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  1. 1. International Conference on Chemistry and Environmental Science Research 2014 (ICCESR 2014) Optimization Study On Adsorption of Methylene Blue on Sugarcane Bagasse using Two Level Full Factorial Design Wong Shi Ting1 , Nik Ahmad Nizam Nik Malek1 *, Auni Afiqah Kamaru1 , Mahmud A. S. Khalifa1 and Nor Suriani Sani2 1 Faculty of Biosciences and Medical Engineering, Universiti Teknologi Malaysia, 81310 UTM, Johor 2 Nanotechnology Research Alliance, Universiti Teknologi Malaysia, 81310 UTM, Skudai, Johor * ABSTRACT The adsorption study of methylene blue (MB) by sugarcane bagasse was performed based on statistical approach using two-level factorial design. The effect of several factors affecting the adsorption capacity of sugarcane bagasse namely contact time (15 – 60 min), shaking rate (50 – 250 rpm), initial MB concentration (50 – 150 mg/L) and adsorbent dosage (0.1 – 0.5 g) were studied. The optimum adsorption capacity of MB on sugarcane bagasse was found at 58 min contact time, 150 mg/L of MB with shaking rate of 250 rpm and adsorbent dosage of 0.1 g. Theoretical adsorption at equilibrium, qe, (24.52 mg/g) at this condition matched closely with the experimental value (22.25 mg/g). Keywords: Sugarcane bagasse, Methylene blue, Adsorption, Two-level factorial design Introduction In Malaysia, 22 % of industrial wastewater was discharged by textile industries [1]. Dyes that contains in industrial wastewater must be treated before being discharged to the environment due to it adverse effects to human as it can cause skin irritation, toxic, allergic, mutagenic and carcinogenic [2]. Currently, the removal and recovery of dyes is by the adsorption method since it is cheaper, efficient and ease in operation [3]. Sugarcane bagasse, one of adsorbent that has been proven having high adsorption capacity for various dyes such as basic blue 69 and basic red 22 [4-5]. Sugarcane bagasse is cheaper compared to other solid support like cellulose pulp, chitosan and synthetic polymers [6]. In this study, the sugarcane bagasse, the low cost
  2. 2. International Conference on Chemistry and Environmental Science Research 2014 (ICCESR 2014) agricultural waste biomass adsorbent has been used to remove dye from water. The effect of adsorbent dosage, initial methylene blue concentration, shaking rate and contact time on the removal of methylene blue dye from aqueous solution have been investigated using 2-level factorial design. Factorial design is a tool that can be used to design experiments. An experiment using factorial design allows examining simultaneous effects of multiple independent variables and their degree of interaction [7-8]. In one-factor-at-a-time (OFAT), each experiments run consider only one factor, numerous run are required to get adequate information about the set of conditions contributing to the problem. The advantage of factorial designs over OFAT is they are more efficient and they allow interaction among studied factors to be detected. Materials and Methods Sugarcane bagasse (SB) has been collected from juice shop in Johor Bahru, Malaysia. Sugarcane waste was firstly placed below sunlight. The pith fragments and fiber were crashed to tiny parts and dried at 90 °C in an oven for 24 hours. Sugarcane bagasse (SB) was changed to fine particles by crushing them using a stainless steel blender. The SB fragments were washed with distilled water under constant stirring at 60-70 °C to remove the remaining sugars, filtered by single filtration and washed again with ethanol 95%, and dried at 90 °C. Lastly, the sample was washed again with the hexane-ethanol (1:1) with a soxhlet apparatus for 4 hours to eliminate lignin extracted and extractives from blending process. It was dried at 90 °C in an oven and stored at room temperature. A two level (24 ) full factorial experimental design was employed with four main factors, namely; contact time (A), initial methylene blue concentration (B), shaking rate (C) and adsorbent dosage (D). The investigated factor levels and range are given in Table 1. The experimental design and statistical significance of investigated factors and their combinations were carried out using Design Expert 6.0.4 software. A multiple regression analysis was conducted based on the first-order response function as given in Equation 1. 𝑌 = 𝛽0 + 𝛽𝑖 𝑋𝑖 + 𝛽𝑖 𝑋𝑖 𝑋𝑗 + 𝜀 (1)
  3. 3. International Conference on Chemistry and Environmental Science Research 2014 (ICCESR 2014) where β0, βi, βij are regression coefficients for the intercept, linear and interactions among factors, respectively, y, is the response vector for qe and R, whereas Xi and Xj are the independent factors in coded units, and ε is the error term. The fitness of regression model was evaluated by calculating the coefficient of determination (R2 ) [9]. Table 1: Experimental range and levels of independent variables for adsorption of methylene blue by sugarcane bagasse Variable Symbol Unit Low level (-1) High level (+1) Contact time A min 15 60 Initial MB concentration B mg/L 50 150 Shaking rate C rpm 50 250 Adsorbent dosage D g 0.1 0.5 The residual methylene blue concentration was measured by collecting the supernatant and was analyzed using VIS spectrophotometer (VIS NANOCOLOR macherey-nagel, German) at wavelength of 661 nm. The methylene blue concentration was calculated from a calibration curve of absorbance versus dye concentration. Then, the adsorption amount at equilibrium, qe (mg/g), was calculated by Equation 2 𝑞 𝑒 = ( 𝐶𝑖 − 𝐶 𝑒 ) 𝑉 𝑊 [2] where qe is the amount of methylene blue adsorption at equilibrium (mg/g), Ci and Ce (mg/L) are the methylene blue concentration at initial and equilibrium, respectively, V (L) is the volume of the solution, and w (g) is the weight of SB used. Results and Discussion Regression Analysis Based on 2-level factorial design, interactions of variables, on adsorption capacity of sugarcane bagasse are summarized in the regression equation, Eq (3):
  4. 4. International Conference on Chemistry and Environmental Science Research 2014 (ICCESR 2014) Adsorption at equilibrium, qe (mg/g) = 11.53 + 0.19A + 3.94B + 0.29C -6.36D + 0.13AB - 0.20AD + 0.12BC - 1.42 BD - 0.24 CD - 0.14 ABD (3) The factor with positive values for their coefficients can improve the respective response vector for an increase in the level of those factors, whereas negative value of the coefficients suggests their inverse relationship with the response vectors [9]. ANOVA Study Interpretation of result was analyzed using the analysis of variance (ANOVA) as appropriate to the experimental design used. This method was used for comparison of the significance factors among the four variables influencing the adsorption capacity of SB. Screening design (24 ) was used to detect the factors or independent variables that had higher impact on the response variable adsorption at equilibrium (qe). The results are tabulated in Table 2. Table 2: Analysis of variance (ANOVA) for selected factorial model influenced the adsorption of methylene blue on the sugarcane bagasse Source Sum of Square DF Mean Square F Value a Prob > F Model 2795.43 10 279.54 3748.61 < 0.0001 A 1.80 1 1.80 24.10 < 0.0001 B 744.25 1 744.25 9980.23 < 0.0001 C 4.14 1 4.14 55.56 < 0.0001 D 1941.53 1 1941.53 26035.47 < 0.0001 AB 0.82 1 0.82 11.02 0.0019 AD 1.87 1 1.87 25.10 < 0.0001 BC 0.69 1 0.69 9.24 0.0041 BD 96.49 1 96.49 1293.86 < 0.0001 CD 2.87 1 2.87 38.53 < 0.0001 ABD 0.97 1 0.97 12.98 0.0008 Curvature 45.60 1 45.60 611.45 < 0.0001 R-Squared 0.9989 Pred-R-Squard 0.9981
  5. 5. International Conference on Chemistry and Environmental Science Research 2014 (ICCESR 2014) Adj R-Squard 0.9986 Adeq Precision 170.861 The “Pred R-Squared” of 0.9981 is in reasonable agreement with the “Adj R- Squared” of 0.9986. Values of “Prob > F” less than 0.05 indicate model terms are significant. The probability value (p-value) for each term and interaction is listed in Table 2. A p- value that less than 0.05 defines the factors is significant. The model is significant with a probability of less than 0.0001. This means that the regression model which has been generated to describe the correlation of adsorption at equilibrium (qe) with the analyzed factors was accurate. Regression coefficient, R2 value of 0.9989, indicated model adequacy and shows that the model is workable and can be accepted. Sum of squares (Table 2) of each factor quantifies its importance in the process and as the value of the sum of squares increases, the significance of the corresponding factor in the undergoing process also increases [10]. F values of 4 factors were as follows: Fcontact time (A) = 24.10, Finitial concentration of methylene blue (B) = 9980.23, Fshaking rate (C) = 55.56, Fadsorbent dosage (D) = 26035.47. The result of F-test meant that the 4 factors were all significant in influencing the adsorption capacity of SB. Value of ―prob > F‖ less than 0.0500 indicates model term was significant. The ―Curvature F-value‖ of 611.45 implies there is significant curvature (as measured by the differences between the average of the center points and the average of the factorial points) in the design space. In addition, the ―Pre R-Squares‖ of 0.9981 is in reasonable agreement with the ―Adj R-Squared‖ of 0.9986. Normal Probability Plot of Residuals Figure 1: Normal probability plots of residuals for adsorption of MB by SB
  6. 6. International Conference on Chemistry and Environmental Science Research 2014 (ICCESR 2014) The normality of the data can be determined by plotting a normal probability plot of the residuals. If the data points on the lot fall fairly close to the straight line, then the data are normally distributed. The normal probability plot of the residuals for adsorption of methylene blue on sugarcane bagasse is shown in Figure 1. It can be seen from this figure that the data points are fairly close to the straight line and it indicates that the experiments are normally distributed population [10]. In this case, the optimal condition for the adsorption capacity of sugarcane bagasse that was determined as A, B, C, D, AB, AD, BC, BD, CD, ABD are significant model term where contact time (A) was 58 min, initial [MB] (B) was 150 mg/L, shaking rate (C) was at 250 rpm with 0.1 g of adsorbent dosage (D) which can be referred in Figure 2. Figure 2: Factors that significantly influenced the adsorption capacity of sugarcane bagasse toward methylene blue analyzed using 2-Level-Factorial Design The optimum and significant factor of initial [MB] in this adsorption study was 150.00 mg/L which indicated that higher [MB] is needed to achieve the highest adsorption capacity. The initial dye concentration is a driving force that can overcome mass transfer resistance which exists between the dye molecules in aqueous solution and adsorbent particles. Thus, the number of dye molecules that compete to adsorb on the adsorbent increases at higher initial dye concentration thus leading to higher adsorption capacity [11]. Nasuha et al. (2010) reported that the adsorption capacity of adsorbent was proportional to the initial concentration of MB. They
  7. 7. International Conference on Chemistry and Environmental Science Research 2014 (ICCESR 2014) found that there was a significant increment in the adsorption capacity of tea waste from 18.6 to 134 mg/g when the concentration of MB dye was increased from 50 to 500 mg/L [12]. Therefore, it can be concluded that the initial dye concentration was the most significant factor for adsorption capacity [9]. In this study, the optimum contact time and adsorbent dosage for achieving the highest adsorption capacity were 58 minutes and 0.1 g, respectively. The interaction between the effect of time and the weight of adsorbent on the percentage removal of MB reveals that time have the direct effect on the adsorption process. As more time of operation means more contact times are needed for transferring mass from solid to liquid phase until equilibrium is reached [13]. Equilibrium time is an important parameter for economical wastewater treatment. As the contact time increases, the rate of adsorption decreases depending on the chemical characteristics on the surface [14]. According to Uddin et al. (2009) the percentage removal of MB increased with the increase in adsorbent dosage, but the adsorption density (qe) of MB decreased with the increment in adsorbent dosage [15]. The optimum shaking rate during the screening factors for adsorption capacity of sugarcane bagasse was at 250 rpm. The influence of increasing the shaking rate is to decrease the liquid film or boundary layer surrounding the adsorbent particles [16]. The higher shaking rate lead to the higher contact between the adsorbent and the dyes thus increase in adsorption capacity of the adsorbents. Conclusion According to the analysis, the optimum process conditions for the MB removal by sugarcane bagasse include contact time 58 min, initial methylene blue concentration of 150 mg/L, shaking rate at 250 rpm and adsorbent dosage of 0.1 g (Figure 1). Theoretical adsorption at equilibrium, qe (24.52 mg/g) at this condition matches very well with the experimental value (22.25 mg/g). The experimental value is 91% of the predicted value. Sugarcane bagasse has been proven to be an effective low-cost adsorbent for the removal of MB via adsorption from aqueous solution.
  8. 8. International Conference on Chemistry and Environmental Science Research 2014 (ICCESR 2014) Acknowledgement Author would like to acknowledge Universiti Teknologi Malaysia (UTM) and Ministry of Education Malaysia for financial support under Research University Grant Tier 1 (Vot No: 08H01) and Faculty of Biosciences and Medical Engineering, UTM. References [1] Hameed, B. and El-Khaiary, M, 2008. Removal of basic dye from aqueous medium using a novel agricultural waste material: Pumpkin seed hull, Journal of Hazardous Materials, vol. 155, pp. 601-609. [2] Royer, B., Cardoso, N. F., Lima, E. C., Vaghetti, J. C., Simon, N. M., Calvete, T. and Veses, R. C, 2009. Applications of Brazilian pine-fruit shell in natural and carbonized forms as adsorbents to removal of methylene blue from aqueous solutions—Kinetic and equilibrium study, Journal of Hazardous Materials, vol.164, pp. 1213-1222. [3] Ahmad, R, 2009. Studies on adsorption of crystal violet dye from aqueous solution onto coniferous pinus bark powder (CPBP), Journal of Hazardous Materials, vol. 171, pp. 767- 773. [4] Gupta, V, 2009. Application of low-cost adsorbents for dye removal–A review, Journal of Environmental Management, vol. 90, pp. 2313-2342. [5] McKay, G., El Geundi, M. and Nassar, M, 1987. Equilibrium studies during the removal of dyestuffs from aqueous solutions using bagasse pith, Water Research, vol.21, pp. 1513- 1520. [6] Garg, U. K., Kaur, M. P., Sud, D. and Garg, V. K, 2009. Removal of hexavalent chromium from aqueous solution by adsorption on treated sugarcane bagasse using response surface methodological approach, Desalination, vol. 249, pp. 475-479. [7] Butler, N. A, 2008. Defining equations for two-level factorial designs, Journal of Statistical Planning and Inference, vol. 138, pp. 3157-3163. [8] Hedayat, A. S. and Pesotan, H, 2007. Tools for constructing optimal two-level factorial designs for a linear model containing main effects and one two-factor interaction, Journal of Statistical Planning and Inference, vol. 137, pp.1452-1463.
  9. 9. International Conference on Chemistry and Environmental Science Research 2014 (ICCESR 2014) [9] Rehman, M. S. U., Kim, I. and Han, J.-I, 2012. Adsorption of methylene blue dye from aqueous solution by sugar extracted spent rice biomass, Carbohydrate Polymers, vol. 90, pp. 1314-1322. [10] Gottipati, R. and Mishra, S, 2010. Process optimization of adsorption of Cr (VI) on activated carbons prepared from plant precursors by a two-level full factorial design, Chemical Engineering Journal, vol. 160, pp. 99-107. [11] Safa, Y. and Bhatti, H. N, 2011. Kinetic and thermodynamic modeling for the removal of Direct Red-31 and Direct Orange-26 dyes from aqueous solutions by rice husk, Desalination, vol. 272, pp. 313-322. [12] Nasuha, N., Hameed, B. and Din, A. T. M, 2010. Rejected tea as a potential low-cost adsorbent for the removal of methylene blue, Journal of Hazardous Materials, vol. 175, pp. 126-132. [13] Chatterjee, S., Kumar, A., Basu, S. and Dutta, S, 2012. Application of response surface methodology for methylene blue dye removal from aqueous solution using low cost adsorbent, Chemical Engineering Journal, vol. 181, pp. 289-299. [14] Anupam, K., Dutta, S., Bhattacharjee, C. and Datta, S, 2011. Adsorptive removal of chromium (VI) from aqueous solution over powdered activated carbon: Optimisation through response surface methodology, Chemical Engineering Journal, vol. 173, pp. 135- 143. [15] Uddin, M. T., Islam, M. A., Mahmud, S. and Rukanuzzaman, M, 2009. Adsorptive removal of methylene blue by tea waste, Journal of Hazardous Materials, vol. 164, pp. 53-60. [16] Chu, H. C. and Chen, K. M, 2002. Reuse of activated sludge biomass: II. The rate processes for the adsorption of basic dyes on biomass, Process Biochemistry, vol. 37, pp. 1129-1134.