Modeling of renewable energy production from the treatment of slaughterhouse wastewater with ruminal liquor in microbial fuel cells

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The present study aims to optimize the application of a microbial fuel cell (MFC) in the treatment of slaughterhouse wastewater and the production of electricity. The methodology included the response surface analysis (RSA) to evaluate the effect of three factors: the standard reduction potential, S...

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Detalles Bibliográficos
Autores: Valdiviezo Gonzales, Lorgio, Cabello-Torres, Rita J., Valentin Torres, Esmeralda, Flores del Pino, Lisveth, Castañeda-Olivera, Carlos A.
Formato: artículo
Fecha de Publicación:2022
Institución:Universidad Tecnológica del Perú
Repositorio:UTP-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.utp.edu.pe:20.500.12867/5838
Enlace del recurso:https://hdl.handle.net/20.500.12867/5838
http://doi.org/10.3303/CET2291108
Nivel de acceso:acceso abierto
Materia:Microbial fuel
Wastewater
Production of electricity
https://purl.org/pe-repo/ocde/ford#2.08.00
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dc.title.es_PE.fl_str_mv Modeling of renewable energy production from the treatment of slaughterhouse wastewater with ruminal liquor in microbial fuel cells
title Modeling of renewable energy production from the treatment of slaughterhouse wastewater with ruminal liquor in microbial fuel cells
spellingShingle Modeling of renewable energy production from the treatment of slaughterhouse wastewater with ruminal liquor in microbial fuel cells
Valdiviezo Gonzales, Lorgio
Microbial fuel
Wastewater
Production of electricity
https://purl.org/pe-repo/ocde/ford#2.08.00
title_short Modeling of renewable energy production from the treatment of slaughterhouse wastewater with ruminal liquor in microbial fuel cells
title_full Modeling of renewable energy production from the treatment of slaughterhouse wastewater with ruminal liquor in microbial fuel cells
title_fullStr Modeling of renewable energy production from the treatment of slaughterhouse wastewater with ruminal liquor in microbial fuel cells
title_full_unstemmed Modeling of renewable energy production from the treatment of slaughterhouse wastewater with ruminal liquor in microbial fuel cells
title_sort Modeling of renewable energy production from the treatment of slaughterhouse wastewater with ruminal liquor in microbial fuel cells
author Valdiviezo Gonzales, Lorgio
author_facet Valdiviezo Gonzales, Lorgio
Cabello-Torres, Rita J.
Valentin Torres, Esmeralda
Flores del Pino, Lisveth
Castañeda-Olivera, Carlos A.
author_role author
author2 Cabello-Torres, Rita J.
Valentin Torres, Esmeralda
Flores del Pino, Lisveth
Castañeda-Olivera, Carlos A.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Valdiviezo Gonzales, Lorgio
Cabello-Torres, Rita J.
Valentin Torres, Esmeralda
Flores del Pino, Lisveth
Castañeda-Olivera, Carlos A.
dc.subject.es_PE.fl_str_mv Microbial fuel
Wastewater
Production of electricity
topic Microbial fuel
Wastewater
Production of electricity
https://purl.org/pe-repo/ocde/ford#2.08.00
dc.subject.ocde.es_PE.fl_str_mv https://purl.org/pe-repo/ocde/ford#2.08.00
description The present study aims to optimize the application of a microbial fuel cell (MFC) in the treatment of slaughterhouse wastewater and the production of electricity. The methodology included the response surface analysis (RSA) to evaluate the effect of three factors: the standard reduction potential, SRP (copper, zinc, and graphite; electrode surface area (ESA), and the doses of ruminal liquor (DOSE). The power density (PD) and the removal of the chemical oxygen demand (COD) were determined as the main response variables. The results indicated that the generation of electrical energy depended significantly on the SRP applied, highlighting the copper-graphite arrangement that generated a maximum PD (0.5685 W/m3) and the graphite-graphite that produced the highest removal of COD (81.33%). Consequently, the RSA produced significant predictive models for the generation of PD (R2 = 0.9485, p = 0.029) and removal of COD (R2 = 0.9888, p = 0.002). MFC is presented as a technology intended to be part of the diversification of renewable energy sources and at the same time recover water resources sustainably.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-07-27T21:35:29Z
dc.date.available.none.fl_str_mv 2022-07-27T21:35:29Z
dc.date.issued.fl_str_mv 2022
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dc.identifier.issn.none.fl_str_mv 2283-9216
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12867/5838
dc.identifier.journal.es_PE.fl_str_mv Chemical Engineering Transactions
dc.identifier.doi.none.fl_str_mv http://doi.org/10.3303/CET2291108
identifier_str_mv 2283-9216
Chemical Engineering Transactions
url https://hdl.handle.net/20.500.12867/5838
http://doi.org/10.3303/CET2291108
dc.language.iso.es_PE.fl_str_mv eng
language eng
dc.relation.ispartofseries.none.fl_str_mv Chemical Engineering Transactions;vol. 91, pp. 643 - 648
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dc.publisher.es_PE.fl_str_mv Associazione Italiana Di Ingegneria Chimica
dc.publisher.country.es_PE.fl_str_mv IT
dc.source.es_PE.fl_str_mv Repositorio Institucional - UTP
Universidad Tecnológica del Perú
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spelling Valdiviezo Gonzales, LorgioCabello-Torres, Rita J.Valentin Torres, EsmeraldaFlores del Pino, LisvethCastañeda-Olivera, Carlos A.2022-07-27T21:35:29Z2022-07-27T21:35:29Z20222283-9216https://hdl.handle.net/20.500.12867/5838Chemical Engineering Transactionshttp://doi.org/10.3303/CET2291108The present study aims to optimize the application of a microbial fuel cell (MFC) in the treatment of slaughterhouse wastewater and the production of electricity. The methodology included the response surface analysis (RSA) to evaluate the effect of three factors: the standard reduction potential, SRP (copper, zinc, and graphite; electrode surface area (ESA), and the doses of ruminal liquor (DOSE). The power density (PD) and the removal of the chemical oxygen demand (COD) were determined as the main response variables. The results indicated that the generation of electrical energy depended significantly on the SRP applied, highlighting the copper-graphite arrangement that generated a maximum PD (0.5685 W/m3) and the graphite-graphite that produced the highest removal of COD (81.33%). Consequently, the RSA produced significant predictive models for the generation of PD (R2 = 0.9485, p = 0.029) and removal of COD (R2 = 0.9888, p = 0.002). 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