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A statistical experimental investigation on arsenic removal using capacitive deionization

Wei Zhang Orcid Logo, Mohamed Mossad, Javad Sadoghi Yazdi, Linda Zou

Desalination and Water Treatment, Volume: 57, Issue: 7, Pages: 3254 - 3260

Swansea University Author: Wei Zhang Orcid Logo

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Abstract

In this study, arsenic removal from water by a solar-powered capacitive deionization (CDI) unit was investigated. The Box–Behnken statistical experiment design (BBD) as an example of response surface methodology was used to investigate the effects of major process parameters. Initial arsenic concent...

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Published in: Desalination and Water Treatment
ISSN: 1944-3994 1944-3986
Published: 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa44280
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spelling 2018-10-08T15:39:33.9110803 v2 44280 2018-09-18 A statistical experimental investigation on arsenic removal using capacitive deionization 3ddabbb54b2cfa2ea10f590ea7da6520 0000-0003-3129-2918 Wei Zhang Wei Zhang true false 2018-09-18 CHEG In this study, arsenic removal from water by a solar-powered capacitive deionization (CDI) unit was investigated. The Box–Behnken statistical experiment design (BBD) as an example of response surface methodology was used to investigate the effects of major process parameters. Initial arsenic concentration, pH, and background sodium chloride concentration were selected as independent variables in BBD, while arsenic removal was considered as the response function. The predicted values of arsenic removal obtained using the response functions were in good agreement with the experimental data. The current CDI technology was found to be an effective and reliable alternative for arsenic removal from water with higher than 80% removal achieved in all designated experiments. In general, CDI removal of arsenate ions favors higher pH and lower salinity conditions. This study showed that BBD methodology was an efficient and feasible approach in predicting the effects of different experimental conditions during an arsenate removal process by CDI. Journal Article Desalination and Water Treatment 57 7 3254 3260 1944-3994 1944-3986 Capacitive deionization, Arsenic removal, Statistical design, Solar power 31 12 2016 2016-12-31 10.1080/19443994.2014.981761 COLLEGE NANME Chemical Engineering COLLEGE CODE CHEG Swansea University 2018-10-08T15:39:33.9110803 2018-09-18T12:15:06.8518262 College of Engineering Engineering Wei Zhang 0000-0003-3129-2918 1 Mohamed Mossad 2 Javad Sadoghi Yazdi 3 Linda Zou 4
title A statistical experimental investigation on arsenic removal using capacitive deionization
spellingShingle A statistical experimental investigation on arsenic removal using capacitive deionization
Wei Zhang
title_short A statistical experimental investigation on arsenic removal using capacitive deionization
title_full A statistical experimental investigation on arsenic removal using capacitive deionization
title_fullStr A statistical experimental investigation on arsenic removal using capacitive deionization
title_full_unstemmed A statistical experimental investigation on arsenic removal using capacitive deionization
title_sort A statistical experimental investigation on arsenic removal using capacitive deionization
author_id_str_mv 3ddabbb54b2cfa2ea10f590ea7da6520
author_id_fullname_str_mv 3ddabbb54b2cfa2ea10f590ea7da6520_***_Wei Zhang
author Wei Zhang
author2 Wei Zhang
Mohamed Mossad
Javad Sadoghi Yazdi
Linda Zou
format Journal article
container_title Desalination and Water Treatment
container_volume 57
container_issue 7
container_start_page 3254
publishDate 2016
institution Swansea University
issn 1944-3994
1944-3986
doi_str_mv 10.1080/19443994.2014.981761
college_str College of Engineering
hierarchytype
hierarchy_top_id collegeofengineering
hierarchy_top_title College of Engineering
hierarchy_parent_id collegeofengineering
hierarchy_parent_title College of Engineering
department_str Engineering{{{_:::_}}}College of Engineering{{{_:::_}}}Engineering
document_store_str 0
active_str 0
description In this study, arsenic removal from water by a solar-powered capacitive deionization (CDI) unit was investigated. The Box–Behnken statistical experiment design (BBD) as an example of response surface methodology was used to investigate the effects of major process parameters. Initial arsenic concentration, pH, and background sodium chloride concentration were selected as independent variables in BBD, while arsenic removal was considered as the response function. The predicted values of arsenic removal obtained using the response functions were in good agreement with the experimental data. The current CDI technology was found to be an effective and reliable alternative for arsenic removal from water with higher than 80% removal achieved in all designated experiments. In general, CDI removal of arsenate ions favors higher pH and lower salinity conditions. This study showed that BBD methodology was an efficient and feasible approach in predicting the effects of different experimental conditions during an arsenate removal process by CDI.
published_date 2016-12-31T04:14:36Z
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