Optimization of Biodiesel Production from Jatropha Oil (Jatropha curcas L.) using Response Surface Methodology

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1 Kasetsart J. (Nat. Sci.) 44 : (010) Optimization of Biodiesel Production from Jatropha Oil (Jatropha curcas L.) using Response Surface Methodology Kanthawut Boonmee 1 *, Sawitri Chuntranuluck 1, Vittaya Punsuvon and Pinya Silayoi 3 ABSTRACT The main purpose of this research was to develop a biodiesel production technique from Jatropha oil (Jatropha curcas). Special attention was paid to the optimization of alkali-catalyzed transesterification for converting fatty acid methyl ester (FAME). Jatropha oil contained.59 mg KOH/g of acid and a molecular weight of 900 g/mol with high oleic acid (41.70%) and linoleic acid (36.98%). A central composite design (CCD) technique was applied for the experimental design. There were 0 experiments involving the three investigated variables of methanol-to-oil molar ratio ( ), sodium hydroxide ( % w/w) and reaction time ( min). The data was statistically analyzed by the Design-Expert program to find the suitable model of % fatty acid methyl ester (% FAME) as a function of the three investigated variables. A full quadratic model was suggested by the program using response surface methodology (RSM) with an R and adjusted R of 97 and 94%, respectively. The optimum conditions for transesterification were a methanol-to-oil molar ratio of 6.00, 1.00% w/w sodium hydroxide and 90 min reaction time. The optimum condition obtained a FAME content of 99.87%. The resulting Jatropha biodiesel properties satisfied both the ASTMD 6751 and EN 1414 biodiesel standards. The production technique developed could be further applied in a pilot plant. Key words: Jatropha curcas L. oil, non-edible oil, transesterification, biodiesel, fatty acid methyl ester (FAME) INTRODUCTION Due to the availability of recoverable agricultural resources, the environmental problems caused by fossil fuel consumption, as well as the dramatic impact of oil imports on Thailand s economy, biodiesel production is being considered as an alternative to petrodiesel. Biodiesel is believed to be able to decrease the dependence on and improve the adverse environmental impact of using oil. However, as it is produced from vegetable oils and animal fats, biodiesel feedstock may affect food supplies in the long-term. The recent focus has been to seek a source of nonedible oils, as a feedstock for biodiesel production. Jatropha curcas L. (Jatropha) has been chosen as an optimal supply source. Jatropha curcas L. is a non-edible oilbearing plant widespread in arid, semi-arid and tropical regions of Thailand. Jatropha curcas L. is a drought-resistant perennial tree that grows in marginal lands and can live over 50 years 1 Department of Biotechnology, Faculty of Agro-Industry, Kasetsart University, Bangkok 10900, Thailand. Department of Chemistry, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand. 3 Department of Packing Technology and Materials, Faculty of Agro-Industry, Kasetsart University, Bangkok 10900, Thailand. * Corresponding author, e -mail: Kanthawut@hotmail.com Received date : 06/08/09 Accepted date : 30/10/09

2 Kasetsart J. (Nat. Sci.) 44() 91 (Bosswell, 003). Jatropha curcas L. has several benefits, such as its stem can be used as a natural toothpaste and toothbrush, latex from the stem can be used as a natural pesticide and to heal wounds, while its leaves are used as fodder for silkworms (Chhetri et al., 008). Compared to any other economic plants, Jatropha curcas L. is very durable in hot climates, such as Thailand experiences, The oil content in Jatropha curcas L. seed is reported to be in the range from 30 to 50% by weight of seed (Kandpal and Madan, 1995; Pramanik, 003) and from 45 to 60% by weight of the kernel itself (Pramanik, 003). Therefore, Jatropha oil has a potential to be used as a substitute fuel in biodiesel production. In addition, Jatropha oil not only has a high level of fat and unsaturated fatty acids, but also low levels of free fatty acids (Foidl et al., 1996). The oil can be used directly in agricultural diesel engines, electric generators, tractors and water pumps without any additives and does not cause any physical damage. For diesel engine use, Jatropha oil has to undergo a transesterification process. In Thailand, Jatropha oil has been placed on the national agenda to encourage its production in the rural community for transportation and agriculture, as a substitute for bio-diesel fuel. A few attempts have been made to produce biodiesel from non-edible sources, such as used frying oil, grease, tallow and lard (Alcantara et al., 000; Canakci and Gerpen, 001; Dorado et al., 00). The production of biodiesel would be inexpensive because it could be extracted from the non-edible oil sources and from certain species that are common in many parts of Thailand. Jatropha curcas L. has ecological advantages and has been found to be an appropriate, renewable, alternative source of biodiesel production in Thailand. However, extracted Jatropha oil cannot be used directly in diesel engines because of its high viscosity. The high viscosity of pure vegetable oils reduces fuel atomization and increases fuel spray penetration, which results in high engine deposits and thickening of the lubricating oil (Silvio et al., 00). Transesterification is a process for the reduction of triglyceride molecules (Van Dyne et al., 1996; Muniyappa, et al., 1996). The use of chemically altered or transesterified vegetable oil, called biodiesel, does not require any modification in the engine or its injection system or fuel lines and can be used in any diesel engine. The stoichiometric equation requires one mole of triglyceride and three moles of alcohol to form three moles of methyl ester and one mole of glycerol in the presence of a strong base or acid (Muniyappa et al., 1996). Methanolysis is the process where methanol is used in biodiesel production (Gervasio, 1996; Ma and Hanna, 1999). Response surface methodology (RSM) is a useful statistical technique, which has been applied in the research of complex variable processes (Myers and Montgomery, 00). Multiple regression and correlation analysis are used as tools to assess the effects of two or more independent factors on the dependent variables. Furthermore, the central composite design (CCD) of RSM has been applied in the optimization of several biotechnological and chemical processes. Its main advantage is the reduction in the number of experimental runs required to generate sufficient information for a statistically acceptable result. RSM has been applied successfully for optimization of biodiesel production in fat and oil feedstocks, including mahua oil (Madhuca indica) (Ghadge and Raheman, 006), Jatropha oil (Tiwari et al., 007), waste rapeseed oil (Yuan et al., 008) and animal fat (Jeong et al., 009). The current study concentrated on developing a technique for biodiesel production from Jatropha oil. RSM was applied to optimize the alkali-catalyzed transesterification to produce fatty acid methyl ester (FAME) as a function of three factors: the methanol-to-oil molar ratio, sodium hydroxide and the reaction time. The fuel properties of Jatropha biodiesel for vehicle use were determined.

3 9 Kasetsart J. (Nat. Sci.) 44() MATERIALS AND METHODS Alkali catalyzed transesterification Crude Jatropha oil used in the experiments was obtained from the Department of Chemical Engineering at Kasetsart University. Methanol (from the J. T. Baker Chemical Co.) and sodium hydroxide (from Merek Ltd.) were analytical reagent grade. Oil was partially purified by filtration and boiling at C for 0.5 h to remove the insoluble portion and water, respectively. The experiments were conducted at the Department of Chemical Engineering, Kasetsart University. In the production of Jatropha biodiesel by the alkali-catalyzed transesterification technique, methanol was chosen as a catalyst because of its low cost. Sodium hydroxide was chosen, since it was reasonably priced and reacted much faster than the acid catalyst (Freedman et al., 1984). The important factors affecting the transesterification reaction were the excessive amount of methanol and sodium hydroxide, and the reaction time (Demirbas, 003). In order to optimize the amount of excess methanol required for the reaction, the experiments were conducted with various methanol-to-oil molar ratios, because the transesterification reaction required 3 moles of methanol to react with 1 mole of vegetable oil (Kavitha, 003). Most researchers used 0.10 to 1.0 (% by weight of oil) NaOH (Alacantara et al., 000). The acid value was defined as milligrams of potassium hydroxide necessary to neutralize fatty acids in 1 g of sample. If the acid value of the oil used was greater than 5 mg KOH/ g, more NaOH would be required to neutralize the free fatty acids (Wright et al., 1944). The reaction time was 90 min, after which the reactant was transferred to a separation funnel (Foidl et al., 1996). A five-level-three-factor CCD was employed in the optimization study, requiring 0 experiments. The methanol-to-oil molar ratio, catalyst concentration and reaction time were the independent variables selected to optimize the conditions for FAME production of sodium hydroxide-catalyzed transesterification. The 0 experiments were carried out and data was statistically analyzed by the Design-Expert program to find the suitable model for the % fatty acid methyl ester (% FAME) as a function of the above three variables. The coded and uncoded levels of the independent variables in this step are given in Table 1. Two replications were carried out for all experimental design conditions. The central values (zero level) chosen for the experimental design were a methanol-to-oil molar ratio of 6:1, 1% w/w catalyst concentration and 90 min reaction time. Table 1 Independent variables and levels used in the central composite design for the alkali catalyzed transesterification process. Variable Symbol Level a (uncoded variable) (-α) (+α) Methanol-to-oil molar ratio M Catalyst concentration C (%w/w) Reaction time T (minutes) Note: a Transformation of variable levels from coded variables of X 1, X and X 3 in Equation 3 to uncoded variables are: M = X 1, C = X and T = X 3.

4 Kasetsart J. (Nat. Sci.) 44() 93 The following experimental procedure was adopted for the production of Jatropha biodiesel. Some Jatropha oil was placed in a threenecked round-bottomed flask. A water-cooled condenser and a thermometer with cork were connected to both sides of the round-bottom flask. The required amount of NaOH and methanol were weighed and dissolved completely, using a magnetic stirrer. The Jatropha oil was warmed by placing the round-bottomed flask in a water bath maintained at 60 C. The sodium methoxide solution was added into the oil using fixed vigorous mixing (400 rpm). The mixture was poured into the separating funnel overnight settling by gravity into two layers, with the clear, golden liquid-jatropha biodiesel on the top and the light brown glycerol on the bottom. After 4 h, the glycerol was drained off. The raw Jatropha biodiesel was collected and water-washed to bring down the ph of bio-diesel to 7 (the ph of water). The percentage of FAME content in the resulting biodiesel was measured by gas chromatography (GC). Quantitative analysis of fatty acid methyl ester content Chromatographic analysis was performed on a Shimadzu GC-010 gas chromatograph equipped with a DB-WAX column (30 m 0.3mm, 0.5µm) and flame ionization detector (FID). The operating conditions involved injector and detector temperatures at 60 C and a split ratio at 1:5. Helium was used as the carrier gas. Methyl heptadecanoate (Supelco Inc.) was used as the internal standard of fatty acid methyl ester. The analysis was performed by dissolving 0.05 g of the biodiesel sample in 1 ml of methyl heptadecanoate and injecting 1 µl of this solution mixture into the gas chromatograph. The percentage of FAME was calculated by the Equation 1: C = (Σ A-A SI )/A SI (C SI V SI )/m 100 (1) where : C = the FAME content (% w/w) ΣA = the total peak area from the methyl ester A SI = the peak area of methyl heptadecanoate C SI = the concentration of used methyl heptadecanoate solution (mg/ml) V SI = the volume of used methyl heptadecanoate solution (ml) m = the weight of sample (g) Statistical analysis The experimental data was analyzed by the response surface regression procedure using a second-order polynomial (Equation ): k k k k y= β0 + βixi + βiix i + βijxixj () i= 1 i= 1 i j i> j where, y is the response variable; x i and x j are the coded independent variables and β o, β i, β ii and β ij are the intercept, linear, quadratic and interaction constant coefficients respectively, and k is the number of factors studied and optimized in the experiment. The Design-Expert program was used in the regression analysis and analysis of variance (ANOVA). The Statistica software program was used to generate surface plots, using the fitted quadratic polynomial equation obtained from the regression analysis, holding one of the independent variables constant. Experiments were carried out to validate the equation, using combinations of the independent variables, which were not part of the original experimental design, but within the experimental region (Ghadge and Raheman, 006). Analysis of Jatropha biodiesel properties The analysis of Jatropha biodiesel qualities considered the density at 15 C, acid value, iodine value, linolenic methyl ester, flash point, cloud point, viscosity at 40 C, free

5 94 Kasetsart J. (Nat. Sci.) 44() glyceride, monoglyceride, diglycerides, triglycerides and total glyceride. The analysis was carried out using the methods developed by the Center of Excellence on Palm Oil, Kasetsart University and compared with the ASTMD6751 and EN 1414 biodiesel standards. RESULTS AND DISCUSSION Properties of Jatropha oil The fatty acid composition of Jatropha oil was 41.70% w/w oleic acid and 36.98% w/w linoleic acid with an acid value of.59 mg KOH/ g, which was an acceptable result for the transesterification process (lower than 5.00 mg KOH/g), according to Gerpen (005). The average molecular weight was 900 g/mole. Alkali catalyzed transesterification The central composite design conditions and responses, and the statistical analysis of the ANOVA are given in Tables and 3, respectively. The multiple regression coefficients were obtained by employing a least square technique to predict a quadratic polynomial model for the FAME content (Table 4). The model was tested for adequacy by analysis of variance. The regression model was found to be highly significant with the correlation coefficients of determination of R-Squared (R ), adjusted R-Squared and predicted R-Squared having a value of 0.97, 0.94 and 0.75, respectively. The predicted model for percentage of FAME content (Y) in terms of the coded factors is shown in Equation 3: Table Central composite design arrangement and response for alkali catalyzed transesterification. Treatment X 1 X X 3 Methanol NaOH Reaction /oil molar concentration time Fatty acid methyl ester ratio (%w/w) (minutes) (%) (M) (C) (T) Experimental Predicted

6 Kasetsart J. (Nat. Sci.) 44() 95 Y = X X X X X X X 1 X X 1 X X X 3 (3) The RSM was used to optimize the conditions of conversion for Jatropha biodiesel and to understand the interaction of the factors affecting Jatropha biodiesel production. Figures 1, and 3 show surface plots between the independent and dependent variables for different fixed parameters. From Figure 1, the % FAME amount increased with increasing catalyst concentration at a low methanol-to-oil molar ratio. From Figure, the % FAME amount increased with the increasing methanol-to-oil molar ratio for a low reaction time. From Figure 3, the % FAME amount increased with increasing reaction time at a high catalyst concentration. The methanol-to-oil molar ratio (X 1 ) was the limiting condition and a small variation in its value altered the conversion. At the same time, there was a significant mutual interaction between the methanol to oil molar ratio and the catalyst concentration (X 1 X ) and the interaction between catalyst concentration and reaction time (X X 3 ). These results were similar to Jeong et al. (009), who studied RSM and the effect of five-level-three-factors in optimizing the reaction conditions of biodiesel production from animal fat. A statistical model (Equation 3) predicted that the highest conversion yield of Jatropha biodiesel was 99.87% FAME content, when the optimized reaction conditions were a catalyst concentration of 1.00% w/w, a methanol-to-oil molar ratio of 6.00 and a reaction time of 90 min. Additional experiments were carried out to validate the equation using these optimal values. It was found that the experimental value of 99.88% of FAME content agreed well with the predicted value. Table 3 Analysis of variance (ANOVA) for the quadratic polynomial model from the transesterification. Model Sum of squares df Mean square F Sig. Regression a Residual Total a Predictors: (Constant), X 1, X, X 3, X 1 X, X 1 X 3, X X 3, X 1, X, X 3. Table 4 Regression coefficients of the predicted quadratic polynomial model for alkali-catalyzed transesterification. Model Unstandardized Standardized t Sig. coefficients coefficients B Std. error Beta (Constant) X X X X X X X 1 X X 1 X X X

7 96 Kasetsart J. (Nat. Sci.) 44() Analysis of Jatropha biodiesel The chromatogram of Jatropha oil methyl ester is shown in Figure 4. The major FAME components were palmitic acid (C16:0), oleic acid (C18:1) and linoleic acid (C18:), which are required for the biodiesel standard. The GC analysis of the FAME from Jatropha oil (Figure 4) showed that FAME mainly contained fatty acid methyl esters (Yuan et al., 008) with oleic acid as the predominant fatty acid. The quality of the Jatropha biodiesel was designed to obtain a high percentage FAME. The Jatropha biodiesel process consisted of a filtration process, reaction process (alkali-catalyzed transesterification process), separation process, washing process, recovery process and Figure 1 The effect of catalyst concentration (% w/w) and methanol-to-oil molar ratio on predicted value of % FAME at 90 min. Figure The effect of reaction time (minutes) and methanol-to-oil molar ratio on predicted value of % FAME at 1% w/w catalyst concentration.

8 Kasetsart J. (Nat. Sci.) 44() 97 dehydration process. In the experiment, the temperature and the agitation were maintained at 60 C and 400 rpm, respectively. Table 5 shows the comparison between the properties of Jatropha biodiesel obtained and the biodiesel standards (ASTMD6751 and EN 1414). It was found that its properties met the ASTMD6751 and EN 1414 standards. Therefore, Jatropha biodiesel was an environmentally friendly, alternative diesel fuel from non-edible oil feedstock. Figure 3 The effect of reaction time (minutes) and catalyst concentration (% w/w) on predicted value of % FAME at methanol-to-oil molar ratio of 6. Figure 4 GC chromatogram of fatty acid methyl ester from Jatropha oil under optimum conditions for transesterification.

9 98 Kasetsart J. (Nat. Sci.) 44() Table 5 Fuel properties of Jatropha biodiesel. Parameter Unit Method Jatropha ASTM EN 1414 biodiesel D 6751 Density at 15 o C Kg/m 3 ASTM D Acid value mg KOH/g AOCS Ca5a <0.80 <0.50 Iodine value g iodine /100g AOCS Cdl <10 Linolenic methyl ester %wt EN <1 Flash point C ASTM D-93-0a >06 >130 >10 Cloud point C ASTM D Report - Viscosity at 40 C mm /s ASTM Free glyceride %wt EN <0.0 Monoglyceride %wt EN <0.80 Diglyceride %wt EN <0.0 Triglyceride %wt EN < <0.0 Total glyceride %wt EN <0.5 CONCLUSION A CCD technique was applied as the experimental design. There were 0 experiments involving the three investigated variables of methanol-to-oil molar ratio (X 1 ), sodium hydroxide (X ) and reaction time (X 3 ). The data was statistically analyzed by the Design-Expert program. The full quadratic model for the percentage of FAME content (Y) as a function of the above three variables was: Y = X X X X X X X 1 X X 1 X X X 3. From the model, the highest conversion yield of Jatropha biodiesel produced 99.87% of FAME content. In the validation process, the predicted value from the model was closely aligned to the experimental value. The resulting Jatropha biodiesel properties also satisfied both the ASTMD 6751 and EN 1414 biodiesel standards. In addition, the major costs in Jatropha biodiesel production were related mainly to raw material cost. The optimizied Jatropha biodiesel production using sodium hydroxide as a catalyst could be applied in a Jatropha biodiesel pilot plant. The comprehensive use of Jatropha biodiesel in industrial applications will benefit overall food supplies and will reduce energy problems. ACKNOWLEDGEMENTS This work was partly supported by the KU-biodiesel project, Kasetsart University, Bangkok. The authors would like to thank the Department of Chemical Engineering at Kasetsart University for the raw Jatropha oil extractions and Assoc. Prof. Dr. Sawitri Chuntranuluck, Assoc. Prof. Dr. Vittaya Punsuvon and Asst. Prof. Dr. Pinya Silayoi for assistance in setting up the experimental stage of the research. LITERATURE CITED Alacantara, R., J. Amores, L. Canoira, E. Hidalgo, M.J. Franco and A. Navarro Catalytic production of biodiesel from soybean oil, used frying oil and tallow. Biomass Bioenerg. 18: Bosswell, M.J Plant oils: Wealth, health, energy and environment. In Proc. International Conference of Renewable Energy Thechnology for Rural Development, Kathmandu, Nepal. Oct Canakci, M. and J.V. Gerpen Biodiesel production from oils and fats with high free

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