185
Views
27
CrossRef citations to date
0
Altmetric
Original Articles

Electrochemical treatment of rice grain-based distillery effluent: chemical oxygen demand and colour removal

&
Pages 242-249 | Received 06 Oct 2012, Accepted 25 Jun 2013, Published online: 25 Aug 2013
 

Abstract

The electrochemical (EC) treatment of rice grain-based distillery wastewater was carried out in a 1.5 dm3 electrolytic batch reactor using aluminium plate electrodes. With the four-plate configurations, a current density (j) of 89.3 A/m2 and pH 8 was found to be optimal, obtaining a maximum chemical oxygen demand (COD) and colour removal of 93% and 87%, respectively. The chemical dissolution of aluminium was strongly influenced by initial pH (pHi). At higher pHi (pH 9.5) anode consumption decreased while energy consumption increased. At the optimal current density 89.3 A/m2, the aluminium electrode consumption was 16.855 g/dm3 wastewater and energy consumption was 31.4 Wh/dm3 achieving a maximum COD removal of 87%. The settling and filterability characteristics of electrochemically treated sludge were also analysed at different pH. It was noted that treated slurry at pHi 9.5 gave best settling characteristic, which decreased with increase in pH. EC-treated effluent at pHi 8 had provided best filterability. Characteristics of scum and residues are also analysed at different pH.

Acknowledgements

Authors gratefully acknowledge Chhattisgarh Council of Science and Technology (CGCOST), Raipur, India for providing research grants to support this work.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 223.00 Add to cart

* Local tax will be added as applicable

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.