No Cover Image

Journal article 46 views

A statistical experimental investigation on arsenic removal using capacitive deionization / Wei Zhang; Mohamed Mossad; Javad Sadoghi Yazdi; Linda Zou

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

Swansea University Author: Zhang, Wei

Full text not available from this repository: check for access using links below.

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...

Full description

Published in: Desalination and Water Treatment
ISSN: 1944-3994 1944-3986
Published: 2016
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa44280
Tags: Add Tag
No Tags, Be the first to tag this record!
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 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.
Keywords: Capacitive deionization, Arsenic removal, Statistical design, Solar power
College: College of Engineering
Issue: 7
Start Page: 3254
End Page: 3260