sludge has become an attractive alternative to the conventional activated sludge due to its high settling velocity, compact structure, and higher tolerance to toxic substances and adverse conditions. Aerobic granular sludge process has been studied intensively in the treatment of municipal and industrial wastewater. However, information on leachate treatment using aerobic granular sludge is very limited. This study investigated the treatment performance of old landfill leachate with different levels of ammonium using two aerobic sequencing batch reactors (SBR): an activated sludge SBR (ASBR) and a granular sludge SBR (GSBR). Aerobic granules were successfully developed using old leachate with low ammonium concentration (136 mg L−1 NH4 +-N). The GSBR obtained a stable chemical oxygen demand (COD) removal of 70% after 15 days of operation; while the ASBR required a start-up of at least 30 days and obtained unstable COD removal varying from 38 to 70%. Ammonium concentration was gradually increased in both reactors. Increasing influent ammonium concentration to 225 mg L−1 N, the GSBR removed 73 ± 8% of COD; while COD removal of the ASBR was 59 ± 9%. The GSBR was also more efficient than the ASBR for nitrogen removal. The granular sludge could adapt to the increasing concentrations of ammonium, achieving 95 ± 7% removal efficiency at a maximum influent concentration of 465 mg L−1 N. Ammonium removal of 96 ± 5% was obtained by the ASBR when it was fed with a maximum of 217 mg L−1 NH4 +-N. However, the ASBR was partially inhibited by free-ammonia and nitrite accumulation rate increased up to 85%. Free-nitrous acid and the low biodegradability of organic carbon were likely the main factors affecting phosphorus removal. The results from this research suggested that aerobic granular sludge have advantage over activated sludge in leachate treatment.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.276

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 communication0.0000.000
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 head0.041
GPT teacher head0.219
Teacher spread0.178 · 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