Dynamic modelling of high biomass density cultivation and biohydrogen production in different scales of flat plate photobioreactors
ABSTRACT This paper investigates the scaling‐up of cyanobacterial biomass cultivation and biohydrogen production from laboratory to industrial scale. Two main aspects are investigated and presented, which to the best of our knowledge have never been addressed, namely the construction of an accurate...
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Veröffentlicht in: | Biotechnology and bioengineering 2015-12, Vol.112 (12), p.2429-2438 |
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creator | Zhang, Dongda Dechatiwongse, Pongsathorn del Rio-Chanona, Ehecatl Antonio Maitland, Geoffrey C. Hellgardt, Klaus Vassiliadis, Vassilios S. |
description | ABSTRACT
This paper investigates the scaling‐up of cyanobacterial biomass cultivation and biohydrogen production from laboratory to industrial scale. Two main aspects are investigated and presented, which to the best of our knowledge have never been addressed, namely the construction of an accurate dynamic model to simulate cyanobacterial photo‐heterotrophic growth and biohydrogen production and the prediction of the maximum biomass and hydrogen production in different scales of photobioreactors. To achieve the current goals, experimental data obtained from a laboratory experimental setup are fitted by a dynamic model. Based on the current model, two key original findings are made in this work. First, it is found that selecting low‐chlorophyll mutants is an efficient way to increase both biomass concentration and hydrogen production particularly in a large scale photobioreactor. Second, the current work proposes that the width of industrial scale photobioreactors should not exceed 0.20 m for biomass cultivation and 0.05 m for biohydrogen production, as severe light attenuation can be induced in the reactor beyond this threshold. Biotechnol. Bioeng. 2015;112: 2429–2438. © 2015 The Authors. Biotechnology and Bioengineering Published by Wiley Peiodicals, Inc.
A dynamic model was constructed to simulate cyanobacterial (Cyanothece sp. ATCC 51142) photo‐heterotrophic growth and biohydrogen production; a stable dynamic parameter estimation methodology was applied to guarantee the model accuracy. The model was used to estimate cyanobacterial growth and hydrogen production in different scales of flat‐plate photobioreactors. It is found that the efficient strategy to increase hydrogen production in laboratory scale processes is to seek the optimal operating conditions, while that in large scale processes is to select low‐chlorophyll mutants. |
doi_str_mv | 10.1002/bit.25661 |
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This paper investigates the scaling‐up of cyanobacterial biomass cultivation and biohydrogen production from laboratory to industrial scale. Two main aspects are investigated and presented, which to the best of our knowledge have never been addressed, namely the construction of an accurate dynamic model to simulate cyanobacterial photo‐heterotrophic growth and biohydrogen production and the prediction of the maximum biomass and hydrogen production in different scales of photobioreactors. To achieve the current goals, experimental data obtained from a laboratory experimental setup are fitted by a dynamic model. Based on the current model, two key original findings are made in this work. First, it is found that selecting low‐chlorophyll mutants is an efficient way to increase both biomass concentration and hydrogen production particularly in a large scale photobioreactor. Second, the current work proposes that the width of industrial scale photobioreactors should not exceed 0.20 m for biomass cultivation and 0.05 m for biohydrogen production, as severe light attenuation can be induced in the reactor beyond this threshold. Biotechnol. Bioeng. 2015;112: 2429–2438. © 2015 The Authors. Biotechnology and Bioengineering Published by Wiley Peiodicals, Inc.
A dynamic model was constructed to simulate cyanobacterial (Cyanothece sp. ATCC 51142) photo‐heterotrophic growth and biohydrogen production; a stable dynamic parameter estimation methodology was applied to guarantee the model accuracy. The model was used to estimate cyanobacterial growth and hydrogen production in different scales of flat‐plate photobioreactors. It is found that the efficient strategy to increase hydrogen production in laboratory scale processes is to seek the optimal operating conditions, while that in large scale processes is to select low‐chlorophyll mutants.</description><identifier>ISSN: 0006-3592</identifier><identifier>EISSN: 1097-0290</identifier><identifier>DOI: 10.1002/bit.25661</identifier><identifier>PMID: 26041472</identifier><identifier>CODEN: BIBIAU</identifier><language>eng</language><publisher>United States: Blackwell Publishing Ltd</publisher><subject>Biohydrogen ; biohydrogen production ; Biomass ; biomass cultivation ; Biotechnology ; Chlorophyll ; Computer simulation ; Construction ; Cultivation ; Cyanobacteria - growth & development ; Cyanobacteria - metabolism ; Cyanothece ; Dynamic models ; dynamic simulation ; Dynamics ; Hydrogen - metabolism ; Hydrogen production ; light attenuation ; Mathematical models ; Models, Theoretical ; Mutation ; photo-heterotrophic growth ; photobioreactor ; Photobioreactors - microbiology ; Simulation</subject><ispartof>Biotechnology and bioengineering, 2015-12, Vol.112 (12), p.2429-2438</ispartof><rights>2015 The Authors. Published by Wiley Peiodicals, Inc.</rights><rights>2015 Wiley Periodicals, Inc.</rights><rights>Copyright Wiley Subscription Services, Inc. Dec 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5841-60220365243b98c919224a33ab5c0acc0c854022bf13a8bece341015390cb05a3</citedby><cites>FETCH-LOGICAL-c5841-60220365243b98c919224a33ab5c0acc0c854022bf13a8bece341015390cb05a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fbit.25661$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fbit.25661$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,1411,27903,27904,45553,45554</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26041472$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Dongda</creatorcontrib><creatorcontrib>Dechatiwongse, Pongsathorn</creatorcontrib><creatorcontrib>del Rio-Chanona, Ehecatl Antonio</creatorcontrib><creatorcontrib>Maitland, Geoffrey C.</creatorcontrib><creatorcontrib>Hellgardt, Klaus</creatorcontrib><creatorcontrib>Vassiliadis, Vassilios S.</creatorcontrib><title>Dynamic modelling of high biomass density cultivation and biohydrogen production in different scales of flat plate photobioreactors</title><title>Biotechnology and bioengineering</title><addtitle>Biotechnol. Bioeng</addtitle><description>ABSTRACT
This paper investigates the scaling‐up of cyanobacterial biomass cultivation and biohydrogen production from laboratory to industrial scale. Two main aspects are investigated and presented, which to the best of our knowledge have never been addressed, namely the construction of an accurate dynamic model to simulate cyanobacterial photo‐heterotrophic growth and biohydrogen production and the prediction of the maximum biomass and hydrogen production in different scales of photobioreactors. To achieve the current goals, experimental data obtained from a laboratory experimental setup are fitted by a dynamic model. Based on the current model, two key original findings are made in this work. First, it is found that selecting low‐chlorophyll mutants is an efficient way to increase both biomass concentration and hydrogen production particularly in a large scale photobioreactor. Second, the current work proposes that the width of industrial scale photobioreactors should not exceed 0.20 m for biomass cultivation and 0.05 m for biohydrogen production, as severe light attenuation can be induced in the reactor beyond this threshold. Biotechnol. Bioeng. 2015;112: 2429–2438. © 2015 The Authors. Biotechnology and Bioengineering Published by Wiley Peiodicals, Inc.
A dynamic model was constructed to simulate cyanobacterial (Cyanothece sp. ATCC 51142) photo‐heterotrophic growth and biohydrogen production; a stable dynamic parameter estimation methodology was applied to guarantee the model accuracy. The model was used to estimate cyanobacterial growth and hydrogen production in different scales of flat‐plate photobioreactors. It is found that the efficient strategy to increase hydrogen production in laboratory scale processes is to seek the optimal operating conditions, while that in large scale processes is to select low‐chlorophyll mutants.</description><subject>Biohydrogen</subject><subject>biohydrogen production</subject><subject>Biomass</subject><subject>biomass cultivation</subject><subject>Biotechnology</subject><subject>Chlorophyll</subject><subject>Computer simulation</subject><subject>Construction</subject><subject>Cultivation</subject><subject>Cyanobacteria - growth & development</subject><subject>Cyanobacteria - metabolism</subject><subject>Cyanothece</subject><subject>Dynamic models</subject><subject>dynamic simulation</subject><subject>Dynamics</subject><subject>Hydrogen - metabolism</subject><subject>Hydrogen production</subject><subject>light attenuation</subject><subject>Mathematical models</subject><subject>Models, Theoretical</subject><subject>Mutation</subject><subject>photo-heterotrophic growth</subject><subject>photobioreactor</subject><subject>Photobioreactors - microbiology</subject><subject>Simulation</subject><issn>0006-3592</issn><issn>1097-0290</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>EIF</sourceid><recordid>eNqNks1u1DAURi0EokNhwQsgS2xgkdb_TjZI0DJtpQKboi4tx3EmLok92Ekha14cz0w7AiSkbmxZ99wj-_oD4CVGRxghcly78YhwIfAjsMCokgUiFXoMFgghUVBekQPwLKWbfJSlEE_BARGIYSbJAvw6nb0enIFDaGzfO7-CoYWdW3WwdmHQKcHG-uTGGZqpH92tHl3wUPtmU-_mJoaV9XAdQzOZbcl52Li2tdH6ESaje5s2yrbXI1znxcJ1F8aQu6PVZgwxPQdPWt0n--JuPwRflx-vTs6Lyy9nFyfvLwvDS4YLgQhBVHDCaF2VpsIVIUxTqmtukDYGmZKzzNQtprqsrbGUYYQ5rZCpEdf0ELzbeddTPdjG5AtG3at1dIOOswraqb8r3nVqFW4VqyQXlcyCN3eCGL5PNo1qcMnksWlvw5QUljJfkDLJH4BSUhJZ0uoBaCa5JJJl9PU_6E2Yos9D2wrz12NMM_V2R5kYUoq23T8RI7UJjMqBUdvAZPbVnzPZk_cJycDxDvjhejv_36Q-XFzdK4tdh0uj_bnv0PGbEpJKrq4_n6nlkp-K6_NPStLf7xXaqA</recordid><startdate>201512</startdate><enddate>201512</enddate><creator>Zhang, Dongda</creator><creator>Dechatiwongse, Pongsathorn</creator><creator>del Rio-Chanona, Ehecatl Antonio</creator><creator>Maitland, Geoffrey C.</creator><creator>Hellgardt, Klaus</creator><creator>Vassiliadis, Vassilios S.</creator><general>Blackwell Publishing Ltd</general><general>Wiley Subscription Services, Inc</general><general>John Wiley and Sons Inc</general><scope>BSCLL</scope><scope>24P</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7T7</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>201512</creationdate><title>Dynamic modelling of high biomass density cultivation and biohydrogen production in different scales of flat plate photobioreactors</title><author>Zhang, Dongda ; Dechatiwongse, Pongsathorn ; del Rio-Chanona, Ehecatl Antonio ; Maitland, Geoffrey C. ; Hellgardt, Klaus ; Vassiliadis, Vassilios S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5841-60220365243b98c919224a33ab5c0acc0c854022bf13a8bece341015390cb05a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Biohydrogen</topic><topic>biohydrogen production</topic><topic>Biomass</topic><topic>biomass cultivation</topic><topic>Biotechnology</topic><topic>Chlorophyll</topic><topic>Computer simulation</topic><topic>Construction</topic><topic>Cultivation</topic><topic>Cyanobacteria - growth & development</topic><topic>Cyanobacteria - metabolism</topic><topic>Cyanothece</topic><topic>Dynamic models</topic><topic>dynamic simulation</topic><topic>Dynamics</topic><topic>Hydrogen - metabolism</topic><topic>Hydrogen production</topic><topic>light attenuation</topic><topic>Mathematical models</topic><topic>Models, Theoretical</topic><topic>Mutation</topic><topic>photo-heterotrophic growth</topic><topic>photobioreactor</topic><topic>Photobioreactors - microbiology</topic><topic>Simulation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Dongda</creatorcontrib><creatorcontrib>Dechatiwongse, Pongsathorn</creatorcontrib><creatorcontrib>del Rio-Chanona, Ehecatl Antonio</creatorcontrib><creatorcontrib>Maitland, Geoffrey C.</creatorcontrib><creatorcontrib>Hellgardt, Klaus</creatorcontrib><creatorcontrib>Vassiliadis, Vassilios S.</creatorcontrib><collection>Istex</collection><collection>Wiley Online Library Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Biotechnology and bioengineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Dongda</au><au>Dechatiwongse, Pongsathorn</au><au>del Rio-Chanona, Ehecatl Antonio</au><au>Maitland, Geoffrey C.</au><au>Hellgardt, Klaus</au><au>Vassiliadis, Vassilios S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dynamic modelling of high biomass density cultivation and biohydrogen production in different scales of flat plate photobioreactors</atitle><jtitle>Biotechnology and bioengineering</jtitle><addtitle>Biotechnol. Bioeng</addtitle><date>2015-12</date><risdate>2015</risdate><volume>112</volume><issue>12</issue><spage>2429</spage><epage>2438</epage><pages>2429-2438</pages><issn>0006-3592</issn><eissn>1097-0290</eissn><coden>BIBIAU</coden><abstract>ABSTRACT
This paper investigates the scaling‐up of cyanobacterial biomass cultivation and biohydrogen production from laboratory to industrial scale. Two main aspects are investigated and presented, which to the best of our knowledge have never been addressed, namely the construction of an accurate dynamic model to simulate cyanobacterial photo‐heterotrophic growth and biohydrogen production and the prediction of the maximum biomass and hydrogen production in different scales of photobioreactors. To achieve the current goals, experimental data obtained from a laboratory experimental setup are fitted by a dynamic model. Based on the current model, two key original findings are made in this work. First, it is found that selecting low‐chlorophyll mutants is an efficient way to increase both biomass concentration and hydrogen production particularly in a large scale photobioreactor. Second, the current work proposes that the width of industrial scale photobioreactors should not exceed 0.20 m for biomass cultivation and 0.05 m for biohydrogen production, as severe light attenuation can be induced in the reactor beyond this threshold. Biotechnol. Bioeng. 2015;112: 2429–2438. © 2015 The Authors. Biotechnology and Bioengineering Published by Wiley Peiodicals, Inc.
A dynamic model was constructed to simulate cyanobacterial (Cyanothece sp. ATCC 51142) photo‐heterotrophic growth and biohydrogen production; a stable dynamic parameter estimation methodology was applied to guarantee the model accuracy. The model was used to estimate cyanobacterial growth and hydrogen production in different scales of flat‐plate photobioreactors. It is found that the efficient strategy to increase hydrogen production in laboratory scale processes is to seek the optimal operating conditions, while that in large scale processes is to select low‐chlorophyll mutants.</abstract><cop>United States</cop><pub>Blackwell Publishing Ltd</pub><pmid>26041472</pmid><doi>10.1002/bit.25661</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Biohydrogen biohydrogen production Biomass biomass cultivation Biotechnology Chlorophyll Computer simulation Construction Cultivation Cyanobacteria - growth & development Cyanobacteria - metabolism Cyanothece Dynamic models dynamic simulation Dynamics Hydrogen - metabolism Hydrogen production light attenuation Mathematical models Models, Theoretical Mutation photo-heterotrophic growth photobioreactor Photobioreactors - microbiology Simulation |
title | Dynamic modelling of high biomass density cultivation and biohydrogen production in different scales of flat plate photobioreactors |
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