Kinetic prediction of biochemical methane potential of pig slurry
Autor(a) principal: | |
---|---|
Data de Publicação: | 2022 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/100495 https://doi.org/10.1016/j.egyr.2022.01.128 |
Resumo: | Empirical Kinetic Models have been used to describe and establish the Anaerobic Digestion kinetics of pig slurry’s (8% TS) Biochemical Chemical Potential. A wide selection of Empirical Kinetic Models were fitted to the experimental data collected in batch assays of different Substrate to Inoculum ratios, 0.65 (BMP1) and 1 (BMP2). For the selection of the most suitable model for each BMP assay, the statistical tools R2 and the RMSE, along with the Information Criterion AIC and BIC, were taken into consideration. From all the studied models, the Weibull model proved to be the most suitable for kinetic parameter prediction for both BMP1 and BMP2 assays. This model presented the lowest values of AIC and BIC, along with the highest value of R2 and the lowest RMSE. In this regard, a R2=0.998, and a RMSE=0.004, was obtained for BMP1, and a R2=0.999 and a RMSE=0.008 for BMP2. |
id |
RCAP_847356b0c0acd61979f401141002e31a |
---|---|
oai_identifier_str |
oai:estudogeral.uc.pt:10316/100495 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Kinetic prediction of biochemical methane potential of pig slurryAnaerobic digestionBiomethane potential testKinetic evaluationKinetic studyNumerical computationPig slurryEmpirical Kinetic Models have been used to describe and establish the Anaerobic Digestion kinetics of pig slurry’s (8% TS) Biochemical Chemical Potential. A wide selection of Empirical Kinetic Models were fitted to the experimental data collected in batch assays of different Substrate to Inoculum ratios, 0.65 (BMP1) and 1 (BMP2). For the selection of the most suitable model for each BMP assay, the statistical tools R2 and the RMSE, along with the Information Criterion AIC and BIC, were taken into consideration. From all the studied models, the Weibull model proved to be the most suitable for kinetic parameter prediction for both BMP1 and BMP2 assays. This model presented the lowest values of AIC and BIC, along with the highest value of R2 and the lowest RMSE. In this regard, a R2=0.998, and a RMSE=0.004, was obtained for BMP1, and a R2=0.999 and a RMSE=0.008 for BMP2.2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/100495http://hdl.handle.net/10316/100495https://doi.org/10.1016/j.egyr.2022.01.128eng23524847Santos, Andreia D.Silva, João R.Castro, Luís Miguel Moura Neves deQuinta-Ferreira, Rosa M.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-06-24T20:31:14Zoai:estudogeral.uc.pt:10316/100495Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:17:52.314851Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Kinetic prediction of biochemical methane potential of pig slurry |
title |
Kinetic prediction of biochemical methane potential of pig slurry |
spellingShingle |
Kinetic prediction of biochemical methane potential of pig slurry Santos, Andreia D. Anaerobic digestion Biomethane potential test Kinetic evaluation Kinetic study Numerical computation Pig slurry |
title_short |
Kinetic prediction of biochemical methane potential of pig slurry |
title_full |
Kinetic prediction of biochemical methane potential of pig slurry |
title_fullStr |
Kinetic prediction of biochemical methane potential of pig slurry |
title_full_unstemmed |
Kinetic prediction of biochemical methane potential of pig slurry |
title_sort |
Kinetic prediction of biochemical methane potential of pig slurry |
author |
Santos, Andreia D. |
author_facet |
Santos, Andreia D. Silva, João R. Castro, Luís Miguel Moura Neves de Quinta-Ferreira, Rosa M. |
author_role |
author |
author2 |
Silva, João R. Castro, Luís Miguel Moura Neves de Quinta-Ferreira, Rosa M. |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Santos, Andreia D. Silva, João R. Castro, Luís Miguel Moura Neves de Quinta-Ferreira, Rosa M. |
dc.subject.por.fl_str_mv |
Anaerobic digestion Biomethane potential test Kinetic evaluation Kinetic study Numerical computation Pig slurry |
topic |
Anaerobic digestion Biomethane potential test Kinetic evaluation Kinetic study Numerical computation Pig slurry |
description |
Empirical Kinetic Models have been used to describe and establish the Anaerobic Digestion kinetics of pig slurry’s (8% TS) Biochemical Chemical Potential. A wide selection of Empirical Kinetic Models were fitted to the experimental data collected in batch assays of different Substrate to Inoculum ratios, 0.65 (BMP1) and 1 (BMP2). For the selection of the most suitable model for each BMP assay, the statistical tools R2 and the RMSE, along with the Information Criterion AIC and BIC, were taken into consideration. From all the studied models, the Weibull model proved to be the most suitable for kinetic parameter prediction for both BMP1 and BMP2 assays. This model presented the lowest values of AIC and BIC, along with the highest value of R2 and the lowest RMSE. In this regard, a R2=0.998, and a RMSE=0.004, was obtained for BMP1, and a R2=0.999 and a RMSE=0.008 for BMP2. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10316/100495 http://hdl.handle.net/10316/100495 https://doi.org/10.1016/j.egyr.2022.01.128 |
url |
http://hdl.handle.net/10316/100495 https://doi.org/10.1016/j.egyr.2022.01.128 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
23524847 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799134074287161344 |