OPTIMIZATION OF PARAMETERS (RETENTION TIME, NUTRIENT DOSING, PH AND AGITATION) FOR MICROBIAL TREATMENT OF EFFLUENT BY USING TAGUCHI APPROACH

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1 CHAPTER 6 OPTIMIZATION OF PARAMETERS (RETENTION TIME, NUTRIENT DOSING, PH AND AGITATION) FOR MICROBIAL TREATMENT OF EFFLUENT BY USING TAGUCHI APPROACH 6.1. Introduction Biological methods for the treatment of pulp and paper industry effluent are environmental friendly and cost effective than physical or chemical methods. During bioremediation, degradable organic matter is used as an organic carbon source in microbial process, resulting in the breakdown of complex components to low molecular weight compounds. This technology accelerates naturally occurring biodegradation under optimized conditions such as oxygen supply, temperature, ph, addition of suitable microbial population and nutrients. Bioremediation can be effective only where environmental conditions permit microbial growth and activity, its application often involves the manipulation of environmental parameters to allow microbial growth and degradation to proceed at a faster rate. So, bioremediation methods have focused on the addition of microorganisms or nutrients concentration and the temperature dependant condition of the process environment. Therefore optimization of parameter for microbial growth is essential in order to get the effective biodegradation in less time and cost. Every experimenter has to plan and conduct experiments to obtain enough and relevant data so that we can infer the science behind the observed phenomenon. It can be done by trial and error approach performing a series of experiments each of which gives some understanding. This requires making measurements after every experiment so that analysis of observed data will allow expermenter to decide what to do next - which parameters should be varied and by how much. Many times such series do not progress much as negative results may discourage or will not allow selection of parameters which ought to be changed in the next experiment. Therefore, such experimentation usually ends well before the number of experiments reaches a double digit. The data is insufficient to draw any significant conclusions and the main problem 165

2 (of understanding the science) still remains unsolved. The approach to solve the problem is design of experiments. Design of experiments is a well planned set of experiments, in which all parameters of interest are varied over a specified range. It is a much better approach to obtain systematic data. Mathematically speaking, such a complete set of experiments ought to give desired results. Usually the number of experiments and resources (materials and time) required are prohibitively large. Often the experimenter decides to perform a subset of the complete set of experiments to save on time and money. In the present study the process of bioremediation was optimized, by Taguchi approach. Genichi Taguchi was a Japanese statistician and engineer who have given Taguchi approach for designing of experiment. The Taguchi method utilizes orthogonal arrays for design of experiments to study a large number of variables with a small number of experiments. An orthogonal array significantly reduces the number of experimental configurations to be studied. In this study the sequential batch reactor was used for the removal of pollutants from the effluent of pulp and paper mill by using bacterial consortium Material and Methods Chemicals and Reagents All chemical used in the present study were of analytical grade. Nutrient broth, agar powder, Tween 80 and glycerol were obtained from Hi-media. The routine chemicals were procured from S.D. fine, Qualigens and Merck India limited. Distilled water was used throughout the study Equipments The equipment used during the present study includes laminar flow (Kartos International), electronic balance (Sartorious), ph meter (Lab India), autoclave (Yorco), incubator shaker (New-Brunswick-Innova 4300), centrifuge (Sorvall-RC 5B Plus), spectrophotometer (Pharmaspec UV 1700, Shimadzu), digital burette (Eppendorf), COD digestor (Spectralab), and bioreactor (Applicon). 166

3 Glassware s / Plastic Wares Storage bottles, Petri dishes were of tarson make. Measuring cylinders, beakers, Erlenmeyer Immholf cone (graduated), beaker, flasks and pipettes were procured from Borosil Adsorbable Organic Halides A parameter that measures the total mass of chlorinated organic matter in water and wastewater. Bleach plant effluents from pulp & paper industries are known to exhibit toxicity to aquatic life. The toxicity is mainly due to discharge of halogenated organic compounds formed during bleaching of pulp with chlorine based chemicals particularly molecular chlorine. Most of the chlorinated organic compounds that are carcinogenic, are adsorbable and hence the discharge of adsorbable organic halide (AOX) needs to be controlled. Measurement of AOX was done at Sri Ram Institute for Industrial Research Delhi Mixed Liquor Suspended Solids (i) Scope Mixed liquor Suspended Solids (MLSS) are composed of active microbial mass, non active microbial mass, non biodegradable organics, and inorganic mass. The level of mixed liquor suspended solids varies widely for various modifications of activated sludge process and under various modes of operation of the same modification. Generally, the higher levels of MLSS calls for higher oxygenation capacities in the system and required larger secondary clarifiers. (ii) Method and Calculations Procedure is same as mentioned in section , except the use of filter paper (WhattMann no. 40) in case of MLSS estimation Sludge Volume Index (i) Scope The settleability of sludge is measured by the sludge volume index (SVI), which is the unit volume of the activated sludge ( ml/g) after half an hour settling of the mixed liquor 167

4 in a 1 L imholf cone. Minimum SVI values which indicate optimum solid liquid separation occur when the activated sludge system has a well balanced microbial population which produces large flocculated particles. For practical needs this factor should be kept below 150 ml/g. With higher SVI values a difficulty arises in the performance of the secondary clarifiers. A distinct increase in the sludge volume index is called sludge bulking. One of the frequent causes of activated sludge bulking is excessive growth of filamentous microorganism in a mixed culture. (ii) Method A Well mixed sample of activated sludge was collected from the aeration tank. The sample was poured in to imholf cone and allowed to settle for 30 min. After 30 min note down the reading. (iii) Calculation F/M Ratio SVI = Settled Sludge Volume (ml) MLSS ( mg l ) x 1000 The F/M is the ratio of food fed to the microorganisms each day to the mass of microorganisms held under aeration. In order to calculate the F/M ratio two quantities are required: 1) the pounds of organic material entering the aeration basin and 2) the pounds of microorganisms in the aeration basin. The standard equation for calculating the food-to-mass (microorganism) ratio is shown in equation 1. This is the most common form of the F/M ratio equation F/M = BOD5 mg l Equation 1: Formula for the F/M ratio Where MG lb x Q x (8.34 day gal ) MLVSS mg lb x (Araetion volume, MG)x (8.34 l gal ) Q = denotes the influent flow rate to the oxidation ditch in units of million gallons per day 168

5 Equation 2 shows a variation of the standard F/M ratio calculation. In this equation two variables have been changed. In the numerator, instead of BOD 5, the calculation uses the organic load based on the chemical oxygen demand (COD). In the denominator, the microorganism population is based on the mixed liquor suspended solids (MLSS) rather than the mixed liquor volatile suspended solids (MLVSS). The organic loading parameter was changed because the organic strength of the wastewater in pulp and paper industry was measured in terms of COD rather than BOD 5 F/M = COD mg l MG lb x Q day x (8.34 gal ) MLSS mg lb l x (Aeration volume, MG)x (8.34 gal ) Equation 2: Modified formula for the F/M ratio In our study we have used equation 2 to calculate the F/M ratio Taguchi Approach for Design of Experiment Taguchi design can determine the effect of factors on characteristic properties and the optimal conditions of factors. This method is a simple and systematic approach to optimize design for performance, quality and cost (Joseph and Piganatiells, 1988; Roy, 2001 and 2007). Taguchi method utilizes orthogonal arrays for design of experiments to study a large number of variables with a small number of experiments. An orthogonal array significantly reduces the number of experimental configurations to be studied. Furthermore, the conclusions drawn from small-scale experiments are valid over the entire experimental region spanned by the control factors and their settings. In the Taguchi approach orthogonal arrays and analysis of variance are used as the tools of analysis. Conventional statistical experimental design can determine the optimal condition on the basis of the measured values of the characteristic properties while Taguchi method can determine the experimental condition having the least variability as the optimal condition. The variability is expressed by signal to noise (S/N) ratio. The terms signal and noise represent the desirable and undesirable values for the output characteristic, respectively. Taguchi method uses the S/N ratio to measure the quality characteristic 169

6 deviating from the desired value. The experimental condition having the maximum S/N ratio is considered as the optimal condition as the variability characteristics is inversely proportional to the S/N ratio. The S/N measures the level of performance and the effect of noise factors on performance and is an evaluation of the stability of performance of an output characteristic. Target values may be: (a) Smaller is better, when goal is to minimize the response. The S/N can be calculated as S N = 10 log10 1 n Yi2 (b) Larger is better: when goal is to maximize the response. The S/N is calculated as S N = 10 log10 1 n 1/Yi2 (c) Nominal is better: when goal is to target the response and it is required to base the S/N on standard deviations only. The S/N is calculated as S N = 10log y S Details of Bioreactor Laboratory scale sequence batch reactor was used with a working volume of 12 liters having a glass vessel accompanying the baffles for minimizing the foam during the treatment process. On the upper side of the metal lid there is one motor attached to the shaft on which blades were embedded for stirring inside the vessel. Different ports were provided one for air supply and two for filling and emptying the vessel. On the surface of the metal lid probes for ph and dissolved oxygen (DO) were also entrenched. For regulating the temperature electric blanket was provided. This blanket covers the vessel from outside. For decreasing the temperature inside the vessel water circulating coil was present which is attached to the chiller outside. 170

7 Air supply was provided by a compressor pump at 2 bar (30 psi) via a solenoid valve to a coarse bubble diffuser. Air flow was regulated by a rotameter. An exhaust tube was used on the surface of the lid of the reactor attached with 0.45micron filter. Air was passed through a filter of same size to remove impurities before it enters the reactor. Figure 6.1 depicts the details of the bioreactor. Figure 6.1: Details of Bioreactor used in treatment study Optimization of Treatment Parameters in Bioreactor Taguchi Approach Signal to noise ratio is the measure of performance as proposed by Taguchi. The S/N is calculated as formula larger the better The main purpose of this study was to find optimum values of the process parameters and also analyze the data for determining the most effective parameter. Taguchi approach was used to set the variable parameter like F/M ratio, nutrient dosing (BOD: nitrogen (N): phosphorus (P)), temperature, dissolve oxygen, ph and retention time. 171

8 Procedure to Design the Experiment using Taguchi Method There are eight steps in the procedure of optimization process which are given below: (i) Determination of Quality Characteristic to be Optimized The quality characteristic is a parameter whose variation has a critical effect on product quality. Characteristic of wastewater is improved to get better quality so, the step of optimization is required. In case of pulp and paper wastewater COD is the primary parameter which includes both inorganic and organic load. Reduction in COD will lead to the reduction in other wastewater parameters. Therefore COD reduction was taken as quality characteristic to be optimized. (ii) Identification of Noise Factors and Test Conditions The next step is to identify the noise factors that can have a negative impact on system performance and quality. Noise factors are those parameters which are either uncontrollable or are too expensive to control. Noise factors include variations in environmental operating conditions, and variation in response between products of same design with the same input. Temperature can be regulated at lab scale but the study was designed keeping in mind the ultimate approach of the consortia at field scale. Therefore the temperature was identified as noise factor in this study, because it is difficult to regulate the temperature at field conditions. Four test condition of temperature were taken i.e., 25 C, 30 C, 35 C and 40 C. (iii) Identification of Control Parameters and their Alternative Levels The third step is to identify the control parameters thought to have significant effects on the quality characteristic. The control (test) parameters are those design factors that can be set and maintained. The levels (test values) for each test parameter must be chosen at this point. The numbers of levels, with associated test values, for each test parameter define the experimental region. 172

9 The levels for each parameter were decided as follows: F/M ratio 0.25 (level 1), 0.50 (level 2), 0.75 (level 3) and 1.00 (level 4), second parameter was nutrient dosing (BOD: N: P) at 100:1.25:0.25 (level 1), 100:2.5:0.5 (level 2), 100:5:1 (level 3) and 100:7.5:1.5 (level 4), third parameter was DO (mg/l) at 0. 5 (level 1), 1.0 (level 2), 1.5 (level 3) and 2.0 (level 4), fourth parameter selected was ph at 6.5 (level 1), 7.0 (level 2), 7.5 (level 3) and 8 (level 4), hydraulic react time was the last parameter selected (hrs) at 14 (level 1), 16 (level 2), 18 (level 3) and 20 (level 4) (Table 6.1). Parameters levels Table 6.1: List of parameters and their alternative levels F/M ratio Nutrient dose (BOD:N:P) Dissolved oxygen(mg/l) ph Hydraulic react time (h) (A) (B) (C) (D) (E) :1.25: :2.5: :5: :7.5: (iv) Designing of the Matrix Experiment and Defining the Data Analysis Procedure The next step is to design the matrix experiment and define the data analysis procedure. First, the appropriate orthogonal arrays for the noise and control parameters to fit a specific study was selected. Taguchi provides many standard orthogonal arrays. A software Minitab 16 was used for design of experiment and analysis of result. After selecting the appropriate orthogonal arrays, a procedure to simulate the variation in the quality characteristic due to the noise factors was defined. As an alternative, Taguchi proposes orthogonal array based simulation to evaluate the mean and the variance of a product s response resulting from variations in noise factors (Bryne and Taguchi, 1986; Phadke, 1989; Taguchi, 1986). With this approach, orthogonal arrays were used to sample the domain of noise factors. The diversity of noise factors were studied by crossing the orthogonal array of control factors by an orthogonal array of noise factors (Bendell, 1988). 173

10 Table 6.2 gives the details of sixteen experiments to be conducted according to L-16 orthogonal array. If we apply fractional factorial design the number of experiments required to optimize six parameters at three levels are 1024, while they reduced to 16 by applying Taguchi approach. Taguchi approach not only reduces the number of experiment but also indirectly help us to reduce the total expenditure in terms of time and cost. Table 6.2: L16 Orthogonal Array Exp. No. A B C D E Y1 (25 C) Y2 (30 C) Y3 (35 C) Y4 (40 C) (v) Conducting the Matrix Experiment The next step was to conduct the matrix experiment and record the results. Operation of Sequence Batch Reactor (SBR) SBR cycle consists of four steps (i) filling, (ii) hydraulic react, (iii) settling and (iv) decant. While working with the bioreactor first step involved the filling of the vessel. For filling the vessel with effluent, peristaltic pump was used. Time required to fill the vessel was min approximately. After that hydraulic react i.e., the aeration and 174

11 mixing of bacterial consortium with effluent was provided for hrs, followed by settling for 1-2 hrs. After that treated wastewater was decant which take approximately min (figure 6.2). The treated sample was analyzed for chemical oxygen demand. During the treatment mixed liquor suspended solids (MLSS) was maintained by removing the extra sludge from the vessel by time to time after settling. Figure 6.2: Steps involve in the treatment of effluent in sequence batch reactor (SBR) (vi) Analysis of the Data and Determination of the Optimum Levels After the experiments have been conducted, the optimal test parameter configuration within the experiment design was determined. To analyze the results, the Taguchi method uses a statistical measure of performance called signal to noise (S/N) ratio borrowed from electrical control theory (Cary and Scott, 2005). The S/N ratio developed by Taguchi is a performance measure to choose control levels that best cope with noise (Bryne and Taguchi, 1986; Phadke, 1989). The S/N ratio takes both the mean and the variability into account. In its simplest form, the S/N ratio is the ratio of the mean (signal) to the standard deviation (noise). The S/N equation depends on the criterion for the quality characteristic to be optimized. While there are many different possible S/N ratios, three of them are considered standard and are generally applicable in the situations (Bryne and Taguchi, 1986; Phadke, 1989); larger is better quality characteristic (strength, yield), Smaller is better quality characteristic (contamination), Nominal is better quality characteristic (dimension). In this study, larger is better was used for analysis of result. 175

12 (vii) Verification Experiment Using Taguchi method for parameter design, the predicted optimum setting need not correspond to one of the rows of the matrix experiment. This is often the case when highly fractioned designs are used (Bryne and Taguchi, 1986; Phadke, 1989). Therefore, as the final step, an experimental confirmation was run using the predicted optimum levels for the control parameters were studied Bioremediation Experiments After optimization of parameters by Taguchi approach, the selected microbial consortium was tested for reproducibility by analyzing the effluent samples for various parameters ph, BOD, COD, colour, AOX, lignin, TSS and TDS. The experiment was repeated three times in the similar manner as explained in section Obtained results were also compared with values obtained from mill ETP of pulp and paper industry Results Optimization Study of Treatment Process According to L16 orthogonal array, sixteen experiments were placed and for each experiment four trials were performed at different temperatures (25ºC - 40ºC). Four different temperatures were selected in order to justify the activity of selected consortium. After observing the results it was concluded that the selected consortium 9 is robust and have showed good activity at all the temperature. After the accomplishment of the experiments, the respective COD was determined and it was observed that the selected consortium 9 effectively reduces COD at all the selected temperatures (Table 6.3). For experiment 1, where the combinations of levels were F/M ratio (0.25), nutrient dose (100:1.25:0.25), dissolved oxygen (0.5 mg/l) and hydraulic retention (14 hrs) the achieved reduction was 52.7% for the COD value of 345 mg/l in comparison of 730 mg/l of untreated effluent at 25ºC. Whereas, at 30ºC the reduction was 56.4% for the COD value 318 mg/l. While observing the results for the experiments run at 35ºC and 40ºC, the reduction achieved was 60.0% and 61.6% with the reduced COD values 292 mg/l and 280 mg/l respectively. In case of experiment 176

13 number 2 the selected levels for each parameters were F/M ratio (0.25), nutrient dosing (100:2.5:0.5), dissolved oxygen (1.0 mg/l), ph (7.0) and hydraulic retention time was 16 hrs, the reduced COD value were 330 mg/l at 25ºC, 290 mg/l at 30ºC, 265 mg/l at 35ºC and 245 mg/l at 40ºC. The percentage degradation was 54.8%, 60.3%, 63.7% and 66.4% respectively. In case of experiment number 3, the combination of levels were F/M ratio (0.25), nutrient dosing (100:5:1), dissolved oxygen (1.5 mg/l), ph (7.5) and hydraulic retention time was 18 hrs. Results of exp no. 3 showed the COD values 325 mg/l at 25ºC, 288 mg/l at 30ºC, 260 mg/l at 35ºC and 248 mg/l at 40ºC. The calculated percentage reduction was 55.5% at 25ºC, 60.5 % at 30ºC, 64.4% at 35ºC and 66.0% at 40ºC. The combinations of levels for different parameters for experiment no. 4 were F/M ratio (0.25), nutrient dosing (100:7.5:1.5), dissolved oxygen (2.0 mg/l), ph (8.0) and hydraulic retention time was 20 hrs. Results revealed that the achieved reduction in the COD values at different temperatures were 332 mg/l at 25ºC, 305 mg/l at 30ºC, 265 mg/l at 35ºC and 245 at 40ºC. The COD values were compared with the control value i.e., 730 mg/l and the percentage reduction was calculated at different temperatures and it was observed that at 25 C, the reduction was 54.5%, whereas at 30 C the reduction was up to 58.2% and finally at 35 C and 40 C, the reduction achieved was 63.7% and 66.4% respectively. For experiment number 5 the combinations of different levels for various parameters were F/M ratio (0.25), nutrient dosing (100:1.25:0.25), dissolved oxygen (0.5 mg/l), ph (6.5) and hydraulic retention time (14 hrs). It was observed at 25 C the achieved value for the COD was 342 mg/l with the percentage reduction of 53.2%. At 30 C the value for reduced COD was 290 mg/l with the achieved reduction of 60.3%. Similarly, at temperature 35 C, the value for COD was 248 mg/l with the achieved reduction of 66.0%. At temperature 40 C, when result was observed, it was seen that the achieved value of COD was 235 mg/l with the reduction value of 67.8%. In case of experiment number 6 the combinations were F/M ratio (0.50), nutrient dosing (100:2.5:0.5), dissolved oxygen (1.0 mg/l), ph (7.0) and hydraulic retention time was (16 hrs). The achieved COD values and the calculated reduction at four different temperatures (25 C, 30 C, 35 C and 40 C) were 320 mg/l (56.2%), 295 mg/l (59.6%), 262 mg/l (64.1%) and 245 mg/l (66.4%) respectively. Similarly in case of experiment number 7 the combinations were made according to the L-16 orthogonal array. For F/M ratio (0.5), nutrient dosing (100:5:1), dissolved oxygen (1.5 mg/l), ph (7.5) and 177

14 hydraulic retention time was 18 hrs. The result at 25 C showed the reduction of COD value 316 mg/l with the calculated percentage reduction of 56.7%. At temperature 30 C, the achieved COD value was 280 mg/l with the reduction of 59.6%. The results at temperature 35 C showed the reduced value of COD up to 238 mg/l with the percentage reduction of 67.4%. Finally at 40 C, the results showed that COD was 220 mg/l with the percentage reduction up to 69.9%. Experiment number 8 was performed and COD was analyzed for different temperatures. The selected levels for the experiment were F/M ratio (0.50), nutrient dosing (100:7.5:1.5), dissolved oxygen (2.0 mg/l), ph 8.0 and hydraulic retention time was 20 hrs. The COD values at different temperatures were 325 mg/ at 25 C, 290 mg/l at 30 C, 268 mg/l at 35 C and 246 mg/l at 40 C. Percentage reduction was calculated with respect to the control COD value of the untreated effluent, which was estimated in the similar manner. The achieved reductions were 55.5% at 25 C, 60.3% at 30 C, 63.3% at 35 C and 66.3% at 40 C. In case of experiment number 9 the different levels for various selected parameters were F/M ratio (0.75), nutrient dosing (100:1.25:0.25), dissolved oxygen (0.5 mg/l), ph (6.5) and hydraulic retention time (14 hrs). The experiment was run at four different temperatures. The reduction in value of COD at 25 C was 290 mg/l with the achieved percentage reduction up to 60.3%. The value of COD at temperature 30 C was up to 265 mg/l with the achieved reduction of 63.7%. At temperature 35 C, the reduction was up to 66.0% with the reduction in COD 248 mg/l. Finally at temperature 40 C, the COD was reduced up to 225 mg/l with the achieved reduction of 69.2%. The combination of levels for experiment number 10 was F/M ratio (0.75), nutrient dosing (100:2.5:0.5), dissolved oxygen (1.0 mg/l), ph (7.5) and hydraulic retention time was (16 hrs). The COD values of treated effluent at different temperature were 305 mg/l, 260 mg/l, 235 mg/l and 210 mg/l respectively and percentage reduction were 58.2% at 25 C, 64.4% at 30 C, 67.8% at 35 C and 71.2% at 40 C. In case of experiment number 11 the combinations of levels for different parameters were F/M ratio (0.75), nutrient dosing (100:5:1), dissolved oxygen (1.5 mg/l), ph (7.5) and hydraulic retention time 18 hrs. The reduced COD value at 25 C was 285 mg/l with the achieved reduction of 61%). The value for COD at 30 C was 240 mg/l with the percentage degradation 67.1%. At temperature 35 C, the value estimated for COD was 225 mg/l with the percentage reduction value of 69.2%. Finally at 40 C the reduced COD value obtained 178

15 was 190 mg/l with the percentage reduction of 74.0%. In case of experiment number 12 the combinations of different levels were F/M ratio (0.75), nutrient dosing (100:7.5:1.5), dissolved oxygen (2.0 mg/l), ph (8.0) and hydraulic retention time (20 hrs). The percentage reduction achieved at different temperature (25 C, 30 C, 35 C and 40 C) was 58.2%, 62.3%, 67.1% and 70.5% respectively. The reduced COD values at these temperatures were 305 mg/l, 275 mg/l, 240 mg/l and 215 mg/l respectively. Experiment number 13 was performed and COD was analyzed for different temperatures. The selected levels for the experiment were F/M ratio (1.00), nutrient dosing (100:1.25:0.25), dissolved oxygen (0.5 mg/l), ph (6.5) and hydraulic retention time 14 hrs. The COD values at different temperatures were 325 mg/l at 25 C, 280 mg/l at 30 C, 220 mg/l at 35 C and 195 mg/l at 40 C. The reduction was calculated with respect to the control COD value of the untreated effluent, which was estimated in the similar manner. The achieved reduction was 55.5% at 25 C, 61.6% at 30 C, 69.9% at 35 C and 73.3% at 40 C. Similarly in case of experiment number 14 the combinations were made according to the L-16 orthogonal array and F/M ratio was (1.00), nutrient dosing (100:2.5:0.5), dissolved oxygen (1.0 mg/l), ph (7.0) and hydraulic retention time was 16 hrs. The result at 25 C showed reduced COD value of 332 mg/l with the percentage reduction 54.5%. At temperature 30 C, the achieved COD value was 278 mg/l with the percentage reduction of 61.9%. At 35 C reduced value of COD was up to 260 mg/l with the percentage reduction 64.4%. Finally at 40 C, the results showed that the achieved value for the reduced COD was 235 mg/l with the percentage reduction up to 67.8%. In case of experiment number 15 the combinations were F/M ratio (1.0), nutrient dosing (100:5:1), dissolved oxygen (1.5 mg/l), ph (7.5) and hydraulic retention time 18 hrs. The achieved COD values and the calculated reduction at four different temperatures (25 C, 30 C, 35 C and 40 C) were 310 mg/l (57.5%), 285 mg/l (61.0%), 255 mg/l (67.1%) and 240 mg/l (67.1% ) respectively. The combination of levels for experiment number 16 were F/M ratio (1.0), nutrient dosing (100:7.5:1.5), dissolved oxygen (2.0 mg/l), ph (8.0) and hydraulic retention time was (20 hrs). The achieved percentage reduction at different temperatures was 58.2% at 25 C, 64.4% at 30 C, 67.1% at 35 C and 68.8% at 40 C. The COD values were 305 mg/l, 260 mg/l, 240 mg/l and 228 mg/l respectively (Table 6.3). 179

16 Table 6.3: Reduction in COD of effluent at different temperature condition and calculated S/N ratio for each experiment Exp No. Value of COD at different temperature (Y1-Y4) Y 1 (25ºC) Y2 (30ºC) Y3 (35ºC ) Y 4 (40ºC) Percentage reduction in COD at different temperature w.r.t control 730 mg/l Y 1 (25ºC) Y2 (30ºC) Y3 (35ºC ) Y 4 (40ºC) S/N ratio For each experiment S/N ratio was calculated, results are given in (table 6.3) The S/N ratio was calculated by using the data obtained after calculating the percentage reduction in COD. The calculated value of S/N ratio for experiment 1 was The value of S/N ratio for experiment 2 was Calculated value of S/N ratio for experiment number 3 was For experiment number 4 the ratio of S/N was The value of S/N ratio for experiment number 5 was For experiment number 6 the ratio was In case of experiment number 7 the S/N ratio was The calculated value of S/N ratio for experiment number 8 was Similarly the S/N ratio was calculated for experiment number The results showed that the calculated value for the S/N ratio was 36.19, 36.23, 36.56, 36.12, 36.11, 35.78, and respectively. 180

17 Level Average Response and Plot for S/N Ratio The level average response analysis was based upon the S/N data. The analysis was done by averaging the S/N data at each level of each factor and plotted the values in a graphical form. The response table of S/N ratios for control factors is displayed in table 6.4. The level average responses from the plots based on the S/N data help in optimizing the objective function under study. The peak points in these plots correspond to the optimum condition. The level average response plots for various quality characteristics based upon the S/N ratios are shown in figure 6.3. Table 6.4: Response table for signal to noise ratios (larger is better) Level Mean S/N value of factors (A-E) A B C D E Delta Rank Delta S/N ratio was calculated by subtracting the minimum average S/N ration from maximum average S/N ratio. After calculation of delta S/N ratio a rank was given to each delta S/N ratio, factor having maximum delta SN ration is most affecting to the process. After calculating the delta value, it is concluded that the most affecting parameter was F/M ratio followed by the hydraulic react time, nutrient dosing, ph, and the least affected parameter was dissolved oxygen. So the rank of the five factor affecting degradation in descending order are A (F/M ratio) > E (time) > B (nutrient dosing) > D (ph) > C (dissolved oxygen). 181

18 Figure 6.3: Main Effects Plot for SN ratios The optimum condition for each parameter was selected by calculating the S/N ratio and plotting them onto a graph. Form the fig 6.3 it is evident that levels 3, 3, 4, 2 and 2 were considered to be optimum conditions because these levels are showing highest S/N ratio for their respective factors. While comparing these results with the table 6.4, it was concluded that for F/M ratio the optimum condition was 0.5, for hydraulic react time the 16 hrs, for nutrient dosing 100:5:1, for ph 7.0 and for dissolve oxygen the condition selected was 2.0 mg/l Verification Experiment Verification experiment is the final step in confirming the conclusions drawn based on level average response and plot for S/N ratio. Verification experiment is a crucial step and is highly recommended by Taguchi to confirm the experimental conclusions. In fact, running verification experiment is necessary to show the optimum conditions and comparing the result with the expected performance. Verification of the obtained optimal conditions was done by performing experiment at different temperatures. Results of verification experiments showed that the biodegradation rate using new design experiment at different temperatures was successful. The final levels at which 182

19 the verification was done were 0.5 for F/M ration, 10:5:1 for nutrient dosing, 2.0 mg/l for dissolved oxygen, 7.0 for ph and 16 hrs hydraulic react time. Verification experiments were carried out in triplicates. COD values obtained at these conditions are shown in table 6.5. The control value for COD i.e., COD value of untreated effluent was 680 mg/l. The results showed that at temperature 25ºC the achieved mean COD reduction was 63.3% with the COD value of mg/l. At temperature 30ºC the reduced COD value was mg/l with the achieved reduction of 63.2%. While observing the results at 35ºC, the reduction was up to 69.6% with the reduced COD value of mg/l. Finally the results were observed for the experiment performed at 40ºC and the value for reduced COD was mg/l with the achieved percentage reduction of 71.9%. From the results it was concluded that the consortium was effectively degrading the effluent at different temperatures. In order to verify the obtained experimental results, the S/N ratio for each temperature was calculated separately and means SN ratio value was The obtained value is within the 95% confidence interval of expected SN ratio i.e So, it is possible to increase biodegradation rate significantly using the proposed robust model. Table 6.5: Results of verification experiments S.No. COD mg/l Percentage Reduction w.r.t control : 730 mg/l Y1 Y2 Y3 Y4 Y1 Y2 Y3 Y4 S/N ratio Mean Bioremediation Studies After optimization of the parameters at different level s the combination selected was F/M ratio (0/75), nutrient dosing (100:5:1), dissolved oxygen (2.0 mg/l), ph (7.0) and hydraulic react time was 16 hrs. The collected sample after the treatment was analyzed for ph, COD, BOD, colour, AOX, lignin, TSS, TDS and sludge volume index (SVI). The experiment was 183

20 performed thrice at different pollution load in order to check the treatment effeciency. In order to check the activity of consortium blank was also placed under the same conditions. The results were compared with control i.e., value of untreated effluent. Experiment 1 Results of experiments are depicted in table 6.6. The ph of the samples was analyzed and it was observed that the value of ph for the control sample was 7.8, for blank the value was 7.7, whereas at 25 C this value was 7.2 and at temperature 30 C the ph value was 7.1. The value of ph at 35 C and 40 C was 6.7 and 6.8 respectively. After analyzing the results for COD it was observed that the achieved reduction at 25 C was 68.3% with the reduced COD value of 260 mg/l, similarly at 30 C the value for COD was 245 mg/l with 70.1% reduction. The experiment performed at 35 C and 40 C reduced the value of COD up to 205 mg/l and 220 mg/l with the achieved reduction up to 75% and 73.2% respectively. The percentage reduction value was calculated by comparing the values with the control value i.e., the value of raw effluent 820mg/l. In order to check the activity of consortium the blank was placed which was not inoculated with the innoculum. The reduced COD value in case of blank was 590 mg/l and the calculated percentage degradation was 28%. The BOD values and the percentage degradation obtained at different temperatures i.e., 25 C, 30 C, 35 C and 40 C was 32 mg/l (88.4%), 22 mg/l (92%), 18 mg/l (93.5%) and 15 mg/l (94.5%) respectively. The BOD value for control and blank was 275 mg/l and 160 mg/l respectively. The achieved degradation in case of blank was 41.8%. The collected sample was also analyzed for colour, lignin and AOX. The raw effluent value for colour was 940 PCU. The value obtained at 25 C was 490 PCU with the percentage degradation value of 47.9%. At 30 C, the reduced colour value was 435 PCU with the reduction of 53.7%. While observing the results at 35 C and 40 C the achieved colour value was 390 PCU and 400 PCU with the percentage degradation of 58.5% and 57.4% respectively. The samples were analyzed for lignin and adsorbable organic halides results showed that at 25 C the achieved reduction was 53.1% with AOX value of 7.5 mg/l and reduction achieved 48.1% with the lignin value of 84 mg/l. At 30 C the estimated value was 7.5 mg/l for AOX and 76 mg/l for lignin with the calculated reduction value of 53.1% and 53.1 respectively. The value was estimated for the experiments performed at 35 C and 40 C and the achieved value was 6.5 mg/l and 6 mg/l for AOX and 67 mg/l and 72 mg/l with 184

21 percentage reduction value of 59.4% and 62.5% for AOX and 58.6 and 58.6 respectively. The obtained blank value was 15 mg/l for AOX and for lignin the value was 159 mg/l with calculated percentage reduction of 6.3% and 1.9% for lignin. For the same experiments, the samples were collected for the analysis of SVI, TDS and TSS. The results showed that at 25 C the value for TSS, TDS and SVI was 25 mg/l, 995 mg/l and 690 mg/l with the calculated percentage reduction of 79.2% for TSS and 7.9% for TDS. The results for the experiment run at 30 C revealed that the achieved values for the three parameters were 20 mg/l, 890 mg/l and 65 mg/l with the percentage reduction of 83.3% and 17.6%. At 35 C the results showed that the percentage reduction was 83.3% and 21.3% for TSS and TDS with the achieved value of 20 mg/l for and 850 mg/l. The samples collected from the experiment run at 40 C showed the value for TSS up to 25 mg/l, for TDS the value was 825 mg/l and for SVI the value was 70 mg/l. The achieved reduction was 79.2% and 23.6% respectively. The control and blank value for the experiment was for TSS 120 mg/l and 1080 mg/l and for blank 80 mg/l and 1065 mg/l. Table 6.6: Reduction in wastewater parameters (ph, COD, BOD, colour, lignin, AOX, TSS, TDS and SVI) by using consortium 9 under optimized conditions. Parameters Final treatment study on different treatment load Percentage degradation w.r.t control Control Blank Y1 Y2 Y3 Y4 Blank Y1 Y2 Y3 Y4 ph COD (mg/l) BOD(mg/l) Colour (PCU) Lignin (mg/l) AOX (mg/l) TSS (mg/l) TDS (mg/l) SVI ND ND

22 Experiment 2: The experiment was repeated again in order to check the repeatability. The results are depicted in table 6.7. The ph of all the collected samples was analyzed and it was found that the ph value for control and blank, at 25 C, 30 C, 35 C and 45 C was 7.6, 7.5, 7.3, 6.8 and 6.8 respectively. The control values obtained for all the parameters was 960 mg/l for COD, 310 mg/l for BOD, 1230 PCU for colour, 219 mg/l for lignin, 18 mg/l for AOX, 140 mg/l for TSS and 1260 mg/l for TDS. These values were used for calculating the percentage reduction achieved at different temperatures. The percentage reduction observed at 25 C was 72.4% for COD (265 mg/l), 87.3% for BOD (35 mg/l), 52.0% for colour (590 PCU), 49.3% for lignin (111 mg/l), 47.2% for AOX (9.5 mg/l), 82.1% for TSS (25 mg/l) and 14.6% for TDS (1070 mg/l). At 30 C, the observed values with the calculated percentage reduction was 250 mg/l (74%) for COD, 24 mg/l (91.3%) for BOD, 480 PCU (61%) for colour, 86 mg/l (60.7%) for lignin, 9 mg/l (50%) for AOX, 25 mg/l (82.1%) for TSS and 825 mg/l (34.5%) for TDS. The calculated values for percentage reduction at 35 C was 76.6% for COD with the reduced COD value of 225 mg/l, 94.2% with the reduced BOD value of 16 mg/l, 63.4% with the reduced colour value of 450 PCU, 64.8% with the reduced lignin value of 77 mg/l, 58.3% with the reduced AOX value of 7.5 mg/l, 85.7% with the reduced TSS value of 20 mg/l and 35.7% with the reduced TDS value of 810 mg/l. Finally the results were observed at 40 C. The percentage reduction value for COD was 75.5%, for colour the reduction value was 65.9% and for lignin the degradation value was up to 65.8%. The reduction value for BOD and AOX was 94.9% and 55.6% with reduced values of 14 mg/l and 8 mg/l respectively. The reduction value for TSS and TDS was 85.7% and 32.5% with the reduced values of 20 mg/l and 825 mg/l respectively. The value obtained for blank was 610 for COD with percentage reduction of 36.5%, 140 mg/l for BOD with calculated reduction value of 49.1%, 1125 PCU for colour with the achieved reduction of 8.5%, 205 mg/l for lignin with the achieved reduction of 6.4%, AOX the achieved value was 18 mg/l no reduction was observed because the control value was also 18 mg/l. The value for TSS was 65 mg/l with an achieved reduction of 53.5%. The value for TDs was 1235 mg/l whereas the calculated percentage reduction was 1.9%. 186

23 Table 6.7: Reduction in wastewater parameters (ph, COD, BOD, colour, lignin, AOX, TSS, TDS and SVI) by using consortium 9 under optimized conditions. Parameters Final treatment study on different treatment load Percentage degradation w.r.t control Control Blank Y1 Y2 Y3 Y4 Blank Y1 Y2 Y3 Y4 ph COD (mg/l) BOD (mg/l) Colour (PCU) Lignin(mg/l) AOX (mg/l) TSS (mg/l) TDS (mg/l) SVI ND ND Experiment 3: In the similar manner the experiment was repeated third time. Results were depicted in table 6.8. The samples were collected from the bioreactor after the optimized treatment duration and analyzed for ph, COD, BOD, colour, lignin, AOX, TSS, TDS and SVI. The ph of the samples was analysed and it was observed that the ph of the control sample was 7.5, ph for blank was 7.4. The ph of the sample at 25 C was 7.3, at 30 C it was about 7.1, at 35 C it was 7.1 and finally the ph of the sample from the experiment run at 40 C was 6.8. The results revealed that the COD value for control was 660 mg/l, for BOD the value was 290 mg/l, for colour the value was 820 PCU, for lignin the value was 178 mg/l, for AOX the value was 14 mg/l, for TSS the value was 110 mg/l and for TDS the achieved value was 1110 mg/l. At 25 C the observed values were 245 mg/l for COD, 26 mg/l for BOD, 425 PCU for colour, 92 mg/l for lignin, 9.5 mg/l for AOX, 20 mg/l for TSS and 860 mg/l for TDS. The achieved reduction for these parameters at 25 C was 62.9%, 91.0%, 48.2%, 48.3%, 32.1%, 81.8% and 22.5% respectively. At 30 C the values obtained were 200 mg/l for COD, 18 mg/l for BOD, 390 PCU for colour, 81 mg/l for lignin, 8 mg/l for AOX, 20 mg/l for TSS and 790 mg/l for TDS. The calculated percentage reduction for these values were 69.7%, 93.8%, 52.4%, 54.5%, 42.9%, 81.8% and 28.8% respectively. The 187

24 samples were collected from the experiment run at 35 C and it was observed the COD reduced to 180 mg/l with the calculated percentage reduction of 72.7%. The value for colour was 375 PCU (54.3%), for BOD the value was 21 mg/l (92.8%), for lignin the value was 71 mg/l (60.1%), for AOX the value was 8.5 mg/l (39.3%), for TSS the value was 20 mg/l (81.8%) and finally for TDS the achieved value was 750 mg/l (32.4%). At 40 C the values was observed for all the parameters COD, BOD, colour, lignin, AOX, TSS and TDS. The values were 190 mg/l (71.2%) for COD, 14 mg/l (95.2%) for BOD, 360 PCU (56.1%) for colour, fro lignin the achieved reduced value was 65 mg/l (63.5%), for AOX the achieved reduction was 9 mg/l (37.7%), for TSS the reduced value was 20 mg/l (81.8%) and for TDS the reduced value was 730 mg/l (34.2%). The value for blank flask was estimated for all the parameters. For COD the value was 540 mg/l (18.2%), for colour 710 PCU (13.4%), for BOD 125 mg/l (56.9%) and for AOX the value was 13 mg/l (7.1%). Table 6.8: Reduction in wastewater parameters ( ph, COD, BOD, colour, lignin, AOX, TSS, TDS and SVI) by using consortium 9 under optimized conditions. Parameters Final treatment study on different treatment load Percentage degradation w.r.t control Control Blank Y1 Y2 Y3 Y4 Blank Y1 Y2 Y3 Y4 ph COD (mg/l) BOD (mg/l) Colour (PCU) Lignin (mg/l) AOX (mg/l) TSS (mg/l) TDS (mg/l) SVI ND ND After observing all the results it can be concluded that the selected consortium 9 was effectively treating the effluent at all temperatures and the results obtained for COD, BOD and TSS were under the standard limits provided by the regulatory agency. 188

25 Comparison with Mill ETP After performing the bioremediation experiment, the positive results were observed at all the temperature which shows that consortium can cater the problem in all different seasons. The results were compared with the value of Mill ETP. The samples were collected during the summer season, therefore the temperature selected at that time was 35.5 C. As depicted in table 6.9 the value of ph for pc outlet was 7.8 in case of blank the value of ph was 7.7 after consortia treatment the value of ph was observed it was around 6.7 near to neutral and in case of mill treatment the ph value was 7.5. So, we can say that after treating the sample with the selected consortium the value of ph is within the range in which bacteria can effectively degrade the wastewater effluent. While observing the results in case of COD mg/l the values depicted in the table shows that the COD of PC outlet was 820 mg/l after the treatment with the selected consortium the value attained was 205 mg/l and the treated value from mill shows the COD reduction value up to 310 mg/l. Blank was also placed in order to check the activity of the consortium. It was observed in case of blank the COD was reduced up to 590 mg/l simultaneously the percentage reduction values were calculated and it was observed that the achieved reduction in case of the sample inoculated with the consortium 9 was 75% whereas the mill treatment attains the percentage reduction of 62.20%. The collected samples were analyzed for the various parameters like BOD mg/l, Colour, lignin, AOX, TSS, TDS and SVI. In case of BOD mg/l it was observed that the value for PC outlet was 275 mg/l whereas after the bacterial treatment the value achieved was 18 mg/l, in case of mill treatment of the same sample the attain value was 25 mg/l. Percentage reduction was calculated and it was observed that the achieved reduction with the selected consortium was % and in the mill it was around 90.91%. While observing the values for colour it was seen that the value for pc outlet was 940 PCU whereas, the value achieved after the bacterial treatment was 390 PCU for the same sample the value attain at mill site was 650 PCU. The value of the blank for the sample was 860 PCU. Calculated percentage reduction values for colour in case of consortium and mill ETP was 58.1% and 30.85% respectively. The lignin value from the PC outlet was 162 mg/l, in case of the mill ETP the value was 140 mg/l while treating the sample with the selected consortium the attain value of lining was 75 mg/l. The calculated reduction values for the consortium and mill ETP was 53.70% and 189

26 13.58% respectively. In case of AOX the value for PC outlet was 16 mg/l, blank showing the value of 15 mg/l, consortium treated value was 20 mg/l whereas; the value from mill ETP was 9 mg/l. The percentage reduction value calculated for consortium treated effluent was 59.38% and in case of mill this attain reduction was %. TSS mg/l was observed and in case of r PC outlet the value was 120 mg/l, with the consortium the achieved value was 80 mg/l, in case of mill ETP the value for TSS was 70 mg/l. The calculated percentage reduction for consortium treated effluent and mill ETP was 83.33% and 41.67% respectively. The value observed while calculating the TDS of the sample in case of PC outlet 1080 mg/l, blank 1065 mg/l, consortium treated effluent was 850 mg/l and mill ETP was 320 mg/l. The percentage reduction value for consortium treated effluent was 21.30% and for mill ETP the achieved reduction value was 11.11%. The SVI was also calculated for the samples in case of consortium treated effluent the value was 65 and in case of mill ETP it was around 320. While comparing F/M ratio, in mill ETP it was observed that F/M was around 0.22, whereas, in case of bioreactor by using bacterial consortium, it was Table 6.9: Comparison of mill ETP values with the consortium treated effluent Parameters PC outlet Blank Treatment study Use of consortium Mill ETP Discharge Std. Percentage reduction w.r.t PC outlet Blank Use of consortium Mill ETP ph COD (mg/l) BOD (mg/l) Colour (PCU) ND Lignin (mg/l) do AOX (mg/l) do TSS (mg/l) TDS SVI ND ND F/M ratio