Optimization and modeling of reduction of wastewater sludge water content and turbidity removal using magnetic iron oxide nanoparticles (MION)

摘要

Economic and rapid reduction of sludge water content in sewage wastewater is difficult and requires special advanced treatment technologies. This study focused on optimizing and modeling decreased sludge water content (Y-1) and removing turbidity (Y-2) with magnetic iron oxide nanoparticles (Fe3O4, MION) using a central composite design (CCD) and response surface methodology (RSM). CCD and RSM were applied to evaluate and optimize the interactive effects of mixing time (X-1) and MION concentration (X-2) on chemical flocculent performance. The results show that the optimum conditions were 14.1min and 22.1mg L-1 for response Y-1 and 16.8min and 8.85mg L-1 for response Y-2, respectively. The two responses were obtained experimentally under this optimal scheme and fit the model predictions well (R-2 = 97.2% for Y-1 and R-2 = 96.9% for Y-2). A 90.8% decrease in sludge water content and turbidity removal of 29.4% were demonstrated. These results confirm that the statistical models were reliable, and that the magnetic flocculation conditions for decreasing sludge water content and removing turbidity from sewage wastewater were appropriate. The results reveal that MION are efficient for rapid separation and are a suitable alterative to sediment sludge during the wastewater treatment process.