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Industrial Crops and Products 60 (2014) 130–137

Contents lists available at ScienceDirect

Industrial Crops and Products

jo u r n al homep age: www.elsev ier .com/ locate / indcrop

ffect of Croton megalocarpus, Calophyllum inophyllum, Moringaleifera, palm and coconut biodiesel–diesel blending on theirhysico-chemical properties

.E. Atabania,b,∗∗, M. Mofijura,∗, H.H. Masjukia, Irfan Anjum Badruddina,.A. Kalama, W.T. Chonga

Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, MalaysiaDepartment of Mechanical Engineering, Erciyes University/Erciyes Teknopark A.S , Yeni Mahalle As ıkveysel Bulvarı Erciyes Teknopark Tekno 3 Binası 2.at No: 28, 38039, Melikgazi/Kayseri, Turkey

r t i c l e i n f o

rticle history:eceived 6 February 2014eceived in revised form 5 June 2014ccepted 9 June 2014

eywords:roton megalocarpus methyl esteralophyllum inophyllum methyl esteroringa oleifera methyl ester

hysico-chemical properties

a b s t r a c t

By 2050, it is predicted that biofuels will provide 27% of total transport fuel and avoid around 2.1 Gt CO2

emissions per year when produced sustainably. Biodiesel is a renewable fuel that can be produced bytrans-esterification in any climate using already developed agricultural practices. This paper aims to studyvarious physical and chemical properties of biodiesel synthesized from edible and non-edible feedstocks.These feedstocks include Croton megalocarpus, Calophyllum inophyllum, Moringa (Moringa oleifera), palm(Elaeis guineensis) and coconut (Cocos nucifera). The physical and chemical properties of biodiesel–dieselblends were also presented. Furthermore, the regression analysis method was used to predict the prop-erties of biodiesel blends. It has been found that blending of diesel with biodiesel has resulted in muchimprovement in kinematic viscosity, density, calorific value and oxidation stability. However, flash point

lendingegression analysis

and viscosity index decrease as the percentage of diesel increases. Moreover, the mathematical relation-ships developed in this study show a high regression values (R2) between properties and biodiesel–dieselblends. As a conclusion, it is believed that the outcome of this study gives the readers valuable results thathelp to predict the properties of biodiesel and its blends with diesel which are substantial parameters inthe design of fuel system for biodiesel engine.

. Introduction

The global energy demand is increasing due to increasingconomy. This increasing demand has generated the interest forlternative energy resources. In this perspective, renewable energyrom natural resources is getting momentum to be alternativenergy sources since that re-generable or replenish-able. It haseen anticipated that, by 2050 biofuels will provide 27% of total

ransport fuel, and avoid around 2.1 Gt CO2 emissions per yearhen produced sustainably (IEA, 2012). Biodiesel (technically

nown as a mono alkyl ester) is a renewable fuel that can be pro-uced in any climate using already developed agricultural practicesAmani et al., 2013; Ávila and Sodré, 2012; Mofijur et al., 2014a).

∗ Corresponding authors at: Department of Mechanical Engineering, Universityf Malaya, Malaysia. Tel.: +6 3 79674448.∗∗ Corresponding authors at: Department of Mechanical Engineering, Erciyes Uni-ersity, Turkey. Tel.: +905366063795.

E-mail addresses: a atabani2@msn.com (A.E. Atabani), mofijduetme@yahoo.comM. Mofijur).

ttp://dx.doi.org/10.1016/j.indcrop.2014.06.011926-6690/© 2014 Elsevier B.V. All rights reserved.

© 2014 Elsevier B.V. All rights reserved.

Biodiesel provides considerable reductions in carbon monoxide(CO), unburned hydrocarbons (UHC), and particulate emissions(PM) from diesel engines compared to fossil diesel. Biodiesel canbe obtained by applying trans-esterification processes to vegetableoils, animal fats, used cooking oil and waste grease from restaurants(Mofijur et al., 2014b, 2013). Biodiesel can be available in both itsneat form (B100) and in blends with petroleum diesel (for exam-ple: B2, B5, B20). The primary feedstock used to make biodiesel inEurope is rapeseed while Soybean is the primary feedstock in USA(Central Carolina Community College, 2013).

Therefore, there is need to find alternate feedstocks. Non-edibleseed oils like Jatropha (Jatropha curcas), Croton megalocarpus andCalophyllum inophyllum are some examples of wild trees that cangrow on any type of soil (Silitonga et al., 2011; Atabani et al.,2012, 2013a,c; Rahman et al. 2014). The physical and chemicalproperties of any fuel are significant factors in the design of fuel

system for biodiesel engines. Therefore, this study aims to study indetails about some of the main the physical and chemical proper-ties of biodiesel synthesized from edible and non-edible biodieselfeedstocks. The properties include kinematic viscosity, density,

A.E. Atabani et al. / Industrial Crops an

Nomenclature

CV Calorific valueFP Flash pointKV Kinematic viscosity

vpscbtp

acbTvei

2

ibho

aJdfivtvdfrcbiheicahtbodcvplasum

LRA Linear regression analysisPRA Polynomial regression analysis

iscosity index, cloud point, pour point, and cold filter pluggingoint, flash point, calorific value and oxidation stability. These feed-tocks include C. megalocarpus, C. inophyllum, Moringa, palm andoconut. The physical and chemical properties of biodiesel–diesellends ratios of (B10–B100) were fully covered and presented inhis study. Although accurate experimental data can be used toredict various properties of biodiesel–diesel blends.

However, it is difficult to provide all the data particularly over large blends range. Therefore, this study suggests the polynomialurve fitting method to predict the properties of the blends at anylends ratio. This method was in fact not covered well in literature.herefore, it is believed that the current study gives the readersaluable results that help them understand and predict the prop-rties of biodiesel from both edible and non-edible feedstocks andts blends with diesel.

. Literature review

Prediction of physical and chemical properties of biodiesel andts blends is vital in the design of fuel spray, atomization, and com-ustion and emission system for diesel engines. Several studiesave been done to investigate the physical and chemical propertiesf biodiesel and its blends with diesel.

Oghenejoboh and Umukoro (2011) investigated the fuel char-cteristics of biodiesel produced from palm oil, palm kernel oil,atropha seed oil and rubber seed oil as compared to petroleumiesel. The authors indicated that blending of biodiesel from theseeedstocks with diesel has resulted in an increase in the heat-ng value, decrease in density, cloud point, pour point, kinematiciscosity and flash point of biodiesel. Rao et al. (2010) assessedhe mathematical relationships between density, viscosity, calorificalue and flash point among numerous biodiesel samples. Theeveloped mathematical relationships between these propertiesollowed the linear regression and showed high coefficient ofegression (R2). Demirbas (2008) has developed equations to cal-ulate higher heating values of various vegetable oils and theiriodiesels from their viscosity, density or flash point. The find-

ngs of this study showed that there is high regression betweenigher heating value, viscosity, density and flash point for veg-table oil and biodiesel samples. Giakoumis (2013) reviewed andnvestigated the physical and chemical properties and the fatty acidomposition of 26 biodiesel feedstocks (comprising of 22 ediblend non-edible vegetable oils and four animal fats). The authoras correlated biodiesels physical and chemical properties withhe degree of unsaturation. An excellent correlation was foundetween the degree of unsaturation and the iodine number. More-ver, good correlations were also established for cetane number,ensity, pour point, carbon content, number of carbon atoms, stoi-hiometric air–fuel ratio, T90 distillate temperature, kinematiciscosity, lower and higher heating values, cloud point and flashoint. Ramírez-Verduzco et al. (2012) derived four empirical corre-

ations to estimate the cetane number, kinematic viscosity, density,

nd higher heating value of fatty acid methyl esters from twotructural features of molecules (molecular weight and degree ofnsaturation). The predicted values of the cetane number, kine-atic viscosity, density and higher heating value of biodiesel have

d Products 60 (2014) 130–137 131

been found to be in a good agreement with the experimental values.Krishna et al. (2008) attempted to improve the cold flow proper-ties of biodiesel derived from four feedstocks; Tallow (14 ◦C) Canola(−2 ◦C), Soy (0 ◦C) and Yellow grease (7 ◦C). For instance, blendingTallow biodiesel with Soy biodiesel at three different percent-ages (20%, 50% and 80% respectively) has resulted in a remarkableimprovement in the cloud point of tallow biodiesel from 14 ◦C(100% Tallow) to 12 ◦C (80% Tallow) to 7 ◦C (50% Tallow) to 4 ◦C(20% Tallow) respectively. Moreover, blending of Tallow biodieselwith Canola biodiesel in three different percentages (20%, 50% and80%) has resulted in a remarkable improvement of the cloud pointof tallow biodiesel from 14 ◦C (100% Tallow) to 12 ◦C (80% Tal-low) to 7 ◦C (50% Tallow) to −1 ◦C (20% Tallow) respectively. Theauthors also studied the effect of blending biodiesel with #2 oilhaving a very low cloud point and found a remarkable reductionin the cloud point of Tallow, Soy and Yellow grease biodiesels.As a conclusion, the authors concluded that the cloud points ofbiodiesel blends correlated well with the saturated fraction. Thelower the fraction of saturates, the better the cold flow. How-ever, stability might be affected. Atabani et al. (2013b) discussedthe concept of biodiesel–biodiesel blending to improve some ofthe properties such as viscosity, cloud, pour and cold filter plug-ging point. For instance, blending of Sterculia foetida methyl ester(SFME) and coconut methyl ester (COME) has resulted in a remark-able improvement in the viscosity of SFME. It was also found thatblending has improved the cold flow properties of palm oil methylester (PME), C. inophyllum methyl ester (CIME) and J. curcas methylester (JCME) respectively. Moreover, the authors have estimatedthe properties of other biodiesel–biodiesel blends using the poly-nomial curve fitting method and the mathematical relationshipsbetween these properties and the blends showed high coefficientof regression (R2 > 0.96). Chen et al. (2011) studied the propertymodification of Jatropha methyl ester by blending with palm andsoybean methyl esters. Jatropha methyl ester was blended withpalm oil and soybean methyl esters at various weight ratios andevaluated for fuel properties as compared to the relevant specifica-tions. The cold filter plugging point and oxidation stability weresignificantly increased through the blending of Jatropha methylester with the palm oil methyl ester, whereas the IV decreased.The oxidation stability of the blend could be greater than 6 h whenthe PME comprised 60 wt.% or higher in the blended biodiesel.However, the cold filter plugging point value of the blend hadalready increased to 3 ◦C when the fraction of the PME was 40 wt.%.This was the result of an increased saturated FAME content in thepalm oil methyl ester. The authors concluded that the optimumJatropha–palm methyl ester blend may be comprised of the JMEand PME at a weight ratio of 80:20 and have the CFPP, IV, and oxi-dation stability of −1 ◦C, 98.84 g I2/100 g, and 4.52 h, respectively.The authors have also developed a multiple linear regression modelwith a high regression coefficients (R2) to predict the CFPP and IVof the biodiesel blends based on methyl linoleate (ML) and methyloleate (MO) contents (in wt.%) using LINEST (the multiple linearregression worksheet function) in Microsoft Excel 2003.

3. Materials and methods

3.1. Materials and chemicals

Crude C. megalocarpus and Moringa oleifera oils, coconut methylester, palm oil methyl ester and C. inophyllum methyl ester weresupplied through a personal communication. Table 1 shows thephysico-chemical properties of crude C. megalocarpus and M.

oleifera oils, (Atabani et al., 2013a). Table 2 shows the Physico-chemical properties of coconut, palm oil and C. inophyllum methylesters. All other chemicals, reagents and accessories were pur-chased from local market.

132 A.E. Atabani et al. / Industrial Crops and Products 60 (2014) 130–137

Table 1Properties of crude C. megalocarpus oil and M. oleifera oils (Atabani et al., 2013a).

Properties Unit Crude Croton oil Crude Moringa oil

Kinematic viscosity at 40 ◦C mm2/s 29.84 43.46Kinematic viscosity at 100 ◦C mm2/s 7.28 9.02Dynamic viscosity at 40 ◦C mPa.s 27.15 38.99Flash point ◦C 235 263Cold filter plugging point ◦C 10 18Density kg/m3 910.0 897.1Acid value mg KOH/g oil 12.07 8.62Calorific value MJ/kg 39.33 39.76Oxidation stability h at 110 ◦C 0.14 41.75Viscosity index – 224.20 195.20Transmission %T 87.5 69.2Absorbance Abs 0.06 0.16Refractive index – 1.47 1.46

Table 2Properties of coconut, C. inophyllum and palm oil methyl esters.

Properties Unit COME CIME POME

Dynamic viscosity at 40 ◦C mPa s 3.51 5.04 3.97Kinematic viscosity at 40 ◦C mm2/s 4.06 5.74 4.62Kinematic viscosity at 100 ◦C mm2/s 1.57 2.03 1.77Density at 40 ◦C kg/m3 866.4 877.4 858.9Viscosity index – 180.7 174.9 195.8Cloud point (CP) ◦C 0 10 10Pour point (PP) ◦C −4 11 11Cold filter plugging point (CFPP) ◦C −4 9 11Oxidation stability h 5.12 9.42 2.41Calorific value MJ/kg 38.00 39.27 39.91Flash point ◦C 120.5 93.5 182.5

COME = Coconut oil methyl ester.CIME = C. inophyllum methyl ester.POME = Palm oil methyl ester.

Table 3Equipment list.

Property Equipment Manufacturer Test method

Kinematic viscosity SVM 3000 (Anton Paar, UK) ASTM D445Density SVM 3000 (Anton Paar, UK) ASTM D1298Oxidation stability 873 Rancimat (Metrohm, Switzerland) EN ISO 14112Flash Point Pensky-martens flash point -automatic NPM 440 (Norma lab, France) ASTM D93Cloud and Pour point Cloud and Pour point tester – automatic NTE 450 (Norma lab, France) ASTM D2500, ASTM D97Cold filter plugging point Cold filter plugging point tester – automatic NTL 450 (Norma lab, France) ASTM D6371Caloric value C2000 basic calorimeter (IKA, UK) ASTM D240

3

tms

TS

Viscosity index SVM 3000

.2. Equipment list

Table 3 displays the equipment used in this experiment to study

he important physical and chemical properties along with the test

ethods used to perform the analysis according to ASTM D6751tandard.

able 4ummary of biodiesel production process from crude C. megalocarpus and M. oleifera oils.

Process parameter Process specification

Process type Acid base catalysed trans-esteReaction temperature 60 ◦C for both processesCatalyst used and concentration 98% pure sulphuric acid (1% v

trans-esterification reactionAlcohol used and molar ration (Methanol) 12:1 for esterificaReaction time 3 h for esterification process aSetting time 24 hStirring speed 600 rpm

(Anton Paar, UK) N/A

3.3. Biodiesel production from crude C. megalocarpus and M.oleifera oils

The production of biodiesel from crude C. megalocarpus andM. oleifera was carried out using 1 L glass reactor (Brand: Favorit)equipped with a reflux condenser, overhead stirrer (IKA EUROSTAR

rification

/v) for esterification reaction and 99% pure potassium hydroxides (1% m/m) for

tion process and 6:1 for trans-esterification processnd 2 h for trans-esterification process

A.E. Atabani et al. / Industrial Crops and Products 60 (2014) 130–137 133

Table 5aPhysico-chemical properties of C. megalocarpus methyl ester and its blends with diesel.

B0 B10 B20 B30 B40 B50 B60 B70 B80 B90 B100

Dynamic viscosity at 40 ◦C 2.69 2.89 2.92 3.00 3.05 3.13 3.20 3.28 3.34 3.44 3.52Kinematic viscosity at 40 ◦C 3.23 3.46 3.50 3.57 3.61 3.69 3.75 3.83 3.88 3.97 4.05Kinematic viscosity at 100 ◦C 1.24 1.34 1.37 1.42 1.45 1.48 1.52 1.55 1.58 1.62 1.66Density at 40 ◦C 827.2 831.2 835.6 840.3 844.1 848.1 852.7 855 861.6 866 867.2Viscosity index 90 119.3 139.8 183.7 197.4 202 228.1 238.9 245.8 255.2 266.4Cloud point (CP) 8 6 5 5 4 4 3 −1 −1 −4 −4Pour point (PP) 0 0 0 0 3 2 2 2 −1 −1 −3Cold filter plugging point (CFPP) 5 7 7 6 6 5 4 0 −4 −6 −4Oxidation stability N/D 19.5 17.5 N/D 7.91 N/D 3.96 N/D 2.4 N/D 1.1Calorific value 45.30 44.90 44.23 43.48 42.81 42.37 41.89 41.17 40.88 40.06 39.53Flash point 68.5 83.5 86.5 N/D 92.5 N/D 100.5 N/D 118.5 N/D 178.5

N/D = not determined.

Table 5bPhysico-chemical properties of C. inophyllum methyl ester and its blends with diesel.

B0 B10 B20 B30 B40 B50 B60 B70 B80 B90 B100

Dynamic viscosity at 40 ◦C 2.69 2.85 3.04 3.21 3.45 3.66 3.90 4.17 4.45 4.77 5.04Kinematic viscosity at 40 ◦C 3.23 3.40 3.61 3.79 4.05 4.28 4.54 4.82 5.12 5.46 5.74Kinematic viscosity at 100 ◦C 1.24 1.315 1.39 1.45 1.53 1.60 1.69 1.76 1.85 1.95 2.03Density at 40 ◦C 834.9 838.8 843.3 847.1 851.7 855.8 860 864.5 868.9 873.6 877.4Viscosity index 90 122.5 130.8 139.2 149.7 156.4 159.6 161.6 163.5 168.9 174.9Cloud point (CP) 8 8 8 7 7 7 7 7 8 9 10Pour point (PP) 0 1 1 4 4 6 6 6 8 8 11Cold filter plugging point (CFPP) 5 7 6 5 4 4 2 2 4 7 9

8

N

dm

3

M(23

diipvwmatp

Y

TP

N

Calorific value 45.30 44.57 44.06 43.27Flash point 68.5 72.5 73.5 N/D

/D = not determined.

igital), thermometer and sampling outlet. Table 4 shows the sum-ary of biodiesel production process.

.4. Biodiesel–diesel blending

Blending of C. megalocarpus, palm oil, Coconut, C. inophyllum and. oleifera methyl esters with diesel was prepared at different ratios

0–100% by volume) using a magnetic stirrer (IKA® C-MAG HS 7) at000 rpm for 30 min and shaker (IKA® KS 130 basic) at 400 rpm for0 min.

In this study the effect of biodiesel and diesel blending atifferent ratios (0–100% by volume) on some physical and chem-

cal properties has been studied and presented. These propertiesnclude kinematic viscosity, viscosity index, density, cloud point,our point, cold filter plugging point, oxidation stability, calorificalue and flash point. In this paper, polynomial curve fitting methodas used to estimate the properties of other biodiesel blends. Thisethod is an attempt to describe the relationship between vari-

ble X as a function of available data and a response Y, which seeks

o find a smooth curve that best fits the data. Mathematically, aolynomial of order k in X is expressed in the following form:

= Co + C1X + C2X2 + . . ... + CkXk (1)

able 5chysico-chemical properties of coconut oil methyl ester and its blends with diesel.

B0 B10 B20 B30

Dynamic viscosity at 40 ◦C 2.69 2.75 2.81 2.89

Kinematic viscosity at 40 ◦C 3.23 3.28 3.34 3.42

Kinematic viscosity at 100 ◦C 1.24 1.30 1.32 1.35

Density at 40 ◦C 834.9 838.1 841.3 844.3

Viscosity index 90 144.7 153.1 155.6

Cloud point (CP) 8 7 7 7

Pour point (PP) 0 0 −15 −12

Cold filter plugging point (CFPP) 5 7 7 7

Oxidation stability N/D N/D 113.06 85.88

Calorific value 45.30 44.53 43.74 43.08

Flash point 68.5 74.5 76.5 N/D

/D = not determined.

42.47 41.78 41.21 40.90 40.33 39.56 39.2775.5 N/D 81.5 N/D 87.5 N/D 93.5

4. Results and discussion

4.1. Physico-chemical properties of biodiesel

The quality of biodiesel depends upon composition of feed-stock, production process, storage and handling. Biodiesel qualityis assessed through the determination of physical and chemicalproperties. The physical and chemical properties of C. megalo-carpus, C. inophyllum, coconut, palm oil and M. oleifera methylesters are presented in Table 5a, Table 5b, Table 5c, Table 5d,Table 5e.

The main findings from this table show that Croton methyl esterpossesses the lowest kinematic viscosity at 40 ◦C of 4.05 mm2/s fol-lowed by coconut methyl ester of 4.06 mm2/s and palm methylester of 4.62 mm2/s. It was found that Croton methyl ester has thebest viscosity index of 266.4 followed by palm methyl ester 195.8and Moringa methyl ester of 184.6.

C. megalocarpus and coconut methyl esters were to found to havegood cold flow properties compared to palm, Moringa and Calo-

phyllum methyl esters. It can be seen that Croton methyl ester hasthe lowest cloud point of −4 ◦C while coconut methyl ester has thelowest pour point of −4 ◦C while both Croton and coconut methylesters possess the lowest cold filter plugging point of −4 ◦C. On

B40 B50 B60 B70 B80 B90 B100

2.96 3.03 3.12 3.22 3.31 3.41 3.513.49 3.57 3.65 3.75 3.84 3.95 4.061.37 1.41 1.43 1.47 1.50 1.54 1.57847.5 850.6 853.7 856 859.9 863.2 866.4155.9 166.2 168.2 175 177.8 179.8 180.77 6 6 4 0 0 0−9 −9 −6 −6 −6 −4 −46 5 2 1 −1 −4 −4N/D 66.44 56.55 41.05 32.08 23.23 5.1242.20 41.46 40.82 40.04 39.39 38.62 38.0081.5 N/D 89.5 N/D 102.5 N/D 120.5

134 A.E. Atabani et al. / Industrial Crops and Products 60 (2014) 130–137

Table 5dPhysico-chemical properties of M. oleifera methyl ester and its blends with diesel.

B0 B10 B20 B30 B40 B50 B60 B70 B80 B90 B100

Dynamic viscosity at 40 ◦C 2.69 2.94 3.06 3.19 3.35 3.49 3.66 3.80 3.99 4.19 4.34Kinematic viscosity at 40 ◦C 3.23 3.54 3.67 3.81 3.99 4.14 4.32 4.48 4.68 4.89 5.05Kinematic viscosity at 100 ◦C 1.24 1.35 1.39 1.47 1.52 1.55 1.64 1.66 1.74 1.81 1.84Density at 40 ◦C 827.2 830.6 833.6 836.4 840.1 843.4 846.7 849.8 853.5 857.1 859.6Viscosity index 90 101.1 111.6 N/D N/D 140 N/D 157.6 174.7 181.4 184.6Cloud point (CP) 8 7 8 9 12 13 14 15 17 18 19Pour point (PP) 0 3 6 9 10 12 14 17 16 19 19Cold filter plugging point (CFPP) 5 6 6 7 8 9 12 15 15 17 18Oxidation stability N/D N/D N/D N/D 88.84 N/D 71.27 N/D 64.25 N/D 26.2Calorific value 45.30 44.74 43.98 43.86 43.27 42.64 41.84 41.52 40.91 40.38 40.05Flash point 68.5 79.5 82.5 N/D 94.5 N/D 105.5 N/D 114.5 N/D 150.5

N/D = not determined.

Table 5ePhysico-chemical properties of Palm oil methyl ester and its blends with diesel.

B0 B10 B20 B30 B40 B50 B60 B70 B80 B90 B100

Dynamic viscosity at 40 ◦C 2.69 2.83 2.91 3.03 3.15 3.26 3.38 3.53 3.67 3.84 3.97Kinematic viscosity at 40 ◦C 3.23 3.38 3.47 3.60 3.73 3.85 3.99 4.15 4.29 4.48 4.62Kinematic viscosity at 100 ◦C 1.24 1.33 1.36 1.41 1.46 1.50 1.54 1.60 1.65 1.71 1.77Density at 40 ◦C 834.9 837.9 840.1 840 844.5 848.1 849.2 851.8 854.4 856.8 858.9Viscosity index 90 140.3 149.8 159.9 167.3 172.7 177.5 185.6 188.0 188.7 195.8Cloud point (CP) 8 8 7 7 7 6 5 7 8 11 10Pour point (PP) −1 −1 −1 −1 2 2 5 8 8 8 11Cold filter plugging point (CFPP) 5 6 4 4 3 3 3 6 9 11 11Oxidation stability N/D 113.64 65.47 33.42 31.03 19.44 13.5 10.14 6.41 4.15 2.41Calorific value 45.30 44.65 43.99 43.32 42.97 42.04 41.72 41.17 40.75 40.18 39.90Flash point 68.5 77.5 78.5 N/D 85.5 N/D 93.5 N/D 112.5 N/D 182.5

N/D = not determined

Table 6Mathematical relations between blends ration and physico-chemical properties.

Property Blends Mathematical equation R2

Kinematic viscosity at 40 ◦C Croton methyl ester–diesel 0.7205x + 3.33 0.9727Calophyllum methyl ester–diesel 2.5379x + 3.1036 0.9911Coconut methyl ester–diesel 0.8337x + 3.186 0.9902Palm methyl ester–diesel 1.3841x + 3.2024 0.9948Moringa methyl ester–diesel 1.7446x + 3.2962 0.996

Kinematic viscosity at 100 ◦C Croton methyl ester–diesel 0.3787x + 1.2896 0.9796Calophyllum methyl ester–diesel 0.7883x + 3.2287 0.9976Coconut methyl ester–diesel 0.3082x + 1.2602 0.9933Palm methyl ester–diesel 0.4976x + 1.2616 0.9941Moringa methyl ester–diesel 0.581x + 1.2795 0.9895

Density at 40 ◦C Croton methyl ester–diesel 0.043x + 0.8271 0.9997Calophyllum methyl ester–diesel 0.0429x + 0.8346 0.9997Coconut methyl ester–diesel 0.0312x + 0.8349 0.9993Palm methyl ester–diesel 0.0238x + 0.8353 0.9979Moringa methyl ester–diesel 0.0328x + 0.827 0.9993

Viscosity index Croton methyl ester–diesel −134.32x2 + 304.89x + 91.683 0.9835Calophyllum methyl ester–diesel −44.242x2 + 103.13x + 113.02 0.9828Coconut methyl ester–diesel −17.235x2 + 60.243x + 139.2 0.9732Palm methyl ester–diesel −43.106x2 + 106.33x + 130.68 0.9936Moringa methyl ester–diesel −11.088x2 + 108.82x + 89.982 0.9925

Calorific value Croton methyl ester–diesel −5798.5x + 45,323 0.9965Calophyllum methyl ester–diesel −5798.5x + 45,323 0.9828Coconut methyl ester–diesel −7328.9x + 45,232 0.9992Palm methyl ester–diesel −5465.1x + 45100 0.9917Moringa methyl ester–diesel −5363.9x + 45,277 0.9942

Oxidation stability Croton methyl ester–diesel 28.003x2 − 51.792x + 25.173 0.9848Coconut methyl ester–diesel −236.64x3 + 453.53x2 − 382.69x + 171.04 0.9928Palm methyl ester–diesel −417.44x3 + 893.48x2 − 641.88x + 165.28 0.9828Moringa methyl ester–diesel −593.44x3 + 1106.5x2 − 724.66x + 238.14 0.9984

Flash point Croton methyl ester–diesel 336.3x3 − 384.77x2 + 156.15x + 70.097 0.997Calophyllum methyl ester–diesel 10.382x2 + 13.54x + 69.655 0.9888Coconut methyl ester–diesel −236.64x3 + 453.53x2 − 382.69x + 171.04 0.9928Palm methyl ester–diesel 348.01x3 − 366.52x2 + 132.24x + 67.398 0.9947Moringa methyl ester–diesel 169.01x3 − 208.93x2 + 121.23x + 68.147 0.9925

x = Percentage of biodiesel in the blend.

A.E. Atabani et al. / Industrial Crops and Products 60 (2014) 130–137 135

F s metm ethy

tw1p

eplp3

te9

4

tpbisv

ig. 1. Correlation between flash point and kinematic viscosity. (a) C. megalocarpuethyl ester–diesel blends, (d) palm oil methyl ester–diesel blends, (e) M. oleifera m

he other hand it was found that Moringa methyl ester has theorst cold flow properties profile among other methyl ester of

9 ◦C (cloud point), 19 ◦C (pour point) and 18 ◦C (cold filter pluggingoint).

The results of oxidation stability showed that Moringa methylster has the best oxidation stability of 26.2 h followed by Calo-hyllum methyl ester of 9.42 h while Croton methyl ester has the

owest oxidation stability of 1.1 h. Moreover, Moringa methyl esterossesses the highest calorific value of 40,050 kJ/kg compared to8,000 kJ/kg of coconut methyl ester.

The results of flash point show that palm methyl ester hashe highest flash point of 182.5 ◦C, followed by Croton methylster of 187.5 ◦C while Calophyllum methyl ester has flash point of3.5 ◦C.

.2. Physico-chemical properties of biodiesel–diesel blends

Table 5a, Table 5b, Table 5c, Table 5d, Tables 5a–5e presenthe physical and chemical properties of C. megalocarpus, C. ino-hyllum, coconut, palm and M. oleifera methyl esters and their

lends with diesel. Blending of diesel with biodiesel can cause some

mprovement in some properties such as kinematic viscosity, den-ity, calorific value, oxidation stability. However, flash point andiscosity index decrease as the percentage of diesel increases. The

hyl ester–diesel blends, (b) C. inophyllum methyl ester–diesel blends, (c) coconutl ester–diesel blends.

next section will present the mathematical correlation between theblends ration and physical and chemical properties.

4.3. Mathematical relationship between blends ration andphysico-chemical properties

Based on the data in Table 5a, Table 5b, Table 5c, Table 5d,Tables 5a–5e, mathematical equations were developed for thecalculation of oxidation stability, kinematic viscosity, density, vis-cosity index, calorific value and flash point of C. megalocarpus, C.inophyllum, coconut, M. oleifera and palm oil methyl esters and theirblends with diesel. Table 6 presents the developed equations.

4.4. Mathematical relationship between physico-chemicalproperties

4.4.1. Flash point (FP) vs. kinematic viscosity (KV)Fig. 1(a–e) depicts the correlations between kinematic viscosi-

ties and flash points of C. megalocarpus, C. inophyllum, coconut, M.oleifera and palm oil methyl esters as follow:

For (Croton methyl ester–diesel blends):

FP = 183.95 × (KV)2 − 1221.6 × (KV) + 2099.5

R2 = 0.9534(2)

136 A.E. Atabani et al. / Industrial Crops and Products 60 (2014) 130–137

F pus mm ethy

i

ig. 2. Correlation between calorific value and kinematic viscosity. (a) C. megalocarethyl ester–diesel blends, (d) palm oil methyl ester–diesel blends, (e) M. oleifera m

For (Calophyllum methyl ester–diesel blends):

FP = 0.4884 × (KV)2 + 5.1448 × (KV) + 47.913

R2 = 0.9887(3)

For (Coconut methyl ester–diesel blends):

FP = 33.934 × (KV)2 − 188.35 × (KV) + 325.3

R2 = 0.9933(4)

For (Palm methyl ester–diesel blends):

FP = 74.797 × (KV)2 − 517.44 × (KV) + 968.12

R2 = 0.9569(5)

For (Moringa methyl ester–diesel blends):

FP = 13.79 × (KV)2 − 73.438 × (KV) + 164.68(6)

R2 = 0.9724

From this figure, it can be understood that flash point of biodieselncreases with increase in kinematic viscosity.

ethyl ester–diesel blends, (b) C. inophyllum methyl ester-diesel blends, (c) coconutl ester–diesel blends.

4.4.2. Calorific value (CV) vs. kinematic viscosity (KV)Fig. 2(a–e) depicts the correlations between kinematic viscosity

and calorific value of C. megalocarpus, C. inophyllum, coconut, palmand M. oleifera methyl esters as follow:

For (Croton methyl ester–diesel blends):

CV = −2410.4 × (KV)2 + 10, 323 × (KV) + 37, 233

R2 = 0.9891(7)

For (Calophyllum methyl ester–diesel blends):

CV = 560.27 × (KV)2 − 7392.4 × (KV) + 63, 326

R2 = 0.9975(8)

For (Coconut methyl ester–diesel blends):

CV = 33.934 × (KV)2 − 188.35 × (KV) + 325.3

R2 = 0.9933(9)

For (Palm methyl ester–diesel blends):

CV = 1413.7 × (KV)2 + 15, 028 × (KV) + 79, 180

R2 = 0.996(10)

ops an

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the physical properties of biodiesel and engine fuel system design requirement.Int. J. Energy Environ. 1, 919–926.

Silitonga, A.S., Atabani, A.E., Mahlia, T.M.I., Masjuki, H.H., Badruddin, I.A., Mekhilef, S.,2011. A review on prospect of Jatropha curcas for biodiesel in Indonesia. Renew.Sust. Energ. Rev. 15, 3733–3756.

A.E. Atabani et al. / Industrial Cr

or (Moringa methyl ester–diesel blends):

CV = −3063.7 × (KV) + 55, 367

R2 = 0.9912(11)

From this figure, it can be observed that calorific value ofiodiesel increases with decrease in kinematic viscosity.

.5. Sample calculation

From Fig. 1 and based on Table 6 in Section 4.3, it can be seen thathe viscosity of Croton methyl ester–diesel blends can be predictedsing the following equation:

inematic viscosity at 40 ◦C = 0.7205x + 3.33. . .x

≡ (%Croton methyl ester–diesel blends)

Therefore, the viscosity of Croton methyl ester–diesel blends cane predicted based on the above equation as follow:

inematic viscosity (B20) = 0.7205 × (0.2) + 3.33 = 3.4741 mm2/s

. Conclusion

This paper presents the physical and chemical properties ofiodiesel produced from C. megalocarpus, C. inophyllum and M.leifera (non-edible), coconut and palm oil (edible) and their blendsith diesel (B0–B100). These properties include kinematic viscos-

ty, density, viscosity index, cloud point, pour point, cold filterlugging point, flash point, calorific value and oxidation stability.he regression analysis method was also suggested in this papero predict the properties of biodiesel blends. It has been found thatlending of diesel with biodiesel showed a remarkable improve-ent in kinematic viscosity, density, calorific value and oxidation

tability. Nevertheless, flash point and viscosity index decreases the percentage of diesel increases. Moreover, the developedathematical models showed high coefficient of regression val-

es between biodiesel properties and biodiesel–diesel blends. As conclusion, the obtained results in the current study can helpo predict the properties of biodiesel–diesel blends at any blendsatio and therefore offer substantial assistance in the design of fuelystem for biodiesel engine.

cknowledgments

The authors would like to acknowledge the Ministry of Higherducation of Malaysia and The Faculty of Engineering of Universityf Malaya, Kuala Lumpur, Malaysia for the financial support underM.C/HIR/MOHE/ENG/06 (D000006-16001).

d Products 60 (2014) 130–137 137

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