Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration

Autores
Cruz, Mercedes Cecilia; Romero, Luis Cesar; Vicente, María Soledad; Rajal, Verónica Beatriz
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We performed a systematic approach using statistical tools to understand the effect of the water chemistry on removal of microorganisms using ultrafiltration. We applied a four-factor at two-level factorial design with central point to synthesize forty mock solutions spiked with two pathogen surrogates, Salmonella Typhimurium and bacteriophage PP7, selected as bacterial and viral models, respectively. Calcium, magnesium, nitrate, and bicarbonate were the mono- and divalent ions considered as factors for the water matrix composition and their concentrations were based on actual ambient waters sourced for human consumption. The influence of natural organic matter (NOM) using commercial humic acids was also evaluated. The statistical analysis showed that steric exclusion was the main mechanism for bacterial removal independently of the presence of NOM. However, for the viral model in the absence of NOM rejection was governed by the electrostatic repulsion theory and the interaction of negative charged ions (nitrate and bicarbonate) played an important role. Aggregation of viral particles to humic acids enhanced their rejection, although removal efficiency was highly impacted by the interaction between chloride and calcium ions, ionic strength, and pH in the feed water. This approach can be applied in other membrane-based processes used in environmental engineered systems like wastewater treatments.
Fil: Cruz, Mercedes Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; Argentina
Fil: Romero, Luis Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; Argentina
Fil: Vicente, María Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; Argentina
Fil: Rajal, Verónica Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; Argentina. Nanyang Technological University; Singapur
Materia
Principal Component Analysis
Qpcr
Ultrafiltration
Virus
Water Disinfection
Water Matrix
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/65620
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/65620
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltrationCruz, Mercedes CeciliaRomero, Luis CesarVicente, María SoledadRajal, Verónica BeatrizPrincipal Component AnalysisQpcrUltrafiltrationVirusWater DisinfectionWater Matrixhttps://purl.org/becyt/ford/2.8https://purl.org/becyt/ford/2https://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1We performed a systematic approach using statistical tools to understand the effect of the water chemistry on removal of microorganisms using ultrafiltration. We applied a four-factor at two-level factorial design with central point to synthesize forty mock solutions spiked with two pathogen surrogates, Salmonella Typhimurium and bacteriophage PP7, selected as bacterial and viral models, respectively. Calcium, magnesium, nitrate, and bicarbonate were the mono- and divalent ions considered as factors for the water matrix composition and their concentrations were based on actual ambient waters sourced for human consumption. The influence of natural organic matter (NOM) using commercial humic acids was also evaluated. The statistical analysis showed that steric exclusion was the main mechanism for bacterial removal independently of the presence of NOM. However, for the viral model in the absence of NOM rejection was governed by the electrostatic repulsion theory and the interaction of negative charged ions (nitrate and bicarbonate) played an important role. Aggregation of viral particles to humic acids enhanced their rejection, although removal efficiency was highly impacted by the interaction between chloride and calcium ions, ionic strength, and pH in the feed water. This approach can be applied in other membrane-based processes used in environmental engineered systems like wastewater treatments.Fil: Cruz, Mercedes Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; ArgentinaFil: Romero, Luis Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; ArgentinaFil: Vicente, María Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; ArgentinaFil: Rajal, Verónica Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; Argentina. Nanyang Technological University; SingapurElsevier Science Sa2017-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/65620Cruz, Mercedes Cecilia; Romero, Luis Cesar; Vicente, María Soledad; Rajal, Verónica Beatriz; Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration; Elsevier Science Sa; Chemical Engineering Journal; 316; 5-2017; 305-3141385-8947CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.cej.2017.01.081info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S138589471730092Xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:01:00Zoai:ri.conicet.gov.ar:11336/65620instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:01:01.038CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration
title Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration
spellingShingle Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration
Cruz, Mercedes Cecilia
Principal Component Analysis
Qpcr
Ultrafiltration
Virus
Water Disinfection
Water Matrix
title_short Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration
title_full Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration
title_fullStr Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration
title_full_unstemmed Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration
title_sort Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration
dc.creator.none.fl_str_mv Cruz, Mercedes Cecilia
Romero, Luis Cesar
Vicente, María Soledad
Rajal, Verónica Beatriz
author Cruz, Mercedes Cecilia
author_facet Cruz, Mercedes Cecilia
Romero, Luis Cesar
Vicente, María Soledad
Rajal, Verónica Beatriz
author_role author
author2 Romero, Luis Cesar
Vicente, María Soledad
Rajal, Verónica Beatriz
author2_role author
author
author
dc.subject.none.fl_str_mv Principal Component Analysis
Qpcr
Ultrafiltration
Virus
Water Disinfection
Water Matrix
topic Principal Component Analysis
Qpcr
Ultrafiltration
Virus
Water Disinfection
Water Matrix
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.8
https://purl.org/becyt/ford/2
https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We performed a systematic approach using statistical tools to understand the effect of the water chemistry on removal of microorganisms using ultrafiltration. We applied a four-factor at two-level factorial design with central point to synthesize forty mock solutions spiked with two pathogen surrogates, Salmonella Typhimurium and bacteriophage PP7, selected as bacterial and viral models, respectively. Calcium, magnesium, nitrate, and bicarbonate were the mono- and divalent ions considered as factors for the water matrix composition and their concentrations were based on actual ambient waters sourced for human consumption. The influence of natural organic matter (NOM) using commercial humic acids was also evaluated. The statistical analysis showed that steric exclusion was the main mechanism for bacterial removal independently of the presence of NOM. However, for the viral model in the absence of NOM rejection was governed by the electrostatic repulsion theory and the interaction of negative charged ions (nitrate and bicarbonate) played an important role. Aggregation of viral particles to humic acids enhanced their rejection, although removal efficiency was highly impacted by the interaction between chloride and calcium ions, ionic strength, and pH in the feed water. This approach can be applied in other membrane-based processes used in environmental engineered systems like wastewater treatments.
Fil: Cruz, Mercedes Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; Argentina
Fil: Romero, Luis Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; Argentina
Fil: Vicente, María Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; Argentina
Fil: Rajal, Verónica Beatriz. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Investigaciones para la Industria Química. Universidad Nacional de Salta. Facultad de Ingeniería. Instituto de Investigaciones para la Industria Química; Argentina. Nanyang Technological University; Singapur
description We performed a systematic approach using statistical tools to understand the effect of the water chemistry on removal of microorganisms using ultrafiltration. We applied a four-factor at two-level factorial design with central point to synthesize forty mock solutions spiked with two pathogen surrogates, Salmonella Typhimurium and bacteriophage PP7, selected as bacterial and viral models, respectively. Calcium, magnesium, nitrate, and bicarbonate were the mono- and divalent ions considered as factors for the water matrix composition and their concentrations were based on actual ambient waters sourced for human consumption. The influence of natural organic matter (NOM) using commercial humic acids was also evaluated. The statistical analysis showed that steric exclusion was the main mechanism for bacterial removal independently of the presence of NOM. However, for the viral model in the absence of NOM rejection was governed by the electrostatic repulsion theory and the interaction of negative charged ions (nitrate and bicarbonate) played an important role. Aggregation of viral particles to humic acids enhanced their rejection, although removal efficiency was highly impacted by the interaction between chloride and calcium ions, ionic strength, and pH in the feed water. This approach can be applied in other membrane-based processes used in environmental engineered systems like wastewater treatments.
publishDate 2017
dc.date.none.fl_str_mv 2017-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/65620
Cruz, Mercedes Cecilia; Romero, Luis Cesar; Vicente, María Soledad; Rajal, Verónica Beatriz; Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration; Elsevier Science Sa; Chemical Engineering Journal; 316; 5-2017; 305-314
1385-8947
CONICET Digital
CONICET
url http://hdl.handle.net/11336/65620
identifier_str_mv Cruz, Mercedes Cecilia; Romero, Luis Cesar; Vicente, María Soledad; Rajal, Verónica Beatriz; Statistical approaches to understanding the impact of matrix composition on the disinfection of water by ultrafiltration; Elsevier Science Sa; Chemical Engineering Journal; 316; 5-2017; 305-314
1385-8947
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.cej.2017.01.081
info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S138589471730092X
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science Sa
publisher.none.fl_str_mv Elsevier Science Sa
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.982451

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