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A Step Forward to the Characterization of Secondary Effuents to Predict Membrane Fouling in a Subsequent Ultrafiltration

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A Step Forward to the Characterization of Secondary Effuents to Predict Membrane Fouling in a Subsequent Ultrafiltration

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dc.contributor.author Anderson-Alejandro Benites-Zelaya es_ES
dc.contributor.author Soler Cabezas, José Luis es_ES
dc.contributor.author Ferrer-Polonio, Eva es_ES
dc.contributor.author Mendoza Roca, José Antonio es_ES
dc.contributor.author Vincent Vela, Maria Cinta es_ES
dc.date.accessioned 2021-06-12T03:33:35Z
dc.date.available 2021-06-12T03:33:35Z
dc.date.issued 2020-07 es_ES
dc.identifier.issn 2073-4441 es_ES
dc.identifier.uri http://hdl.handle.net/10251/167861
dc.description.abstract [EN] Nowadays, wastewater reuse in Mediterranean countries is necessary to cover the water demand. This contributes to the protection of the environment and encourages the circular economy. Due to increasingly strict regulation, the secondary effluent of a wastewater treatment plant requires further (tertiary) treatment to reach enough quality for its reuse in agriculture. Ultrafiltration is a membrane technique suitable for tertiary treatment. However, the most important drawback of ultrafiltration is membrane fouling. The aim of this work is to predict membrane fouling and ultrafiltered wastewater permeate quality for a particular membrane, using the information given by an exhaustive secondary effluent characterization. For this, ultrafiltration of real and simulated wastewaters and of their components after fractionation has been performed. In order to better characterize the secondary effluent, resin fractionation and further membrane ultrafiltration of the generated fractions and wastewater were performed. The results indicated that hydrophobic substances were lower than hydrophilic ones in the secondary effluent. Supelite DAX-8, Amberlite XAD-4 and Amberlite IRA-958 resins were found not to be specific for humic acids, proteins and carbohydrates, which are the main components of the effluent organic matter. Two models have been performed using statistics (partial least squares, PLS) and an artificial neural network (ANN), respectively. The results showed that the ANN model predicted permeate quality and membrane fouling with higher accuracy than PLS. es_ES
dc.description.sponsorship This study was funded by Generalitat Valenciana (Project AICO 18/319). es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation GV/AICO/2018/319 es_ES
dc.relation.ispartof Water es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Secondary effluent es_ES
dc.subject Tertiary treatment es_ES
dc.subject Ultrafiltration es_ES
dc.subject Artificial neural network es_ES
dc.subject Organic matter fractionation es_ES
dc.subject.classification INGENIERIA QUIMICA es_ES
dc.title A Step Forward to the Characterization of Secondary Effuents to Predict Membrane Fouling in a Subsequent Ultrafiltration es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/w12071975 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Química y Nuclear - Departament d'Enginyeria Química i Nuclear es_ES
dc.description.bibliographicCitation Anderson-Alejandro Benites-Zelaya; Soler Cabezas, JL.; Ferrer-Polonio, E.; Mendoza Roca, JA.; Vincent Vela, MC. (2020). A Step Forward to the Characterization of Secondary Effuents to Predict Membrane Fouling in a Subsequent Ultrafiltration. Water. 12(7):1-17. https://doi.org/10.3390/w12071975 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/w12071975 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 17 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 7 es_ES
dc.relation.pasarela S\415597 es_ES
dc.contributor.funder Generalitat Valenciana es_ES


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