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http://hdl.handle.net/10266/3142
Title: | Dairy Waste Water Treatment by Continuous Electrochemical Process |
Authors: | Kumari, Poonam |
Supervisor: | Kushwaha, J. P. Sangal, V. K. |
Keywords: | Electro-coagulation,;COD;BOD;Dairy wastewater |
Issue Date: | 4-Sep-2014 |
Abstract: | Increased demand in processed milk products globally directed rapid growth of dairy industries. Subsequently, the discharged wastewater volume has also been increased. Due to high biochemical oxygen demand (BOD) and chemical oxygen demand (COD), high load of dissolved and suspended solids, together with fats and nutrients, dairy wastewater must be treated before discharge. Existing technologies for the treatment of dairy wastewaters includes biological and physico-chemical methods. Biological treatment methods showed significant COD removal, but these methods require high energy and/or operational controlling. Among physico-chemical methods coagulation/ flocculation are generally used, however, high reagent costs and low soluble COD removal are major drawback of these methods. Electrochemical (EC) treatment has been reported as a feasible method for the treatment of various type of wastewater including dairy wastewater. However, no study reports continuous EC treatment of dairy wastewater. In the present work, actual dairy wastewater treatment by means of continuous electrochemical (EC) treatment was investigated using aluminum electrode. The effects of independent variables such as initial pH (pHi), residence time (τ) and elapsed time (t) on the %COD removal (Y1) and specific energy consumed (kWh per kg of COD removed, Y2) were explored. In highly acidic pH values, Al3+ and various hydrolyzed species; Al(OH)2+, Al(OH)2+ etc. were found responsible for COD removal. While, at highly basic pH ClO─ ions indirectly oxidized the COD. Five level full factorial central composite design (CCD) of response surface methodology (RSM) was applied to design experiments and modeling. For optimization of the EC treatment of dairy wastewater, multi-response process optimization utilizing desirability function of RSM was used, and for this purpose, residence time (τ) and Y2 were set to be minimized within elapsed time studied, whereas Y1 was maximized. ANOVA showed significant quadratic model fitting showing R2 and adjusted R2 of 0.862 and 0.776, respectively, for response Y1, while respective values for Y2 were found to be 0.98 and 0.96, respectively. Optimized values of τ, t, Y1 and Y2 by RSM were found to be 141 min, 52 min, 67% and 4.62 kWh/kg of COD removed, respectively, with desirability value of 0.464. At this optimized set of variables actual experiment showed Y1 and Y2 values being 71.21% and 4.32 kWh/kg of COD removed, respectively. |
Description: | Master of Technology, Chemical Engineering |
URI: | http://hdl.handle.net/10266/3142 |
Appears in Collections: | Masters Theses@CHED |
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