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Production of biodiesel from waste cooking oil using a homogeneous catalyst: Study of semi-industrial pilot of microreactor
Renewable Energy 136 (2019) 677e682
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Renewable Energy journal homepage: www.elsevier.com/locate/renene
Production of biodiesel from waste cooking oil using a homogeneous catalyst: Study of semi-industrial pilot of microreactor Majid Mohadesi, Babak Aghel*, Mahmoud Maleki, Ahmadreza Ansari Chemical Engineering Department, Faculty of Energy, Kermanshah University of Technology, Kermanshah, Iran
a r t i c l e i n f o
a b s t r a c t
Article history: Received 17 May 2018 Received in revised form 13 December 2018 Accepted 12 January 2019 Available online 16 January 2019
This study investigated the transesterification of waste cooking oil (WCO) with methanol in the presence of potassium hydroxide as the catalyst. A semi-industrial pilot of microreactor with 50 tubes with a diameter of 0.8 mm was used to produce 5 L/h biodiesel. Initially, the acidity of waste cooking oil was reduced to less than 1 mg KOH/g oil by using methanol at 60 C in the presence of 1% sulfuric acid. Using Box-Behnken design method, the effects of methanol to oil molar ratio (6:1e12:1), catalyst weight (0.5 e1.5 wt %), and reaction temperature (55e65 C) were studied. The methanol to oil molar ratio of 9.4:1, the catalyst concentration of 1.16 wt %, and the reaction temperature of 62.4 C was achieved under optimum condition. Finally, the effect of reaction time (30e120 s) was examined at the optimum condition. The highest level of biodiesel purity or fatty acid methyl esters % (FAMEs %) was 98.26%. In addition, the properties of produced biodiesel were determined and compared with those of the standard ASTM D6751. © 2019 Elsevier Ltd. All rights reserved.
Keywords: Biodiesel Waste cooking oil Optimization Semi-industrial pilot Microreactor
1. Introduction The increase in oil consumption, the variation in the global price of petroleum, the reduction of fossil fuel resources, and the intensification of environmental pollution have gradually increased the demand for renewable energy resources [1e5]. Renewable biofuels are considered as the fourth source of energy in the world [6] and they are usually used to produce electricity or heat [7,8]. As estimated, by 2030, biofuels will account for 4e7% of the total energy consumption in the world [9]. Moreover, biodiesel or fatty acid methyl ester (FAME) and alkyl esters of long chain fatty acids, as a basic product of the transesterification of renewable sources, is an attractive renewable fuel which can be produced through the trans-oxidation of triglycerides with an alcohol [10e12]. The main feedstock used for biodiesel production are animal fats, edible or non-edible vegetable oil, waste cooking oil, etc. The cost of feed and the shortage of raw vegetable oil are always critical to biodiesel production; for instance, the cost of vegetable oil can account for up to 75% of the total cost of production [13e16]. Hence, the use of waste cooking oils instead of raw oils can significantly
* Corresponding author. Chemical Engineering Department, Kermanshah University of Technology, Imam Khomeini Highway, Kermanshah, Iran. E-mail addresses: [email protected], [email protected] (B. Aghel). https://doi.org/10.1016/j.renene.2019.01.039 0960-1481/© 2019 Elsevier Ltd. All rights reserved.
reduce the costs of biodiesel production; this method, which is an effective method to decrease the cost of raw materials, can help to reduce the costs of biodiesel production by 60e70% [17e19]. Both homogeneous and heterogeneous catalysts are frequently used to produce biodiesel through transesterification reaction [20e22]. On the other hand, a large number of researchers investigated the production of biodiesel with homogeneous catalysts because they have a higher level of efficiency, a shorter reaction time, and an easier separation process, as compared with heterogeneous catalysts [23,24]. The most popular type of catalysts used as homogeneous catalysts are potassium hydroxide and sodium hydroxide [25e27]. Generally, researches produce biodiesel from waste cooking oils and animal fat via different types of catalyst in laboratory scales; however, a few number of studies have used waste cooking oils especially with high FFAs in a pilot plant scale [28,29]. a nek et al. [30] studied the biodiesel production at the pilotS plant level from waste frying oils and animal fats using tetramethylammonium hydroxide. According to their experimental results the conversion in all cases exceeded 98% achieved with 1:6 M ratio of feedstock to methanol, 1.5% w/w of the catalyst, the reaction time of 2 h and the temperature of 65 C. On the other hand, to improve the efficiency of biodiesel production, due to environmental and economic benefits microscale technologies has been considered. For instance, several researchers have put emphasis on the benefits of microreactor and its capacity
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to increase the production rate and overcome the limitations on mass transfer in transesterification process [31e33]. Santana et al. used numerical simulations to investigate the role of microchannels with circular obstructions, as a novel device, in increasing the interaction between the phases and enhancing mass transfer in biodiesel synthesis [34]. According to their experimental results, the use of obstructions had a strong impact on mixing and conversion efficiency. Recently, the effect of two co-solvents (nhexane/tetrahydrofuran) on heterogeneous transesterification reaction in a microreactor were investigated by Aghel et al. [35]. Under the optimal conditions, they achieved the biodiesel purity equal to 97.03% and 95.21% when using n-hexane and THF cosolvent, respectively [35]. Since the performance of transesterification process in the pilot plant depends strongly on the contact between streams. Therefore, in this work, we applied the semi-industrial pilot of microreactor to synthesis of biodiesel from waste cooking oil with methanol and potassium hydroxide, as the catalyst. The effects of process parameters such as temperature, KOH concentration, and methanol to oil molar ratio on the purity of biodiesel were experimentally investigated by BoxeBehnken method. After the optimization of biodiesel purity by response surface methodology (RSM), using the least squares error method the purity equation was achieved which had a good agreement with pilot results. 2. Materials and methods 2.1. Materials The waste cooking oil was purchased from Kermanshah restaurants and potassium hydroxide (KOH) was used as the catalyst. The physical properties and composition of waste cooking oil used in this study are similar to Aghel et al. study [35]. In addition, the acidity number, density, and kinematic viscosity of the oil were measured through ASTM D664, D941, and D445 methods, respectively. Methanol 99.7%, sulfuric acid 97%, and potassium hydroxide 98% were purchased from Merck Company, and methyl laurate (methyl dodecanoate) > 99.7% were purchased from Sigma (St. Louis, MO). All the chemicals such as water were of analytical grade. 2.2. Preparation of waste cooking oil At first, the waste cooking oil was filtered to eliminate waste substances, and then heated at 60 C for about 30 min and then water particles were settled by separation funnel. The waste cooking oil was prepared using 1% sulfuric acid and methanol before undergoing transesterification reaction. To decrease the acidity number from 3.12 mg KOH/g oil to less than 1 mg KOH/g oil (approximately 0.7 mg KOH/g oil), the methanol and waste cooking oil were reacted with a molar ratio of 6:1 at a temperature of 60 C using Tanawanpong et al.’s method [36]. 2.3. Transesterification in microreactor The transesterification reaction was performed in a semiindustrial pilot of microreactor. The schematic diagram and real image of the microreactor system are shown in Fig. 1. The pilot had a micromixer and 50 microtubes with an internal diameter of 0.8 mm and a length of 530 cm which formed a continuous reactor with a volume of 200 ml. All the microtubes were fixed and heated in an insulated cylindrical water bath with a diameter of 12.5 cm and a length of 500 cm. Through the experimental test, methanol solution (methanol þ KOH catalyst) and WCO from different reservoirs were fed into the T-shaped micromixer and mixed completely. Then, they
Fig. 1. Schematic diagram and view of the biodiesel production microreactor semiindustrial plant.
entered the microtubes to proceed the transesterification reaction. The methanol solution was prepared through mixing methanol and potassium hydroxide (0.5e1.5 wt % in proportion to the oil). The output stream exited the microreactor after a given residence time; a sample was taken from the outlet side quenched quickly by icy water and neutralized by sulfuric acid. In addition, the mixture of produced FAME, glycerol, and the residue were separated from each other via centrifugation (Hettich Universal 320R Centrifuge UK). The main product was collected from the upper layer and the materials in the lower layer was drained as a byproduct and the excess feedstock. Finally, to eliminate excess materials and ensure the accuracy of the results, the main product which contained methyl ester was washed three times with hot distilled water and subsequently heated up to 110 C in an oven (Binder Drying and heating chambers Classic. Line, Series FD) to remove the moisture from FAME. In each experimental run, the WCO and the methoxide (KOH þ methanol solution) were fed into the pilot to maintain the prescribed ratios and catalyst concentration (Table 1). It should be noted that, to provide the required level of heating for the reaction, the temperature of the cylindrical water bath was adjusted before Table 1 Experimental range and levels of variable. Factors
Unit
Reaction temperature Catalyst concentration (based oil) Methanol to oil molar ratio
C
wt. % mol:mol
Symbol
T C MR
Range and levels Low
Middle
High
55 0.5 6:1
60 1.0 9:1
65 1.5 12:1
M. Mohadesi et al. / Renewable Energy 136 (2019) 677e682
feeding the two streams into the microtubes.
Table 2 Experimental design of the three independent variables and the results.
2.4. Analyses
Run No.
Afterward, about 1 g of FAME phase and 5 mg of internal standard solution were mixed and then 1 mL of the prepared mixture was injected into the HP 6890 gas chromatograph (GC) with a flame ionization detector (FID). The capillary column was a BPX-70 high polar column with a length of 120 m, a film thickness of 0.25 mm and an internal diameter of 0.25 mm. Nitrogen was used as the carrier gas and also as an auxiliary gas for FID. One mL of the sample was injected using a 6890 Agilent Series Injector. The inlet temperature of sample into injector was 50 C, which was heated up to 230 C. Methyl laurate (C12:0) was added as a reference into the crude biodiesel and the samples were analyzed by GC that was mentioned above. The following equation suggested by Wang et al. [37] was used to determine the weight percentage of FAME or biodiesel purity:
FAME % ¼
area of all FAME weight of reference 100 area of reference weight of biodiesel sample (1)
2.5. Experimental design The production of biodiesel depends on various parameters, and it can be said that among all the factors the most important are residence time and production costs. Therefore, to reduce these two factors, it was necessary to design experiments and determine the optimum condition. Many researchers have investigated the effects of different parameters on biodiesel production using response surface methodology to analyze regression and determine the relationships between the measured responses and the vital input factors [38e40]. In this study, a 3-level 3-factor Box-Behnken experimental design was applied to evaluate the interaction between the variables and find the optimal condition for maximizing biodiesel purity in the pilot plant. The effects of the main operation variables on the purity of biodiesel including methanol to oil molar ratio (MR), catalyst concentration (C), and temperature (T) were investigated. The variables and their levels (low, middle, and high) were selected based on the previous experimental studies on the transesterification process [4,31]. Three independent variables for the transesterification reaction were methanol to oil molar ratio (6:1e12:1), KOH concentration (0.5e1.5 wt %), and temperature (55e65 C). Table 1 shows the ranges of the independent variables used for the Box-Behnken experimental design and Table 2 presents the experimental runs performed and FAME % obtained from each run. In addition, response surface methodology was used to examine the influence of the three independent variables on the percentage of methyl ester as a response variable. Analysis of variance (ANOVA) is an appropriate and reliable method for analyzing and determining the degree of test results [41]. The quadratic regression model was used to analyze the relationship between the independent variable and the predicted response variable (FAME %) which a mathematical model shown in Equation (2).
Y ¼ b0 þ
3 X i¼1
bi Xi þ
3 X i¼1
bii X 2i þ
2 3 X X i¼1 j¼iþ1
bij Xij
679
(2)
Manipulated variables
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Response
T , C
C, wt. %
MR, mol:mol
P, %
65 55 65 60 60 60 65 60 55 65 60 55 55 60 60
0.5 1.0 1.0 1.0 1.0 0.5 1.0 0.5 1.0 1.5 1.5 1.5 0.5 1.5 1.0
9:1 6:1 12:1 9:1 9:1 12:1 6:1 6:1 12:1 9:1 12:1 9:1 9:1 6:1 9:1
82.26 75.23 85.53 95.24 97.12 80.03 82.84 70.48 73.64 93.61 86.25 79.21 76.69 77.42 96.33
where Y is the response, Xi and Xij are the independent variables, b0 is the offset term, and bi , bii , bij are the regression coefficients. The quality of the mathematical experimental model was checked by using the coefficients of determination (R2 ). In ANOVA, the level of significance or P-value was set at 0.05. ANOVA was used to determine the significance of the second-order models. The statistical significance of the second-order models was determined by F value. Whenever the calculated F value is higher than the given F value, the P value will be much smaller; this fact indicates the significance of the statistical model. Calculated F value is defined as the mean-square regression (including linear, square, and interaction) and the mean-square residual [41].
F value ¼
MSregression MSresidual
(3)
where:
MSregression ¼
MSresidual ¼
SSregression DFregression
SSresidual DFresidual
(4)
(5)
Regression degree of freedom (DFregression ) is the number of sentences minus one, and the residual degrees of freedom (DFresidual ) is the total degree of freedom minus regression degree of freedom [41].
3. Results and discussion 3.1. Effect of reaction temperature Due to the consumption of energy in the transesterification process, the reaction temperature is an important parameter. This parameter was set at three levels in a range of 55e65 C with a step of 5 C. As shown in Figs. 2 and 3, with increasing the temperature from 55 C to about 62 C, the purity of biodiesel significantly increased within 60 s. However, further increase in the temperature did not have a significant effect on the purity of biodiesel; increasing the temperature beyond the optimum point only lead to the waste of energy. The optimum temperature was 62.4 C, and when reaching this temperature, the highest FAME % was achieved (Figs. 2 and 3).
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M. Mohadesi et al. / Renewable Energy 136 (2019) 677e682
purity of biodiesel was gradually reduced. As shown in this figures, optimum weight percentage of the catalyst was obtained at 1.16 wt % for producing biodiesel within 60 s. 3.3. Effect of methanol to oil molar ratio
Fig. 2. Three-dimension plots of FAME % based on the temperature and catalyst concentration in semi-industrial pilot (t ¼ 60s).
One of the most important parameters affecting the production of biodiesel is the methanol to oil molar ratio. As shown in Figs. 3 and 4, the effect of the methanol to oil molar ratio on the purity of biodiesel, within a residence time of 60 s, was investigated at three levels, including low level (6:1), middle level (9:1), and high level (12:1). When using the low level, the purity of biodiesel was the minimum level, however, with increasing the methanol to oil molar ratio, the purity increased. However, with increasing the molar ratio beyond the middle level, there was a reduction in the purity percentage. In optimal conditions, the methanol to oil molar ratio was 9.4:1. 3.4. Response analysis of variance Using the least squares error method, a second-order (quadratic) model was achieved to determine the biodiesel purity percentage expressed by Equation (6) as follows:
FAME% ¼ 912:271 þ 29:516T þ 11:067C þ 17:969MR þ 0:883T:C þ 0:071T:MR 0:120C:MR 0:250T 2 28:105C 2 1:184MR2 (6)
Fig. 3. Three-dimension plots of FAME % based on the temperature and methanol to oil molar ratio in semi-industrial pilot (t ¼ 60s).
3.2. Effect of catalyst concentration
biodiesel purity (FAME %) model, R2 and R2adj: were 0.963 and 0.896, respectively.
100 95 Predicted FAME, %
In this study, potassium hydroxide was used as the catalyst and it was used at three levels of 0.5, 1.0, and 1.5 wt %. The effect of the weight percentage of the catalyst on the purity of the produced biodiesel (FAME %) is presented in Figs. 2 and 4. As shown in these figures, with increasing the weight percentage of the catalyst to the middle level (about 1.1 wt %), the percentage of the purity of the produced biodiesel increased remarkably. With a further increase in catalyst concentration, the
where T, C and MR are the reaction temperature, catalysts concentration (oil based), and methanol to oil molar ratio, respectively. Based on the obtained model and using 3-D plots, further relationship between the variables and FAME % were investigated and the results are shown in Figs. 2e4. Fig. 5 shows the values predicted by the second-order model (Equation (6)) as compared with the observed values of FAME %. In
90 85 80 75 70
Fig. 4. Three-dimension plots of FAME % based on the catalyst concentration and methanol to oil molar ratio in semi-industrial pilot (t ¼ 60s).
70
75
80 85 90 Experimental FAME, %
95
Fig. 5. Comparing the experimental and predicted values of FAME %.
100
M. Mohadesi et al. / Renewable Energy 136 (2019) 677e682
3.5. The effect of residence time Under optimum conditions obtained from Equation (6) (T ¼ 62:4 C, C ¼ 1:126 wt:%, and MR ¼ 9:4 : 1), experiments were performed again in five different residence times (t). The residence times were: 30, 45, 60, 90, and 120 s. The results of the tests are shown Fig. 6. The test was repeated three times for each sample, and the results were averaged. According to this figure, as expected, with increasing the residence time, FAME % was increased sharply and then the percentage of purity was increased slightly. Therefore, at a residence time of less than 60 s the purity of the produced biodiesel was low and it can be concluded that the residence time was very inadequate. The purity of the produced biodiesel during residence time of 60 s is 97.2%, while by increasing the time to 120 s, the purity increased into 98.26%.
3.6. Physical properties of biodiesel The physical properties of the produced biodiesel were also examined and the values are presented in Table 4. As shown in this table, the properties of the produced biodiesels compared by ASTM D6751 show that they are in the standard range.
120 100 FAME, %
Table 3 presents the results of ANOVA test which was carried out to assess the biodiesel purity models. Total degree of freedom in each model was 14. As presented in Table 3, degrees of freedom for regression and residual error were 9 and 5, respectively. Table 3 compares calculated F-values with tabulated F-values; as shown, the F-value calculated for the model is larger and is statistically more significant. Using the model, T, C, T 2 , C 2 , and MR2 were identified as significant regression terms. P-values larger than 0.05 indicate that the regression terms are not significant, though the main factor must remain in the models. The empirical model (Equation (6)) used for FAME % are plotted in 3-D diagrams (Figs. 2e4). Each 3-D diagram of FAME % is plotted via changing two variables. The other variable are set at the middle level. The optimum condition were obtained by derivation of Equation (6) for the three variables (T, C, and MR). In the optimal condition i.e. T ¼ 62:4 C, C ¼ 1:126 wt:%, and MR ¼ 9:4 : 1. FAME % was maximized. Using Equation (6), FAME % in optimal condition was 99.65%. Based on the results of experimental test (repeated three times) in optimal condition (temperature of 62.4 C, catalyst concentration of 1.16 wt %, and methanol to oil molar ratio or 9.4:1), FAME % was 97.21%.
681
80 60 40 20 0
0
30
45
60
90
120
Fig. 6. Effect of residence time on FAME % in optimal condition (T ¼ 62:4 C, C ¼ 1:126 wt:%, and MR ¼ 9:4 : 1).
Table 4 Properties of produced biodiesels compared by ASTM D6751. Property
Unit
Biodiesel
ASTM D6751
Density at 15 C Kinematic viscosity at 40 C Pour point Cloud point Water content Total glycerin
g/cm3 cSt C C % %
0.880 4.6 5 6 0.03 0.13
0.86 to 0.90 4 to 6 15 to 10 3 to 12 0.05 0.24
3.7. Comparing biodiesel production in batch reactor and microreactor In order to show the overall advantage of microreactor a we conducted a comparative study between the results of current study and the results obtained from conventional batch systems (Table 5). Although rectors cannot be compared directly but the order of magnitude of criterion can help readers a qualitative judgment.
Table 5 Review of different kinds of semi-pilot in the literature. Authors
MR, mol:mol
TC
C, wt. %
t r , min
FAME, %
a nek et al. [30] S Sahu et al. [42] Bouaid et al. [43] Alptekin et al. [44] Present work
6:1 6:1 6:1 6:1 9.4:1
65 65 30 60 62.4
1.5 1.0 1.5 1.0 1.16
120 180 30 120 2
98.0 91.2 99.24 91.0 98.3
Table 3 Analysis of variance (ANOVA) for the second-order FAME % model. Sources
SS
DF
MS
F-value
p-value
Degree of significance
Regression T C MR T:C T:MR C:MR T2
1031.51 194.74 91.33 47.43 19.49 4.58 0.13 144.75
9 1 1 1 1 1 1 1
112.61 194.74 91.33 47.43 19.49 4.58 0.13 144.75
14.36 24.84 11.65 6.05 2.49 0.58 0.017 18.46
0.0045 0.0042 0.0190 0.0572 0.1757 0.4792 0.9027 0.0077
significant significant significant not significant not significant not significant not significant significant
C2
182.28
1
182.28
23.25
0.0048
significant
MR2 Residual error Lack e of e fit Pure error Total
419.48
1
419.48
53.51
0.0070
significant
39.20 37.42 1.78 1052.70
5 3 2 14
7.84 12347 0.89
14.00
0.0674
not significant
682
M. Mohadesi et al. / Renewable Energy 136 (2019) 677e682
Comparing the two methods in terms of the residence time and FAME % showed the preference of using this system over conventional pilot scale reactor. Increasing the biodiesel production in this case due to special mixing conditions, not only results in a reduction in the residence time and saves the energy but also increases FAME %.
[18]
[19]
4. Conclusion
[20]
A semi-industrial pilot of microreactor with 50 tubes of 0.8 mm diameter, 5 L/h, was used to investigate the production of biodiesel from waste cooking oil as a low cost feedstock and with potassium hydroxide (KOH) as the catalyst. FAME was produced through the transesterification of waste cooking oil in a pilot scale and was analyzed by GC. The weight percentage of FAME % or biodiesel purity was also calculated. According to the results of laboratory tests, the highest levels of biodiesel purity obtained by using the model and through performing the experiment during 1 min were 99.65% and 97.21%, respectively. In addition, the optimization of the biodiesel purity showed that, the most suitable methanol to waste oil molar ratio was 9.4:1, the best catalyst concentration was 1.16 wt %, and the optimum reaction temperature was 62.4 C. In optimal conditions, experiments were performed within different reaction times, and the highest biodiesel content was 98.26% which was obtained at a residence time of 120 s. Finally, to show the overall advantage of the microreactor over batch reactors, the residence time and purity of the two methods were compared and the experimental results proved the superiority of microreactor.
[21]
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Eng. 95 (7) (2017) 1280e1287. F. Mohammadi, M. Rahimi, A. Parvareh, M. Feyzi, Stimulation of magnetic nanoparticles to intensify transesterification of soybean oil in micromixers for biodiesel production, Chem. Eng. Process Process Intensif. 122 (2017) 109e121. N. Chueluecha, A. Kaewchada, A. Jaree, Enhancement of biodiesel synthesis using co-solvent in a packed-microchannel, J. Ind. Eng. Chem. 51 (2017) 162e171. H.S. Santana, J.L.S. Júnior, O.P. Taranto, Numerical simulations of biodiesel synthesis in microchannels with circular obstructions, Chem. Eng. Process: Process Intensif. 98 (2015) 137e146. B. Aghel, M. Mohadesi, S. Sahraei, Effect of different cosolvents on transesterification of waste cooking oil in a microreactor, Chem. Eng. Technol. 41 (3) (2018) 598e605. Y. Tanawannapong, A. Kaewchada, A. Jaree, Biodiesel production from waste cooking oil in a microtube reactor, J. Ind. Eng. Chem. 19 (1) (2013) 37e41. Y. Wang, S. Ou, P. Liu, F. Xue, S. Tang, Comparison of two different processes to synthesize biodiesel by waste cooking oil, J. Mol. Catal. Chem. 252 (1e2) (2006) 107e112. B.R. Vahid, N. Saghatoleslami, H. Nayebzadeh, J. Toghiani, Effect of alumina loading on the properties and activity of SO2 4 /ZrO2 for biodiesel production: process optimization via response surface methodology, J. Taiwan Inst. Chem. Eng. 83 (2018) 115e123. M. Mostafaei, H. Javadikia, L. Naderloo, Modeling the effects of ultrasound power and reactor dimension on the biodiesel production yield: comparison of prediction abilities between response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS), Energy 115 (2016) 626e636. S. Saeidi, P. Jouybanpour, A. Mirvakilli, D. Iranshahi, J.J. Klemes, A comparative study between Modified Data Envelopment Analysis and Response Surface Methodology for optimisation of heterogeneous biodiesel production from waste cooking palm oil, J. Clean. Prod. 136 (2016) 23e30. D.C. Montgomery, Design and Analysis of Experiments, John Wiley, New York, 2001. G. Sahu, L.M. Das, B.K. Sharma, S.N. Naik, Pilot plant study on biodiesel production from Karanja and Jatropha oils, Asia Pac. J. Chem. Eng. 6 (2011) 38e43. A. Bouaid, R. V azquez, M. Martinez, J. Aracil, Effect of free fatty acids contents on biodiesel quality. Pilot plant studies, Fuel 174 (2016) 54e62. E. Alptekin, M. Canakci, H. Sanli, Biodiesel production from vegetable oil and waste animal fats in a pilot plant, Waste Manag. 34 (11) (2014) 2146e2154.
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Renewable Energy journal homepage: www.elsevier.com/locate/renene
Production of biodiesel from waste cooking oil using a homogeneous catalyst: Study of semi-industrial pilot of microreactor Majid Mohadesi, Babak Aghel*, Mahmoud Maleki, Ahmadreza Ansari Chemical Engineering Department, Faculty of Energy, Kermanshah University of Technology, Kermanshah, Iran
a r t i c l e i n f o
a b s t r a c t
Article history: Received 17 May 2018 Received in revised form 13 December 2018 Accepted 12 January 2019 Available online 16 January 2019
This study investigated the transesterification of waste cooking oil (WCO) with methanol in the presence of potassium hydroxide as the catalyst. A semi-industrial pilot of microreactor with 50 tubes with a diameter of 0.8 mm was used to produce 5 L/h biodiesel. Initially, the acidity of waste cooking oil was reduced to less than 1 mg KOH/g oil by using methanol at 60 C in the presence of 1% sulfuric acid. Using Box-Behnken design method, the effects of methanol to oil molar ratio (6:1e12:1), catalyst weight (0.5 e1.5 wt %), and reaction temperature (55e65 C) were studied. The methanol to oil molar ratio of 9.4:1, the catalyst concentration of 1.16 wt %, and the reaction temperature of 62.4 C was achieved under optimum condition. Finally, the effect of reaction time (30e120 s) was examined at the optimum condition. The highest level of biodiesel purity or fatty acid methyl esters % (FAMEs %) was 98.26%. In addition, the properties of produced biodiesel were determined and compared with those of the standard ASTM D6751. © 2019 Elsevier Ltd. All rights reserved.
Keywords: Biodiesel Waste cooking oil Optimization Semi-industrial pilot Microreactor
1. Introduction The increase in oil consumption, the variation in the global price of petroleum, the reduction of fossil fuel resources, and the intensification of environmental pollution have gradually increased the demand for renewable energy resources [1e5]. Renewable biofuels are considered as the fourth source of energy in the world [6] and they are usually used to produce electricity or heat [7,8]. As estimated, by 2030, biofuels will account for 4e7% of the total energy consumption in the world [9]. Moreover, biodiesel or fatty acid methyl ester (FAME) and alkyl esters of long chain fatty acids, as a basic product of the transesterification of renewable sources, is an attractive renewable fuel which can be produced through the trans-oxidation of triglycerides with an alcohol [10e12]. The main feedstock used for biodiesel production are animal fats, edible or non-edible vegetable oil, waste cooking oil, etc. The cost of feed and the shortage of raw vegetable oil are always critical to biodiesel production; for instance, the cost of vegetable oil can account for up to 75% of the total cost of production [13e16]. Hence, the use of waste cooking oils instead of raw oils can significantly
* Corresponding author. Chemical Engineering Department, Kermanshah University of Technology, Imam Khomeini Highway, Kermanshah, Iran. E-mail addresses: [email protected], [email protected] (B. Aghel). https://doi.org/10.1016/j.renene.2019.01.039 0960-1481/© 2019 Elsevier Ltd. All rights reserved.
reduce the costs of biodiesel production; this method, which is an effective method to decrease the cost of raw materials, can help to reduce the costs of biodiesel production by 60e70% [17e19]. Both homogeneous and heterogeneous catalysts are frequently used to produce biodiesel through transesterification reaction [20e22]. On the other hand, a large number of researchers investigated the production of biodiesel with homogeneous catalysts because they have a higher level of efficiency, a shorter reaction time, and an easier separation process, as compared with heterogeneous catalysts [23,24]. The most popular type of catalysts used as homogeneous catalysts are potassium hydroxide and sodium hydroxide [25e27]. Generally, researches produce biodiesel from waste cooking oils and animal fat via different types of catalyst in laboratory scales; however, a few number of studies have used waste cooking oils especially with high FFAs in a pilot plant scale [28,29]. a nek et al. [30] studied the biodiesel production at the pilotS plant level from waste frying oils and animal fats using tetramethylammonium hydroxide. According to their experimental results the conversion in all cases exceeded 98% achieved with 1:6 M ratio of feedstock to methanol, 1.5% w/w of the catalyst, the reaction time of 2 h and the temperature of 65 C. On the other hand, to improve the efficiency of biodiesel production, due to environmental and economic benefits microscale technologies has been considered. For instance, several researchers have put emphasis on the benefits of microreactor and its capacity
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to increase the production rate and overcome the limitations on mass transfer in transesterification process [31e33]. Santana et al. used numerical simulations to investigate the role of microchannels with circular obstructions, as a novel device, in increasing the interaction between the phases and enhancing mass transfer in biodiesel synthesis [34]. According to their experimental results, the use of obstructions had a strong impact on mixing and conversion efficiency. Recently, the effect of two co-solvents (nhexane/tetrahydrofuran) on heterogeneous transesterification reaction in a microreactor were investigated by Aghel et al. [35]. Under the optimal conditions, they achieved the biodiesel purity equal to 97.03% and 95.21% when using n-hexane and THF cosolvent, respectively [35]. Since the performance of transesterification process in the pilot plant depends strongly on the contact between streams. Therefore, in this work, we applied the semi-industrial pilot of microreactor to synthesis of biodiesel from waste cooking oil with methanol and potassium hydroxide, as the catalyst. The effects of process parameters such as temperature, KOH concentration, and methanol to oil molar ratio on the purity of biodiesel were experimentally investigated by BoxeBehnken method. After the optimization of biodiesel purity by response surface methodology (RSM), using the least squares error method the purity equation was achieved which had a good agreement with pilot results. 2. Materials and methods 2.1. Materials The waste cooking oil was purchased from Kermanshah restaurants and potassium hydroxide (KOH) was used as the catalyst. The physical properties and composition of waste cooking oil used in this study are similar to Aghel et al. study [35]. In addition, the acidity number, density, and kinematic viscosity of the oil were measured through ASTM D664, D941, and D445 methods, respectively. Methanol 99.7%, sulfuric acid 97%, and potassium hydroxide 98% were purchased from Merck Company, and methyl laurate (methyl dodecanoate) > 99.7% were purchased from Sigma (St. Louis, MO). All the chemicals such as water were of analytical grade. 2.2. Preparation of waste cooking oil At first, the waste cooking oil was filtered to eliminate waste substances, and then heated at 60 C for about 30 min and then water particles were settled by separation funnel. The waste cooking oil was prepared using 1% sulfuric acid and methanol before undergoing transesterification reaction. To decrease the acidity number from 3.12 mg KOH/g oil to less than 1 mg KOH/g oil (approximately 0.7 mg KOH/g oil), the methanol and waste cooking oil were reacted with a molar ratio of 6:1 at a temperature of 60 C using Tanawanpong et al.’s method [36]. 2.3. Transesterification in microreactor The transesterification reaction was performed in a semiindustrial pilot of microreactor. The schematic diagram and real image of the microreactor system are shown in Fig. 1. The pilot had a micromixer and 50 microtubes with an internal diameter of 0.8 mm and a length of 530 cm which formed a continuous reactor with a volume of 200 ml. All the microtubes were fixed and heated in an insulated cylindrical water bath with a diameter of 12.5 cm and a length of 500 cm. Through the experimental test, methanol solution (methanol þ KOH catalyst) and WCO from different reservoirs were fed into the T-shaped micromixer and mixed completely. Then, they
Fig. 1. Schematic diagram and view of the biodiesel production microreactor semiindustrial plant.
entered the microtubes to proceed the transesterification reaction. The methanol solution was prepared through mixing methanol and potassium hydroxide (0.5e1.5 wt % in proportion to the oil). The output stream exited the microreactor after a given residence time; a sample was taken from the outlet side quenched quickly by icy water and neutralized by sulfuric acid. In addition, the mixture of produced FAME, glycerol, and the residue were separated from each other via centrifugation (Hettich Universal 320R Centrifuge UK). The main product was collected from the upper layer and the materials in the lower layer was drained as a byproduct and the excess feedstock. Finally, to eliminate excess materials and ensure the accuracy of the results, the main product which contained methyl ester was washed three times with hot distilled water and subsequently heated up to 110 C in an oven (Binder Drying and heating chambers Classic. Line, Series FD) to remove the moisture from FAME. In each experimental run, the WCO and the methoxide (KOH þ methanol solution) were fed into the pilot to maintain the prescribed ratios and catalyst concentration (Table 1). It should be noted that, to provide the required level of heating for the reaction, the temperature of the cylindrical water bath was adjusted before Table 1 Experimental range and levels of variable. Factors
Unit
Reaction temperature Catalyst concentration (based oil) Methanol to oil molar ratio
C
wt. % mol:mol
Symbol
T C MR
Range and levels Low
Middle
High
55 0.5 6:1
60 1.0 9:1
65 1.5 12:1
M. Mohadesi et al. / Renewable Energy 136 (2019) 677e682
feeding the two streams into the microtubes.
Table 2 Experimental design of the three independent variables and the results.
2.4. Analyses
Run No.
Afterward, about 1 g of FAME phase and 5 mg of internal standard solution were mixed and then 1 mL of the prepared mixture was injected into the HP 6890 gas chromatograph (GC) with a flame ionization detector (FID). The capillary column was a BPX-70 high polar column with a length of 120 m, a film thickness of 0.25 mm and an internal diameter of 0.25 mm. Nitrogen was used as the carrier gas and also as an auxiliary gas for FID. One mL of the sample was injected using a 6890 Agilent Series Injector. The inlet temperature of sample into injector was 50 C, which was heated up to 230 C. Methyl laurate (C12:0) was added as a reference into the crude biodiesel and the samples were analyzed by GC that was mentioned above. The following equation suggested by Wang et al. [37] was used to determine the weight percentage of FAME or biodiesel purity:
FAME % ¼
area of all FAME weight of reference 100 area of reference weight of biodiesel sample (1)
2.5. Experimental design The production of biodiesel depends on various parameters, and it can be said that among all the factors the most important are residence time and production costs. Therefore, to reduce these two factors, it was necessary to design experiments and determine the optimum condition. Many researchers have investigated the effects of different parameters on biodiesel production using response surface methodology to analyze regression and determine the relationships between the measured responses and the vital input factors [38e40]. In this study, a 3-level 3-factor Box-Behnken experimental design was applied to evaluate the interaction between the variables and find the optimal condition for maximizing biodiesel purity in the pilot plant. The effects of the main operation variables on the purity of biodiesel including methanol to oil molar ratio (MR), catalyst concentration (C), and temperature (T) were investigated. The variables and their levels (low, middle, and high) were selected based on the previous experimental studies on the transesterification process [4,31]. Three independent variables for the transesterification reaction were methanol to oil molar ratio (6:1e12:1), KOH concentration (0.5e1.5 wt %), and temperature (55e65 C). Table 1 shows the ranges of the independent variables used for the Box-Behnken experimental design and Table 2 presents the experimental runs performed and FAME % obtained from each run. In addition, response surface methodology was used to examine the influence of the three independent variables on the percentage of methyl ester as a response variable. Analysis of variance (ANOVA) is an appropriate and reliable method for analyzing and determining the degree of test results [41]. The quadratic regression model was used to analyze the relationship between the independent variable and the predicted response variable (FAME %) which a mathematical model shown in Equation (2).
Y ¼ b0 þ
3 X i¼1
bi Xi þ
3 X i¼1
bii X 2i þ
2 3 X X i¼1 j¼iþ1
bij Xij
679
(2)
Manipulated variables
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Response
T , C
C, wt. %
MR, mol:mol
P, %
65 55 65 60 60 60 65 60 55 65 60 55 55 60 60
0.5 1.0 1.0 1.0 1.0 0.5 1.0 0.5 1.0 1.5 1.5 1.5 0.5 1.5 1.0
9:1 6:1 12:1 9:1 9:1 12:1 6:1 6:1 12:1 9:1 12:1 9:1 9:1 6:1 9:1
82.26 75.23 85.53 95.24 97.12 80.03 82.84 70.48 73.64 93.61 86.25 79.21 76.69 77.42 96.33
where Y is the response, Xi and Xij are the independent variables, b0 is the offset term, and bi , bii , bij are the regression coefficients. The quality of the mathematical experimental model was checked by using the coefficients of determination (R2 ). In ANOVA, the level of significance or P-value was set at 0.05. ANOVA was used to determine the significance of the second-order models. The statistical significance of the second-order models was determined by F value. Whenever the calculated F value is higher than the given F value, the P value will be much smaller; this fact indicates the significance of the statistical model. Calculated F value is defined as the mean-square regression (including linear, square, and interaction) and the mean-square residual [41].
F value ¼
MSregression MSresidual
(3)
where:
MSregression ¼
MSresidual ¼
SSregression DFregression
SSresidual DFresidual
(4)
(5)
Regression degree of freedom (DFregression ) is the number of sentences minus one, and the residual degrees of freedom (DFresidual ) is the total degree of freedom minus regression degree of freedom [41].
3. Results and discussion 3.1. Effect of reaction temperature Due to the consumption of energy in the transesterification process, the reaction temperature is an important parameter. This parameter was set at three levels in a range of 55e65 C with a step of 5 C. As shown in Figs. 2 and 3, with increasing the temperature from 55 C to about 62 C, the purity of biodiesel significantly increased within 60 s. However, further increase in the temperature did not have a significant effect on the purity of biodiesel; increasing the temperature beyond the optimum point only lead to the waste of energy. The optimum temperature was 62.4 C, and when reaching this temperature, the highest FAME % was achieved (Figs. 2 and 3).
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M. Mohadesi et al. / Renewable Energy 136 (2019) 677e682
purity of biodiesel was gradually reduced. As shown in this figures, optimum weight percentage of the catalyst was obtained at 1.16 wt % for producing biodiesel within 60 s. 3.3. Effect of methanol to oil molar ratio
Fig. 2. Three-dimension plots of FAME % based on the temperature and catalyst concentration in semi-industrial pilot (t ¼ 60s).
One of the most important parameters affecting the production of biodiesel is the methanol to oil molar ratio. As shown in Figs. 3 and 4, the effect of the methanol to oil molar ratio on the purity of biodiesel, within a residence time of 60 s, was investigated at three levels, including low level (6:1), middle level (9:1), and high level (12:1). When using the low level, the purity of biodiesel was the minimum level, however, with increasing the methanol to oil molar ratio, the purity increased. However, with increasing the molar ratio beyond the middle level, there was a reduction in the purity percentage. In optimal conditions, the methanol to oil molar ratio was 9.4:1. 3.4. Response analysis of variance Using the least squares error method, a second-order (quadratic) model was achieved to determine the biodiesel purity percentage expressed by Equation (6) as follows:
FAME% ¼ 912:271 þ 29:516T þ 11:067C þ 17:969MR þ 0:883T:C þ 0:071T:MR 0:120C:MR 0:250T 2 28:105C 2 1:184MR2 (6)
Fig. 3. Three-dimension plots of FAME % based on the temperature and methanol to oil molar ratio in semi-industrial pilot (t ¼ 60s).
3.2. Effect of catalyst concentration
biodiesel purity (FAME %) model, R2 and R2adj: were 0.963 and 0.896, respectively.
100 95 Predicted FAME, %
In this study, potassium hydroxide was used as the catalyst and it was used at three levels of 0.5, 1.0, and 1.5 wt %. The effect of the weight percentage of the catalyst on the purity of the produced biodiesel (FAME %) is presented in Figs. 2 and 4. As shown in these figures, with increasing the weight percentage of the catalyst to the middle level (about 1.1 wt %), the percentage of the purity of the produced biodiesel increased remarkably. With a further increase in catalyst concentration, the
where T, C and MR are the reaction temperature, catalysts concentration (oil based), and methanol to oil molar ratio, respectively. Based on the obtained model and using 3-D plots, further relationship between the variables and FAME % were investigated and the results are shown in Figs. 2e4. Fig. 5 shows the values predicted by the second-order model (Equation (6)) as compared with the observed values of FAME %. In
90 85 80 75 70
Fig. 4. Three-dimension plots of FAME % based on the catalyst concentration and methanol to oil molar ratio in semi-industrial pilot (t ¼ 60s).
70
75
80 85 90 Experimental FAME, %
95
Fig. 5. Comparing the experimental and predicted values of FAME %.
100
M. Mohadesi et al. / Renewable Energy 136 (2019) 677e682
3.5. The effect of residence time Under optimum conditions obtained from Equation (6) (T ¼ 62:4 C, C ¼ 1:126 wt:%, and MR ¼ 9:4 : 1), experiments were performed again in five different residence times (t). The residence times were: 30, 45, 60, 90, and 120 s. The results of the tests are shown Fig. 6. The test was repeated three times for each sample, and the results were averaged. According to this figure, as expected, with increasing the residence time, FAME % was increased sharply and then the percentage of purity was increased slightly. Therefore, at a residence time of less than 60 s the purity of the produced biodiesel was low and it can be concluded that the residence time was very inadequate. The purity of the produced biodiesel during residence time of 60 s is 97.2%, while by increasing the time to 120 s, the purity increased into 98.26%.
3.6. Physical properties of biodiesel The physical properties of the produced biodiesel were also examined and the values are presented in Table 4. As shown in this table, the properties of the produced biodiesels compared by ASTM D6751 show that they are in the standard range.
120 100 FAME, %
Table 3 presents the results of ANOVA test which was carried out to assess the biodiesel purity models. Total degree of freedom in each model was 14. As presented in Table 3, degrees of freedom for regression and residual error were 9 and 5, respectively. Table 3 compares calculated F-values with tabulated F-values; as shown, the F-value calculated for the model is larger and is statistically more significant. Using the model, T, C, T 2 , C 2 , and MR2 were identified as significant regression terms. P-values larger than 0.05 indicate that the regression terms are not significant, though the main factor must remain in the models. The empirical model (Equation (6)) used for FAME % are plotted in 3-D diagrams (Figs. 2e4). Each 3-D diagram of FAME % is plotted via changing two variables. The other variable are set at the middle level. The optimum condition were obtained by derivation of Equation (6) for the three variables (T, C, and MR). In the optimal condition i.e. T ¼ 62:4 C, C ¼ 1:126 wt:%, and MR ¼ 9:4 : 1. FAME % was maximized. Using Equation (6), FAME % in optimal condition was 99.65%. Based on the results of experimental test (repeated three times) in optimal condition (temperature of 62.4 C, catalyst concentration of 1.16 wt %, and methanol to oil molar ratio or 9.4:1), FAME % was 97.21%.
681
80 60 40 20 0
0
30
45
60
90
120
Fig. 6. Effect of residence time on FAME % in optimal condition (T ¼ 62:4 C, C ¼ 1:126 wt:%, and MR ¼ 9:4 : 1).
Table 4 Properties of produced biodiesels compared by ASTM D6751. Property
Unit
Biodiesel
ASTM D6751
Density at 15 C Kinematic viscosity at 40 C Pour point Cloud point Water content Total glycerin
g/cm3 cSt C C % %
0.880 4.6 5 6 0.03 0.13
0.86 to 0.90 4 to 6 15 to 10 3 to 12 0.05 0.24
3.7. Comparing biodiesel production in batch reactor and microreactor In order to show the overall advantage of microreactor a we conducted a comparative study between the results of current study and the results obtained from conventional batch systems (Table 5). Although rectors cannot be compared directly but the order of magnitude of criterion can help readers a qualitative judgment.
Table 5 Review of different kinds of semi-pilot in the literature. Authors
MR, mol:mol
TC
C, wt. %
t r , min
FAME, %
a nek et al. [30] S Sahu et al. [42] Bouaid et al. [43] Alptekin et al. [44] Present work
6:1 6:1 6:1 6:1 9.4:1
65 65 30 60 62.4
1.5 1.0 1.5 1.0 1.16
120 180 30 120 2
98.0 91.2 99.24 91.0 98.3
Table 3 Analysis of variance (ANOVA) for the second-order FAME % model. Sources
SS
DF
MS
F-value
p-value
Degree of significance
Regression T C MR T:C T:MR C:MR T2
1031.51 194.74 91.33 47.43 19.49 4.58 0.13 144.75
9 1 1 1 1 1 1 1
112.61 194.74 91.33 47.43 19.49 4.58 0.13 144.75
14.36 24.84 11.65 6.05 2.49 0.58 0.017 18.46
0.0045 0.0042 0.0190 0.0572 0.1757 0.4792 0.9027 0.0077
significant significant significant not significant not significant not significant not significant significant
C2
182.28
1
182.28
23.25
0.0048
significant
MR2 Residual error Lack e of e fit Pure error Total
419.48
1
419.48
53.51
0.0070
significant
39.20 37.42 1.78 1052.70
5 3 2 14
7.84 12347 0.89
14.00
0.0674
not significant
682
M. Mohadesi et al. / Renewable Energy 136 (2019) 677e682
Comparing the two methods in terms of the residence time and FAME % showed the preference of using this system over conventional pilot scale reactor. Increasing the biodiesel production in this case due to special mixing conditions, not only results in a reduction in the residence time and saves the energy but also increases FAME %.
[18]
[19]
4. Conclusion
[20]
A semi-industrial pilot of microreactor with 50 tubes of 0.8 mm diameter, 5 L/h, was used to investigate the production of biodiesel from waste cooking oil as a low cost feedstock and with potassium hydroxide (KOH) as the catalyst. FAME was produced through the transesterification of waste cooking oil in a pilot scale and was analyzed by GC. The weight percentage of FAME % or biodiesel purity was also calculated. According to the results of laboratory tests, the highest levels of biodiesel purity obtained by using the model and through performing the experiment during 1 min were 99.65% and 97.21%, respectively. In addition, the optimization of the biodiesel purity showed that, the most suitable methanol to waste oil molar ratio was 9.4:1, the best catalyst concentration was 1.16 wt %, and the optimum reaction temperature was 62.4 C. In optimal conditions, experiments were performed within different reaction times, and the highest biodiesel content was 98.26% which was obtained at a residence time of 120 s. Finally, to show the overall advantage of the microreactor over batch reactors, the residence time and purity of the two methods were compared and the experimental results proved the superiority of microreactor.
[21]
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