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Cited by 440

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Removal of Microbeads from Wastewater Using Electrocoagulation

Open access
Perren, William, Wojtasik, Arkadiusz, Cai, Qiong·2018·ACS Omega

Abstract

Abstract The need for better microplastic removal from wastewater streams is clear, to prevent potential harm the microplastic may cause to the marine life. This paper aims to investigate the efficacy of electrocoagulation (EC), a well-known and established process, in the unexplored context of microplastic removal from wastewater streams. This premise was investigated using artificial wastewater containing polyethylene microbeads of different concentrations. The wastewater was then tested in a 1 L stirred-tank batch reactor. The effects of the wastewater characteristics (initial pH, NaCl concentration, and current density) on removal efficiency were studied. Microbead removal efficiencies in excess of 90% were observed in all experiments, thus suggesting that EC is an effective method of removing microplastic contaminants from wastewater streams. Electrocoagulation was found to be effective with removal efficiencies in excess of 90%, over pH values ranging from 3 to 10. The optimum removal efficiency of 99.24% was found at a pH of 7.5. An economic evaluation of the reactor operating costs revealed that the optimum NaCl concentration in the reactor is between 0 and 2 g/L, mainly due to the reduced energy requirements linked to higher water conductivity. In regard to the current density, the specific mass removal rate (kg/kWh) was the highest for the lowest tested current density of 11 A/m2, indicating that low current density is more energy efficient for microbead removal.

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Crossref · 10.1021/acsomega.7b02037

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Metadata

Authors
Perren, W., Wojtasik, A., & Cai, Q.
Venue
ACS Omega
Published
2018-03-20
Volume
3
Issue
3
Pages
3357-3364
ISSN
2470-1343 (ISSN-L)
OpenAlex
W2792529997
Cited by
440
References
1
FWCI
7.96
Type
journal article
Language
en
Open access
gold

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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