Optimization of Biodiesel Production from Jatropha Oil using Response Surface Methodology
Kasetsart J. (Nat. Sci.) 44 : 290 - 299 (2010) Optimization of Biodiesel Production from Jatropha Oil (Jatropha curcas L.) using Response Surface Methodology Kanthawut Boonmee1*, Sawitri Chuntranuluck1, Vittaya Punsuvon2 and Pinya Silayoi3 ABSTRACT The main purpose of this research was to develop a biodiesel production technique from Jatrophaoil (Jatropha curcas). Special attention was paid to the optimization of alkali-catalyzed transesterificationfor converting fatty acid methyl ester (FAME). Jatropha oil contained 2.59 mg KOH/g of acid and amolecular weight of 900 g/mol with high oleic acid (41.70%) and linoleic acid (36.98%). A centralcomposite design (CCD) technique was applied for the experimental design. There were 20 experimentsinvolving the three investigated variables of methanol-to-oil molar ratio (0.95-11.50), sodium hydroxide(0.16-1.84% w/w) and reaction time (39.55-140.45 min). The data was statistically analyzed by theDesign-Expert program to find the suitable model of % fatty acid methyl ester (% FAME) as a functionof the three investigated variables. A full quadratic model was suggested by the program using responsesurface methodology (RSM) with an R2 and adjusted R2 of 97 and 94%, respectively. The optimumconditions for transesterification were a methanol-to-oil molar ratio of 6.00, 1.00% w/w sodium hydroxideand 90 min reaction time. The optimum condition obtained a FAME content of 99.87%. The resultingJatropha biodiesel properties satisfied both the ASTMD 6751 and EN 14214 biodiesel standards. Theproduction 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 vegetable oils and animal fats, biodiesel feedstock may affect food supplies in the long-term. The Due to the availability of recoverable recent focus has been to seek a source of non-agricultural resources, the environmental problems edible oils, as a feedstock for biodiesel production.caused by fossil fuel consumption, as well as the Jatropha curcas L. (Jatropha) has been chosen asdramatic impact of oil imports on Thailand’s an optimal supply source.economy, biodiesel production is being considered Jatropha curcas L. is a non-edible oil-as an alternative to petrodiesel. Biodiesel is bearing plant widespread in arid, semi-arid andbelieved to be able to decrease the dependence on tropical regions of Thailand. Jatropha curcas L.and improve the adverse environmental impact of is a drought-resistant perennial tree that grows inusing oil. However, as it is produced from marginal lands and can live over 50 years1 Department of Biotechnology, Faculty of Agro-Industry, Kasetsart University, Bangkok 10900, Thailand.2 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.comReceived date : 06/08/09 Accepted date : 30/10/09
Kasetsart J. (Nat. Sci.) 44(2) 291(Bosswell, 2003). Jatropha curcas L. has several deposits and thickening of the lubricating oilbenefits, such as its stem can be used as a natural (Silvio et al., 2002). Transesterification is a processtoothpaste and toothbrush, latex from the stem can for the reduction of triglyceride molecules (Vanbe used as a natural pesticide and to heal wounds, Dyne et al., 1996; Muniyappa, et al., 1996). Thewhile its leaves are used as fodder for silkworms use of chemically altered or transesterified(Chhetri et al., 2008). vegetable oil, called biodiesel, does not require Compared to any other economic plants, any modification in the engine or its injectionJatropha curcas L. is very durable in hot climates, system or fuel lines and can be used in any dieselsuch as Thailand experiences, The oil content in engine. The stoichiometric equation requires oneJatropha curcas L. seed is reported to be in the mole of triglyceride and three moles of alcohol torange from 30 to 50% by weight of seed (Kandpal form three moles of methyl ester and one mole ofand Madan, 1995; Pramanik, 2003) and from 45 glycerol in the presence of a strong base or acidto 60% by weight of the kernel itself (Pramanik, (Muniyappa et al., 1996). Methanolysis is the2003). Therefore, Jatropha oil has a potential to process where methanol is used in biodieselbe used as a substitute fuel in biodiesel production. production (Gervasio, 1996; Ma and Hanna, 1999).In addition, Jatropha oil not only has a high level Response surface methodology (RSM)of fat and unsaturated fatty acids, but also low is a useful statistical technique, which has beenlevels of free fatty acids (Foidl et al., 1996). The applied in the research of complex variableoil can be used directly in agricultural diesel processes (Myers and Montgomery, 2002).engines, electric generators, tractors and water Multiple regression and correlation analysis arepumps without any additives and does not cause used as tools to assess the effects of two or moreany physical damage. For diesel engine use, independent factors on the dependent variables.Jatropha oil has to undergo a transesterification Furthermore, the central composite design (CCD)process. In Thailand, Jatropha oil has been placed of RSM has been applied in the optimization ofon the national agenda to encourage its production several biotechnological and chemical processes.in the rural community for transportation and Its main advantage is the reduction in the numberagriculture, as a substitute for bio-diesel fuel. of experimental runs required to generate sufficient A few attempts have been made to information for a statistically acceptable result.produce biodiesel from non-edible sources, such RSM has been applied successfully foras used frying oil, grease, tallow and lard optimization of biodiesel production in fat and oil(Alcantara et al., 2000; Canakci and Gerpen, 2001; feedstocks, including mahua oil (Madhuca indica)Dorado et al., 2002). The production of biodiesel (Ghadge and Raheman, 2006), Jatropha oil (Tiwariwould be inexpensive because it could be extracted et al., 2007), waste rapeseed oil (Yuan et al., 2008)from the non-edible oil sources and from certain and animal fat (Jeong et al., 2009).species that are common in many parts of Thailand. The current study concentrated onJatropha curcas L. has ecological advantages and developing a technique for biodiesel productionhas been found to be an appropriate, renewable, from Jatropha oil. RSM was applied to optimizealternative source of biodiesel production in the alkali-catalyzed transesterification to produceThailand. However, extracted Jatropha oil cannot fatty acid methyl ester (FAME) as a function ofbe used directly in diesel engines because of its three factors: the methanol-to-oil molar ratio,high viscosity. The high viscosity of pure vegetable sodium hydroxide and the reaction time. The fueloils reduces fuel atomization and increases fuel properties of Jatropha biodiesel for vehicle usespray penetration, which results in high engine were determined.
292 Kasetsart J. (Nat. Sci.) 44(2) MATERIALS AND METHODS 1.20 (% by weight of oil) NaOH (Alacantara et al., 2000). The acid value was defined asAlkali catalyzed transesterification milligrams of potassium hydroxide necessary to Crude Jatropha oil used in the neutralize fatty acids in 1 g of sample. If the acidexperiments was obtained from the Department value of the oil used was greater than 5 mg KOH/of Chemical Engineering at Kasetsart University. g, more NaOH would be required to neutralize theMethanol (from the J. T. Baker Chemical Co.) and free fatty acids (Wright et al., 1944). The reactionsodium hydroxide (from Merek Ltd.) were time was 90 min, after which the reactant wasanalytical reagent grade. Oil was partially purified transferred to a separation funnel (Foidl et al.,by filtration and boiling at 105-110°C for 0.5 h to 1996).remove the insoluble portion and water, A five-level-three-factor CCD wasrespectively. The experiments were conducted at employed in the optimization study, requiring 20the Department of Chemical Engineering, experiments. The methanol-to-oil molar ratio,Kasetsart University. catalyst concentration and reaction time were the In the production of Jatropha biodiesel independent variables selected to optimize theby the alkali-catalyzed transesterification conditions for FAME production of sodiumtechnique, methanol was chosen as a catalyst hydroxide-catalyzed transesterification. The 20because of its low cost. Sodium hydroxide was experiments were carried out and data waschosen, since it was reasonably priced and reacted statistically analyzed by the Design-Expertmuch faster than the acid catalyst (Freedman et program to find the suitable model for the % fattyal., 1984). The important factors affecting the acid methyl ester (% FAME) as a function of thetransesterification reaction were the excessive above three variables.amount of methanol and sodium hydroxide, and The coded and uncoded levels of thethe reaction time (Demirbas, 2003). In order to independent variables in this step are given inoptimize the amount of excess methanol required Table 1. Two replications were carried out for allfor the reaction, the experiments were conducted experimental design conditions. The central valueswith various methanol-to-oil molar ratios, because (zero level) chosen for the experimental designthe transesterification reaction required 3 moles were a methanol-to-oil molar ratio of 6:1, 1%of methanol to react with 1 mole of vegetable oil w/w catalyst concentration and 90 min reaction(Kavitha, 2003). Most researchers used 0.10 to time.Table 1 Independent variables and levels used in the central composite design for the alkali catalyzed transesterification process. Variable Symbol Levela (uncoded variable) -1.68 -1 0 +1 +1.68 (-α) (+α) Methanol-to-oil molar ratio M 0.95 3.00 6.00 9.00 11.50 Catalyst concentration C 0.16 0.50 1.00 1.50 1.84 (%w/w) Reaction time T 39.55 60.00 90.00 120.00 140.45 (minutes)Note:a Transformation of variable levels from coded variables of X , X and X in Equation 3 to uncoded variables are: M = 6.00+3.00X , 1 2 3 1 C = 1.00+0.50X2 and T = 90.00+30.00X3.
Kasetsart J. (Nat. Sci.) 44(2) 293 The following experimental procedure where :was adopted for the production of Jatropha C = the FAME content (% w/w)biodiesel. Some Jatropha oil was placed in a three- ΣA = the total peak area from thenecked round-bottomed flask. A water-cooled methyl estercondenser and a thermometer with cork were ASI = the peak area of methylconnected to both sides of the round-bottom flask. heptadecanoateThe required amount of NaOH and methanol were CSI = the concentration of used methylweighed and dissolved completely, using a heptadecanoate solution (mg/ml)magnetic stirrer. The Jatropha oil was warmed by VSI = the volume of used methylplacing the round-bottomed flask in a water bath heptadecanoate solution (ml)maintained at 60°C. The sodium methoxide m = the weight of sample (g)solution was added into the oil using fixedvigorous mixing (400 rpm). The mixture was Statistical analysispoured into the separating funnel overnight settling The experimental data was analyzed byby gravity into two layers, with the clear, golden the response surface regression procedure using aliquid-Jatropha biodiesel on the top and the light second-order polynomial (Equation 2):brown glycerol on the bottom. After 24 h, the k k k kglycerol was drained off. The raw Jatropha y = β 0 + ∑ β i X i + ∑ β ii X 2 i + ∑ ∑ β ij X i X j (2)biodiesel was collected and water-washed to bring i =1 i =1 ii> j jdown the pH of bio-diesel to 7 (the pH of water). where, y is the response variable; xi and xj are theThe percentage of FAME content in the resulting coded independent variables and βo, βi, βii and βijbiodiesel was measured by gas chromatography are the intercept, linear, quadratic and interaction(GC). constant coefficients respectively, and k is the number of factors studied and optimized in theQuantitative analysis of fatty acid methyl ester experiment.content The Design-Expert program was used in Chromatographic analysis was the regression analysis and analysis of varianceperformed on a Shimadzu GC-2010 gas (ANOVA). The Statistica software program waschromatograph equipped with a DB-WAX column used to generate surface plots, using the fitted(30 m × 0.32mm, 0.25µm) and flame ionization quadratic polynomial equation obtained from thedetector (FID). The operating conditions involved regression analysis, holding one of the independentinjector and detector temperatures at 260°C and a variables constant. Experiments were carried outsplit ratio at 1:25. Helium was used as the carrier to validate the equation, using combinations of thegas. Methyl heptadecanoate (Supelco Inc.) was independent variables, which were not part of theused as the internal standard of fatty acid methyl original experimental design, but within theester. The analysis was performed by dissolving experimental region (Ghadge and Raheman,0.05 g of the biodiesel sample in 1 ml of methyl 2006).heptadecanoate and injecting 1 µl of this solutionmixture into the gas chromatograph. The Analysis of Jatropha biodiesel propertiespercentage of FAME was calculated by the The analysis of Jatropha biodieselEquation 1: qualities considered the density at 15°C, acid value, iodine value, linolenic methyl ester, flashC = (Σ A-ASI)/ASI × (CSI×VSI)/m×100 (1) point, cloud point, viscosity at 40°C, free
294 Kasetsart J. (Nat. Sci.) 44(2)glyceride, monoglyceride, diglycerides, Alkali catalyzed transesterificationtriglycerides and total glyceride. The analysis was The central composite design conditionscarried out using the methods developed by the and responses, and the statistical analysis of theCenter of Excellence on Palm Oil, Kasetsart ANOVA are given in Tables 2 and 3, respectively.University and compared with the ASTMD6751 The multiple regression coefficients were obtainedand EN 14214 biodiesel standards. by employing a least square technique to predict a quadratic polynomial model for the FAME content RESULTS AND DISCUSSION (Table 4). The model was tested for adequacy by analysis of variance. The regression model wasProperties of Jatropha oil found to be highly significant with the correlation The fatty acid composition of Jatropha coefficients of determination of R-Squared (R2),oil was 41.70% w/w oleic acid and 36.98% w/w adjusted R-Squared and predicted R-Squaredlinoleic acid with an acid value of 2.59 mg KOH/ having a value of 0.97, 0.94 and 0.75, respectively.g, which was an acceptable result for the The predicted model for percentage of FAMEtransesterification process (lower than 5.00 mg content (Y) in terms of the coded factors is shownKOH/g), according to Gerpen (2005). The average in Equation 3:molecular weight was 900 g/mole.Table 2 Central composite design arrangement and response for alkali catalyzed transesterification. Treatment X1 X2 X3 Methanol NaOH Reaction /oil molar concentration time Fatty acid methyl ester ratio (%w/w) (minutes) (%) (M) (C) (T) Experimental Predicted 1 -1 -1 -1 3.00 0.50 60.00 57.08 60.79 2 -1 -1 +1 3.00 0.50 120.00 89.98 90.63 3 -1 +1 -1 3.00 1.50 60.00 57.43 52.90 4 -1 +1 +1 3.00 1.50 120.00 90.14 91.42 5 +1 -1 -1 9.00 0.50 60.00 94.31 92.73 6 +1 -1 +1 9.00 0.50 120.00 78.13 82.36 7 +1 +1 -1 9.00 1.50 60.00 93.71 92.76 8 +1 +1 +1 9.00 1.50 120.00 95.08 91.07 9 0 0 -1.68 6.00 1.00 39.55 71.60 73.45 10 0 0 +1.68 6.00 1.00 140.45 98.55 97.13 11 0 -1.68 0 6.00 0.16 90.00 89.17 84.86 12 0 +1.68 0 6.00 1.84 90.00 80.83 85.56 13 -1.68 0 0 0.95 1.00 90.00 65.61 64.81 14 +1.68 0 0 11.05 1.00 90.00 90.14 91.37 15 0 0 0 6.00 1.00 90.00 100.00 99.87 16 0 0 0 6.00 1.00 90.00 99.42 99.87 17 0 0 0 6.00 1.00 90.00 100.00 99.87 18 0 0 0 6.00 1.00 90.00 99.89 99.87 19 0 0 0 6.00 1.00 90.00 100.00 99.87 20 0 0 0 6.00 1.00 90.00 100.00 99.87
Kasetsart J. (Nat. Sci.) 44(2) 295Y = + 99.87 + 7.90 X1 + 0.21 X2 + 7.04 X3 At the same time, there was a significant mutual - 7.70 X12 - 5.18 X22 - 5.16 X32 + 1.98 X1X2 interaction between the methanol to oil molar ratio - 10.05 X1X3 + 2.17 X2X3 (3) and the catalyst concentration (X1X2) and the The RSM was used to optimize the interaction between catalyst concentration andconditions of conversion for Jatropha biodiesel and reaction time (X2X3). These results were similarto understand the interaction of the factors to Jeong et al. (2009), who studied RSM and theaffecting Jatropha biodiesel production. Figures effect of five-level-three-factors in optimizing the1, 2 and 3 show surface plots between the reaction conditions of biodiesel production fromindependent and dependent variables for different animal fat.fixed parameters. From Figure 1, the % FAME A statistical model (Equation 3) predictedamount increased with increasing catalyst that the highest conversion yield of Jatrophaconcentration at a low methanol-to-oil molar ratio. biodiesel was 99.87% FAME content, when theFrom Figure 2, the % FAME amount increased optimized reaction conditions were a catalystwith the increasing methanol-to-oil molar ratio for concentration of 1.00% w/w, a methanol-to-oila low reaction time. From Figure 3, the % FAME molar ratio of 6.00 and a reaction time of 90 min.amount increased with increasing reaction time at Additional experiments were carried out toa high catalyst concentration. The methanol-to-oil validate the equation using these optimal values.molar ratio (X1) was the limiting condition and a It was found that the experimental value of 99.88% ofsmall variation in its value altered the conversion. 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 3779.179 9 419.909 34.253 .000aResidual 122.589 10 12.259Total 3901.768 19a Predictors: (Constant), X1, X2, X3, X1X2, X1X3, X2X3, X12, X22, X32.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) 99.871 1.428 69.943 0.000 X1 7.901 0.948 0.467 8.336 0.000 X2 0.209 0.948 0.012 0.220 0.830 X3 7.041 0.948 0.416 7.429 0.000 X1 2 -7.710 0.924 -0.472 -8.346 0.000 X22 -5.186 0.924 -0.317 -5.613 0.000 X3 2 -5.159 0.924 -0.316 -5.585 0.000 X1X2 1.980 1.238 0.090 1.599 0.141 X1X3 -10.052 1.238 -0.455 -8.121 0.000 X2X3 2.170 1.238 0.098 1.753 0.110
296 Kasetsart J. (Nat. Sci.) 44(2)Analysis of Jatropha biodiesel methyl esters (Yuan et al., 2008) with oleic acid The chromatogram of Jatropha oil as the predominant fatty acid.methyl ester is shown in Figure 4. The major The quality of the Jatropha biodiesel wasFAME components were palmitic acid (C16:0), designed to obtain a high percentage FAME. Theoleic acid (C18:1) and linoleic acid (C18:2), which Jatropha biodiesel process consisted of a filtrationare required for the biodiesel standard. The GC process, reaction process (alkali-catalyzedanalysis of the FAME from Jatropha oil (Figure transesterification process), separation process,4) showed that FAME mainly contained fatty acid washing process, recovery process andFigure 1 The effect of catalyst concentration (% w/w) and methanol-to-oil molar ratio on predicted value of % FAME at 90 min.Figure 2 The effect of reaction time (minutes) and methanol-to-oil molar ratio on predicted value of % FAME at 1% w/w catalyst concentration.
Kasetsart J. (Nat. Sci.) 44(2) 297dehydration process. In the experiment, the 14214). It was found that its properties met thetemperature and the agitation were maintained at ASTMD6751 and EN 14214 standards. Therefore,60°C and 400 rpm, respectively. Jatropha biodiesel was an environmentally Table 5 shows the comparison between friendly, alternative diesel fuel from non-edible oilthe properties of Jatropha biodiesel obtained and feedstock.the biodiesel standards (ASTMD6751 and ENFigure 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.
298 Kasetsart J. (Nat. Sci.) 44(2)Table 5 Fuel properties of Jatropha biodiesel. Parameter Unit Method Jatropha ASTM EN 14214 biodiesel D 6751 Density at 15oC Kg/m3 ASTM D 1298 880.53 - 860-900 Acid value mg KOH/g AOCS Ca5a-40 0.27 <0.80 <0.50 Iodine value g iodine /100g AOCS Cdl-25 98.41 - <120 Linolenic methyl ester %wt EN 14103 0.17 - <12 Flash point °C ASTM D-93-02a >206 >130 >120 Cloud point °C ASTM D 2500 4.90 Report - Viscosity at 40°C mm2/s ASTM 445 4.36 1.90-6.00 3.50-5.00 Free glyceride %wt EN 14105 0.01 ≤0.02 <0.02 Monoglyceride %wt EN 14105 0.47 - <0.80 Diglyceride %wt EN 14105 0.09 - <0.20 Triglyceride %wt EN 14105 <0.01 - <0.20 Total glyceride %wt EN 14105 0.14 ≤0.24 <0.25 CONCLUSION ACKNOWLEDGEMENTS A CCD technique was applied as the This work was partly supported by theexperimental design. There were 20 experiments KU-biodiesel project, Kasetsart University,involving the three investigated variables of Bangkok. The authors would like to thank themethanol-to-oil molar ratio (X 1 ), sodium Department of Chemical Engineering at Kasetsarthydroxide (X2) and reaction time (X3). The data University for the raw Jatropha oil extractions andwas statistically analyzed by the Design-Expert Assoc. Prof. Dr. Sawitri Chuntranuluck, Assoc.program. The full quadratic model for the Prof. Dr. Vittaya Punsuvon and Asst. Prof. Dr.percentage of FAME content (Y) as a function of Pinya Silayoi for assistance in setting up thethe above three variables was: Y = + 99.87 + 7.90 experimental stage of the research.X1 + 0.21 X2 + 7.04 X3 - 7.70 X12 - 5.18 X22- 5.16 X32 + 1.98 X1X2 - 10.05 X1X3 + 2.17 X2X3. LITERATURE CITEDFrom the model, the highest conversion yield ofJatropha biodiesel produced 99.87% of FAME Alacantara, R., J. Amores, L. Canoira, E. Hidalgo,content. In the validation process, the predicted M.J. Franco and A. Navarro. 2000. Catalyticvalue from the model was closely aligned to the production of biodiesel from soybean oil, usedexperimental value. The resulting Jatropha frying oil and tallow. Biomass Bioenerg. 18:biodiesel properties also satisfied both the ASTMD 515-527.6751 and EN 14214 biodiesel standards. Inaddition, the major costs in Jatropha biodiesel Bosswell, M.J. 2003. Plant oils: Wealth, health,production were related mainly to raw material energy and environment. In Proc.cost. The optimizied Jatropha biodiesel production International Conference of Renewableusing sodium hydroxide as a catalyst could be Energy Thechnology for Ruralapplied in a Jatropha biodiesel pilot plant. The Development, Kathmandu, Nepal. Oct 12-14.comprehensive use of Jatropha biodiesel in 2003.industrial applications will benefit overall food Canakci, M. and J.V. Gerpen. 2001. Biodieselsupplies and will reduce energy problems. production from oils and fats with high free
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