Modeling of Nitrous Oxide Production from Nitritation Reactors Treating Real Anaerobic Digestion Liquor.
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Auteurs : Qilin Wang [Australie] ; Bing-Jie Ni [Australie] ; Romain Lemaire [France] ; Xiaodi Hao [République populaire de Chine] ; Zhiguo Yuan [Australie]Source :
- Scientific reports [ 2045-2322 ] ; 2016.
Abstract
In this work, a mathematical model including both ammonium oxidizing bacteria (AOB) and heterotrophic bacteria (HB) is constructed to predict N2O production from the nitritation systems receiving the real anaerobic digestion liquor. This is for the first time that N2O production from such systems was modeled considering both AOB and HB. The model was calibrated and validated using experimental data from both lab- and pilot-scale nitritation reactors. The model predictions matched the dynamic N2O, ammonium, nitrite and chemical oxygen demand data well, supporting the capability of the model. Modeling results indicated that HB are the dominant contributor to N2O production in the above systems with the dissolved oxygen (DO) concentration of 0.5-1.0 mg O2/L, accounting for approximately 75% of N2O production. The modeling results also suggested that the contribution of HB to N2O production decreased with the increasing DO concentrations, from 75% at DO = 0.5 mg O2/L to 25% at DO = 7.0 mg O2/L, with a corresponding increase of the AOB contribution (from 25% to 75%). Similar to HB, the total N2O production rate also decreased dramatically from 0.65 to 0.25 mg N/L/h when DO concentration increased from 0.5 to 7.0 mg O2/L.
DOI: 10.1038/srep25336
PubMed: 27125491
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China.</nlm:affiliation><country xml:lang="fr" wicri:curation="lc">République populaire de Chine</country><wicri:regionArea>Key Laboratory of Urban Stormwater System and Water Environment/R&D Centre for Sustainable Wastewater Treatment (Beijing University of Civil Engineering and Architecture), Ministry of Education, Beijing 100044</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Yuan, Zhiguo" sort="Yuan, Zhiguo" uniqKey="Yuan Z" first="Zhiguo" last="Yuan">Zhiguo Yuan</name><affiliation wicri:level="1"><nlm:affiliation>Advanced Water Management Centre (AWMC), The University of Queensland, QLD 4072, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Advanced Water Management Centre (AWMC), The University of Queensland, QLD 4072</wicri:regionArea><wicri:noRegion>QLD 4072</wicri:noRegion></affiliation></author></analytic><series><title level="j">Scientific reports</title><idno type="eISSN">2045-2322</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In this work, a mathematical model including both ammonium oxidizing bacteria (AOB) and heterotrophic bacteria (HB) is constructed to predict N2O production from the nitritation systems receiving the real anaerobic digestion liquor. This is for the first time that N2O production from such systems was modeled considering both AOB and HB. The model was calibrated and validated using experimental data from both lab- and pilot-scale nitritation reactors. The model predictions matched the dynamic N2O, ammonium, nitrite and chemical oxygen demand data well, supporting the capability of the model. Modeling results indicated that HB are the dominant contributor to N2O production in the above systems with the dissolved oxygen (DO) concentration of 0.5-1.0 mg O2/L, accounting for approximately 75% of N2O production. The modeling results also suggested that the contribution of HB to N2O production decreased with the increasing DO concentrations, from 75% at DO = 0.5 mg O2/L to 25% at DO = 7.0 mg O2/L, with a corresponding increase of the AOB contribution (from 25% to 75%). Similar to HB, the total N2O production rate also decreased dramatically from 0.65 to 0.25 mg N/L/h when DO concentration increased from 0.5 to 7.0 mg O2/L.</div></front></TEI><pubmed><MedlineCitation Status="In-Process" Owner="NLM"><PMID Version="1">27125491</PMID><DateCreated><Year>2016</Year><Month>04</Month><Day>29</Day></DateCreated><DateRevised><Year>2017</Year><Month>08</Month><Day>07</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">2045-2322</ISSN><JournalIssue CitedMedium="Internet"><Volume>6</Volume><PubDate><Year>2016</Year><Month>04</Month><Day>29</Day></PubDate></JournalIssue><Title>Scientific reports</Title><ISOAbbreviation>Sci Rep</ISOAbbreviation></Journal><ArticleTitle>Modeling of Nitrous Oxide Production from Nitritation Reactors Treating Real Anaerobic Digestion Liquor.</ArticleTitle><Pagination><MedlinePgn>25336</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1038/srep25336</ELocationID><Abstract><AbstractText>In this work, a mathematical model including both ammonium oxidizing bacteria (AOB) and heterotrophic bacteria (HB) is constructed to predict N2O production from the nitritation systems receiving the real anaerobic digestion liquor. This is for the first time that N2O production from such systems was modeled considering both AOB and HB. The model was calibrated and validated using experimental data from both lab- and pilot-scale nitritation reactors. The model predictions matched the dynamic N2O, ammonium, nitrite and chemical oxygen demand data well, supporting the capability of the model. Modeling results indicated that HB are the dominant contributor to N2O production in the above systems with the dissolved oxygen (DO) concentration of 0.5-1.0 mg O2/L, accounting for approximately 75% of N2O production. The modeling results also suggested that the contribution of HB to N2O production decreased with the increasing DO concentrations, from 75% at DO = 0.5 mg O2/L to 25% at DO = 7.0 mg O2/L, with a corresponding increase of the AOB contribution (from 25% to 75%). Similar to HB, the total N2O production rate also decreased dramatically from 0.65 to 0.25 mg N/L/h when DO concentration increased from 0.5 to 7.0 mg O2/L.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Qilin</ForeName><Initials>Q</Initials><AffiliationInfo><Affiliation>Advanced Water Management Centre (AWMC), The University of Queensland, QLD 4072, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ni</LastName><ForeName>Bing-Jie</ForeName><Initials>BJ</Initials><AffiliationInfo><Affiliation>Advanced Water Management Centre (AWMC), The University of Queensland, QLD 4072, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lemaire</LastName><ForeName>Romain</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Veolia Technical and Performance Department, St-Maurice, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hao</LastName><ForeName>Xiaodi</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Key Laboratory of Urban Stormwater System and Water Environment/R&D Centre for Sustainable Wastewater Treatment (Beijing University of Civil Engineering and Architecture), Ministry of Education, Beijing 100044, P.R. China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Yuan</LastName><ForeName>Zhiguo</ForeName><Initials>Z</Initials><AffiliationInfo><Affiliation>Advanced Water Management Centre (AWMC), The University of Queensland, QLD 4072, Australia.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2016</Year><Month>04</Month><Day>29</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Sci Rep</MedlineTA><NlmUniqueID>101563288</NlmUniqueID><ISSNLinking>2045-2322</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Water Res. 2014 Feb 1;49:23-33</RefSource><PMID 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Chine"><noRegion><name sortKey="Hao, Xiaodi" sort="Hao, Xiaodi" uniqKey="Hao X" first="Xiaodi" last="Hao">Xiaodi Hao</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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