Comparative analysis of effect of methanol and ethanol on Karanja biodiesel production and its optimisation

Fuel 180 (2016) 164–174

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Comparative analysis of effect of methanol and ethanol on Karanja biodiesel production and its optimisation Puneet Verma ⇑, M.P. Sharma Biofuel Research Laboratory, Alternate Hydro Energy Centre, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand 247667, India

a r t i c l e

i n f o

Article history: Received 13 December 2015 Received in revised form 5 April 2016 Accepted 6 April 2016

Keywords: Biodiesel Transesterification Response Surface Methodology (RSM) Methanol Ethanol Optimisation

a b s t r a c t Extensive use of fossil fuel resources especially petroleum has resulted in situation to look for alternative fuel sources. Biodiesel offers a good choice due to its renewable nature. In recent times, mainly methanol has been used in transesterification reaction for biodiesel production as it is derived from fossil sources, and biodiesel produced cannot be termed as completely renewable while other alcohols such as ethanol, being obtained from renewable sources such as potatoes, sugarcane, grains, corn and sorghum can be used for transesterification reaction. The aim of this work was to investigate the impact of ethanol on biodiesel production from Karanja oil and then optimise process variables for transesterification process. Further a comparison was done in optimised reaction parameters for methanolysis and ethanolysis. The result of experimental investigation shows that Karanja biodiesel yield of 91.05% was achieved with molar ratio of 10.44:1 for methanol using 1.22% w/w KOH as catalyst for 90.78 min at the temperature of 66.8 °C. On the other hand for, ethanolysis, optimised reaction conditions were, 8.42:1 molar ratio, 61.3 °C reaction temperature with 1.21% of catalyst and 120 min of reaction time to obtain yield of 77.4%. Ó 2016 Elsevier Ltd. All rights reserved.

1. Introduction The rapidly increasing demand and price of fossil fuel resources along with environmental degradation have shaken up the economies around the world. All these problems along with environmental issues have created an awareness to look towards unconventional fuel sources [1]. Straight Vegetable Oils (SVOs) are considered as substitutes to diesel but these suffer with the problem of high viscosity. Higher viscosity of SVOs is the main reason for their difficult combustion in diesel engines. The most effective and practical way to use vegetable oils as fuel is to convert them into their corresponding esters by transesterification process. These vegetable oil esters are popularly known as biodiesel. One of the potential alternatives to petroleum diesel is the biodiesel which is renewable in nature as it is derived from vegetable oils and fats. There are several advantages of biodiesel such as relatively less hazardous to environment, higher flash point causing ease in storage and less hydrocarbon and carbon monoxide emissions, making it eco-friendly [2]. There are four ways in which oils and fats can be converted into biodiesel namely transesterification, blending, micro-emulsions and pyrolysis. The most common method to produce biodiesel is transesterification of vegetable oils and animal fats in the presence of a catalyst such as acid, alkali or ⇑ Corresponding author. E-mail address: [email protected] (P. Verma). http://dx.doi.org/10.1016/j.fuel.2016.04.035 0016-2361/Ó 2016 Elsevier Ltd. All rights reserved.

enzyme [3–5]. The main complication faced in biodiesel production is the presence of Free Fatty Acids (FFAs) in non-edible oils especially Karanja and waste cooking oil. Adoption of homogeneous base catalyst, results in formation of soaps causing strenuous separation thus decreasing ester yield. Therefore high FFA feedstock, acid catalyst is preferred to produce biodiesel, but it demands more reaction time and alcohol. For oils or fats having high FFA acid esterification is advantageous, as acid catalyse the FFA esterification to produce fatty acid methyl ester (FAME), increasing the biodiesel yield, but reaction time and alcohol requirement are substantially higher than those of base catalysed transesterification [6–8]. Prominent feedstocks for biodiesel production are edible oils, non-edible oils, algae, waste oils. Karanja oil also known as Pongamia is said to be barren land plant. It requires no care and can be grown in the waste lands. Also Karanja seeds are reported to have high oil content (25–30%) [9,10]. Mostly, methanol has been used for biodiesel production through transesterification reaction. Methanol is derived from fossil resources and therefore biodiesel produced cannot be termed as fully renewable. Therefore, there is scope of using ethanol for producing biodiesel. Ethanol is produced from a number of crops such as potatoes, sugarcane, grains, corn and sorghum [11]. Biodiesel is the mono-alkyl ester of vegetable oils or animal fats, which is produced via transesterification reaction with the help of alcohol in presence of catalyst. Two main problems associated with use of biodiesel are its stability and cold region performance [12,13]. Fatty acid

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ethyl esters (FAEEs) present a higher cetane number and calorific value, oxidation stability and lubricant characteristics than methyl esters, and also have lower tail pipe emissions. Moreover, lower CP and PP signify their better colder region properties [14,15]. Type of alcohol and its molar ratio play significant role in biodiesel yield and its properties. Significant literature is available on optimisation of process variables of biodiesel production from different oils using Response Surface Methodology (RSM) but little work is reported in reference to particularly Karanja oil and comparison of impact of different alcohols on biodiesel production to optimise the reaction parameters. Aniya et al. [16] produced Karanja oil biodiesel using KOH (1% w/w) as catalyst, methanol to oil molar ratio of 6:1 at 600 rpm and temperature between 35 and 55 °C. The yield of fatty acid methyl esters was found to increase with time and as the equilibrium is attained, ester concentration attained a steady state. Rathore et al. [17] used dimethyl carbonate (DMC) to produce biodiesel from Jatropha and Karanja oil. Maximum yield of 96.8% and 97.2% was obtained for Jatropha and Karanja biodiesel. Prabhavathi Devi et al. [18] obtained >99% biodiesel yield from Karanja oil having 7.5% Free Fatty Acids (FFAs) using SO3Hcarbon catalyst. Reaction conditions kept were 1:45 alcohol to oil mole ratio, catalyst 20 wt.% of oil, temperature 160 °C and reaction time of 4 h. Authors recommended solid acid catalysts for single step conversion of high FFA oils into biodiesel. Thiruvengadaravi et al. [19] also employed solid acid catalyst for production of biodiesel from high FFA oil and achieved 90% yield under molar ratio of 9:1, temperature 60 °C and time 120 min. Naik et al. [20] obtained 96.6–97% of biodiesel yield from Karanja oil having 20% FFAs using dual esterification. Joshi et al. [21] produced biodiesel from Karanja oil and achieved yield in range of 25.4% and 95.4%. Sahoo and Das [22] observed that molar ratio of 11.5:1 is optimum for obtaining yield of 91% of Karanja biodiesel with having transesterification reaction for 120 min. Kamath et al. [23] obtained Karanja biodiesel of 89.9% under microwave irradiation. Betiku et al. [24] obtained 99.94% biodiesel yield from shea tree (Vitellaria paradoxa) oil and optimised parameters using RSM and Artificial Neural Network (ANN) under optimised condition of 82 °C temperature and molar ratio of 2.62 with KOH of 0.40 weight/volume. Meher et al. [25] obtained yield of 97–98% under optimised reaction conditions of 1% KOH, 6:1 molar ratio and 65 °C temperature for Karanja oil methyl ester (KOME). Avramovic´ et al. [26] used RSM to optimise biodiesel production from sunflower oil. Ethanol was used as alcohol for transesterification reaction and highest yield of 97.8% was obtained which was close to predicted yield of 99.2%. Narvaez et al. [27] produced biodiesel from palm oil on ethanolysis using 0.2–1 wt.% NaOH at temperature between 60 and 80 °C and ethanol to oil molar ratio 6:1. Highest yield of 96% with 100% conversion of fatty acids into methyl esters was obtained on 1 h of reaction. Rubio-Caballero et al. [28] produced fatty acid ethyl esters from sunflower oil with yield of 95% on using heterogeneous catalyst Calcium zincate at 78 °C reaction temperature. Stamenkovic´ et al. [29] optimised sunflower biodiesel

production with RSM technique and achieved yield of 98.6% which was well close to predicted value of 98.9%. Optimum reaction conditions found were temperature in range of 50–59 °C ethanol-to-oil molar ratio of 12:1, 0.75% catalyst and reaction time of 15 min. Barbosa et al. [30] did ethanolysis of castor and soybean oils and found out yield more than 90% for soybean oil biodiesel and around 30% for castor biodiesel. Velicˇkovic´ et al. [31] applied RSM to ethanolysis of sunflower oil for production of biodiesel and obtained good relation between predicted and actual values of yield obtained with 93.7% accuracy. In addition to this, there have been some studies that focused on use of numerical modelling of biodiesel fuelled engine for combustion and exhaust emission analysis [32–37]. From the above literature, it is noted that, there has been limited study on comparison of impact of alcohol and optimisation of reaction parameters on biodiesel production. The aim of this paper was to optimise the biodiesel production from Karanja oil and compare the results for two different alcohols that are methanol and ethanol and to understand their impact on yield of biodiesel. 2. Materials and methods Karanja oil (KO) was purchased from M/s Katyani Exports Pvt Ltd, New Delhi. All chemicals such as KOH, and alcohols such as methanol and ethanol were of AR grade and 99% pure. Karanja oil was filtered to remove all insoluble impurities from the oil followed by heating at 100 °C for 10 min to remove all the moisture. The fuel properties of Karanja oil after refining were determined as per standard methods. The properties of Karanja oil, methanol and ethanol and their comparison with standard values of diesel are reported in Table 1. Table 1 indicates that KO has high FFA content (8.2%) and so, pretreatment (esterification) process was applied with using 1% H2SO4 (v/v) to reduce the FFA content <2% and followed by base catalyst transesterification using KOH. After the completion of reaction, alcohol-catalyst was separated from upper layer. Next, the esterified oil is washed with distilled water, until the remains of catalyst were removed and heated to remove water content. This step led to reduction in FFAs of oil up to 1.82%, which was then transesterified using base catalyst to methyl/ethyl esters. The range of parameters adopted during transesterification is given in Table 2. Table 2 Independent variables used for Box–Behnken design for optimising in transesterification of KO. Variables

Symbols

Reaction temperature (°C) Alcohol to oil molar ratio Catalyst amount (wt.%) Reaction time (min)

A B C D

Levels
1

0

1

50 6:1 0.5 60

65 10.5:1 1.25 90

80 15:1 2 120

Table 1 Fuel properties of Karanja oil, diesel, methanol and ethanol. Property

Test method

KO

Diesel

Methanol

Ethanol

Density, at 15 °C (kg/m3) Boiling temperature (°C) Cetane number Viscosity (cSt s at 40 °C) Flash point (°C) Auto ignition temperature (°C) Gross calorific value (MJ/kg) CFPP (°C) Lubricity (lm corrected wear scar) FFA (%) Acid value

IS 1448 ASTM D7169 ASTM D613 ASTM D445 ASTM D93 ASTM E659 ASTM D7314 ASTM D6371 ASTM D6079 ASTM D5555-95 ASTM D 1980-87

875 – – 21.4 208

835 187–343 40–55 3.5–5 74 315 45.54
17 315 – –

791.3 65 – 0.58 11.11 463–465 22.31 <
51 1100 – –

789.4 78 – 1.13 12.78 420–425 29.67 <
51 1057 – –

35.60 – – 8.2 16.4

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3. Experimental design

4. Result and discussion

A Box–Behnken experimental design, was employed using four variables to analyse the response patterns and optimise the process variables. The effect of the A (reaction temperature (°C)), B (molar ratio of alcohol to oil), C (catalyst concentration (wt.%)) and D (reaction time (min)) at three variable levels in the reaction process is shown in Table 2. A total of 29 experiments were conducted separately for getting the experimental response of yield of Karanja oil methyl ester (KOME) and Karanja oil ethyl ester (KOEE). The above variables were independent variables selected for optimisation. The coded and uncoded levels of the independent variables used for the transesterification of KO are given in Table 2.

4.1. Transesterification process The experimental and predicted values for biodiesel yield responses at the design points and all the four variables in uncoded form are given in Table 3 for both methanol and ethanol. The regression equations (1) and (2) for the determination of predicted values of output parameter (i.e. biodiesel yield) for KOME (YKOME) and KOEE (YKOEE) transesterification respectively are given as follows:

Y KOME ¼ 90:96 þ 2:65  A
0:91  B
1:51  C þ 0:033  D þ 1:75  A  B þ 4:33  A  C þ 3:22  A  D
0:25  B  C
3:52  B  D þ 3:1  C  D
10:45  A2
29:54  B2
12:31  C 2
6:82  D2

3.1. Statistical analysis

Y KOEE ¼ 74:98
0:62  A
5:78  B
1:2  C þ 1:08  D þ 2:7  A  B þ 0:38  A  C
0:05  A  D
0:25  B  C

The Design Expert 9.0.6.2 software was used for the regression and graphical analysis of the data. The highest value of biodiesel yield was taken as the response of the design experiment for transesterification process. The experimental data obtained by the above procedure were analysed by the response surface regression using the following polynomial equation:

A ¼ b0 þ

þ 1:25  B  D þ 0:98  C  D
3:92  A2
5:61  B2
1:86  C 2 þ 1:06  D2

j¼1

ð2Þ

The graph between the predicted and actual biodiesel yield (%) given in Fig. 1 (Fig. 1(a) for methanolysis and (b) for ethanolysis) shows that the predicted values are quite close to the experimental values, thereby, validating the reliability of the model developed for establishing a correlation between the process variables and the biodiesel yield.

j
1 X n n n X X X bj X j þ bjj X j2 þ bij X i X j þ e j¼1

ð1Þ

i¼1 j¼2

4.2. Impact of process variables on biodiesel yield

where A is the response, i and j are the linear and quadratic coefficients respectively, xi and xj are the uncoded independent variables, n is the number of factors studied and optimised in the experiment. Equation was also validated by carrying out confirmatory experiments.

Fig. 2 shows the effect of different reaction parameters that are catalyst concentration (KOH), reaction temperature, reaction time and alcohol/oil ratio on biodiesel yield.

Table 3 Responses for transesterification of KO using methanol and ethanol as alcohol. Run

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

Temperature (°C)

65 50 80 50 65 65 50 65 65 65 65 65 65 80 80 50 65 65 80 65 65 65 65 50 80 50 65 80 65

Molar ratio

15 10.5 15 15 10.5 10.5 10.5 10.5 10.5 6 15 10.5 10.5 10.5 10.5 6 10.5 6 6 10.5 10.5 6 15 10.5 10.5 10.5 6 10.5 15

Catalyst concentration (wt.%)

0.5 1.25 1.25 1.25 2 0.5 2 1.25 1.25 1.25 1.25 2 1.25 1.25 0.5 1.25 1.25 2 1.25 0.5 1.25 0.5 1.25 1.25 1.25 0.5 1.25 2 2

Time (min)

90 120 90 90 120 120 90 90 90 60 60 60 90 120 90 90 90 90 90 60 90 90 120 60 60 90 120 90 90

KOME

KOEE

Actual value

Predicted value

Actual value

Predicted value

51.3 74.3 52.6 45.6 76.1 71 55.7 90.24 90.24 52.9 62.8 66.2 91 82.6 68.9 52.6 91 50.8 52.6 73.5 92.3 55.6 46.1 74.6 70 67 50.3 74.9 45.5

49.96 67.853 60.51 45.66 73.453 70.273 59.71 90.96 90.96 51.957 57.177 77.14 90.96 79.593 68.03 50.98 90.96 43.54 62.33 76.407 90.96 51.28 50.203 74.227 73.087 71.39 59.063 73.67 46.44

60.4 73.6 62.1 61.9 73.5 75.1 68.1 78.1 78.6 79.1 62.8 68.3 71.9 73.4 71.8 71.2 76.2 75.9 60.6 73.8 70.1 76.9 66.5 71.5 71.5 71 77.8 70.4 58.4

63.18 73.87 63.59 57.59 75.04 75.48 68.24 74.98 74.98 76.38 62.32 71.92 74.98 72.53 69.4 74.55 74.98 65.48 75.15 75.28 74.98 74.24 66.98 71.61 70.47 71.4 76.04 67.76 60.28

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Fig. 1. Predicted vs. actual KB yield values for (a) methanolysis and (b) ethanolysis.

It is observed from the figure that biodiesel yield increases with increase in temperature and then decreases for both types of reaction. This may be attributed to the fact that higher temperature lower downs the viscosity and faster conversion of fatty acids into alkyl esters is possible [38]. For methanol transesterification, initially the yield increases with increase in molar ratio, achieves peak point and then starts dropping down whereas for ethanol excessive molar ratio results in drop in yield and peak in yield is achieved much earlier in comparison with methanol transesterification. Thus it can be said that optimum molar ratio for ethanol transesterification is less than that for methanol transesterification. Similarly, for catalyst concentration, yield first increases and then decreases with addition of excessive catalyst for both types of reaction. Biodiesel yield increases due to conversion rate of fatty acid esters increases with reaction time.

4.3. Impact of reaction parameters The 3D response curves were drawn to show the impact of independent parameters on dependent ones. The highest projected values were confined by smallest ellipse in the contour diagram. Elliptical contours were obtained when there was a perfect interaction between the independent variables. These graphs were drawn by projecting two other parameters at their zero level, which were shown in Figs. 3–8 for KOME and 9–14 for KOEE. It was observed that there was a substantial relation among two variables and there was a highest projected yield as indicated by the surface confined in the smallest ellipse in the contour diagrams. There is a relationship between the two independent variables and their effects on the response variable (biodiesel yield). For methanolysis as shown in Fig. 4, yield increases with increase in catalyst concentration and

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Fig. 2. Effect of reaction parameters on KB yield for (a) methanolysis and (b) ethanolysis.

Fig. 3. Response surface and contour plots of biodiesel yield vs. catalyst concentration and molar ratio for KOME.

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Fig. 4. Response surface and contour plots of biodiesel yield vs. catalyst concentration and temperature for KOME.

Fig. 5. Response surface and contour plots of biodiesel yield vs. molar ratio and temperature for KOME.

Fig. 6. Response surface and contour plots of biodiesel yield vs. time and catalyst concentration for KOME.

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Fig. 7. Response surface and contour plots of biodiesel yield vs. time and molar ratio for KOME.

Fig. 8. Response surface and contour plots of biodiesel yield vs. time and temperature for KOME.

temperature but a downward trend is seen with excessive increase. This might be due to fact that higher % of catalyst aids to the side reactions of tri-glycerides. Therefore less % of tri-glycerides are available to get converted into methyl esters. Moreover, excessive catalyst results in emulsions which ultimately reflects on higher viscosity. In addition to it, recovery of biodiesel by removal of side products formed during the reaction also becomes an expensive process [38]. The optimum molar ratio alcohol holds a significant role among different reaction parameters to decide overall biodiesel yield. Lesser molar ratio will affect conversion ability of tri-glycerides into methyl esters. On the other hand, higher molar ratio may lower down the yield. MeOH causes emulsification of polar hydroxyl groups of glycerol. This emulsification favours backward reaction which causes reduction in biodiesel yield. However, the transesterification reaction is reversible in nature, so excess amount of alcohol is required to keep the reaction in the forward direction. The above facts are correlating with the plots in Figs. 3,

5 and 7 as when methanol was used for transesterification, yield increases initially with increase in molar ratio but after achieving peak point, it starts dropping down. Effect of temperature is minimal at higher reaction time as the longer period of reaction allows the reaction to reach higher yield even though at low reaction temperature. Figs. 9–14 show that yield starts reducing as molar ratio of ethanol to oil becomes excessive. This shows that optimum molar ratio for ethanol transesterification is less than methanol. But, ethanolysis requires more time to achieve equilibrium than methanolysis. This can be attributed to the fact that methanol is more reactive than ethanol. In addition, when methanolysis process was conducted at high temperature and longer reaction time, the yield suffers a slight decrease as the elevated temperature encourages decomposition during methanolysis reduces the biodiesel yield due to prolonged reaction period. It can be concluded from above that methanolysis is temperature dependent whereas ethanolysis is time dependent for biodiesel yield.

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Fig. 9. Response surface and contour plots of KB yield of biodiesel yield vs. catalyst concentration and molar ratio for KOEE.

Fig. 10. Response surface and contour plots of KB yield of biodiesel yield vs. catalyst concentration and temperature for KOEE.

5. Optimisation of parameters The optimisation of individual responses was performed to maximise biodiesel yield based on basis mathematical equations. The optimum process parameters are given in Table 4. Predicted response is found to be in good agreement with the experimental results as reported in Table 5 and also it is compared with some of the related work found in the literature. Karanja biodiesel yield was of 91.05% for methanolysis at optimised reaction condition whereas for ethanolysis, yield obtained was 77.4%. The lesser yield can be due to the less reactivity of ethanol as compared to methanol and difficult separation from glycerine. As comparing with the results from the literature, it has been observed that as we switch from methanol to ethanol for biodiesel production, yield gets lowered. Most of the studies found did experimental optimisation. Likozar et al. [40] also observed similar results for biodiesel production with different short chain alcohols and alkyl ester conversion in range of 80.2–99.9%. For Karanja

biodiesel, Dwivedi and Sharma [41] observed to have maximum yield of 98.4% at optimised conditions whereas in this study yield for methanolysis was 91.05%. This may be due to the reason that in the previous study feedstock used was having low FFA (0.7%) whereas in the present study FFA was found to be higher that 8.2% which also demanded pre-esterification with acid catalyst. Also more time and temperature are required to reach equilibrium which directly corresponds to higher FFA in oil. Table 4 Optimum process parameters for biodiesel yield. Name

Goal

Lower limit

Upper limit

Reaction temperature (°C) Molar ratio (alcohol:oil) Catalyst concentration (wt.%) Reaction time (min) KOME yield (%) KOEE yield (%)

Within range Within range Within range Within range Maximise Maximise

50 6:1 0.5 60 – –

80 15:1 2 120 92.3 79.1

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Table 5 Results of model validation under optimum conditions. S. no.

Biodiesel

Alcohol

Alcohol/oil molar ratio

Reaction temperature (°C)

Catalyst loading (wt.%)

Reaction time (min)

Predicted biodiesel yield (%)

Experimental biodiesel yield (%)

Reference

1. 2. 3. 4. 7.

Karanja Karanja Jatropha curcas Jatropha curcas Pongamia

Methanol Ethanol Methanol Ethanol Methanol

10.44:1 8.42:1 6:1 6:1 11.06:1

66.8 61.3 60 60 56.6

1.22 1.21 1 1 1.43

90.78 120 – – 81.4

91.15 78.25 – – 100

91.05 77.4 98 92 98.4

This study This study [39] [39] [41]

Fig. 11. Response surface and contour plots of KB yield of biodiesel yield vs. molar ratio and temperature for KOEE.

Fig. 12. Response surface and contour plots of biodiesel yield vs. time and catalyst concentration for KOEE.

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Fig. 13. Response surface and contour plots of biodiesel yield vs. time and molar ratio for KOEE.

Fig. 14. Response surface and contour plots of biodiesel yield vs. time and temperature for KOEE.

Hanh et al. [42] also observed decrease in conversion for ethanol as compared to methanol. For production of biodiesel from triolein, about 70% conversion was found for methanol whereas for ethanol conversion was lowered down by 1–2%. 6. Conclusion The present study has discussed the comparison between methanolysis and ethanolysis of Karanja biodiesel and attempt has been made to optimise the process variables of transesterification reaction through RSM technique. A yield of 91.05% was achieved by keeping molar ratio of 10.44:1 for methanol using 1.22% w/w KOH as catalyst for 90.78 min at the temperature of 66.8 °C for methanolysis whereas for ethanolysis, optimised reaction conditions were, 8.42:1 molar ratio, 61.3 °C reaction temperature

with 1.21% of catalyst and 120 min of reaction time to obtain yield of 77.4%. It was concluded that for methanolysis, temperature plays most significant role in biodiesel yield whereas ethanolysis mainly depends upon reaction time due to its less reactivity. From comparison of both processes, it was observed that catalyst concentration was having negligible effect with respect to alcohol used for transesterification whereas temperature and molar ratio played key role. Also it was observed that separation of ethyl esters is difficult from glycerine in comparison with methyl esters. Thus, ethanol can be recommended as an acyl acceptor for transesterification reaction, though yield obtained is lesser and more time is required to complete the reaction than that for methanol but as it is derived from bio-based resources and also promoted by government of India as potential source of biofuel, thus giving an advantage for completely renewable biodiesel.

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7. Future scope of study In the present study, biodiesel was produced from Karanja oil with help of methanol and ethanol to understand the effect of alcohol on biodiesel yield and reaction parameters were optimised by Response surface methodology. Grey relational analysis or fuzzy grey relational analysis can be implemented to test and verify the correlation among effect factors for different alcohols on biodiesel production [43,44]. To have further improvement in biodiesel yield, scope lies in use of heterogeneous catalysts and nontraditional biodiesel production techniques such as microwave assisted transesterification reaction. Acknowledgment One of the authors (Puneet Verma) acknowledges the financial support from the Ministry of Human Resource Development (MHRD), Government of India, in the form of a research scholarship of graduate studies to carry out this work. References [1] Takase M, Zhao T, Zhang M, Chen Y, Liu H, Yang L, et al. An expatiate review of neem, jatropha, rubber and Karanja as multipurpose non-edible biodiesel resources and comparison of their fuel, engine and emission properties. Renew Sustain Energy Rev 2015;43:495–520. [2] Agarwal AK, Khurana D, Dhar A. Improving oxidation stability of biodiesels derived from Karanja, Neem and Jatropha: step forward in the direction of commercialisation. J Clean Prod 2015;2015(107):646–52. [3] Bala VSS, Thiruvengadaravi KV, Kumar PS, Premkumar MP, Kumar VV, Subash sankar S, et al. Removal of free fatty acids in Pongamia pinnata (Karanja) oil using divinylbenzene-styrene copolymer resins for biodiesel production. Biomass Bioenergy 2012;37:335–41. [4] Verma P, Sharma MP, Dwivedi G. Impact of alcohol on biodiesel production and properties. Renew Sustain Energy Rev 2016;56:319–33. [5] Dwivedi G, Sharma MP. Cold flow behaviour of biodiesel – a review. Int J Renew Energy Res 2013;3(4):827–36. [6] Nabi MN, Hoque SMM, Akhter MS. Karanja (Pongamia pinnata) biodiesel production in Bangladesh, characterization of Karanja biodiesel and its effect on diesel emissions. Fuel Process Technol 2009;90:1080–6. [7] Verma P, Sharma MP, Dwivedi G. Potential use of eucalyptus biodiesel in compressed ignition engine. Egypt J Petrol 2016;25. http://dx.doi.org/10.1016/ j.ejpe.2015.03.00. [8] Verma P, Sharma MP, Dwivedi G. Evaluation and enhancement of cold flow properties of palm oil and its biodiesel. Energy Rep 2016;2:8–13. [9] Atadashi IM, Aroua MK, Aziz ARA, Sulaiman NMN. Production of biodiesel using high free fatty acid feedstocks. Renew Sustain Energy Rev 2012;16:3275–85. [10] Baiju B, Naik MK, Das LM. A comparative evaluation of compression ignition engine characteristics using methyl and ethyl esters of Karanja oil. Renew Energy 2009;34:1616–21. [11] Mofijur M, Rasul MG, Hyde J, Azad AK, Mamat R, Bhuiya MMK. Role of biofuel and their binary (diesel–biodiesel) and ternary (ethanol–biodiesel–diesel) blends on internal combustion engines emission reduction. Renew Sustain Energy Rev 2016;53:265–78. [12] Verma P, Sharma MP, Dwivedi G. Investigation of metals and antioxidants on stability characteristics of biodiesel. Mater Today: Proc 2015;2:3196–202. [13] Dwivedi G, Sharma MP. Effect of metal on stability and cold flow property of pongamia biodiesel. Mater Today: Proc 2015;2:1421–6. [14] Zanuttini MS, Pisarello ML, Querini CA. Butia Yatay coconut oil: process development for biodiesel production and kinetics of esterification with ethanol. Energy Convers Manage 2014;85:407–16. [15] Verma P, Sharma MP, Dwivedi G. Operational and environmental impact of biodiesel on engine performance: a review of literature. Int J Renew Energy Res 2015;5(4):961–70. [16] Aniya VK, Muktham RK, Alka K, Satyavathi B. Modeling and simulation of batch kinetics of non-edible karanja oil for biodiesel production: a mass transfer study. Fuel 2015;161:137–45. [17] Rathore V, Tyagi S, Newalkar B, Badoni RP. Jatropha and Karanja oil derived DMC–biodiesel synthesis: a kinetics study. Fuel 2015;140:597–608. [18] Prabhavathi Devi BLA, Reddy TVK, Lakshmi KV, Prasad RBN. A green recyclable SO3H-carbon catalyst derived from glycerol for the production of biodiesel from FFA-containing Karanja (Pongamia glabra) oil in a single step. Bioresour Technol 2014;153:370–3.

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