143
Views
18
CrossRef citations to date
0
Altmetric
Articles

Treatment of Cr, Ni and Zn from galvanic rinsing wastewater by electrocoagulation process using iron electrodes

, &
Pages 1191-1201 | Received 17 Sep 2013, Accepted 06 Jul 2014, Published online: 22 Aug 2014
 

Abstract

Galvanizing plants contain reasonable amounts of heavy metal ions which pose a serious risk to humans, animals and the environment. In the present study, removal efficiencies of Cr, Ni and Zn from galvanic rinse wastewater (GRW) by electrocoagulation (EC) process using iron plate electrodes were investigated in a laboratory scale EC reactor. The effects of operational variables, such as operating time (0–50 min), current density (10–40 A/m2), initial pHi (2.4–6.4) and electrode connection modes (MP-P: monopolar-parallel, MP-S: monopolar-serial and BP-S: bipolar-serial), on the removal efficiencies of heavy metals were explored to determine the optimum operating conditions. Removal efficiencies of 99.77% for Cr, 85.62% for Ni and 99.04% for Zn at the optimum operating conditions (pHi 5.4, current density of 30 A/m2, operating time of 30 min and MP-P electrode connection mode) were obtained. The results showed that Cr, Ni and Zn removal efficiencies from GRW increased with increasing current density and pH at MP-P electrode connection mode. The results showed that EC can effectively reduce metal ions to a very low level. Amount of sludge generated and operating cost at the optimum conditions during the EC process were calculated as 2.32 kg/m3 and 0.70 €/m3. This study revealed that the EC process was very effective for removal of Cr, Ni and Zn from GRW.

Acknowledgements

The authors would like to express their appreciation for the financial support from Gebze Institute of Technology.

Notes

Presented at the 4th International Conference on Environmental Management, Engineering, Planning and Economics (CEMEPE), 24–28 June 2013, Mykonos, Greece

Log in via your institution

Log in to Taylor & Francis Online

There are no offers available at the current time.

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.