Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools

Detalhes bibliográficos
Autor(a) principal: Leal, Cristiano
Data de Publicação: 2022
Outros Autores: Val del Río, Angeles, Mesquita, D. P., Amaral, António Luís Pereira, Ferreira, Eugénio C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/1822/75533
Resumo: Steroid estrogens namely 17-estradiol (E2) and 17-ethinylestradiol (EE2) and antibiotics including sulfamethoxazole (SMX) are pharmaceutically active compounds (PhAC) of emerging concern due to their environmental and human health impacts even at ppb range concentrations. These compounds usually flow to wastewater treatment plants (WWTP) and are released to the aquatic systems due to inefficient removal in conventional biological systems. In this work, a sequencing batch reactor (SBR) with aerobic granular sludge (AGS) was operated in the presence of E2, EE2 and SMX. SVI5, SVI30/SVI5 ratio, VSS, and TSS of mature AGS (in absence of PhAC), as well as in the presence of PhAC (0.221mgL-1 of E2, 0.278mgL-1 of EE2 and 0.290mgL-1 of SMX), were successfully predicted with multilinear regression (MLR) using morphological and structural parameters of floccular and granular fractions of AGS obtained from quantitative image analysis (QIA). Good prediction models were obtained for the SVI5 (R2 of 0.976), floccular VSS (R2 of 0.949) and TSS (R2 of 0.934), granular VSS (R2 of 0.930) and TSS (R2 of 0.916), SVI30/SVI5 ratio (R2 of 0.917) and density (R2 of 0.889). These results emphasize the usefulness of this methodology for monitoring dysfunctions in AGS in the presence of the studied PhAC.
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spelling Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric toolsGranularFloccularSettleability and density predictionGranules stabilityQuantitative image analysisChemometric toolsPharmaceutically active compoundsGranular, floccular, settleability and density prediction<p>Granular,& nbsp;floccular,& nbsp;& nbsp;settleability and density & nbsp;prediction</p>Ciências Naturais::Ciências BiológicasScience & TechnologySteroid estrogens namely 17-estradiol (E2) and 17-ethinylestradiol (EE2) and antibiotics including sulfamethoxazole (SMX) are pharmaceutically active compounds (PhAC) of emerging concern due to their environmental and human health impacts even at ppb range concentrations. These compounds usually flow to wastewater treatment plants (WWTP) and are released to the aquatic systems due to inefficient removal in conventional biological systems. In this work, a sequencing batch reactor (SBR) with aerobic granular sludge (AGS) was operated in the presence of E2, EE2 and SMX. SVI5, SVI30/SVI5 ratio, VSS, and TSS of mature AGS (in absence of PhAC), as well as in the presence of PhAC (0.221mgL-1 of E2, 0.278mgL-1 of EE2 and 0.290mgL-1 of SMX), were successfully predicted with multilinear regression (MLR) using morphological and structural parameters of floccular and granular fractions of AGS obtained from quantitative image analysis (QIA). Good prediction models were obtained for the SVI5 (R2 of 0.976), floccular VSS (R2 of 0.949) and TSS (R2 of 0.934), granular VSS (R2 of 0.930) and TSS (R2 of 0.916), SVI30/SVI5 ratio (R2 of 0.917) and density (R2 of 0.889). These results emphasize the usefulness of this methodology for monitoring dysfunctions in AGS in the presence of the studied PhAC.The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020 unit and the project AGeNT - PTDC/BTA-BTA/31264/2017 (POCI-01-0145-FEDER-031264). The authors wish to thank the company Aguas do Tejo Atlantico, S.A. for supplying the granules. Cristiano Leal is recipient of a fellowship supported by a doctoral advanced training (call NORTE-69-2015-15) funded by the European Social Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. A. Val del Rio is supported by Xunta de Galicia (ED418B 2017/ 075) and program Iacobus (2018/2019). Cristiano Leal also thanks Renê Benevides for all the support during the experimental activities.info:eu-repo/semantics/publishedVersionElsevier BVUniversidade do MinhoLeal, CristianoVal del Río, AngelesMesquita, D. P.Amaral, António Luís PereiraFerreira, Eugénio C.2022-042022-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/75533engLeal, Cristiano; Val del Río, Angeles; Mesquita, Daniela P.; Amaral, A. Luís; Ferreira, Eugénio C., Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools. Journal of Environmental Chemical Engineering, 105(2), 107136, 20222213-343710.1016/j.jece.2022.107136https://www.sciencedirect.com/science/article/abs/pii/S2213343722000094info: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:RCAAP2024-11-16T01:26:51Zoai:repositorium.sdum.uminho.pt:1822/75533Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-11-16T01:26:51Repositório 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 Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools
title Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools
spellingShingle Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools
Leal, Cristiano
Granular
Floccular
Settleability and density prediction
Granules stability
Quantitative image analysis
Chemometric tools
Pharmaceutically active compounds
Granular, floccular, settleability and density prediction
<p>Granular,& nbsp;floccular,& nbsp;& nbsp;settleability and density & nbsp;prediction</p>
Ciências Naturais::Ciências Biológicas
Science & Technology
title_short Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools
title_full Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools
title_fullStr Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools
title_full_unstemmed Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools
title_sort Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools
author Leal, Cristiano
author_facet Leal, Cristiano
Val del Río, Angeles
Mesquita, D. P.
Amaral, António Luís Pereira
Ferreira, Eugénio C.
author_role author
author2 Val del Río, Angeles
Mesquita, D. P.
Amaral, António Luís Pereira
Ferreira, Eugénio C.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Leal, Cristiano
Val del Río, Angeles
Mesquita, D. P.
Amaral, António Luís Pereira
Ferreira, Eugénio C.
dc.subject.por.fl_str_mv Granular
Floccular
Settleability and density prediction
Granules stability
Quantitative image analysis
Chemometric tools
Pharmaceutically active compounds
Granular, floccular, settleability and density prediction
<p>Granular,& nbsp;floccular,& nbsp;& nbsp;settleability and density & nbsp;prediction</p>
Ciências Naturais::Ciências Biológicas
Science & Technology
topic Granular
Floccular
Settleability and density prediction
Granules stability
Quantitative image analysis
Chemometric tools
Pharmaceutically active compounds
Granular, floccular, settleability and density prediction
<p>Granular,& nbsp;floccular,& nbsp;& nbsp;settleability and density & nbsp;prediction</p>
Ciências Naturais::Ciências Biológicas
Science & Technology
description Steroid estrogens namely 17-estradiol (E2) and 17-ethinylestradiol (EE2) and antibiotics including sulfamethoxazole (SMX) are pharmaceutically active compounds (PhAC) of emerging concern due to their environmental and human health impacts even at ppb range concentrations. These compounds usually flow to wastewater treatment plants (WWTP) and are released to the aquatic systems due to inefficient removal in conventional biological systems. In this work, a sequencing batch reactor (SBR) with aerobic granular sludge (AGS) was operated in the presence of E2, EE2 and SMX. SVI5, SVI30/SVI5 ratio, VSS, and TSS of mature AGS (in absence of PhAC), as well as in the presence of PhAC (0.221mgL-1 of E2, 0.278mgL-1 of EE2 and 0.290mgL-1 of SMX), were successfully predicted with multilinear regression (MLR) using morphological and structural parameters of floccular and granular fractions of AGS obtained from quantitative image analysis (QIA). Good prediction models were obtained for the SVI5 (R2 of 0.976), floccular VSS (R2 of 0.949) and TSS (R2 of 0.934), granular VSS (R2 of 0.930) and TSS (R2 of 0.916), SVI30/SVI5 ratio (R2 of 0.917) and density (R2 of 0.889). These results emphasize the usefulness of this methodology for monitoring dysfunctions in AGS in the presence of the studied PhAC.
publishDate 2022
dc.date.none.fl_str_mv 2022-04
2022-04-01T00:00:00Z
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 https://hdl.handle.net/1822/75533
url https://hdl.handle.net/1822/75533
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Leal, Cristiano; Val del Río, Angeles; Mesquita, Daniela P.; Amaral, A. Luís; Ferreira, Eugénio C., Prediction of sludge settleability, density and suspended solids of aerobic granular sludge in the presence of pharmaceutically active compounds by quantitative image analysis and chemometric tools. Journal of Environmental Chemical Engineering, 105(2), 107136, 2022
2213-3437
10.1016/j.jece.2022.107136
https://www.sciencedirect.com/science/article/abs/pii/S2213343722000094
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 BV
publisher.none.fl_str_mv Elsevier BV
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 mluisa.alvim@gmail.com
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