Optimization and effect of pH on treatability of metal plating wastewater by electrocoagulation process: a pilot study

• Published in: International journal of environmental science and technology (Tehran) 2023-07, Vol.20 (7), p.7671-7688
• Main Authors: Ilhan, F., Avsar, Y., Kurt, U., Saral, A.
• Format: Article
• Language: English
• Subjects: Aquatic Pollution; chemical treatment; confidence interval; cyanides; Earth and Environmental Science; Ecotoxicology; electrocoagulation; Environment; Environmental Chemistry; Environmental Science and Engineering; heavy metals; industrial wastewater; industry; nickel; Original Paper; response surface methodology; sludge; Soil Science & Conservation; toxicity; Waste Water Technology; Water Management; Water Pollution Control
• ISSN: 1735-1472; 1735-2630
• DOI: 10.1007/s13762-023-04972-z

Metal plating industry wastewater is a highly toxic wastewater due to its heavy metal and cyanide. This characteristic of wastewater is due to different types of processes used in the metal plating industry. In order to meet discharge limits for the receiving environment, classical chemical treatment methods are widely applied in this type of industry. Consequently, high treatment chemicals are required, resulting in excessive amounts of hazardous sludge. For these reasons, in this study, a pilot scale electrocoagulation (EC) process was developed as an alternative to the conventional chemical treatment currently applied in a metal plating plant. In this study, the effect of pH adjustment on the removal efficiency of the EC process was investigated before and after EC processing in a pilot scale reactor. Particularly, two heavy metals such as copper (Cu) and nickel (Ni), which are problematic to be eliminated in the current treatment, removals were invesigated. With the optimization studies, it was observed that Cu and Ni removals were over 93.75%. Similarly, Cu and Ni removal efficiencies were determined over 95% in the optimization of the EC process after pH adjustment. Indeed, these efficiencies were also achieved in the control study. As a result of the optimization of the study, model analyses were made with response surface methodology and it was observed that the regression coefficients were > 94.00% which were within the 95% confidence interval. This indicated that both the real operating conditions and the results obtained from the model are consistent with each other. Graphical abstract