Estimation of effluent quality parameters from an activated sludge system using quantitative image analysis
Autor(a) principal: | |
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Data de Publicação: | 2016 |
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/1822/37914 |
Resumo: | Abstract The efficiency of an activated sludge system is generally evaluated by determining several key parameters related to organic matter removal, nitrification and/or denitrification processes. Off-line methods for the determination of these parameters are commonly labor, time consuming, and environmentally harmful. In contrast, quantitative image analysis (QIA) has been recognized as a prompt method for assessing activated sludge contents and structure. In the present study an activated sludge system was operated under different experimental conditions leading to a variety of operational data. Key parameters such as chemical oxygen demand (COD) and ammonium (N-NH4+), and nitrate (N-NO3-) concentrations, throughout the experimental periods, were measured by classical analytical techniques. QIA was further used for the microbial community characterization. Partial Least Squares (PLS) models were used to correlate QIA information and the aforementioned key parameters. It was found that the use of the morphological and physiological data allowed predicting, at some extent, the effluent COD, N-NH4+, and N-NO3- concentrations based on chemometric techniques. |
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Estimation of effluent quality parameters from an activated sludge system using quantitative image analysisWastewater TreatmentActivated sludgeQuantitative Image Analysis (QIA)MorphologyPhysiologyPartial Least Squares (PLS)Partial least squares (PIS)Science & TechnologyAbstract The efficiency of an activated sludge system is generally evaluated by determining several key parameters related to organic matter removal, nitrification and/or denitrification processes. Off-line methods for the determination of these parameters are commonly labor, time consuming, and environmentally harmful. In contrast, quantitative image analysis (QIA) has been recognized as a prompt method for assessing activated sludge contents and structure. In the present study an activated sludge system was operated under different experimental conditions leading to a variety of operational data. Key parameters such as chemical oxygen demand (COD) and ammonium (N-NH4+), and nitrate (N-NO3-) concentrations, throughout the experimental periods, were measured by classical analytical techniques. QIA was further used for the microbial community characterization. Partial Least Squares (PLS) models were used to correlate QIA information and the aforementioned key parameters. It was found that the use of the morphological and physiological data allowed predicting, at some extent, the effluent COD, N-NH4+, and N-NO3- concentrations based on chemometric techniques.The authors thank the FCT Strategic Project of UID/BIO/04469/2013 unit and the project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462). The authors also acknowledge the financial support to Daniela P. Mesquita through the postdoctoral Grant (SFRH/BPD/82558/2011) provided by FCT - Portugal.Elsevier B.V.Universidade do MinhoMesquita, D. P.Amaral, A. L.Ferreira, Eugénio C.2016-022016-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/37914engMesquita, D. P.; Amaral, A. L.; Ferreira, E. C., Estimation of effluent quality parameters from an activated sludge system using quantitative image analysis. Chemical Engineering Journal, 285, 349-357, 20161385-89471385-894710.1016/j.cej.2015.09.110http://www.elsevier.com/locate/issn/13858947info: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:RCAAP2023-07-21T11:58:35Zoai:repositorium.sdum.uminho.pt:1822/37914Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:48:19.149022Repositório 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 |
Estimation of effluent quality parameters from an activated sludge system using quantitative image analysis |
title |
Estimation of effluent quality parameters from an activated sludge system using quantitative image analysis |
spellingShingle |
Estimation of effluent quality parameters from an activated sludge system using quantitative image analysis Mesquita, D. P. Wastewater Treatment Activated sludge Quantitative Image Analysis (QIA) Morphology Physiology Partial Least Squares (PLS) Partial least squares (PIS) Science & Technology |
title_short |
Estimation of effluent quality parameters from an activated sludge system using quantitative image analysis |
title_full |
Estimation of effluent quality parameters from an activated sludge system using quantitative image analysis |
title_fullStr |
Estimation of effluent quality parameters from an activated sludge system using quantitative image analysis |
title_full_unstemmed |
Estimation of effluent quality parameters from an activated sludge system using quantitative image analysis |
title_sort |
Estimation of effluent quality parameters from an activated sludge system using quantitative image analysis |
author |
Mesquita, D. P. |
author_facet |
Mesquita, D. P. Amaral, A. L. Ferreira, Eugénio C. |
author_role |
author |
author2 |
Amaral, A. L. Ferreira, Eugénio C. |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Mesquita, D. P. Amaral, A. L. Ferreira, Eugénio C. |
dc.subject.por.fl_str_mv |
Wastewater Treatment Activated sludge Quantitative Image Analysis (QIA) Morphology Physiology Partial Least Squares (PLS) Partial least squares (PIS) Science & Technology |
topic |
Wastewater Treatment Activated sludge Quantitative Image Analysis (QIA) Morphology Physiology Partial Least Squares (PLS) Partial least squares (PIS) Science & Technology |
description |
Abstract The efficiency of an activated sludge system is generally evaluated by determining several key parameters related to organic matter removal, nitrification and/or denitrification processes. Off-line methods for the determination of these parameters are commonly labor, time consuming, and environmentally harmful. In contrast, quantitative image analysis (QIA) has been recognized as a prompt method for assessing activated sludge contents and structure. In the present study an activated sludge system was operated under different experimental conditions leading to a variety of operational data. Key parameters such as chemical oxygen demand (COD) and ammonium (N-NH4+), and nitrate (N-NO3-) concentrations, throughout the experimental periods, were measured by classical analytical techniques. QIA was further used for the microbial community characterization. Partial Least Squares (PLS) models were used to correlate QIA information and the aforementioned key parameters. It was found that the use of the morphological and physiological data allowed predicting, at some extent, the effluent COD, N-NH4+, and N-NO3- concentrations based on chemometric techniques. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-02 2016-02-01T00:00:00Z |
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/1822/37914 |
url |
http://hdl.handle.net/1822/37914 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Mesquita, D. P.; Amaral, A. L.; Ferreira, E. C., Estimation of effluent quality parameters from an activated sludge system using quantitative image analysis. Chemical Engineering Journal, 285, 349-357, 2016 1385-8947 1385-8947 10.1016/j.cej.2015.09.110 http://www.elsevier.com/locate/issn/13858947 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier B.V. |
publisher.none.fl_str_mv |
Elsevier B.V. |
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 |
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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 |
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1799132244212711425 |