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Record W4408748724 · doi:10.1002/wer.70059

Maximizing the efficiency of single‐stage partial nitrification/Anammox granule processes and balancing microbial competition using insights of a numerical model study

2025· article· en· W4408748724 on OpenAlexafffund
Ahmed Elsayed, Taeho Lee, Younggy Kim

Bibliographic record

VenueWater Environment Research · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsMcMaster University
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaNational Research Foundation of KoreaNational Research Foundation
KeywordsAnammoxChemistryPopulationAmmoniaSaturation (graph theory)NitriteReaction rate constantBacterial growthOxygenEnvironmental chemistryBacteriaNitrogenKineticsDenitrificationBiologyBiochemistryDenitrifying bacteria

Abstract

fetched live from OpenAlex

Abstract Granulation is an efficient approach for the rapid growth of anaerobic ammonia oxidation (Anammox) bacteria () to limit the growth of nitrite‐oxidizing bacteria (). However, the high sensitivity of Anammox bacteria to operational conditions and the competition with other microorganisms lead to a critical challenge in maintaining sufficient population. In this study, a one‐dimensional steady‐state model was developed and calibrated to investigate the kinetic constants of growth and mass transport in individual granules, including the liquid film. According to the model calibration results, the range of the maximum specific growth rate constant of () was 0.033 to 0.10 d −1 . In addition the other kinetic constants of were 0.003 d −1 for decay rate constant (), 0.10 mg‐O 2 /L for oxygen half‐saturation constant (), 0.07 mg‐N/L for ammonia half‐saturation constant (), and 0.05 mg‐N/L for nitrite half‐saturation constant (). The model simulation results showed that the dissolved oxygen of about 0.10 mg‐O 2 /L was found to be optimal to maintain high population. In addition, minimal COD concentration is required to control heterotrophs () and improve ammonia oxidation by ammonia‐oxidizing bacteria (). It was also emphasized that moderate mixing conditions ( 100 μm) are preferable to decrease the diffusion of oxygen to the deep layers of the granules, controlling the competition between and . A single‐factor relative sensitivity analysis (RSA) on microbial kinetics revealed that is the governing factor in the efficient operation of the single‐stage PN/A processes. In addition, it was found that nitrite concentration is a rate‐limiting parameter on the success of the process due to the competition between and . These findings can be used to enhance our understanding on the importance of microbial competition and mass transport in the single‐stage PN/A process. Practitioner Points A one‐dimensional steady‐state model was developed and calibrated for simulating the single‐stage partial nitrification/Anammox (PN/A) granule process. Moderate liquid films ( 100 μm) are preferable for better performance of Anammox growth in single‐stage PN/A processes. Moderate dissolved oxygen (DO 0.10 mg‐O 2 /L) is highly recommended for efficient growth of Anammox bacteria in single‐stage PN/A granulation. Minimal COD (COD 0) is preferable for successful operation of the single‐stage PN/A granule process. Nitrite concentration is a rate‐limiting parameter on the competition between Anammox and nitrite‐oxidizing bacteria in the single‐stage PN/A processes.

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 score0.020
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.043
GPT teacher head0.283
Teacher spread0.240 · 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

Citations4
Published2025
Admission routes2
Has abstractyes

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