Optimization of production variables of biodiesel using calcium oxide as a heterogeneous catalyst: an optimized process

Hilary Rutto1 and Christopher Enweremadu2 1Department of Chemical Engineering, Vanderbijlpark Campus, Vaal University Of Technology, Private Bag X021,

Vanderbijlpark, South Africa, 1900 2 Department of Mechanical and Industrial Engineering, University of South Africa, Florida Campus, Private Bag X6,

Florida 1710, South Africa

In this study biodiesel was produced from waste cooking oil (WCO) using calcium oxide (CaO) as a heterogeneous catalyst. The effect of experimental variables such as temperature, reaction time, methanol to oil ratio, and amount of catalyst were investigated. Using a central composite design (CCD) of experiments variables, a mathematical model was developed to correlate the experimental variables to the percentage of biodiesel yield. The model shows optimum conditions for biodiesel production were found as follows: amount of catalyst of 2.75 grams, temperature 73.23 °C, methanol to oil ratio 30.08 wt % and reaction time of 3.86 h. A yield of 85.96 % biodiesel was obtained. The results show that the important fuel properties of the biodiesel produced at optimum conditions met the biodiesel ASTM standard.

Keywords: Biodiesel, WCO, calcium oxide, central composite design, transesterification, model

1. Introduction

The energy and transport sector are the major sources of greenhouse emission. Growing economies such as India and South Africa will raise the global consumption of energy leading to more environmental havoc which will affect the quality of the environment and human life [1-2]. Moreover the world crude oils are depleting this has caused the cost of extraction and production to increase resulting to prices of crude oil going up. This scenario is particular evident in the transport sector and therefore there is a need to find clean and renewable energy sources which is the most challenging problem facing mankind presently [3]. Examples of renewable energy that can be used include geothermal, biofuels, solar energy, wind, hydrothermal, biomass, biofuel and among others [4]. Nowadays the promising biofuel is biodiesel which can be produced from edible vegetable oils like canola, soybean and corn found to be good as a diesel substitute [5] and non-edible oils such as animal fats, Jatrophacurcas, and waste oils such as soybean soapstock and yellow grease have been used in the production of biodiesel [6-9]. There are basically two types of catalyst that are used in the production of biodiesel namely Homogenous and heterogeneous. The term of Homogeneous means the catalysts are in the same phase with its reactants, whereas heterogeneous means that the catalysts are in a different phase from its reactant. Further homogenous catalyst can be categorised into homogenous bases and acids. In biodiesel production Potassium hydroxide, sodium hydroxide, sodium methoxide are the commonly used basic catalysts production [10]. An example of commonly used homogenous acid catalyst is sulphuric acids, sulphuric acids is commonly used esterify excess free fatty acids when the free fatty acid content is high. The disadvantages of using homogenous catalysts are that they cannot be recovered; intolerance of high free fatty acid (FFA) and also they require washing of biodiesel with pure water to remove the catalyst present. This results in wastewater generation, water contamination and loss of biodiesel as a result of water washing and this increases cost on municipal water treatment plants. Heterogeneous catalysts can be classified into two main classes’ namely heterogeneous solid acid and heterogeneous base catalysts. Heterogeneous acid catalysts for example, heteropolyacid impregnated on different supports (silica, zirconia, alumina, and activated carbon), SO4-ZrO2 and WO3-ZrO2 as solid acid catalyst were indicated as catalysts for the transesterification of canola oil with methanol to produce biodiesel [11-13]. Unfortunately, these catalysts had drawbacks including longer reaction time and higher temperatures which make them unfavourable. Heterogeneous solid base catalyst such as calcium oxide has some advantages over homogeneous catalyst because the catalyst can be reused (cost effective), has a tolerance of moisture and FFA (which allows the use of lower-quality used/waste oils), is inexpensive (obtainable from waste shells), has low methanol solubility, is non-corrosive and is environmental friendly. The main objective of this work is to study the feasibility of using calcium oxide to produce biodiesel from waste vegetable oil via a one-step alkali transesterification process. A central composite design (CCD) was adopted to survey the effects of four transesterification process variable (amount of methanol in oil, amount of catalyst, reaction period, and reaction temperature) on the yield of biodiesel. A mathematical model was established and used to correlate the transesterification process to the yield of FAME. Some of the crucial fuel properties of biodiesel produced at optimum conditions was compared with fuel properties of biodiesel at ASTM standard.

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2. Material and method

2.1 Material

The waste cooking oil was obtained from the university cafeteria. Potassium hydroxide, Isopropanol, CaO, methanol and Phenolphthalein indicator were supplied by Rochelle chemical, a local chemical supplier.

2.2 Method

2.2.1 Experimental Design.

An experimental design is essential as it serves as a theoretical way of determining the number of runs required to conduct a particular investigation. A factorial experimental design will be chosen for the investigation of the various objectives under consideration. Factorial method (24 = 16) was used for analysis. The biodiesel synthesis was developed and optimized using response surface methodology (RSM) [14]. Table 1 below shows the transesterification process variables employed for this study

Table 1: Levels of transesterification process variables employed for this study

Variable Coding Units levels

-2 -1 0 1 2

Temperature

Amount of catalyst

Methanol to oil ratio

Reaction time

x1

x2

x3

x4

°C

grams

wt %

hr

40

2

10

2

55

2.75

20

2.75

70

3.5

30

3.5

85

4.25

40

4.25

50

5

50

5

The experimental sequence was randomized in order to minimize the effects of the uncontrolled factors. Each response of the yield of biodiesel was used to develop a mathematical model that correlates the yield of biodiesel to the experimental variables through first order, second order, third order, and interaction terms, according to the following third order polynomial equation (Y = yield of biodiesel , 0 = offset term, j = linear effect, ij = first order interaction effect, jj = squared effect, and kjj = second order interaction). = 0 + ∑ jXj + ∑ ijXiXj , + ∑ jj + ∑ kjj, , + ∑ (1)

2.2.2 Model fitting and statistical analysis

The experiments were conducted according to the experimental design matrix shown in Table 2. The regression analysis was done using design expert (6.0.6) software so as to fit the experimental data to the third order polynomial regression model.

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Table 2: Experimental design matrix and yield of biodiesel

2.2.3 Evaluation of free fatty acid.

The waste cooking oil obtain from Vaal University of Technology was heated for 4 hrs at hundred degrees Celsius 100 °C to remove excess water. Standard solution of potassium hydroxide 1 gram per 1000 ml of distilled water was prepared and used for titration. Three samples were taken to evaluate the free fatty acid, 1 ml of waste cooking oil and 10 ml Isopropanol. 4 to 5 drops of Phenolphthalein was added to each mixture. Pipette was filled to a given volume with the standard solution. When the samples turned pink the titration was stopped and the value of the volume of lye was recorded.

2.2.4 Production of biodiesel

The conical flask (reactor) was loaded with required amount of waste cooking oil heated up to desired reaction conditions stipulated in Table 2. At the end of each transesterification process the product was transferred to the separating funnel (decanter) and allowed to settle over night to enhance the separation. The samples showed three distinct phases namely the glycerol, catalyst and biodiesel phase. The bottom catalyst and glycerol layer was discarded. The biodiesel phase layer was then washed with deionised water at 50°C repeatedly until the washed water became clear. The excess methanol and water in ester phase were then removed by heating the mixture at 100 °C for

Process variables

Exp no: Temperature

(°C)

Amount of

catalyst

(g)

Methanol to oil

ratio

(wt %)

Reaction Time

(hr)

Biodiesel yield

(wt %)

B1 55 2.75 20 2.75 45.81 B2 85 2.75 20 2.75 26.31 B3 55 4.25 20 2.75 83.19 B4 85 4.25 20 2.75 39.44 B5 55 2.75 40 2.75 41.91 B6 85 2.75 40 2.75 71.92 B7 55 4.25 40 2.75 46.92 B8 85 4.25 40 2.75 49.75 B9 55 2.75 20 4.25 74.31 B10 85 2.75 20 4.25 93.06 B11 55 4.25 20 4.25 71.69 B12 85 4.25 20 4.25 15.69 B13 55 2.75 40 4.25 79 B14 85 2.75 40 4.25 41.08 B15 55 4.25 40 4.25 37.25 B16 85 4.25 40 4.25 15.08 B17 40 3.5 30 3.5 39.85 B18 100 3.5 30 3.5 72.28 B19 70 2 30 3.5 82.14 B20 70 5 30 3.5 60.57 B21 70 3.5 10 3.5 32.94 B22 70 3.5 50 3.5 49.3 B23 70 3.5 30 2 50.28 B24 70 3.5 30 5 26.64 B25 70 3.5 30 3.5 79 B26 70 3.5 30 3.5 74.78 B27 70 3.5 30 3.5 77.36 B28 70 3.5 30 3.5 76.36 B29 70 3.5 30 3.5 73.78 B30 70 3.5 30 3.5 84.42

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10-15 minutes. The biodiesel yield was calculated based on the amount of biodiesel produced and amount of oil that was initially used.

2.2.5 Characterization of fuel properties of Biodiesel

The biodiesel produced at optimal conditions was measured using the ASTM biodiesel standard. The following parameters were determined: Viscosity, density and flash point was determined using the ASTM D445, ASTM 1298 and ASTM D93 respectively.

3. Results and discussion

3.1 Development of the regression model equation

By using multiple regression analysis, the response obtained in Table 2 was linked using the polynomial equation, evaluated using the Design expert software to give the above full regression model equation. The final model in terms of actual value after excluding the insignificant terms (identified using Fisher’s Test) is

The negative sign in front of the terms specifies an antagonistic effect, while the positive sign indicates synergistic effect. The coefficient correlation (R2) can be used to evaluate the quality of the model. The R2 for Eq. 1) is 0.6878. This suggests that 68.78 % of the total deviation in the biodiesel yield responses is clarified by the model.

3.2 Effect of process variables

(a) (b)

Figure 1: The effect of methanol to oil ratio and temperature on the biodiesel yield (a) response surface plot (b) two dimensional plot where the methanol to oil ratio is held at + 40 and -20 wt %. Fig.1 shows the effect of varying the amount of methanol to oil ratio and the reaction temperature on the yield of biodiesel, the reaction time and the amount of catalyst are held constant at 3.5 hr and 3.5 grams respectively. As seen at low level of methanol to oil ratio the biodiesel yield is higher, but as the temperature increases the biodiesel yield decreases. Studies have shown that at high temperature diminishes the molecular interaction time between methanol, oil and catalyst and thus reduces the biodiesel yield [15]. Moreover thermal degradation of biodiesel at high temperature also reduces the yield of biodiesel. When high level of methanol to oil ratio is used the biodiesel yield is low, but as the temperature increases the yield increases slightly but decreases at a high temperature. As the amount of methanol to oil

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ratio is increased there is a reverse transersterification reaction forming more oil and thus reducing the biodiesel yield [16]. As shown in figure there is an interaction between the amount of methanol to oil ratio and reaction temperature. Fig. 2 shows the influence of reaction time and amount of catalyst on the yield of biodiesel, the amount of methanol to oil ratio and reaction temperature are held constants at 30 wt % and 70°C respectively. When the reaction period is prolonged, the biodiesel yield increases, but as the amount of catalyst is increases the biodiesel yield decreases. High amounts of catalyst increases the formation of soap than the esterification of triglyceride into biodiesel [17]. At low reaction time the biodiesel yield is low. At low reaction time there could be incomplete reaction; this causes the molecular interaction between the triglyceride and methanol to reduce [18]. Figure 3 shows the effects of amount of catalyst and reaction temperature on the yield of biodiesel, the amount of methanol to oil ratio and reaction time are held constant at 30 wt % and 3.5 hr respectively. As it can be seen in figure 3, when large amount of catalyst is used the biodiesel yield decreases and vice versa. As explained more usage of catalyst causes the formation of more soap and thus reducing the biodiesel yield. As the temperature increases the biodiesel yield decreases when large amount of catalyst is used. Morever when low amount of catalyst is used as temperature increases the biodiesel yield increases, this shows that the amount of catalyst as a very huge impact on the biodiesel yield.

(a) (b)

Figure 2: The effect of reaction time and amount of catalyst on the biodiesel yield (a) response surface plot (b) two dimensional plot where the reaction time is held at + 4.25 and -2.75 hr.

(a) (b)

Figure 3: The effect of amount of catalyst and temperature on the biodiesel yield (a) response surface plots (b) two dimensional plot where amount of catalyst is held at + 4.25 and 2.75 grams.

46.5642

55.9699

65.3755

74.7812

84.1869

Bio

dies

el y

ield

( w

t %)

2.75

3.13

3.50

3.88

4.25

2.75

3.13

3.50

3.88

4.25

Amount of catalyst (g)

Reaction time (hr)

Amount of cataly st (g)

Bio

dies

el y

ield

( w

t %)

2.75 3.13 3.50 3.88 4.25

15.08

34.575

54.07

73.565

93.06

-

+

Temperature (°C)

Bio

dies

el y

ield

(wt %

)

55.00 62.50 70.00 77.50 85.00

53.8183

60.9429

68.0675

75.1922

82.3168

-+

53.8183

60.9414

68.0645

75.1875

82.3106

Bio

dies

el y

ield

(wt %

)

55.00

62.50

70.00

77.50

85.00

2.75

3.13

3.50

3.88

4.25

Temperature (°C)

Amount of catalyst (g)

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Figure 4: Individual influence of reaction variables biodiesel yield. A-Temperature, B-Amount of catalyst, C-Methanol to oil ratio, D-Reaction time. The effect of all reaction variables at a point in the design space can be discussed from the perturbation plot as shown in fig. 4. Influence of one factor was evaluated and plotted alongside the yield while the other parameters were kept constant. The amount of catalyst displayed a greater influence on the biodiesel yield than the other three parameters. It was followed by the reaction temperature, methanol to oil ratio and lastly by the reaction period. It can generally be observed that the biodiesel yield decreases as all transesterification variables are increased which shows an excellent agreement with literature.

3.3 Fuel properties of Waste vegetable oil methyl ester compared to other oil methyl ester

Important fuel properties of biodiesel from WCO were determined and compared to properties of Jatropha [19] and palm oil [20] is shown in Table 3. The fuel properties of biodiesel produced from waste vegetable oil are within the ASTM standards of biodiesel. The density of marula methyl ester is 866 kg/m3 lower than jatropha (880 kg/m3) and palm methyl ester (864.4 kg/m3) ultimately all are within the specified limit of (860-900 kg/m3). The kinematic viscosity of waste cooking oil methyl ester (4.32 mm2 s-1) at 40 °C is slightly lower than jatropha (4.4 mm2 s-1) and palm oil (4.5 mm2 s-1) but all meet the viscosity ASTM standard of biodiesel. The flash point of biodiesel from waste cooking oil is within the ASTM standard.

Table 3: Fuel properties of waste vegetable biodiesel compared to other biodiesel and ASTM standard

Parameter WVO Jatropha Palm ASTM D6751-02

Density at 25 ºC (kg m³־) 860-900 864.4 880 886

Kinematic viscosity 40 ºC (mm² s¹־) 1.9-6.00 4.5 4.4 4.32

Flash point (°C) 181 163 176 >130

4. Conclusion

This study has demonstrated the feasibility of using calcium oxide as catalyst to produce biodiesel from waste cooking oil via a one alkali catalyst technique. The response surface technique was used to determine the optimal condition that can be used to produce biodiesel from waste cooking oil. The optimum conditions for producing biodiesel were: reaction temperature of 73.23 °C, amount of catalyst at 2.75 g, reaction time at 3.86 hr, and amount of methanol in the oil at 30,08 wt %. The optimum yield of biodiesel was 85.96%. It was found out that that important fuel properties biodiesel produced at optimum condition met the biodiesel ASTM standard.

Dev iation f rom Ref erence Point

Bio

dies

el y

ield

(wt %

)

-1.000 -0.500 0.000 0.500 1.000

15.08

34.575

54.07

73.565

93.06

AA

B

BCC

D D

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Acknowledgement The support by V Mtakati and G Makhuluza is gratefully acknowledged in this work, together with the funds from the university lab fee.

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