MétaCan
Menu
← Retour à la cohorte
Enregistrement W7019709915

Hypoxic Methane Oxidation Coupled to Denitrification in a Membrane Biofilm Reactor

2020· dissertation· en· W7019709915 sur OpenAlexaboutno aff

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2020
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueWastewater Treatment and Nitrogen Removal
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDenitrificationAnaerobic oxidation of methaneNitrateMethaneNitriteWastewaterMembrane reactorBioreactorSewage treatment
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Nitrate removal has become a necessity in Canada and around the globe as a means to mitigate \nharmful effects from nitrogen compounds, such as eutrophication, which pose toxic hazards to \nboth aquatic life as well as human health. Nitrogen compounds, among other contaminants, will \nbe or already have been regulated for drinking water and wastewater effluent. Thus, to aid in \ncompliance with regulations, biological nitrogen removal has been thoroughly investigated using \nnumerous bioreactor configurations and electron donors with consideration given to minimizing \ncarbon footprint and finding cost-efficient methods. The membrane biofilm reactor (MBfR) is a \nbio-technique that has been investigated for the removal of various contaminants from water \nbodies and wastewater. This approach uses a gaseous substrate that serves as an electron donor \n(e.g., methane or hydrogen), which is supplied via a hollow-fiber membrane lumen to the \nacclimated biofilm on the outer surface. This technology is an option for efficient nitrate removal \nwith methane as the primary electron donor and carbon source. This treatment is both practical \nand eco-friendly because methane can be produced on-site in wastewater treatment plants at a \nlower cost than methanol that is widely used for denitrification. Hence, the objectives of this \nstudy was to gain an advanced understanding of the process of methane oxidation coupled to \ndenitrification (MOD) in a methane-based membrane biofilm reactor. The study also aimed to \nsystematically characterize and optimize the effects of operating conditions, hydraulic retention \ntime (HRT), nitrate loading rate (NLR), methane flux at high and low methane pressures. In \naddition, nitrite removal via methane-based MBfR was also explored to evaluate the \nsustainability of nitrite reduction compared to nitrate reduction in the denitrification process \nunder hypoxic conditions. In addition, the microbial population in the MBfR was studied under \ndifferent operating scenarios. \nAn MBfR with gas-permeable hydrophobic polyethylene fibers, enriched with MOD culture was \noperated while applying high methane pressures (7, 5, and 2 psig), and total specific surface area \nof 35 m2/m3, have showed a relatively low nitrate removal rate, with 1.2 – 1.3 mg N/L-h at \nmethane pressure of 2-7 psig and HRT 12 h, while the dissolved methane was as high as (8 -13 \nmg CH4/L). These results suggest that the methane oxidation and nitrate reduction are limited by \nthe microorganism’s kinetics, rather than methane transfer to the biofilm. The sequencing analysis showed Methylocystaceae was dominant, with 21% of bacterial SSU rRNA genes. \nMoreover, there were no traces of archaea in the community in either biofilm or planktonic \nsamples. An MBfR enriched with Methylocystaceae using a hydrophobic polyvinylidene \ndifluoride (PVDF) gas permeable membranes, with total surface area of 188.5 cm2, was operated \nat low methane pressures (0.05 – 0.25 psig) to monitor the impact on the dissolved methane \nconcentrations and nitrate reduction. The nitrate concentration in the effluent was 4.0 mg NO3 \n- \n/L, with a minimal methane concentration in the effluent of 3.3 mg CH4/L with a hydraulic \nretention time of 4 hours. These results imply that the implication of this type of gas permeable \nmembranes have proven to be more efficient in methane gas delivery, in which the nitrate \nremoval flux was as high as 412.2 mg N/m2-d, and successfully managed to decrease the \ndissolved methane in the effluent. The dissolved oxygen in the MBfR recorded an average of \n0.04 mg O2/L. The 16S rRNA gene sequencing analysis detected Methylococcus bacteria that are \nable to oxidize methane coupled to denitrification. The results indicated syntrophic microbial \ninteraction in a consortium of aerobic methanotrophs and denitrifiers in the active biofilm of a \nmethane-based MBfR under hypoxic conditions. A methane-based MBfR inoculated with 21% \nMethylocystaceae in bacterial SSU rRNA genes, evidenced to have the ability to remove nitrite; \nwith a removal flux was up to 885 mg N/m2-d, at a relatively low methane pressure of 2.4 kPa \n(0.35 psig); indicating that nitrite reduction step is not the main rate limiting step in the \ndenitrification process inside the biofilm. The microbial community sequencing showed the \nexistence of Methylococcus capsulatus, a Type I methanotroph, at relative abundance of 78% for \nthe maximum HRT of 12 hours and a methane pressure of 0.35 kPa (0.05 psig), while the \nrelative abundance decreased when the HRT was 4 and 2 hours at the same methane pressure. \nThis implies that we cannot correlate Methylococcus capsulatus abundance to the electron donor \n(methane) flux in this particular experimental set. The study outcomes support that methanebased \nMBfRs can be a proficient and sustainable biotechnology approach to meet strict nitrogen \nstandards in wastewater effluent, under hypoxic conditions with insignificant methane buildup.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,010
Score d'incertitude au seuil0,019

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,200
Écart entre enseignants0,188 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueUWSpace (University of Waterloo)→Même sujetWastewater Treatment and Nitrogen Removal→Travaux en français237 207→