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
Autor(a) principal: | |
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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: | 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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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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1817544663430594560 |