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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/65620
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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 Técnicas2025-09-29T09:33:01Zoai: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:34982025-09-29 09:33:01.851CONICET 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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13.070432 |