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Review on anaerobic digestion models: Model classification & elaboration of process phenomena

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dc.title Review on anaerobic digestion models: Model classification & elaboration of process phenomena en
dc.contributor.author Emebu, Samuel
dc.contributor.author Pecha, Jiří
dc.contributor.author Janáčová, Dagmar
dc.relation.ispartof Renewable and Sustainable Energy Reviews
dc.identifier.issn 1364-0321 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.issn 1879-0690 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2022
utb.relation.volume 160
dc.type article
dc.language.iso en
dc.publisher Pergamon-Elsevier Science Ltd
dc.identifier.doi 10.1016/j.rser.2022.112288
dc.relation.uri https://www.sciencedirect.com/science/article/pii/S1364032122002076
dc.subject biogas en
dc.subject anaerobic digestion en
dc.subject single-equation model en
dc.subject single-step degradation model en
dc.subject multi-step dynamic model en
dc.subject AM2 en
dc.subject ADM1 en
dc.subject mathematical modelling en
dc.subject heat and mass transfer en
dc.subject hydrolysis en
dc.subject model classification en
dc.subject microbial kinetics en
dc.description.abstract Biogas is a well-established renewable energy source produced from anaerobic digestion (AD) of biomass/ feedstock. It is probably the most versatile and efficient biofuel in terms of utilisable feedstocks and energy applications. To monitor, optimise, and control anaerobic digestion (AD), numerous mathematical models describing AD have been developed and reported. Although literature on the use of these models and their reviews have been published, their differences have not been collectively analysed and no generalised classification criteria for these models has been proposed based on such an analysis. This review covers most reported AD models, from the simplest linear equation capturing biogas production rate to complex Anaerobic Digestion Model No. 1. In addition to model classification and biochemical stages in AD, other processes like feedstock hydrolysis or mass and heat transfer essential to AD were discussed, analysed, and available models on them reviewed. This collective and comprehensive review approach has been undertaken to enable the evaluation of the interdependence of all processes, process factors, and process estimations and their individual, and interactive effects on AD. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1010890
utb.identifier.obdid 43883617
utb.identifier.scopus 2-s2.0-85125762739
utb.identifier.wok 000778938900002
utb.identifier.coden RSERF
utb.source j-scopus
dc.date.accessioned 2022-03-21T08:23:45Z
dc.date.available 2022-03-21T08:23:45Z
dc.description.sponsorship Norges Teknisk-Naturvitenskapelige Universitet, NTNU; Univerzita Tomáše Bati ve Zlíně: IGA/CebiaTech/2020/001, IGA/CebiaTech/2021/002
dc.description.sponsorship Internal Grant Agency of the Tomas Bata University in Zlin, Czech Republic [IGA/CebiaTech/2020/001, IGA/CebiaTech/2021/002]
utb.contributor.internalauthor Emebu, Samuel
utb.contributor.internalauthor Pecha, Jiří
utb.contributor.internalauthor Janáčová, Dagmar
utb.fulltext.affiliation Samuel Emebu, Jiří Pecha *, Dagmar Janáčová Faculty of Applied Informatics, Tomas Bata University in Zlín, Nad Stráněmi 4511, 760 05, Zlín, Czech Republic
utb.fulltext.dates Received 21 July 2021 Received in revised form 27 January 2022 Accepted 16 February 2022
utb.fulltext.sponsorship This work was supported by the Internal Grant Agency of the Tomas Bata University in Zlín, Czech Republic: projects (IGA/CebiaTech/2020/001) and (IGA/CebiaTech/2021/002).
utb.wos.affiliation [Emebu, Samuel; Pecha, Jiri; Janacova, Dagmar] Tomas Bata Univ Zlin, Fac Appl Informat, Stranemi 4511, Zlin 76005, Czech Republic
utb.scopus.affiliation Faculty of Applied Informatics, Tomas Bata University in Zlín, Nad Stráněmi 4511, Zlín, 760 05, Czech Republic
utb.fulltext.projects IGA/CebiaTech/2020/001
utb.fulltext.projects IGA/CebiaTech/2021/002
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.ou -
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