In-plant wastewater treatment strategies to handle bypass wastewater exceeding design capacity are insufficiently investigated in the scientific literature notwithstanding their importance in ensuring sustainable wastewater management. In this study, the effectiveness of iron electrocoagulation was investigated, for the first time, to enhance primary treatment capability in removing soluble chemical oxygen demand (sCOD) from bypass wastewater. In addition, the appropriate assumptions and experimental protocols for the application of adsorption isotherm models, widely used to describe the electrocoagulation process, were discussed in light of experimental results. Under neutral pH conditions, the bypass wastewater treatment was performed to test the effects of three preselected variables (electrolysis duration, current density, and temperature) on sCOD removal. Using a 15 mA/cm current density, an average 52% sCOD removal efficiency was achieved after 15 min at 23 °C while approximately 40 min were needed to attain comparable removal efficiency at 8 °C. sCOD removals of 74% and 87% were achieved after 40 min treatment using a 22 mA/cm current density at 8 °C and 23 °C, respectively. Experimental results and theory show that adsorption equilibrium was not reached in the electrocoagulation cell; consequently, variable-order-kinetic (VOK) models derived from Langmuir and Langmuir-Freundlich adsorption expressions were adapted to describe the process. These models were modified to account for the de facto estimation of ferric hydroxide (adsorbent) mass that accounts for the conversion of ferrous ion to particulate end products. The Langmuir-based VOK model was found to better describe sCOD removal under all the operating conditions tested and showed the sCOD removal mechanism to be consistent with chemisorption. This research shows the promising ability of iron electrocoagulation to achieve superior removal of sCOD as compared to established and emerging standalone bypass wastewater treatment technologies.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.scitotenv.2019.136076 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!