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Original article
2021
:14;
202108
doi:
10.1016/j.arabjc.2021.103263

Eco-benign biodiesel production from waste cooking oil using eggshell derived MM-CaO catalyst and condition optimization using RSM approach

, , , , , , , ,
a Department of Chemistry, University of Agriculture, Faisalabad, Pakistan
b Department of Chemistry, Govt. College Women University, Faisalabad, Pakistan
c Department of Chemistry, The University of Lahore, Lahore, Pakistan
d National Centre of Excellence in Physical Chemistry, University of Peshawar, Peshawar 25120, Pakistan
e Department of Physics, College of Sciences, Princess Nourah bint Abdulrahman University (PNU), Riyadh 11671, Saudi Arabia

⁎Corresponding author. ambreenashar2013@gmail.com (A. Ashar), Bosalvee@yahoo.com (M. Iqbal), Nmtamam@pnu.edu.sa (N. Tamam)

Received: , Accepted: ,
© The Author(s) 2021
Disclaimer:
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.

Abstract

Fatty acid methyl ester (FAME) was produced from waste cooking oil (WCO) utilizing eggshells derived solid base catalyst. Eggshells derived multi modal CaO (MM-CaO) also provides a cost-effective way for the preparation of green fuel. The nano-scaled MM-CaO was prepared using ball milling followed by calcination at 800 °C for 2 h form eggshells powder. The characterization of calcined powder was executed by XRD, EDX, SEM and FTIR techniques. Diffractogram of MM-CaO showed cubic crystal structure and presence of calcium, carbon and oxygen was confirmed by EDX. The morphology of MM-CaO was revealed by SEM having bandgap energy (3.02 eV) which declared MM-CaO as photoactive in solar range. Catalytic transesterification process furnished 75.2% yield, whereas in photocatalytic process, 86.8% yield was obtained at optimum conditions (temperature 50 °C, reaction time 180 min and 1.5 g catalyst dose). The FAME formation was monitored by GC and FTIR analysis. Physiochemical properties of produced biodiesel were also determined and equated with standards. Results depicted that MM-CaO is highly efficient for conversion of WCO to biodiesel.

Keywords

Heterogeneous catalyst
Waste cooking oil
Eggshells
Biodiesel properties
1

1 Introduction

Energy is one of the basic requirements in different sectors of life. As a viable fuel, oil has been serving the world to address its issue of energy utilization. Larger part of energy consumed is based on fossil fuel resources, which that are non-renewable. The reliance of mankind totally on the conventional fuels could cause considerable deficiency in future. The energy demand is increased drastically, which on the other hand pollutes the environment by generating gases. The extensive use of fossil fuel is depleting its reserve and emitting a high concentration of air pollutants (Jafarinejad, 2016, 2017a,b; Jiménez-Cruz et al., 2021; Kuniyil et al., 2021; Tamborini et al., 2019). Renewable energy resources are efficient to substitute the conventional fossil-based fuels. Biodiesel is fatty acid methyl ester (FAME), a biomass-inferred fuel and it is an alternate to diesel fuel. It is free from or it contains very less aromatic content, low sulfur and low particulates content in diesel exhaust (Nisar et al., 2018). Biodiesel is eco-benign, easily transportable, readily accessible, safe and biodegradable (Atadashi et al., 2010; Mumtaz et al., 2017; Obi et al., 2020). Thus, the utilization of biodiesel is beneficial because of its natural cordiality over conventional diesel (Gangadhara and Prasad, 2016; Mootabadi et al., 2010; Ramos et al., 2019). A detail review related to biodiesel production based on various sustainable resources and systems has been documented by Ramos et al. (2019). Transesterification is an excellent process to produce biodiesel. Non-edible vegetable oil is the most effective feedstock for biodiesel because of its low cost (Fukuda et al., 2001; Hiwot, 2017; Mardhiah et al., 2017). In the transesterification process, both homogenous or heterogeneous catalysts can be utilized to enhance the rate of reaction (Sharma and Rangaiah, 2013). However, the use of homogenous catalyst KOH/NaOH is not preferable because it is difficult to handle in reaction mixture, like separation and purification etc. Heterogeneous catalysis has supremacy to thrash the harms of homogeneous catalysis (Hiwot, 2018; Pedavoah et al., 2018). The solid catalysts can be used, separated and reutilize because of their easy separation (Huang et al., 2013). CaO catalyst can be prepared from different waste sources, i.e., eggshells containing 94% CaCO3 (Pedavoah et al., 2018). The CaCO3 constituent can be transformed into CaO and CO2 under elevated temperature (Jazie et al., 2013; Kesić et al., 2016). CaO is also known as quick lime or burnt lime (Joya et al., 2016). Amongst the heterogeneous impetuses that are utilized in transesterification, CaO has a prominent position (Kostić et al., 2016; Niju et al., 2014; Puna et al., 2010). The oil reacts with methanol in the existence of a catalyst and forms esterified vegetable oil by a process called transesterification (Ranganathan and Sampath, 2011).

The CaO is a semiconductor. It consisting of Ca(OH)2, CaCO3 and CaO so-known as multi-model CaO (MM-CaO). It can be employed as an efficient heterogeneous catalyst due to its promising catalytic activity (Song and Zhang, 2010). In the presence of sunlight, the efficiency of MM-CaO increased and it has been used in the formation of biodiesel. When sunlight falls on the surface of MM-CaO electrons of the VB get excited and due to excess energy, these electrons move from VB to CB and generate electron-hole pairs (CaO + hv → h+ + e−) and participate in a chemical reaction. The generated hole attack on methanol adsorbed on the catalyst surface and form H+ and CH3O•. Methanol is oxidized by +ve hole. At the same time R_COOH• form by the reduction of RCOO_H adsorbed on the catalyst surface reacting with photo-generated electron. The produced CH3O•, H+, RCOO_H• then react to form intermediates and finally, the transesterification process occurred (Corro et al., 2013).

Present study was carried out to prepare biodiesel from WCO through using catalytic process. MM-CaO was used as an efficient heterogeneous photocatalyst derived from waste eggshells. Catalytic and photocatalytic transesterification processes were employed to compare the enhancement in biodiesel yield. Optimization of variables like reaction parameters was done by response surface methodology.

2

2 Material and methods

2.1

2.1 Material and reagents

Waste vegetable oil and eggshells were obtained from the local restaurant, Faisalabad, Pakistan. NaOH/KOH, HCl acid and CH3OH were procured from sigma Aldrich and distilled water is used for the preparation of solutions and washing purposes throughout the study.

2.2

2.2 Treatment of waste oil and preparation of MM-CaO

Waste vegetable oil contains many food residues and also water, which increased the free fatty acid value i.e., 2.5% of waste oil that resulted in the formation of large amount of soap instead of biodiesel. Therefore, it needed treatment before its use. Food residues from WCO were eliminated by filtration and after filtration oil was heated to remove water. MM-CaO was prepared from eggshells, which were washed with excess water in order to eradicate impurities on its surface and then dried at room temperature and after drying, ground in a ball mill to fine powder followed by calcination (Muffle Furnace) at 800 °C for 2 h in order to transform CaCO3 content of eggshells into MM-CaO (Scheme 1 and Fig. 1).

Representation of MM-CaO synthesis and biodiesel production application.
Scheme 1
Representation of MM-CaO synthesis and biodiesel production application.
Schematic presentation for the preparation of MM-CaO.
Fig. 1
Schematic presentation for the preparation of MM-CaO.

2.3

2.3 Transesterification

Transesterification process was done to transform the oil into biodiesel. Photocatalytic transesterification was done in the occurrence of natural sunlight and a hot plate was utilized as an external heating source and a thermometer was also utilized in order to maintain the required reaction temperature. MM-CaO was mixed in methanol by stirring for 45 min and then WCO was heated below the boiling point of methanol i.e., 64.5 °C and after this methanol, MM-CaO mixture was added in by 3:1 oil to methanol molar ratio. The contents were agitated for 30 min and irradiated to sunlight. After reaction completion, the product was allowed to settle for one day for complete separation of layers. The reaction was done at different catalyst doses, reaction temperature and irradiation time in order to determine maximum yield. Catalytic transesterification was also done under the similar optimized conditions but in the absence of light.

2.4

2.4 Characterization of MM-CaO

X-ray diffraction (XRD, JoelJDX-3532 diffractometer, Japan) analysis was performed out to deduce the crystal structure. Particle size was determined by the Debye formula. Scanning Electron Microscopy (SEM, Quanta 250, FEG (USA) analysis was conducted to determine the surface morphology. The EDX analysis was done to identify the elements present in the prepared material. Fourier transform infrared spectroscopy (FTIR, Bruker IFS 125HR Japan) was done to identify the functional groups.

2.5

2.5 Statistical analysis

A three-level factorial, central composite design (CCD) was applied for the optimization of conditions by utilizing designer expert (version 7.0.0) (Zhang et al., 2011). The RSM utilizing CCD was utilized (Kirubakaran and Selvan, 2021) to optimize the operational reaction parameters (i.e., catalyst dose, temperature and reaction irradiation time), A complete design for photocatalytic and catalytic processes are depicted in Tables 1 and 2.

Table 1 Process variables at three levels employed for photocatalytic process.
Factors Variables Units Lower-Level Higher-Level
A Photocatalyst concentration g 0.5 2.5
B Temperature °C 34 66
C Sunlight Irradiation Time Minutes 120 240
Table 2 Process variables and their levels employed in CCD for catalytic process.
Factors Variables Units Lower-Level Higher-Level
A Catalyst concentration g 0.50 2.5
B Temperature °C 34 66
C Time Minutes 120 240

2.6

2.6 Analysis of biodiesel (FAME)

FTIR of biodiesel was done to determine the functional groups. GC analysis of biodiesel was done to identify FAME and conditions are given in Table 3.

Table 3 GC conditions for FAME analysis.
Column DBWEX 30 M 0.25
Mobile phase Nitrogen
Flow rate 30 mL/min
Split flow 51 mL
Injection Volume 0.49 µl
Detection FID (260 °C)
FID Temperature 140 °C for 2 min to 250 °C @ 2.3/min, injector 240 °C

2.7

2.7 Biodiesel properties

Flash and fire point of biodiesel was calculated by utilizing an open cup tester. Iodine value (IV) was determined by taking 0.1 g biodiesel sample in a 250 mL iodine flask and mixed in 20 mL CCl4 and wijs solution (25 mL), which was placed for 30 min in dark and KI solution (20 mL) and water (100 mL) was mixed in it. The contents thus obtained was titrated (using 0.1N Na2S2O3.5H2O) in the presence of indicator (starch solution).

(1)
IV = Blank - s a m p l e . N Na 2 S 2 O 3 . 127.100 Sample m a s s ( g )

For saponification value (SV) determination, biodiesel (0.5 g) and KOH (alcoholic) solution (20 ml) was mixed, which was heated in a condenser till a clear solution and after cooling (room temperature) the content, indicator (few drop of phenolphthalein) was dropped and

(2)
SV = Blank - s a m p l e . N . 56.1 Sample m a s s ( g )

Cetane number (CN) indicates the quality of biodiesel (Sivaramakrishnan and Ravikumar, 2012), which was assessed using a relation CN = 46.3 + 5458/SV–0.225. IV.

For acid value (AV) determined, oil (0.5 g), ethanol (10 mL) along with indicator (2 drop, phenolphthalein was taken in a flask and content was titrated using NaOH (0.1N) and end point was noted on the appearance of pink color. Free fatty acid (FFA) as oleic acid was calculated by this formula, FFA% = V. N. 28.2/w. Where, v is the volume in ml of titrated solution, N is the normality, w is the sample mass in g, %age FFA was converted into AV by formula, AV = 1.989. FFA%.

3

3 Results and discussion

3.1

3.1 Characterization

XRD analysis was performed (Amer and Awwad, 2021; Shammout and Awwad, 2021), to study the crystal structure (Fig. 2). The peaks recorded in diffractogram at 18.67°, 29.89°, 32.2, 34.08°, 37.3, 39.40°, 47.50°, 51.39°, 57.48°. The diffraction peak appeared at 29.89° was of CaCO3 indicating the high concentration of calcite in the sample. Small diffraction peaks appeared at 2θ° value of 32.2°, 37.39°, 47.50°, 51.3°, 57.48° were for MM-CaO, which were in good conformity with standard JCPDS file (JCPDS82-1691). Small diffraction peaks also appeared at 18.67°, 34.08° were for Ca(OH)2. XRD analysis results showed that CaO has cubic crystal structure, Ca(OH)2 with rhombohedral crystal and MM-CaO particle size was of 41 nm.

XRD analysis of MM-CaO.
Fig. 2
XRD analysis of MM-CaO.

The FTIR of MM-CaO was done to identify the functional group involved (Al-Fa et al., 2021; Awwad et al., 2020b) and outcome is depicted in Fig. 3. The sharp peak appeared at 3640 cm−1 was due to the O—H group. The strong peak at 500 cm−1 indicated the existence of Ca—O bond. Peaks at 1410 cm−1, 1180 cm−1 and 850 cm−1 were due to C—O bond related to the carbonation of CaO nano-particles (Jazie et al., 2012). The SEM analysis was done to determine the morphology of the prepared catalyst (Awwad and Amer, 2020; Awwad et al., 2020a) and outcomes are displayed in Fig. 4. At high magnification plate like structures are visible in micrographs. Due to high surface charge the plates are agglomerated and surface of plates is rough and porous (Lee et al., 2015).

FTIR analysis of MM-CaO.
Fig. 3
FTIR analysis of MM-CaO.
SEM analysis of MM-CaO (a) at 5 K Magnification (b) at 25 K Magnification.
Fig. 4
SEM analysis of MM-CaO (a) at 5 K Magnification (b) at 25 K Magnification.

EDX was done to identify the individual elements. EDX analysis confirmed that sample contained calcium, carbon, oxygen and traces of magnesium (Fig. 5). Outcomes also showed that calcium is present in large amount as compared to oxygen. EDX analysis of synthesized MM-CaO is shown in Table 4. Diffused reflectance spectroscopy (DRS) of MM-CaO was performed to find out the optical properties. In the presence of sunlight excitation of electron to conduction band leads to generation of electron and hole pair. This can be attributed to band gap energy falling in the solar region (Fig. 6a). On inserting DRS data in Kubelka–Munk relationship, the band gap energy was calculated to be 3.02 eV (Fig. 6b). This value of band gap energy further supported that harvesting of solar radiation in the visible region was likely to carry out photocatalysis for synthesis of biodiesel.

EDX of MM-CaO, a) Surface concentration of calcium b) oxygen and c) carbon.
Fig. 5
EDX of MM-CaO, a) Surface concentration of calcium b) oxygen and c) carbon.
Table 4 EDX data of synthesized MM-CaO.
Sr No. Element Symbol Mass%
1 Calcium Ca 61.5
2 Oxygen O2 24.4
3 Carbon C 13.2
4 Magnesium Mg 0.9
(a) DRS of MM-CaO and (b) Band gap energy of MM-CaO.
Fig. 6
(a) DRS of MM-CaO and (b) Band gap energy of MM-CaO.

3.2

3.2 Biodiesel synthesis and optimization

Synthesis of biodiesel was done by two routes, i.e., catalytic and photocatalytic transesterification process for biodiesel production. Optimization of independent variables, i.e., catalyst dose, temperature and sunlight irradiation time were studied. RSM in combination with CCD was utilized for determining the interaction between the independent operational factors. The list of variables, their actual lower and higher levels for are given in the following Tables 1 and 2. Design expert software utilized 3 factors CCD with 6 axial and 6 center points. The following term represents the total number of runs was carried as, (23 = 8) + (2 × 3 = 6; axial points) + 6 (center points; 6 replication) = 20. Biodiesel yield was determined as (Yield% = Biodiesel weight/Weight of oil * 100).

3.3

3.3 Effect of process variables on biodiesel production

The ANOVA (analysis of variance) was done to find out the significance of the process variables and their interaction for biodiesel production (Tables 5 and 6). Model F-value of 104.00 specifies the significance of the developed model. Values of “Prob > F” lower than 0.0500 specify that model terms are significant and A, B, A2, B2, C2 are found to be significant to enhance the biodiesel production. Values larger than 0.1000 points out that model terms are not considerable. The F-value (3.03) in Lack of Fit designates non-comparison with pure error and its chances are 12.39% of this higher value of Lack of Fit, which reveals the gooness of the model. Non-significant lack of fit is best. The Predicted R2 of 0.9356 is in appropriate conformity with Adj R2 of 0.9799. Adequateaccuracy calculates the signal-to-noise ratio. A fraction larger than 4 is desirable. A ratio of 36.124 shows enough signal. Predicted value of R2 = 0.9356 suggests that the information fit effectively with the design in the selected range (Mohsin et al., 2020).

Table 5 ANOVA performed for photocatalytic process for biodiesel production.
Source Sum of squares DF Mean square F-value P-value prob > F
Model 7780.71 9 864.52 104.0 <0.0001 significant
A-Photocatalyst conc. 195.03 1 195.03 23.46 0.0007
B-Temperature 1094.56 1 1094.56 131.67 <0.0001
C-Sunlight radiation time 39.26 1 39.26 4.72 0.0549
AB 1.71 1 1.71 0.21 0.6597
AC 9.90 1 9.90 1.19 0.3007
BC 3.51 1 3.51 0.42 0.5304
A2 557.52 1 557.52 67.07 <0.0001
B2 6184.36 1 6184.36 743.93 <0.0001
C2 78.29 1 78.29 9.42 0.0119
Residual 83.13 10 8.31
Lack of Fit 62.52 5 12.50 3.03 0.1243 Insignificant
Pure Error 20.61 5 4.12
Cor Total 7863.84 19

Std. Dev. = 2.88 R2 = 0.989 AdjR2 = 0.9799 Estimated R2 = 0.9356 Adequate precision = 36.12

C.V = 4.48%

Table 6 ANOVA performed for catalytic process for biodiesel production.
Source Sum of squares DF Mean square F-value P-value prob > F
Model 4661.86 9 517.98 104.0 <0.0001 significant
A-Catalyst conc. 122.81 1 122.81 36.30 0.0001
B-Temperature 4398.11 1 1398.11 1299.89 <0.0001
C-Time 80.13 1 80.13 23.68 0.0007
AB 0.10 1 0.10 0.030 0.8661
AC 0.031 1 0.031 9.236E−0030.9253
BC 0.031 1 0.031 9.236E−003
A2 32.56 1 32.56 9.62 0.0112
B2 29.57 1 29.57 8.74 0.0144
C2 78.29 1 78.29 9.42 0.0119
Residual 1.01 10 1.01 0.30 0.5968
Lack of Fit 24.55 5 4.91 2.65 0.1546 Insignificant
Pure Error 9.28 5 1.86
Cor Total 4695.76 19

Std. Dev. = 1.84 R2 = 0.993 AdjR2 = 0.9863 Estimated R2 = 0.9575 Adequate precision = 36.41

C.V = 3.89%

The F-value of 153.09 is also an indication of model significance and there may be 0.01% coincidence of larger F-value due to noise. The P < 0.0500 is also anotehr criteria of model significance of the developed model and based on this criteria the A, B, C, A2, B2 terms are significant. The Predicted R2 (0.9575) and adjusted R 2 (0.9863), model is also significant because these valeus are close to 1. Hence, based on Lack of Fit, P value and R values this model values provide the significance of the regression model applied to deduce the effect of input variables. It also shows the connection between response and independent operational variables. “Adequate Precision” determines the signal-to-noise ratio. A ratio larger than 4 is enviable. Fraction of 46.408 suggests a sufficient signal. Predicted R2 = 0.9928 suggests that the data fit well with the model in the studied range. On the other hand, residual analysis was done to confirm the adequacy of the model. This was done by observing the normal possibility plot of the residuals. Results showed that the photocatalytic transesterification process provided 86.8% yield of biodiesel. Biodiesel was also prepared by catalytic transesterification process utilizing catalyst dose 1.5 g, reaction time 180 min., temperature 50 °C. Catalytic process gives 75.2% yield that is approximately 10% less than the photocatalytic process, which is because in the presence of sunlight efficiency of MM-CaO was enhanced (Song and Zhang, 2010). Normal possibility residual plots of photocatalysis and catalysis are shown in Fig. 7. Almost >85% point existed on the standard line (Fig. 7) that confirmed the fitness of the model.

Normal possibility plot of residuals for (a) photocatalytic and (b) catalytic processes.
Fig. 7
Normal possibility plot of residuals for (a) photocatalytic and (b) catalytic processes.

The interactive impact of catalyst dose and temperature is shown in Fig. 8(a). It can be apparently seen that a rise in temperature and catalyst dose leads to increase in biodiesel yield, but only up to a certain limit. This is because if the temperature is above the BP of methanol, it starts to evaporate, and large quantity of catalyst dose leads to soap formation instead of biodiesel due to its basic nature. Conclusively, 50 °C is the optimum temperature and 1.5 g is the optimum catalyst dose for maximum production of biodiesel. The input variables catalyst dose and time of irradiation impact on the yield is shown in Fig. 8(b). The irradiation time also affected the yield of biodiesel. It has been shown that as irradiation time has been increased methyl ester yield also increased, but only a certain limit, i.e., 180 min. The mutual effect of sunlight irradiation time and temperature for the production of biodiesel is shown in Fig. 8(c). The biodiesel production enhanced with irradiation time and temperature. But, at higher temperatures; the yield was decreased. Investigation showed that 50 °C is the optimum temperature (Nejad and Zahedi, 2018).

3D plots of biodiesel yield as a function of (a) Sunlight Irradiation versus photocatalyst, (b) Sunlight Irradiation versus temperature, (c) temperature versus photocatalyst, (d) temperature versus catalyst, (e) UV irradiation and catalyst & (f) UV irradiation and temperature.
Fig. 8
3D plots of biodiesel yield as a function of (a) Sunlight Irradiation versus photocatalyst, (b) Sunlight Irradiation versus temperature, (c) temperature versus photocatalyst, (d) temperature versus catalyst, (e) UV irradiation and catalyst & (f) UV irradiation and temperature.

The interactive impact of catalyst and temperature on biodiesel production is seen in Fig. 8(d). It can be clearly observed that catalyst dose has positive impact on the amount of biodiesel, but higher amount did not affect the yield of biodiesel. A 1.5 g catalyst dose gives maximum quantity of biodiesel. The biodiesel yield was enhanced by increasing the temperature and catalyst dose up to certain limit. This is because if temperature increased above the boiling point of methanol, methanol starts to evaporate, and enormous dose of catalyst leads to the production of soap instead of biodiesel due to its basic nature. Hence, 50 °C is the optimum temperature (Onukwuli et al., 2017). The interactive impact of reaction time and catalyst dose on the yield of biodiesel is depicted in Fig. 8(e). A remarkable interaction among catalyst and reaction time on methyl ester yield was observed. Reaction time also affected the yield of biodiesel. The interactive effect of heating time and temperature on biodiesel yield is depicted in Fig. 8(f). Biodiesel yield increases with the increase in time and temperature. As heating time increased methyl ester yield also increased, but after certain limit, a raise in time does not influence the yield of biodiesel. As the temperature increased, the yield was also enhanced up to 50 °C, which is the optimum level for maximum yield of biodiesel. The findings revealed the MM-CaO is highly efficiecnt for the conversion of WCO to biodiesel and this process is economical versus other physico-chemical methods. The biodiesel thus produced will be used in combination to the diesel fuel, which will help to lessen the environmental issue of pollution (Abulude et al., 2018; Chokor, 2021; Mene and Iwuoha, 2021; Sasmaz, 2020; Sinanoglu and Sasmaz, 2019; Tsegaye et al., 2021).

3.4

3.4 Analysis of FAME

FTIR of analysis of FAME was done for the identification of functional groups (Al Banna et al., 2020). A band at 742 cm−1 was due to ⚌C—H groups, which indicates a methylene functional presence (Thanh et al., 2012). The characteristic peak found at 1185 cm−1 is attributed to O—CH3, which is a typical of biodiesel (Fig. 9). The peak at 1410 cm−1 is corelated with C—H methyl group. The peak at 1750 cm−1 is ascribed to C⚌O groups, which indicate the presence of carbonyl functional groups in the biodiesel (Oyerinde and Bello, 2016). This group also revealed the transformation of triglycerides in the oil to methyl ester (Popovicheva et al., 2017; Saifuddin and Refal, 2014). The peaks at 2820 and 2940 (cm-1) exhibited is due to of C-H groups (symmetric/asymmetric), which indicating the presence of methyl or methylene group (-CH3) in biodiesel structure of ester. FAME was monitored using method reported elsewhere. FAME composition was identified by GC analysis (Farooq et al., 2015) (Fig. 10). The peaks that appeared in the chromatogram, correspond to different FAME present in the biodiesel sample. The composition of FAME determined by GC is shown in Table 7.

FTIR analysis of biodiesel prepared using MM-CaO from waste cooking oil.
Fig. 9
FTIR analysis of biodiesel prepared using MM-CaO from waste cooking oil.
GC analysis of prepared biodiesel utilizing MM-CaO from waste cooking oil.
Fig. 10
GC analysis of prepared biodiesel utilizing MM-CaO from waste cooking oil.
Table 7 FAME composition of synthesized Biodiesel.
No. Retention time Conc.% Identified compound
1 1.980 0.3 Butyric acid methyl ester (ME)
2 4.607 0.2 Enanthaic acid ME
3 7.540 0.1 Caprylic acid ME
4 20.980 0.4 Capric acid ME
5 22.140 9.7 Capric acid ME
6 32.500 78.4 Myristoleic acid ME
7 33.307 1.1 Myristic acid ME
8 36.333 0.6 Unknown
9 38.373 2.2 Penta decanoic acid ME
10 39.027 1.5 Heptadecanoic acid ME
11 39.927 1.9 Palmitoleic acid ME
12 45.587 0.14 α-Linoleic acid ME
13 46.793 1.0 γ-Linoleic acid ME
14 49.060 0.6 Nonadecanoic acid ME

The properties of biodiesel like SV, IV, CN, AV, flash point, fire point, cloud & pour point was determined & then compared with standards (American Society for Testing Materials (ASTM D-6751), European Union Standard for biodiesel fuel (EN 14214)) reported and deplayed in Table 8. IV determines the degree of un-saturation. CN determines the quality of biodiesel (Okullo et al., 2012). Flashpoint of biodiesel showed that it is a safer fuel due to its higher ignition temperature. The pour point of biodiesel revealed the temperature at which biodiesel becomes solid and no longer flows.

Table 8 Properties of Biodiesel in comparison with standards.
Properties Unit Prepared Biodiesel ASTM-D6751 EN-14214
Saponification Value mg KOH/g 242 – –
Iodine value mgI2/g 59 – max 110
Cetane number 55 47 48–60
Acid Value mg KOH/g 0.87 <0.7 <0.5
Flashpoint °C 135 100–170 120
Fire point °C 150 100–170 –
Cloud point °C 10 −3 to 12 –
Pour point °C 4 −15 to 16 –

4

4 Conclusion

Biodiesel is an alternate and renewable energy fuel. Biodiesel was prepared by utilizing eggshells derived catalyst from WCO. The MM-CaO demonstrated an efficient and effective efficiency as catalyst for the transformation of WCO into biodiesel. Transesterification process was employed for the production of biodiesel. The catalytic and photocatalytic processes yielded 75.2 and 86.8 (%) biodiesel under optimized conditions, i.e., temperature 50 °C, reaction time 180 min and 1.5 g catalyst dose. Results showed that the photocatalytic transesterification process enhances the yield up to 11.6% as compared to catalytic process. Hence photocatalysis process shows more efficiency. Chemical properties of biodiesel were also determined in comparison to European and American standards, which were in the recommended limit. Based on efficiency, the catalyst derived from eggshell is economical and eco-benign, which could be used for the conversion of WCO into biodiesel.

Acknowledgment

This research was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the Fast-track Research Funding Program.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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