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Record W3084153891 · doi:10.3389/fmicb.2020.551925

Autotrophic Fixed-Film Systems Treating High Strength Ammonia Wastewater

2020· article· en· W3084153891 on OpenAlexafffund
Hussain Aqeel, Steven N. Liss

Bibliographic record

VenueFrontiers in Microbiology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsToronto Metropolitan UniversityQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAutotrophAmmoniaWastewaterChemistryEnvironmental chemistryChemical engineeringEnvironmental scienceBiochemistryBiologyEnvironmental engineeringBacteriaEngineeringGenetics

Abstract

fetched live from OpenAlex

The potential of autotrophic fixed-film and hybrid bioreactors to treat high strength ammonia wastewater (1000 mgN/L) was investigated in this study. Two configurations of fixed-film systems, including moving bed bioreactor (MBBR) and BioCord™, both setup in a sequencing batch reactor (SBR) and continuous stirred tank reactor (CSTR) configuration, were operated for 306 days. The laboratory-scale bioreactors were seeded with activated sludge from a municipal wastewater treatment plant and fed synthetic wastewater with no organics. After a startup time of 45 days, the influent ammonia concentration was gradually increased (10% every five days) from 130 to 1000 mgN/L for the enrichment of nitrifying bacteria and seamless acclimation to high strength ammonia wastewater. Stable ammonia removal was observed up to 750 mgN/L (on day 145) in the MBBR SBR (94-100%) and CSTR (72-100%), and BioCord™ SBR (96-100%) and CSTR (92-100%). Ammonia removal declined to 87% ±6, in all bioreactors treating 1000 mgN/L (on day 185). Following long-term operation at 1000 mgN/L (on day 306), ammonia removal was 93-94% in both the MBBR SBR and BioCord™ CSTR; whereas, ammonia removal was relatively lower in MBBR CSTR (20-35%) and BioCord™ SBR (45-54%). Acclimation to increasing concentrations of ammonia led to the enrichment of nitrifying (Nitrosomonas, Nitrospira, and Nitrobacter) and denitrifying (Comamonas, OLB8, and Rhodanobacter) bacteria (16S rRNA gene sequencing (Illumina)) in all bioreactors. In the hybrid bioreactor, the nitrifying and denitrifying bacteria were relatively more abundant in flocs and biofilms, respectively. The abundance of Nitrosomonas was relatively higher in the microbial communities of the SBRs compared to the CSTRs. Nitrospira and OLB8 were relatively more abundant in microbial communities of MBBR bioreactors; whereas, Rhodanobacter was relatively predominant in BioCord™ bioreactors. The presence of dead cells (in biofilms) suggests that in the absence of an organic substrate, endogenous decay is a likely contributor of nutrients for denitrifying bacteria. Further studies are required to assess the contribution of organic material produced in autotrophic biofilms (by endogenous decay and soluble microbial products) to the overall treatment process. Furthermore, the possibility of sustaining autotrophic nitrogen in high strength waste-streams in the presence of organic substrates warrants further investigation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.181
Teacher spread0.174 · 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 source (direct Gemma or distilled Codex), 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

Citations34
Published2020
Admission routes2
Has abstractyes

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