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Biodiesel production from microalgal biomass using CaO catalyst synthesized from natural waste material
Renewable Energy 136 (2019) 837e845
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Biodiesel production from microalgal biomass using CaO catalyst synthesized from natural waste material Priti R. Pandit, M.H. Fulekar* School of Environment and Sustainable Development, Central University of Gujarat, Gandhinagar, Gujarat, India
a r t i c l e i n f o
a b s t r a c t
Article history: Received 11 October 2017 Received in revised form 14 November 2018 Accepted 13 January 2019 Available online 16 January 2019
Calcium oxide (CaO) catalyst was prepared using chicken egg shell waste and tested as a catalyst for the production of biodiesel from Chlorella vulgaris biomass. The calcination method was adopted for the synthesis of CaO catalyst. Transmission electron microscope (TEM) image showed that the catalyst had a spherical structure with average particle size of 46.1 ± 2.1 nm, further analysis was carried out using Brunauer-Emmett-Teller (BET) adsorption, scanning electron microscopy, elemental analysis, X-ray diffraction and Fourier-transform infrared spectroscopy. Transesterification process was conducted by using response surface methodology (RSM) based on central composite design (CCD). The optimum reaction conditions were observed at 70 C, 10:1 methanol: dry biomass ratio, 1.39% catalyst loading, 3 h reaction time, and 140 rpm stirring rate resulted 92.03% biodiesel yield. The key fuel properties includes; iodine value (88.5 g I2 100/g), cetane number (50.0), cloud point (9.2 C), pour point (3.1 C), oxidation stability (7.4 h), higher heating value (44.7), kinematic viscosity (4.5 mm2/s) and density (0.9 g/cm3) resulted good quality of microalgae biodiesel. Our research finding shows that the CaO catalyst derived from egg shell waste is an economically potential and eco-friendly catalyst for biodiesel production. © 2019 Elsevier Ltd. All rights reserved.
Keywords: Transesterification Catalyst Biodiesel and Brunauer-Emmett-Teller
1. Introduction Microalgae have grabbed great attention during past decades, as a renewable biofeedstock for biodiesel production, owing to its high photosynthetic yield compared to other traditional crops, high lipid content, rapid growth rate, higher biomass productivity and eco-friendly nature [1]. Despite of various benefits, microalgal biodiesel production still faces techno-economical problems, mainly in the large-scale cultivation, lipid extraction and fuel conversion process [2]. The main critical points are lipid extraction process with energy consumption near 90%, and lipid transesterification, with a 10% of total energy consumption from microalgal biodiesel production [3,4]. Hence, lipid extraction is considered as one of the most limiting step for the industrial scale up process [5]. With the purpose of eliminating lipid extraction process, the implementation of direct (in-situ) transesterification of microalgal biomass in the presence of catalyst has been investigated. Im et al. [6] reported, 91.1% of biodiesel yield obtained by direct transesterification of wet microalgal biomass at 95 C with
* Corresponding author. E-mail addresses: [email protected] (P.R. Pandit), mhfulekar@yahoo. com (M.H. Fulekar). https://doi.org/10.1016/j.renene.2019.01.047 0960-1481/© 2019 Elsevier Ltd. All rights reserved.
2:1 chloroform methanol ratio, 0.3 g H2SO4, 65% moisture content and a reaction time of 90 min. Moreover, Ortia et al. [7] studied in situ transesterification of Chlorella vulgaris and reported 77.6 wt % biodiesel yield using NaOH as a catalyst and a methanol/lipid molar ratio of 600:1 at 60 C for 75 min. While, 88% of biodiesel yield using 315:1 methanol lipid molar ratio was reported by Ehime et al. [8]. Ma et al. [9] resulted 89.53% biodiesel yield from microalgae using KOH/Al2O3 heterogeneous catalyst. Doyle et al. [10] prepared FAU-type zeolite catalyst from shale rock and reported 78% conversion of biodiesel. Umdu et al. [11] reported 97.3% of biodiesel yield in Nannochloropsis oculata lipid by using Al2O3 supported CaO and MgO catalyst. Doyle et al. [12] reported a Zeolite Y with a Si/Al catalyst for esterification of oleic acid. Whereas, Albayati and Doyle [13] prepared encapsulated heterogeneous base catalyst onto SBA-15 nanoporous material for transesterification of sunflower oil to biodiesel and reported 96% yield of fatty acid methyl ester. However, high yield of biodiesel were obtained by these studies but the technology associated with these methods are very expensive, demands high energy and hence; increases the production cost of biodiesel. Therefore, efforts have been made to utilize eggshell waste as a cheap and widely available potential source for synthesis of catalyst. Chicken egg shell waste contains more than 94% CaCO3 [14] and simply by calcination process CaO catalyst can be formed. Moreover, CaO has
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been known for its high alkalinity, low solubility in methanol and high catalytic activity that makes CaO potential solid base catalyst for biodiesel production [15]. Hence, the utilization of eggshell waste as raw material for catalyst synthesis could eliminate the waste and simultaneously produce the catalyst with high cost effectiveness [16]. Here, we show that chicken egg shell waste is the excellent source to prepare CaO heterogeneous catalyst for direct transesterification of microalgal biomass to biodiesel. The calcination method was used for the preparation of CaO catalyst. The impact of transesterification reaction parameters and their interaction were analysed by using central composite design based on resonance surface model. The fuel properties of the biodiesel produced were described by iodine value, cetane number, cloud point, pour point, oxidation stability, higher heating value, kinematic viscosity and density. In addition, CaO leaching, catalyst stability and reusability were also assessed. The purity of biodiesel was characterized by nuclear magnetic resonance analysis.
2. Materials and method 2.1. Chemical reagents and microalgae The chemical reagents used in this study, including methanol and ethyl acetate were purchased from Himedia (India; HPLC-grade >99.8%). Heptadecanoic acid, potassium bromide (FTIR- grade) and chloroform (NMR-grade) were purchased from Sigma-Aldrich. Microalgae (Chlorella vulgaris), which were isolated from low tidal region of Dwarka coast, Gujarat, India. The C. vulgaris was cultured in BG-11 medium and incubated in 5L photobioreactor with 3L of culture media at 25 ± 2 C and illuminated by fluorescent lamps for 16 h (90.15 m mol m2 s1). After 15 days, the microalge strain was harvested by centrifugation at 5000 rpm for 10 min. The obtained microalgal biomass was dried at 40 C in hot air oven for overnight and ground in mortar for subsequent use. Characterization was performed on the C. vulgaris biomass, including moisture content and ash content. It was found that the microalgae biomass contains 1.28 wt % moisture and 10.2 wt % ash content on a dry weight basis.
2.2. Synthesis of CaO catalyst In our pervious reported literature CaO catalyst was synthesized by calcination- hydration-dehydration method [17]. Here, we applied simple calcination method for the synthesis of CaO catalyst. The chicken-egg shells waste was collected from University canteen, Gujarat, India. The egg shells were thoroughly washed with distilled water for 2e3 times and boiled for 10 min in order to separate the adhering membrane. The egg shells were then dried at 105 C in a hot air oven for overnight. After that, dried shells were grinded using a blender until it become fine powder and calcinated in a muffle furnace at 900 C for 4 h. The obtained calcinated powder was labeled as CaO catalyst and used for characterization analysis. 2.3. Characterization of CaO catalyst The obtained CaO catalyst was characterized using fourier transform infrared (FTIR)-spectrophotometer (Spectrum 65 series, Perkin Elmer) with KBr (AR, Sigma USA) powder for structure analysis. The IR spectrum in the range of 400e4000 cm1 was recorded. The surface morphology of catalyst was performed using field-emission scanning electron microscopy (FE-SEM) equipped with an energy-dispersive X-ray analysis (EDX) for elemental composition (EVO 18, Carl Zesis) and for crystalline properties X-ray diffraction pattern was recorded. Size and shape of the CaO catalyst were obtained by using a transmission electron microscope (TEM). The textural properties were determined by Brunauer-Emmett-Teller (BET) for surface area and Barrett-Joyner-Halenda (BJH) method were applied to obtain pore volume and pore diameter respectively. 2.4. Experimental setup The process of direct transesterification in the presence of CaO catalyst for biodiesel production is shown in Fig. 1. The experiment was performed in 150 ml round bottom flask equipped with reflux condenser and magnetic stirrer. To the round bottom flask, 1 g of dried C. vulgaris biomass was taken. The required amount of CaO
Fig. 1. Showing direct transesterification process using CaO catalyst.
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catalyst (0.5e2.5 w/w) was poured into a beaker containing corresponding amount of manually optimized methanol to biomass ratio of 10:1 wt/vol and allowed to mix for 15 min to homogenize the mixture. After that, the mixture was added to the round bottom flask containing biomass and the reaction was allowed to react at a continuous stirring speed (50e200 rpm) with constant temperature 70 C for a period of 1e4 h. After completion of reaction, mixture was allowed to cool. The reaction mixture was transferred in the separating funnel and was separated by adding the mixture of water and ethyl acetate in the ratio of 3:1. The upper organic layer containing methyl ester was thoroughly washed with distilled water and passed over anhydrous sodium sulphate column to remove traces of water. The phase containing ethyl acetate was evaporated on a rotary evaporator to recover fatty acid methyl esters (FAME). The amount of fatty acid methyl ester (biodiesel) was gravimetrically quantified and stored at 4 C for the analysis of FAME content by using nuclear magnetic resonance and gas chromatography. All the experiments were performed in triplicate and average results were reported. 2.5. Statistical analysis of experimental design The biodiesel optimization was carried out using the Response Surface Methodology (RSM) created by Minitab 17.1, PA, USA. RSM design tool known as central composite design (CCD) was applied to study the effect of the reaction parameters and their interaction. Table 1 depicts the ranges and levels of the three identified independent reaction parameters (variables). The independent variable are coded as low (-a) and high (þa) where as value of a ¼ 1.62 FAME yield was chosen as the response obtained from the reaction. The total number of experiments was calculated by following equation [18].
Table 1 Levels and ranges of transesterification parameters in CCD. Factors
Levels
Reaction time (h) (A) Catalyst concentration (%w/w) (B) Stirring rate (rpm) (C)
1
0
þ1
2 0.5 100
3 1.25 150
4 2 200
839
N ¼ 2K þ 2K þ 6 ¼ 23 þ ð2 X 3Þ þ 6 ¼ 20 runs
(1)
Where, N ¼ total number of experiments, K ¼ number of parameters and 6 is the number of replicates at the centre points to calculate the pure error. The complete design matrix obtained from CCD design for experiment and predicted results are tabulated in Table 2. The experiment runs were performed at random in order to minimize the error occurred from the systematic trends in the variables. To predict the optimal level between the response and independent variables of transesterfication reaction, a second-order polynomial equation model was applied:
BY ¼ b0 þ
3 X i¼1
bi ki þ
3 X
bii k2i þ
i¼1
2 X
3 X
i¼1
i < j¼1
bij ki kj
(2)
Where, BY is the predicted biodiesel yield, b0 bj bij and bjj are constant coefficients; ki and kj are the coded independent parameters, ε is random error. The quality of model was evaluated by regression analysis and analysis of variance (ANOVA). Contour and surface plots were developed using the quadratic polynomial equation obtained from regression analysis. To validate the quadratic polynomial model, confirmatory experiment were also performed. 2.6. FAME characterization and fuel properties The FAME was characterized by 1H Nuclear Magnetic Resonance Spectroscopy (NMR) using Bruker 500 MHz Avance III (AV 500) spectrometer. Chloroform (CDCl3) was used as solvent. NMR spectrum was recorded with pulse duration of 48 , a recycle delay of 1.30 s and 16 scans. The percentage conversion of methyl ester was calculated according to the literature reported by Knothe [19]. Furthermore, the fuel quality parameters such as iodine value g I2100 g 1 (IV), cetane number (CN), saponification value (SV), degree of unsaturation % wt. (DU), cloud point oC (CP), higher heating value MJ/Kg (HHV); long chain saturated factor oC (LCSF); kinematic viscosity mm2/s (y); pour point oC (PP), oxidative stability h (OS) and the density g/cm3 (r) were determined based on fatty acid profiling using GC-MS.
Table 2 Experiment design using central composite matrix for C. vulgaris for biodiesel yield (% w/w). Level of experimental factor Run order
Std order
Point
A (h)
B (w/w)
C (rpm)
Yield (%)
Prediction
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
6 10 15 17 2 7 11 16 18 5 19 9 20 14 1 8 13 4 12 3
1 1 0 0 1 1 1 0 0 1 0 1 0 1 1 1 1 1 1 1
4 4 3 3 4 2 3 3 3 2 3 2 3 3 2 4 3 4 3 2
0.5 1.25 1.25 1.25 0.5 2 0.5 1.25 1.25 0.5 1.25 1.25 1.25 1.25 0.5 2 1.25 2 2 2
200 150 150 150 100 200 150 150 150 200 150 150 150 200 100 200 100 100 150 100
68.93 85.23 90.46 90.27 63.43 66.23 67.93 91.37 92.04 44.23 91.02 81.06 89.08 85.09 40.5 58.23 87.31 65.41 79.56 80.2
69.63 85.87 90.82 90.82 62.72 67.01 67.11 90.82 90.82 44.08 90.82 80.07 90.82 84.61 41.45 57.35 87.44 65.63 80.03 79.58
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2.7. Catalyst reusability The stability and reusability of the synthesized CaO catalyst is an important concern for the calciumebased catalyst, due to the leaching of CaO to other reactants during transesterification processes. The reusability of obtained CaO catalyst was performed upto six reuse cycles. After first cycle of reaction, the catalyst was recovered from reaction mixture by filtration and washing with methanol for several times. The recovered catalyst was oven dried for overnight and recalcinated at 800 C for 2 h before reusing. This process was continued for rest of the reusable cycles, performed at optimal transesterification parametric conditions, including; 1.39% (wt/wt) catalyst concentration, reaction time 3 (h) and stirring rate 140 (rpm) at constant 70 C temperature and 1:10 (wt/vol) biomass/methanol ratio. The surface morphology of recovered catalyst was investigated by using FE-SEM (EVO 18, Carl Zesis). The biodiesel obtained from each cycle was tested using inductive coupled plasma mass spectrometry (ICP: Model: 7300DV, Perkin Elmer) to measure the amount of calcium ions concentration leached into the biodiesel.
3. Result and discussion 3.1. CaO nano catalyst characterization The IR spectra of the CaO catalyst derived from chicken egg shell calcined for 3 h at 900 C were shown in Fig. 2. The IR spectra of sample were obtained using KBr method at room temperature and spectra were recorded at 400-4000 cm1. The characteristic peaks at 1420 and 874.1 cm1 attributed to CeO stretching and bending mode of CaCO3. Similar peak was also recorded by Nurhayati et al. [20] using Anadaragranosa shell as catalyst. Besides, the board transmission band at 3642.3 cm1 was associated with OH stretching vibration. This was due to the physisorbed water molecule on the surface of the CaO [21]. Furthermore, during calcination CaCO3 decomposed into CaO and CO2, sharp band at around 526.4 cm1 contributed to the presence of CaO. The results were in accordance with our pervious publication Pandit and Fulekar [17]. The XRD spectra of CaO catalyst were matched with the JCPDS 77e9574, the intense peaks were observed at 36.25, 53.12 and 64.12 with corresponding (hkl) value (200), (220) and (311) respectively (Fig. 3). The average crystalline size of CaO catalyst was found to be 49 nm. FE-SEM micrograph was carried out to determine the surface morphology of the CaO catalyst (Fig. 4a). The results depict nearly distorted spherical shape of the calcium oxide catalyst due to the
Fig. 3. XRD spectra of CaO catalyst.
formation of aggregates. The chemical composition of CaO catalyst was performed using EDX, and the results were illustrated in Fig. 4b. The composition of the catalyst produced by calcination of egg shell mainly consists of CaO 98.12% by weight with small amount of other metal as impurities as shown in Fig. 4b. Fig. 5a, illustrated the TEM micrograph of CaO catalyst. From TEM micrograph, it was found that the CaO nano particles were bonded together to form aggregates. The smaller size and aggregation is directly proportional to the higher specific surface area [22]. Particle size distribution of CaO nanoparticles were shown in Fig. 5b by counting nearly 50 particles from TEM image. The average particle size was 46.1 nm with spherical shape. The results obtained were in accordance with our perviuos publication Pandit and Fulekar [17]. The textual properties (specific surface area, average pore diameter and pore volume) of CaO catalyst was determined by BET and BJH analysis. These properties are very important for the solid base heterogeneous catalyst because they influence the catalytic efficiency of transesterification process [23]. The specific surface area, average pore diameter and pore volume of CaO catalyst was 15.73 m2g, 3 nm and 0.013 cc2g respectively. The reported mean pore diameters of CaO catalyst are between 2 and 50 nm, which represents mesopores and illustrates their suitability as a catalyst, for adsorption etc [24]. Mirghiasi et al. [25] reported specific surface area of CaO catalyst at different temperatures of 500, 750 and 900 C were 5.2, 4.7 and 4.1 m2g, respectively. Correria et al. [26] derived CaO from eggshell and crab shell with specific surface area value of 1.93 and 1.60 m2g with average pore volume 0.006 and 0.004 for biodiesel production from sunflower oil, respectively. Thus, in this study the specific surface area of CaO nano catalyst synthesized from egg shells have higher specific surface area as compared to above reported literatures.
3.2. Regression analysis for optimal microalgal biodiesel yield
Fig. 2. FT-IR spectra of CaO catalyst.
A central composite design of 20 experiments was conducted to analyze the influence of the variables and their interactions on the biodiesel (FAME) yield. The optimal reaction condition for maximizing biodiesel yield, responses of FAME yield with varying variables for in situ transesterification process is presented in Table 2. The comparative results between the experimental and predicted yield for both microalgal strains in percentage were represented graphically in Supplementary Fig. S1. The results depicted that the predicted yield were closely adjoining with the experimental yield. Thus, indicates the reliability of the predicted model and also an intimate interaction among the studied three independent input variables and dependent response parameter on microalgal biodiesel yield.
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Fig. 4. CaO catalyst showing: a) FE-SEM image b) EDX- composition.
Fig. 5. CaO catalyst a) TEM micrograph b) particle size distribution histogram.
The multiple regression coefficients of the model were obtained from the statistical software Minitab 17.1 tabulated in Table 3. The significance of each coefficient was determined by the p-value (probability < 0.05). The regression coefficients b1, b2 and b3 represent linear factors A, B and C; b11, b22 and b33 represent quadratic coefficients A2, B2 and C2 whereas b12 b13 and b23 represent interaction coefficients AB, AC and BC respectively and were significant because each of the value were less than 0.05 (95% confidence interval). The prediction model derived from the regression coefficients in coded variables are:
C: vulgaris biodiesel yield ¼ e139:42 þ 61:44A þ 135:66B þ 0:609C 7:846A2 30:66B2 2
0:001916C 11:737AB
Table 3 Regression coefficients estimation for microalgae (C. vulgaris) biodiesel yield. Coefficient C. vulgaris b0 Constant Linear b1 (A) b2 (B) b3 (C) Square b11 (A2) b22 (B2) b33 (C2) Interaction b12 (AB) b13 (AC) b23 (BC)
Value
SE
T-Value
P-value
90.820
0.370
245.62
0.000
2.901 6.461 1.414
0.340 0.340 0.340
8.53 19.00 4.16
0.000 0.000 0.002
7.846 17.246 1.894
0.649 0.649 0.649
12.10 26.59 7.39
8.803 1.070 3.798
0.380 0.231 9.99
23.15 2.81 9.99
0.000 0.000 0.000 0.000 0.000 0.008 0.000
þ 0:02140AC 0:1013BC (3)
3.3. ANOVA for microalgal biodiesel yield To determine the fitness and significance of regression model, analysis of variance (ANOVA) tests were conducted (Table 4). The
regression model was statistically well-fitted since the R2 value of model prediction was 0.9975%. It implies that 99.75% as a total variation with 99.53% as the adjusted R2 value. Moreover, the pvalue was less than 0.05 which further indicates precision and fitness for associated model. In addition, insignificant lack of fit further indicates the adequacy of the predicted model.
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Table 4 Analysis of Variance (ANOVA) for response surface quadratic model of FAMEs. Source
DF
Adj.SS
Adj.MS
F
P
Model Linear Square Interaction Residual error Lack-of-fit Pure error Total
9 3 3 3 10 5 5 19
4708.79 521.60 2334.35 744.40 11.57 6.36 5.21 4720.36
523.20 173.87 778.12 248.13 1.16 1.27 1.04
452.24 150.28 89.95 214.48
0 0 0 0.000
1.22
0.417
R2 ¼ 99.75%, adj R2 ¼ 99.53%, R-sq(pred) ¼ 97.79% (DF e degree of freedom; Adj. SS e adjusted Sum of squares; Adj. MS e adjusted mean of square; F e probability distribution; P e probability > F).
3.4. Impact of transesterification parameters and interactions for C. vulgaris biodiesel yield Impact of reaction time, catalyst concentration and stirring rate on the response microalgal biodiesel yield are depicted graphically in Fig. 5. The reaction temperature and dry microalgal biomass to methanol ratio was kept constant at 75 C and 1:10 (wt/vol) respectively for all experiment runs. Fig. 6a illustrates reaction time (A) and catalyst concentration (B) and their interaction on C. vulgaris biodiesel yield at constant stirring rate (C) of 150 rpm.
Based on the 2D and 3D plots, the effect of the increased reaction time from 2 to 3.5 h, starting from a catalyst ratio of 0.5e1.67 (wt/ wt), proportionally increased biodiesel yield and beyond this the response declines. This result indicated that increasing catalyst concentration with an increment in the reaction time increased the biodiesel yield. This was because longer reaction time favoured the distribution of cell wall, accelerated the release of lipid from microalgae and provides sufficient time to contact with reactant mixtures and hence increase the biodiesel yield. Zhang et al. [3] reported 90.18% of biodiesel yield for direct transesterification of microalgal biomass at 2.0 h reaction time. While, as shown in Fig. 6 (a) the biodiesel yield start decreasing as the catalyst concentration was increased further. This was due to higher dosage of catalyst lead to the saponification reaction, caused by Ca(OH)2 hence decreased the biodiesel yield. Ma et al. [27] also reported biodiesel yield was increased from 27.73% to 86.35% as the KF/CaO catalyst concentration increased from 4% to 12% and decreased beyond 14% catalyst concentration. The results were also in accordance with Widayat et al. [28] and Chen et al. [29]. The maximum biodiesel yield of 91.4% with catalyst concentration 1.37% and reaction time 3.0 h was achieved with the combination of these two parameters. Fig. 6b shows the interaction between catalyst concentration and stirring rate while other parameters are kept constant (molar
Fig. 6. Surface and contour plots of a) reaction time and catalyst ratio interaction b) reaction time and stirring rate interaction and c) stirring and catalyst ratio interaction impact on microalgal (Chlorella vulgaris) biodiesel yield; A ¼ reaction time; (h) B ¼ catalyst ratio (% wt/wt); C¼ Stirring rate (rpm).
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ratio 1:10, reaction time 3 h). It can be seen in Fig. 6b that an increase in catalyst concentration affects the biodiesel yield for both the low and high stirring rate. It was observed that the transesterification reaction was practically incomplete at 110 rpm and only 65% of biodiesel yield. However, at 137.7 rpm stirring speed with 1.3% catalyst concentration 91.37% of biodiesel yield was achieved. The plots, shows that stirring rate have moderate effect on the biodiesel yield but when coupled with the catalyst concentration the response shows significant increase in the biodiesel yield upto 91%. Thus, stirring prevents the clumping of biomass with methanol mixture and helps in forming homogenized reaction mixture and hence increase biodiesel yield. However, beyond optimum stirring rate decrease the biodiesel yield. This was because higher stirring rate favours the soap formation due to the reverse behavior of transesterification reaction [30]. Fig. 6c illustrates the effect of reaction time with stirring and their interaction on the response biodiesel yield at constant catalyst ratio of 1.25 (wt/ wt). From the 2D plot, the response region results only a range of 87.5e90.0% and thus depicts moderate impact of these interaction on the biodiesel yield. However, with increase in the This finding was similar to our pervious reported literature Pandita and Fulekar [17]. In conclusion, by fixing suitable reaction variable ranges at their mean values i. e catalyst ¼ 1.39%, time < 3 h and stirring rate <140 rpm, the maximum biodiesel can be obtained. 3.5. Optimization of microalgal biodiesel yield The optimized reaction condition for transesterification reaction was determined from experimental data obtained from statistical software Minitab 17.1. The predicted optimum transesterification reaction conditions for C. vulgaris biodiesel production were
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estimated as 1.39% (wt/wt) catalyst concentration, reaction time 3 h and stirring rate 140 rpm. Transesterification reaction of microalgal biomass was carried out in triplicate at optimized conditions and the average value on biodiesel was reported. The maximum predicted biodiesel under the optimum condition yield for C. vulgaris was found to be 91.63% which was comparable result to the yield with CaO 92.03% under the same reaction condition. This result indicates egg shell waste can be used in biodiesel production as a catalyst. 3.6. CaO catalyst recovery The reusability and stability of calcium based catalyst in the biodiesel production is one of the major concerns for economical stability of microalgal biodiesel. After completion of the each transesterification reaction process, the calcium oxide catalyst was recovered and calcinated at 800 C. Based on the SEM image in Fig. 7aec, there was change on the surface morphology of CaO during third consecutive catalyst and resulted decreased biodiesel yield as depicted in Fig. 6d. However, the change in the surface catalyst was due to the agglomeration of other particles with the catalyst and mixing of CaO catalyst with the reactants. Moreover, the decreased catalytic activity during six reusable cycles may due the following reasons i) poisoning of the catalyst active sites with reactant which reduces contact area between reactant and catalytic sites and ii) the trace solubility of calcium oxide in the reaction mixture [31]. The calcium ion concentration in microalgae biodiesel was determined using ICP. The result depicted the lowest calcium ion loss in the biodiesel produced during fresh CaO catalyst at 0.72 ppm, which changed to 2.61, 3.91 and 9.21 ppm for first, third and sixth cycles respectively. Moreover, metal ion leaching was in
Fig. 7. a-c) SEM- image after 1st, 3rd and 6th reuse cycles d) Reusability of CaO catalyst (%).
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between the range of 1.21e4.78 ppm upto third reuse cycle and resulted suitability of microalgae biodiesel produced that compiles EN 14214 fuel standard [32]. However, there was sudden drop of the calcium element concentration in the sixth reuse cycle, resulting in increased calcium ion leaching and decreased microalgae biodiesel yield. Hence, reusability study depicted that egg shell waste CaO catalyst was stable upto three reuse cycles. 3.7. Analysis of biodiesel by nuclear magnetic resonance (1H NMR) The 1H NMR spectra was obtained after converting triglycerides into FAME with the presence of egg shell CaO catalyst (Supplementary Fig. S2). The characteristic peak of a-methylene protons as a triplet at 2.30 ppm and methoxy protons as a singlet at 3.66 ppm was recorded. These two sharp peaks confirm the presence of methyl esters [33]. The other peaks were recorded at (0.8e0.9) ppm due to the presence of terminal methyl group protons and a strong doublet peak at 1.57 ppm arises from the methylene proton of carbon chain [34]. A small characteristic peak around at 1.63 ppm was due to b carbonyl methylene protons and a single peak at 5.35 ppm was due to olefinic hydrogen [35]. The results obtained in this study were according to the Niju et al. [34]. The percentage conversion of methyl ester was found to be 90.12%. 3.8. Characterization of microalgal biodiesel The fatty acid profiling is considered important in evaluating the quality of biodiesel produced. The biodiesel quality mainly depends upon the percentage of unsaturation and saturation because unsaturation enhanced cold fuel properties while saturation maintains good cetane number as well as oxidative stability. The FA composition of the C. vulgaris was 0.5 wt % myristic acid, 27.0 wt % palmitic acid, 14 wt % palmitoleic acid, 21 wt % stearic acid, 12.3 wt % oleic acid, 17 wt % linoleic acid, 7.4 wt % linolenic acid, 0.7 arachidic acid, 0.4 wt % behenic acid and 0.2 wt % Lignoceric acid. Table 5, summaries the fuel properties of microalgal (C. vulgaris) biodiesel. These properties were then compared with the standards prescribed by EN 14214 and ASTM 6751. Cetane number, cold-flow properties and viscosity is affected by the length and degree of saturation and unsaturation of the fatty acid. The microalgal biodiesel showed cetane number of 50.0 and iodine value of 88.7 gI2100/g value were within the range of biodiesel standards. The biodiesel with low cetane number makes the engine difficult to start and produce noise while low iodine value biodiesel is prone to oxidation [36]. The kinematic viscosity plays an important role in the performance of fuel atomization during combustion. Biodiesel with high viscosity tend to form larger droplets and lead to poor fuel atomization [37].
The kinematic viscosity of biodiesel was determined to be 4.5 mm2/s, which were within the range of ASTM 6751 and EN 14214 standards. Density directly affects the fuel injection system as it measures fuel by volume. Thus, change in the mass of injected fuel will change in density and effects engine performance [38]. Long chain saturation factor (LCSF) influences both oxidative stability (OS) and cold response of biodiesel. The LCSF, OS, APE and BAPE were within the range of the biodiesel standards. The oxidative stability of microalgal biodiesel is another important parameter, especially in places with warm climate. The oxidative stability depends upon the number of double bond and existence of allylic and bis-allylic hydrogen [39]. The fuel with large amount of unsaturation is more susceptible to oxidation than those having more saturated fatty acid. OS significantly influenced by the conditions such as storage, transport, and handling and can be modified by anti-oxidant additives [40]. The biodiesel from C. vulgaris resulted high degree of unsaturation, hence process of oxidation started at low temperature. While, APE and BAPE were highly influenced by number and position of carbon double bond. In BAPE presence of one bis-allylic position at C-11 in linoleic acid and two bis-allylic positions at C-11 and C-14 in linolenic acid were more prone to auto oxidation than APE [41]. The lowest temperature at which crystals grow and become visible is known as cloud point. The highest temperature at which the crystal fused together and agglomerates which restrict flow of fuel and hinder operability of diesel engine is called as pour point. The flow properties including CP and PP have value of 3.1 C and 9 C respectively, which meets the biodiesel standards which ranges from 3 to 15 and -5 to 10 respectively. The CP and PP properties are affected by i) chain length longer carbon chain increases melting point and decreases the performance at lower temperature ii) double bond with cis configuration improve biodiesel cold properties than trans configuration [42]. However, the problem associated with reliable cold flow properties can be overcome by blending with an appropriate depressants. Therefore, the biodiesel produced from C. vulgaris using CaO catalyst obtained from waste eggshells can be utilized as substitute fuel for commercial diesel. 4. Conclusion The experiment results showed that CaO catalyst derived from egg shell waste was successfully used for the direct conversion of microalgae biomass to biodiesel. The parameters such as catalyst loading, reaction time and stirring rate were evaluated, where biodiesel yield was significantly affected by the investigated variables. The transesterification reaction kinetics were investigated by using RSM based CCD matrix and a 92.03% microalgae biodiesel yield was reported at optimal reaction conditions, of 1.39% (wt/wt)
Table 5 Fuel properties of microalgal biodiesel. Biodiesel properties
ASTM -6751 biodiesel standard
EN-14214 biodiesel standard
Degree of Unsaturation (DU) Saponification Value (SV) Iodine Value (IV) g I2 100/g Cetane Number (CN) Long Chain Saturated Factor (LCSF) Cloud Point (CP) C Pour point (PP) Allylic Position Equivalents (APE) Bis Allylic Position Equivalents (BAPE) Oxidation Stability (OS) (hours) Higher Heating Value (HHV) Kinematic Viscosity (U) (mm2/s) Density (r) (g/cm3)
e e e 47-65 e 3 to 15 5 to 10 e e 3 min 127, 042 1.9e6.0 0.86
e e 120 51e120 e e e e e 6 min e 3.5e5 0.85e0.90
Fuel values C. vulgaris 88.7 233.71 88.5 50.0 14.5 9.2 3.1 75.3 33.6 7.4 44.7 4.5 0.9
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catalyst concentration, reaction time 3 (h) and stirring rate 140 (rpm) at constant 75 C temperature and 1:10 (wt/vol) biomass/ methanol ratio. The reusability study revealed that the catalyst was stable upto three cycles and conferms to an average of 85.22% microalgae biodiesel yield. The fuel properties of microalge biodiesel as obtained were found to be closely related to the biodiesel standards.
[17]
[18]
[19]
Acknowledgments The authors expresses thanks to Centre for Nanoscience and Nanotechnology (Jamia Millia Islamia, New Delhi) for assistance with instruments (TEM and SEM) facility, BIT Bangalore for BET analysis and the Central University of Gujarat for providing the research facilities to carry out the present research study.
[20]
[21] [22]
[23]
Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.renene.2019.01.047. References [1] P. Patil, H. Reddy, T. Muppaneni, S. Ponnusamy, Y. Sun, P. Dailey, P. Cooke, U. Patil, S. Deng, Bioresource Technology Optimization of microwaveenhanced methanolysis of algal biomass to biodiesel under temperature controlled conditions, Bioresour. Technol. 137 (2013) 278e285, https:// doi.org/10.1016/j.biortech.2013.03.118. [2] S. Wahidin, A. Idris, S. Raehanah, M. Shaleh, Rapid Biodiesel Production Using Wet Microalgae via Microwave Irradiation, 2018, pp. 3e5. [3] Y. Zhang, Y. Li, X. Zhang, T. Tan, Bioresource Technology Biodiesel Production by Direct Transesterification of Microalgal Biomass with Co-solvent, vol. 196, 2015, pp. 712e715. [4] P. Hidalgo, G. Ciudad, S. Schober, M. Mittelbach, R. Navia, Improving the FAME Yield of in Situ Transesteri Fi Cation from Microalgal Biomass through Particle Size Reduction and Cosolvent Incorporation, 2014, https://doi.org/10.1021/ ef5023303. [5] P. Hidalgo, G. Ciudad, M. Mittelbach, R. Navia, Biodiesel production by direct conversion of Botryococcus braunii lipids : reaction kinetics modelling and optimization, Fuel 153 (2015) 544e551, https://doi.org/10.1016/ j.fuel.2015.03.039. [6] H. Im, H. Lee, M.S. Park, J. Yang, J.W. Lee, Bioresource Technology Concurrent extraction and reaction for the production of biodiesel from wet microalgae 152 (2014) 534e537. [7] J.G.M. Orta, S.B. Lee, A. Harvey, Alkaline in Situ Transesterification of Chlorella Vulgaris, vol. 94, 2012, pp. 544e550, https://doi.org/10.1016/ j.fuel.2011.11.045. [8] E.A. Ehimen, Z. Sun, G.C. Carrington, Use of ultrasound and Co-solvents to improve the in-situ transesterification of microalgae biomass, Proced. Environ. Sci. 15 (2012) 47e55, https://doi.org/10.1016/j.proenv.2012.05.009. [9] G. Ma, W. Hu, H. Pei, L. Jiang, Y. Ji, R. Mu, Study of KOH/Al 2 O 3 as heterogeneous catalyst for biodiesel production via in situ transesterification from microalgae, Environ. Technol. 36 (2015) 622e627, https://doi.org/10.1080/ 09593330.2014.954629. [10] A.M. Doyle, Z.T. Alismaeel, T.M. Albayati, A.S. Abbas, High Purity FAU-type Zeolite Catalysts from Shale Rock for Biodiesel Production High Purity FAUtype Zeolite Catalysts from Shale Rock for Biodiesel Production, 2017, https://doi.org/10.1016/j.fuel.2017.02.098. [11] M. Alsharifi, H. Znad, S. Hena, M. Ang, Biodiesel production from canola oil using novel Li/TiO 2 as a heterogeneous catalyst prepared via impregnation method, Renew. Energy 114 (2017) 1077e1089, https://doi.org/10.1016/ j.renene.2017.07.117. [12] A.M. Doyle, T.M. Albayati, A.S. Abbas, Z.T. Alismaeel, Biodiesel Production by Esteri Fi Cation of Oleic Acid over Zeolite Y Prepared from Kaolin, vol. 97, 2016, pp. 19e23. [13] T.M. Albayati, A.M. Doyle, Encapsulated Heterogeneous Base Catalysts onto SBA-15 Nanoporous Material as Highly Active Catalysts in the Transesterification of Sunflower Oil to Biodiesel, vol. 17, 2015, pp. 1e10, https:// doi.org/10.1007/s11051-015-2924-6. [14] T.A. Hassan, V.K. Rangari, R.K. Rana, S. Jeelani, Ultrasonics sonochemistry sonochemical effect on size reduction of CaCO3 nanoparticles derived from waste eggshells, Ultrason. Sonochem. 20 (2013) 1308e1315, https://doi.org/ 10.1016/j.ultsonch.2013.01.016. [15] M.D. Putra, Y. Ristianingsih, R. Jelita, C. Irawan, I.F. Nata, Potential waste from palm empty fruit bunches and eggshells as a heterogeneous catalyst for biodiesel production, RSC Adv. 7 (2017) 55547e55554, https://doi.org/ 10.1039/C7RA11031F. [16] A. Buasri, N. Chaiyut, V. Loryuenyong, C. Wongweang, S. Khamsrisuk,
[24]
[25]
[26]
[27]
[28]
[29]
[30] [31]
[32]
[33] [34] [35]
[36] [37]
[38]
[39]
[40]
[41]
[42]
845
Application of eggshell wastes as a heterogeneous catalyst for biodiesel production, Sustain. Energy 1 (2013) 7e13, https://doi.org/10.12691/rse-1-2-1. P.R. Pandit, M.H. Fulekar, Egg shell waste as heterogeneous nanocatalyst for biodiesel production : optimized by response surface methodology, J. Environ. Manag. 198 (2017) 319e329, https://doi.org/10.1016/j.jenvman.2017.04.100. K. Kanaga, A. Pandey, S. Kumar, Bioresource Technology Multi-objective optimization of media nutrients for enhanced production of algae biomass and fatty acid biosynthesis from Chlorella pyrenoidosa, NCIM 2738 (200) (2016) 940e950. G. Knothe, Analyzing biodiesel: standarts and other methods, JAOCS (J. Am. Oil Chem. Soc.) 83 (2006), https://doi.org/10.1007/s11746-006-5033-y. A. Linggawati, S. Anita, T.A. Amri, Preparation and Characterization of Calcium Oxide Heterogeneous Catalyst Derived from Anadara Granosa Shell for Biodiesel Synthesis, 2016, 2016, pp. 1e8, https://doi.org/10.18502/keg.v1i1.494. Y.Y. Margaretha, H.S. Prastyo, A. Ayucitra, S. Ismadji, Calcium Oxide from Pomacea Sp . Shell as a Catalyst for Biodiesel Production, 2012, pp. 1e9. N. Viriya-empikul, P. Krasae, B. Puttasawat, B. Yoosuk, N. Chollacoop, K. Faungnawakij, Bioresource Technology Waste Shells of Mollusk and Egg as Biodiesel Production Catalysts, vol. 101, 2010, pp. 3765e3767, https://doi.org/ 10.1016/j.biortech.2009.12.079. R. Ljupkovi, M. Tehnicki, M. Pupin, N. Radulovi, A. Boji, Significance of the Structural Properties of CaO Catalyst in the Production of Biodiesel : an Effect on the Reduction of, 2014, https://doi.org/10.2298/HEMIND130612063L. R. Anr, A.A. Saleh, S. Islam, S. Hamdan, A. Maleque, Biodiesel Production from Crude Jatropha Oil Using a Highly Active Heterogeneous Nanocatalyst by Optimizing Transesteri Fi Cation Reaction Parameters, 2015, https://doi.org/ 10.1021/acs.energyfuels.5b01899. Z. Mirghiasi, F. Bakhtiari, E. Darezereshki, Journal of Industrial and Engineering Chemistry Preparation and Characterization of CaO Nanoparticles from Ca ( OH ) 2 by Direct Thermal Decomposition Method, vol. 20, 2014, pp. 113e117. P. Boey, G. Pragas, S. Abd, Bioresource Technology Biodiesel Production via Transesterification of Palm Olein Using Waste Mud Crab ( Scylla serrata ) Shell as a Heterogeneous Catalyst, vol. 100, 2009, pp. 6362e6368, https://doi.org/ 10.1016/j.biortech.2009.07.036. H. Liu, L. Su, Y. Shao, L. Zou, Biodiesel production catalyzed by cinder supported CaO/KF particle catalyst, Fuel 97 (2012) 651e657, https://doi.org/ 10.1016/j.fuel.2012.02.002. W. Widayat, T. Darmawan, R.A. Rosyid, H. Hadiyanto, Biodiesel production by using CaO catalyst and ultrasonic assisted, J. Phys. Conf. Ser. 877 (2017), https://doi.org/10.1088/1742-6596/877/1/012037. G. Chen, R. Shan, J. Shi, B. Yan, Ultrasonic-assisted production of biodiesel from transesterification of palm oil over ostrich eggshell-derived CaO catalysts, Bioresour. Technol. 171 (2014), https://doi.org/10.1016/ j.biortech.2014.08.102. M. Mathiyazhagan, a Ganapathi, Factors affecting biodiesel production, Res. Plant Biol. 1 (2011) 1e5. I. Istadi, U. Mabruro, B.A. Kalimantini, L. Buchori, D.D. Anggoro, Reusability and stability tests of calcium oxide based catalyst (K2O/CaO-ZnO) for transesterification of soybean oil to biodiesel, Bull. Chem. React. Eng. Catal. 11 (2016) 34e39, https://doi.org/10.9767/bcrec.11.1.413.34-39. R. Anr, A.A. Saleh, M.S. Islam, S. Hamdan, M.A. Maleque, Biodiesel production from crude jatropha oil using a highly active heterogeneous nanocatalyst by optimizing transesterification reaction parameters, Energy Fuels 30 (2016) 334e343, https://doi.org/10.1021/acs.energyfuels.5b01899. G. Knothe, Analyzing biodiesel : standards and other methods 83 (2006) 823e833. S. Niju, K.M.M.S. Begum, N. Anantharaman, Modification of Egg Shell and its Application in Biodiesel Production, 2014, pp. 702e706. ~o, A.G. Ferreira, Determination of M.R. Monteiro, A.R.P. Ambrozin, L.M. Lia biodiesel blend levels in different diesel samples by 1 H NMR 88 (2009) 691e696, https://doi.org/10.1016/j.fuel.2008.10.010. O. Download, P. Export, Waste Capiz ( Amusium Cristatum ) Shell as a New Heterogeneous Catalyst for Biodiesel Production, 2017, pp. 2012e2014. L.F. Ramírez-Verduzco, J.E. Rodríguez-Rodríguez, A.D.R. Jaramillo-Jacob, Predicting cetane number, kinematic viscosity, density and higher heating value of biodiesel from its fatty acid methyl ester composition, Fuel 91 (2012) 102e111, https://doi.org/10.1016/j.fuel.2011.06.070. Y.H. Chen, B.Y. Huang, T.H. Chiang, T.C. Tang, Fuel properties of microalgae (Chlorella protothecoides) oil biodiesel and its blends with petroleum diesel, Fuel 94 (2012) 270e273, https://doi.org/10.1016/j.fuel.2011.11.031. L.M.D.S. Freire, I.M.G. Dos Santos, J.R. De Carvalho Filho, A.M.T.D.M. Cordeiro, L.E.B. Soledade, V.J. Fernandes, A.S. De Araujo, A.G. De Souza, Influence of the synthesis process on the properties of flow and oxidative stability of biodiesel from Jatropha curcas biodiesel, Fuel 94 (2012) 313e316, https://doi.org/ 10.1016/j.fuel.2011.10.054. E.G. Giakoumis, A statistical investigation of biodiesel physical and chemical properties, and their correlation with the degree of unsaturation, Renew. Energy 50 (2013) 858e878, https://doi.org/10.1016/j.renene.2012.07.040. Pe rez, Influence of fatty M.J. Ramos, C.M. Fern andez, A. Casas, L. Rodríguez, A. acid composition of raw materials on biodiesel properties, Bioresour. Technol. 100 (2009) 261e268, https://doi.org/10.1016/j.biortech.2008.06.039. G. Knothe, Biodiesel: current trends and properties, Top. Catal. 53 (2010) 714e720, https://doi.org/10.1007/s11244-010-9457-0.
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Biodiesel production from microalgal biomass using CaO catalyst synthesized from natural waste material Priti R. Pandit, M.H. Fulekar* School of Environment and Sustainable Development, Central University of Gujarat, Gandhinagar, Gujarat, India
a r t i c l e i n f o
a b s t r a c t
Article history: Received 11 October 2017 Received in revised form 14 November 2018 Accepted 13 January 2019 Available online 16 January 2019
Calcium oxide (CaO) catalyst was prepared using chicken egg shell waste and tested as a catalyst for the production of biodiesel from Chlorella vulgaris biomass. The calcination method was adopted for the synthesis of CaO catalyst. Transmission electron microscope (TEM) image showed that the catalyst had a spherical structure with average particle size of 46.1 ± 2.1 nm, further analysis was carried out using Brunauer-Emmett-Teller (BET) adsorption, scanning electron microscopy, elemental analysis, X-ray diffraction and Fourier-transform infrared spectroscopy. Transesterification process was conducted by using response surface methodology (RSM) based on central composite design (CCD). The optimum reaction conditions were observed at 70 C, 10:1 methanol: dry biomass ratio, 1.39% catalyst loading, 3 h reaction time, and 140 rpm stirring rate resulted 92.03% biodiesel yield. The key fuel properties includes; iodine value (88.5 g I2 100/g), cetane number (50.0), cloud point (9.2 C), pour point (3.1 C), oxidation stability (7.4 h), higher heating value (44.7), kinematic viscosity (4.5 mm2/s) and density (0.9 g/cm3) resulted good quality of microalgae biodiesel. Our research finding shows that the CaO catalyst derived from egg shell waste is an economically potential and eco-friendly catalyst for biodiesel production. © 2019 Elsevier Ltd. All rights reserved.
Keywords: Transesterification Catalyst Biodiesel and Brunauer-Emmett-Teller
1. Introduction Microalgae have grabbed great attention during past decades, as a renewable biofeedstock for biodiesel production, owing to its high photosynthetic yield compared to other traditional crops, high lipid content, rapid growth rate, higher biomass productivity and eco-friendly nature [1]. Despite of various benefits, microalgal biodiesel production still faces techno-economical problems, mainly in the large-scale cultivation, lipid extraction and fuel conversion process [2]. The main critical points are lipid extraction process with energy consumption near 90%, and lipid transesterification, with a 10% of total energy consumption from microalgal biodiesel production [3,4]. Hence, lipid extraction is considered as one of the most limiting step for the industrial scale up process [5]. With the purpose of eliminating lipid extraction process, the implementation of direct (in-situ) transesterification of microalgal biomass in the presence of catalyst has been investigated. Im et al. [6] reported, 91.1% of biodiesel yield obtained by direct transesterification of wet microalgal biomass at 95 C with
* Corresponding author. E-mail addresses: [email protected] (P.R. Pandit), mhfulekar@yahoo. com (M.H. Fulekar). https://doi.org/10.1016/j.renene.2019.01.047 0960-1481/© 2019 Elsevier Ltd. All rights reserved.
2:1 chloroform methanol ratio, 0.3 g H2SO4, 65% moisture content and a reaction time of 90 min. Moreover, Ortia et al. [7] studied in situ transesterification of Chlorella vulgaris and reported 77.6 wt % biodiesel yield using NaOH as a catalyst and a methanol/lipid molar ratio of 600:1 at 60 C for 75 min. While, 88% of biodiesel yield using 315:1 methanol lipid molar ratio was reported by Ehime et al. [8]. Ma et al. [9] resulted 89.53% biodiesel yield from microalgae using KOH/Al2O3 heterogeneous catalyst. Doyle et al. [10] prepared FAU-type zeolite catalyst from shale rock and reported 78% conversion of biodiesel. Umdu et al. [11] reported 97.3% of biodiesel yield in Nannochloropsis oculata lipid by using Al2O3 supported CaO and MgO catalyst. Doyle et al. [12] reported a Zeolite Y with a Si/Al catalyst for esterification of oleic acid. Whereas, Albayati and Doyle [13] prepared encapsulated heterogeneous base catalyst onto SBA-15 nanoporous material for transesterification of sunflower oil to biodiesel and reported 96% yield of fatty acid methyl ester. However, high yield of biodiesel were obtained by these studies but the technology associated with these methods are very expensive, demands high energy and hence; increases the production cost of biodiesel. Therefore, efforts have been made to utilize eggshell waste as a cheap and widely available potential source for synthesis of catalyst. Chicken egg shell waste contains more than 94% CaCO3 [14] and simply by calcination process CaO catalyst can be formed. Moreover, CaO has
838
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been known for its high alkalinity, low solubility in methanol and high catalytic activity that makes CaO potential solid base catalyst for biodiesel production [15]. Hence, the utilization of eggshell waste as raw material for catalyst synthesis could eliminate the waste and simultaneously produce the catalyst with high cost effectiveness [16]. Here, we show that chicken egg shell waste is the excellent source to prepare CaO heterogeneous catalyst for direct transesterification of microalgal biomass to biodiesel. The calcination method was used for the preparation of CaO catalyst. The impact of transesterification reaction parameters and their interaction were analysed by using central composite design based on resonance surface model. The fuel properties of the biodiesel produced were described by iodine value, cetane number, cloud point, pour point, oxidation stability, higher heating value, kinematic viscosity and density. In addition, CaO leaching, catalyst stability and reusability were also assessed. The purity of biodiesel was characterized by nuclear magnetic resonance analysis.
2. Materials and method 2.1. Chemical reagents and microalgae The chemical reagents used in this study, including methanol and ethyl acetate were purchased from Himedia (India; HPLC-grade >99.8%). Heptadecanoic acid, potassium bromide (FTIR- grade) and chloroform (NMR-grade) were purchased from Sigma-Aldrich. Microalgae (Chlorella vulgaris), which were isolated from low tidal region of Dwarka coast, Gujarat, India. The C. vulgaris was cultured in BG-11 medium and incubated in 5L photobioreactor with 3L of culture media at 25 ± 2 C and illuminated by fluorescent lamps for 16 h (90.15 m mol m2 s1). After 15 days, the microalge strain was harvested by centrifugation at 5000 rpm for 10 min. The obtained microalgal biomass was dried at 40 C in hot air oven for overnight and ground in mortar for subsequent use. Characterization was performed on the C. vulgaris biomass, including moisture content and ash content. It was found that the microalgae biomass contains 1.28 wt % moisture and 10.2 wt % ash content on a dry weight basis.
2.2. Synthesis of CaO catalyst In our pervious reported literature CaO catalyst was synthesized by calcination- hydration-dehydration method [17]. Here, we applied simple calcination method for the synthesis of CaO catalyst. The chicken-egg shells waste was collected from University canteen, Gujarat, India. The egg shells were thoroughly washed with distilled water for 2e3 times and boiled for 10 min in order to separate the adhering membrane. The egg shells were then dried at 105 C in a hot air oven for overnight. After that, dried shells were grinded using a blender until it become fine powder and calcinated in a muffle furnace at 900 C for 4 h. The obtained calcinated powder was labeled as CaO catalyst and used for characterization analysis. 2.3. Characterization of CaO catalyst The obtained CaO catalyst was characterized using fourier transform infrared (FTIR)-spectrophotometer (Spectrum 65 series, Perkin Elmer) with KBr (AR, Sigma USA) powder for structure analysis. The IR spectrum in the range of 400e4000 cm1 was recorded. The surface morphology of catalyst was performed using field-emission scanning electron microscopy (FE-SEM) equipped with an energy-dispersive X-ray analysis (EDX) for elemental composition (EVO 18, Carl Zesis) and for crystalline properties X-ray diffraction pattern was recorded. Size and shape of the CaO catalyst were obtained by using a transmission electron microscope (TEM). The textural properties were determined by Brunauer-Emmett-Teller (BET) for surface area and Barrett-Joyner-Halenda (BJH) method were applied to obtain pore volume and pore diameter respectively. 2.4. Experimental setup The process of direct transesterification in the presence of CaO catalyst for biodiesel production is shown in Fig. 1. The experiment was performed in 150 ml round bottom flask equipped with reflux condenser and magnetic stirrer. To the round bottom flask, 1 g of dried C. vulgaris biomass was taken. The required amount of CaO
Fig. 1. Showing direct transesterification process using CaO catalyst.
P.R. Pandit, M.H. Fulekar / Renewable Energy 136 (2019) 837e845
catalyst (0.5e2.5 w/w) was poured into a beaker containing corresponding amount of manually optimized methanol to biomass ratio of 10:1 wt/vol and allowed to mix for 15 min to homogenize the mixture. After that, the mixture was added to the round bottom flask containing biomass and the reaction was allowed to react at a continuous stirring speed (50e200 rpm) with constant temperature 70 C for a period of 1e4 h. After completion of reaction, mixture was allowed to cool. The reaction mixture was transferred in the separating funnel and was separated by adding the mixture of water and ethyl acetate in the ratio of 3:1. The upper organic layer containing methyl ester was thoroughly washed with distilled water and passed over anhydrous sodium sulphate column to remove traces of water. The phase containing ethyl acetate was evaporated on a rotary evaporator to recover fatty acid methyl esters (FAME). The amount of fatty acid methyl ester (biodiesel) was gravimetrically quantified and stored at 4 C for the analysis of FAME content by using nuclear magnetic resonance and gas chromatography. All the experiments were performed in triplicate and average results were reported. 2.5. Statistical analysis of experimental design The biodiesel optimization was carried out using the Response Surface Methodology (RSM) created by Minitab 17.1, PA, USA. RSM design tool known as central composite design (CCD) was applied to study the effect of the reaction parameters and their interaction. Table 1 depicts the ranges and levels of the three identified independent reaction parameters (variables). The independent variable are coded as low (-a) and high (þa) where as value of a ¼ 1.62 FAME yield was chosen as the response obtained from the reaction. The total number of experiments was calculated by following equation [18].
Table 1 Levels and ranges of transesterification parameters in CCD. Factors
Levels
Reaction time (h) (A) Catalyst concentration (%w/w) (B) Stirring rate (rpm) (C)
1
0
þ1
2 0.5 100
3 1.25 150
4 2 200
839
N ¼ 2K þ 2K þ 6 ¼ 23 þ ð2 X 3Þ þ 6 ¼ 20 runs
(1)
Where, N ¼ total number of experiments, K ¼ number of parameters and 6 is the number of replicates at the centre points to calculate the pure error. The complete design matrix obtained from CCD design for experiment and predicted results are tabulated in Table 2. The experiment runs were performed at random in order to minimize the error occurred from the systematic trends in the variables. To predict the optimal level between the response and independent variables of transesterfication reaction, a second-order polynomial equation model was applied:
BY ¼ b0 þ
3 X i¼1
bi ki þ
3 X
bii k2i þ
i¼1
2 X
3 X
i¼1
i < j¼1
bij ki kj
(2)
Where, BY is the predicted biodiesel yield, b0 bj bij and bjj are constant coefficients; ki and kj are the coded independent parameters, ε is random error. The quality of model was evaluated by regression analysis and analysis of variance (ANOVA). Contour and surface plots were developed using the quadratic polynomial equation obtained from regression analysis. To validate the quadratic polynomial model, confirmatory experiment were also performed. 2.6. FAME characterization and fuel properties The FAME was characterized by 1H Nuclear Magnetic Resonance Spectroscopy (NMR) using Bruker 500 MHz Avance III (AV 500) spectrometer. Chloroform (CDCl3) was used as solvent. NMR spectrum was recorded with pulse duration of 48 , a recycle delay of 1.30 s and 16 scans. The percentage conversion of methyl ester was calculated according to the literature reported by Knothe [19]. Furthermore, the fuel quality parameters such as iodine value g I2100 g 1 (IV), cetane number (CN), saponification value (SV), degree of unsaturation % wt. (DU), cloud point oC (CP), higher heating value MJ/Kg (HHV); long chain saturated factor oC (LCSF); kinematic viscosity mm2/s (y); pour point oC (PP), oxidative stability h (OS) and the density g/cm3 (r) were determined based on fatty acid profiling using GC-MS.
Table 2 Experiment design using central composite matrix for C. vulgaris for biodiesel yield (% w/w). Level of experimental factor Run order
Std order
Point
A (h)
B (w/w)
C (rpm)
Yield (%)
Prediction
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
6 10 15 17 2 7 11 16 18 5 19 9 20 14 1 8 13 4 12 3
1 1 0 0 1 1 1 0 0 1 0 1 0 1 1 1 1 1 1 1
4 4 3 3 4 2 3 3 3 2 3 2 3 3 2 4 3 4 3 2
0.5 1.25 1.25 1.25 0.5 2 0.5 1.25 1.25 0.5 1.25 1.25 1.25 1.25 0.5 2 1.25 2 2 2
200 150 150 150 100 200 150 150 150 200 150 150 150 200 100 200 100 100 150 100
68.93 85.23 90.46 90.27 63.43 66.23 67.93 91.37 92.04 44.23 91.02 81.06 89.08 85.09 40.5 58.23 87.31 65.41 79.56 80.2
69.63 85.87 90.82 90.82 62.72 67.01 67.11 90.82 90.82 44.08 90.82 80.07 90.82 84.61 41.45 57.35 87.44 65.63 80.03 79.58
840
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2.7. Catalyst reusability The stability and reusability of the synthesized CaO catalyst is an important concern for the calciumebased catalyst, due to the leaching of CaO to other reactants during transesterification processes. The reusability of obtained CaO catalyst was performed upto six reuse cycles. After first cycle of reaction, the catalyst was recovered from reaction mixture by filtration and washing with methanol for several times. The recovered catalyst was oven dried for overnight and recalcinated at 800 C for 2 h before reusing. This process was continued for rest of the reusable cycles, performed at optimal transesterification parametric conditions, including; 1.39% (wt/wt) catalyst concentration, reaction time 3 (h) and stirring rate 140 (rpm) at constant 70 C temperature and 1:10 (wt/vol) biomass/methanol ratio. The surface morphology of recovered catalyst was investigated by using FE-SEM (EVO 18, Carl Zesis). The biodiesel obtained from each cycle was tested using inductive coupled plasma mass spectrometry (ICP: Model: 7300DV, Perkin Elmer) to measure the amount of calcium ions concentration leached into the biodiesel.
3. Result and discussion 3.1. CaO nano catalyst characterization The IR spectra of the CaO catalyst derived from chicken egg shell calcined for 3 h at 900 C were shown in Fig. 2. The IR spectra of sample were obtained using KBr method at room temperature and spectra were recorded at 400-4000 cm1. The characteristic peaks at 1420 and 874.1 cm1 attributed to CeO stretching and bending mode of CaCO3. Similar peak was also recorded by Nurhayati et al. [20] using Anadaragranosa shell as catalyst. Besides, the board transmission band at 3642.3 cm1 was associated with OH stretching vibration. This was due to the physisorbed water molecule on the surface of the CaO [21]. Furthermore, during calcination CaCO3 decomposed into CaO and CO2, sharp band at around 526.4 cm1 contributed to the presence of CaO. The results were in accordance with our pervious publication Pandit and Fulekar [17]. The XRD spectra of CaO catalyst were matched with the JCPDS 77e9574, the intense peaks were observed at 36.25, 53.12 and 64.12 with corresponding (hkl) value (200), (220) and (311) respectively (Fig. 3). The average crystalline size of CaO catalyst was found to be 49 nm. FE-SEM micrograph was carried out to determine the surface morphology of the CaO catalyst (Fig. 4a). The results depict nearly distorted spherical shape of the calcium oxide catalyst due to the
Fig. 3. XRD spectra of CaO catalyst.
formation of aggregates. The chemical composition of CaO catalyst was performed using EDX, and the results were illustrated in Fig. 4b. The composition of the catalyst produced by calcination of egg shell mainly consists of CaO 98.12% by weight with small amount of other metal as impurities as shown in Fig. 4b. Fig. 5a, illustrated the TEM micrograph of CaO catalyst. From TEM micrograph, it was found that the CaO nano particles were bonded together to form aggregates. The smaller size and aggregation is directly proportional to the higher specific surface area [22]. Particle size distribution of CaO nanoparticles were shown in Fig. 5b by counting nearly 50 particles from TEM image. The average particle size was 46.1 nm with spherical shape. The results obtained were in accordance with our perviuos publication Pandit and Fulekar [17]. The textual properties (specific surface area, average pore diameter and pore volume) of CaO catalyst was determined by BET and BJH analysis. These properties are very important for the solid base heterogeneous catalyst because they influence the catalytic efficiency of transesterification process [23]. The specific surface area, average pore diameter and pore volume of CaO catalyst was 15.73 m2g, 3 nm and 0.013 cc2g respectively. The reported mean pore diameters of CaO catalyst are between 2 and 50 nm, which represents mesopores and illustrates their suitability as a catalyst, for adsorption etc [24]. Mirghiasi et al. [25] reported specific surface area of CaO catalyst at different temperatures of 500, 750 and 900 C were 5.2, 4.7 and 4.1 m2g, respectively. Correria et al. [26] derived CaO from eggshell and crab shell with specific surface area value of 1.93 and 1.60 m2g with average pore volume 0.006 and 0.004 for biodiesel production from sunflower oil, respectively. Thus, in this study the specific surface area of CaO nano catalyst synthesized from egg shells have higher specific surface area as compared to above reported literatures.
3.2. Regression analysis for optimal microalgal biodiesel yield
Fig. 2. FT-IR spectra of CaO catalyst.
A central composite design of 20 experiments was conducted to analyze the influence of the variables and their interactions on the biodiesel (FAME) yield. The optimal reaction condition for maximizing biodiesel yield, responses of FAME yield with varying variables for in situ transesterification process is presented in Table 2. The comparative results between the experimental and predicted yield for both microalgal strains in percentage were represented graphically in Supplementary Fig. S1. The results depicted that the predicted yield were closely adjoining with the experimental yield. Thus, indicates the reliability of the predicted model and also an intimate interaction among the studied three independent input variables and dependent response parameter on microalgal biodiesel yield.
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Fig. 4. CaO catalyst showing: a) FE-SEM image b) EDX- composition.
Fig. 5. CaO catalyst a) TEM micrograph b) particle size distribution histogram.
The multiple regression coefficients of the model were obtained from the statistical software Minitab 17.1 tabulated in Table 3. The significance of each coefficient was determined by the p-value (probability < 0.05). The regression coefficients b1, b2 and b3 represent linear factors A, B and C; b11, b22 and b33 represent quadratic coefficients A2, B2 and C2 whereas b12 b13 and b23 represent interaction coefficients AB, AC and BC respectively and were significant because each of the value were less than 0.05 (95% confidence interval). The prediction model derived from the regression coefficients in coded variables are:
C: vulgaris biodiesel yield ¼ e139:42 þ 61:44A þ 135:66B þ 0:609C 7:846A2 30:66B2 2
0:001916C 11:737AB
Table 3 Regression coefficients estimation for microalgae (C. vulgaris) biodiesel yield. Coefficient C. vulgaris b0 Constant Linear b1 (A) b2 (B) b3 (C) Square b11 (A2) b22 (B2) b33 (C2) Interaction b12 (AB) b13 (AC) b23 (BC)
Value
SE
T-Value
P-value
90.820
0.370
245.62
0.000
2.901 6.461 1.414
0.340 0.340 0.340
8.53 19.00 4.16
0.000 0.000 0.002
7.846 17.246 1.894
0.649 0.649 0.649
12.10 26.59 7.39
8.803 1.070 3.798
0.380 0.231 9.99
23.15 2.81 9.99
0.000 0.000 0.000 0.000 0.000 0.008 0.000
þ 0:02140AC 0:1013BC (3)
3.3. ANOVA for microalgal biodiesel yield To determine the fitness and significance of regression model, analysis of variance (ANOVA) tests were conducted (Table 4). The
regression model was statistically well-fitted since the R2 value of model prediction was 0.9975%. It implies that 99.75% as a total variation with 99.53% as the adjusted R2 value. Moreover, the pvalue was less than 0.05 which further indicates precision and fitness for associated model. In addition, insignificant lack of fit further indicates the adequacy of the predicted model.
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Table 4 Analysis of Variance (ANOVA) for response surface quadratic model of FAMEs. Source
DF
Adj.SS
Adj.MS
F
P
Model Linear Square Interaction Residual error Lack-of-fit Pure error Total
9 3 3 3 10 5 5 19
4708.79 521.60 2334.35 744.40 11.57 6.36 5.21 4720.36
523.20 173.87 778.12 248.13 1.16 1.27 1.04
452.24 150.28 89.95 214.48
0 0 0 0.000
1.22
0.417
R2 ¼ 99.75%, adj R2 ¼ 99.53%, R-sq(pred) ¼ 97.79% (DF e degree of freedom; Adj. SS e adjusted Sum of squares; Adj. MS e adjusted mean of square; F e probability distribution; P e probability > F).
3.4. Impact of transesterification parameters and interactions for C. vulgaris biodiesel yield Impact of reaction time, catalyst concentration and stirring rate on the response microalgal biodiesel yield are depicted graphically in Fig. 5. The reaction temperature and dry microalgal biomass to methanol ratio was kept constant at 75 C and 1:10 (wt/vol) respectively for all experiment runs. Fig. 6a illustrates reaction time (A) and catalyst concentration (B) and their interaction on C. vulgaris biodiesel yield at constant stirring rate (C) of 150 rpm.
Based on the 2D and 3D plots, the effect of the increased reaction time from 2 to 3.5 h, starting from a catalyst ratio of 0.5e1.67 (wt/ wt), proportionally increased biodiesel yield and beyond this the response declines. This result indicated that increasing catalyst concentration with an increment in the reaction time increased the biodiesel yield. This was because longer reaction time favoured the distribution of cell wall, accelerated the release of lipid from microalgae and provides sufficient time to contact with reactant mixtures and hence increase the biodiesel yield. Zhang et al. [3] reported 90.18% of biodiesel yield for direct transesterification of microalgal biomass at 2.0 h reaction time. While, as shown in Fig. 6 (a) the biodiesel yield start decreasing as the catalyst concentration was increased further. This was due to higher dosage of catalyst lead to the saponification reaction, caused by Ca(OH)2 hence decreased the biodiesel yield. Ma et al. [27] also reported biodiesel yield was increased from 27.73% to 86.35% as the KF/CaO catalyst concentration increased from 4% to 12% and decreased beyond 14% catalyst concentration. The results were also in accordance with Widayat et al. [28] and Chen et al. [29]. The maximum biodiesel yield of 91.4% with catalyst concentration 1.37% and reaction time 3.0 h was achieved with the combination of these two parameters. Fig. 6b shows the interaction between catalyst concentration and stirring rate while other parameters are kept constant (molar
Fig. 6. Surface and contour plots of a) reaction time and catalyst ratio interaction b) reaction time and stirring rate interaction and c) stirring and catalyst ratio interaction impact on microalgal (Chlorella vulgaris) biodiesel yield; A ¼ reaction time; (h) B ¼ catalyst ratio (% wt/wt); C¼ Stirring rate (rpm).
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ratio 1:10, reaction time 3 h). It can be seen in Fig. 6b that an increase in catalyst concentration affects the biodiesel yield for both the low and high stirring rate. It was observed that the transesterification reaction was practically incomplete at 110 rpm and only 65% of biodiesel yield. However, at 137.7 rpm stirring speed with 1.3% catalyst concentration 91.37% of biodiesel yield was achieved. The plots, shows that stirring rate have moderate effect on the biodiesel yield but when coupled with the catalyst concentration the response shows significant increase in the biodiesel yield upto 91%. Thus, stirring prevents the clumping of biomass with methanol mixture and helps in forming homogenized reaction mixture and hence increase biodiesel yield. However, beyond optimum stirring rate decrease the biodiesel yield. This was because higher stirring rate favours the soap formation due to the reverse behavior of transesterification reaction [30]. Fig. 6c illustrates the effect of reaction time with stirring and their interaction on the response biodiesel yield at constant catalyst ratio of 1.25 (wt/ wt). From the 2D plot, the response region results only a range of 87.5e90.0% and thus depicts moderate impact of these interaction on the biodiesel yield. However, with increase in the This finding was similar to our pervious reported literature Pandita and Fulekar [17]. In conclusion, by fixing suitable reaction variable ranges at their mean values i. e catalyst ¼ 1.39%, time < 3 h and stirring rate <140 rpm, the maximum biodiesel can be obtained. 3.5. Optimization of microalgal biodiesel yield The optimized reaction condition for transesterification reaction was determined from experimental data obtained from statistical software Minitab 17.1. The predicted optimum transesterification reaction conditions for C. vulgaris biodiesel production were
843
estimated as 1.39% (wt/wt) catalyst concentration, reaction time 3 h and stirring rate 140 rpm. Transesterification reaction of microalgal biomass was carried out in triplicate at optimized conditions and the average value on biodiesel was reported. The maximum predicted biodiesel under the optimum condition yield for C. vulgaris was found to be 91.63% which was comparable result to the yield with CaO 92.03% under the same reaction condition. This result indicates egg shell waste can be used in biodiesel production as a catalyst. 3.6. CaO catalyst recovery The reusability and stability of calcium based catalyst in the biodiesel production is one of the major concerns for economical stability of microalgal biodiesel. After completion of the each transesterification reaction process, the calcium oxide catalyst was recovered and calcinated at 800 C. Based on the SEM image in Fig. 7aec, there was change on the surface morphology of CaO during third consecutive catalyst and resulted decreased biodiesel yield as depicted in Fig. 6d. However, the change in the surface catalyst was due to the agglomeration of other particles with the catalyst and mixing of CaO catalyst with the reactants. Moreover, the decreased catalytic activity during six reusable cycles may due the following reasons i) poisoning of the catalyst active sites with reactant which reduces contact area between reactant and catalytic sites and ii) the trace solubility of calcium oxide in the reaction mixture [31]. The calcium ion concentration in microalgae biodiesel was determined using ICP. The result depicted the lowest calcium ion loss in the biodiesel produced during fresh CaO catalyst at 0.72 ppm, which changed to 2.61, 3.91 and 9.21 ppm for first, third and sixth cycles respectively. Moreover, metal ion leaching was in
Fig. 7. a-c) SEM- image after 1st, 3rd and 6th reuse cycles d) Reusability of CaO catalyst (%).
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between the range of 1.21e4.78 ppm upto third reuse cycle and resulted suitability of microalgae biodiesel produced that compiles EN 14214 fuel standard [32]. However, there was sudden drop of the calcium element concentration in the sixth reuse cycle, resulting in increased calcium ion leaching and decreased microalgae biodiesel yield. Hence, reusability study depicted that egg shell waste CaO catalyst was stable upto three reuse cycles. 3.7. Analysis of biodiesel by nuclear magnetic resonance (1H NMR) The 1H NMR spectra was obtained after converting triglycerides into FAME with the presence of egg shell CaO catalyst (Supplementary Fig. S2). The characteristic peak of a-methylene protons as a triplet at 2.30 ppm and methoxy protons as a singlet at 3.66 ppm was recorded. These two sharp peaks confirm the presence of methyl esters [33]. The other peaks were recorded at (0.8e0.9) ppm due to the presence of terminal methyl group protons and a strong doublet peak at 1.57 ppm arises from the methylene proton of carbon chain [34]. A small characteristic peak around at 1.63 ppm was due to b carbonyl methylene protons and a single peak at 5.35 ppm was due to olefinic hydrogen [35]. The results obtained in this study were according to the Niju et al. [34]. The percentage conversion of methyl ester was found to be 90.12%. 3.8. Characterization of microalgal biodiesel The fatty acid profiling is considered important in evaluating the quality of biodiesel produced. The biodiesel quality mainly depends upon the percentage of unsaturation and saturation because unsaturation enhanced cold fuel properties while saturation maintains good cetane number as well as oxidative stability. The FA composition of the C. vulgaris was 0.5 wt % myristic acid, 27.0 wt % palmitic acid, 14 wt % palmitoleic acid, 21 wt % stearic acid, 12.3 wt % oleic acid, 17 wt % linoleic acid, 7.4 wt % linolenic acid, 0.7 arachidic acid, 0.4 wt % behenic acid and 0.2 wt % Lignoceric acid. Table 5, summaries the fuel properties of microalgal (C. vulgaris) biodiesel. These properties were then compared with the standards prescribed by EN 14214 and ASTM 6751. Cetane number, cold-flow properties and viscosity is affected by the length and degree of saturation and unsaturation of the fatty acid. The microalgal biodiesel showed cetane number of 50.0 and iodine value of 88.7 gI2100/g value were within the range of biodiesel standards. The biodiesel with low cetane number makes the engine difficult to start and produce noise while low iodine value biodiesel is prone to oxidation [36]. The kinematic viscosity plays an important role in the performance of fuel atomization during combustion. Biodiesel with high viscosity tend to form larger droplets and lead to poor fuel atomization [37].
The kinematic viscosity of biodiesel was determined to be 4.5 mm2/s, which were within the range of ASTM 6751 and EN 14214 standards. Density directly affects the fuel injection system as it measures fuel by volume. Thus, change in the mass of injected fuel will change in density and effects engine performance [38]. Long chain saturation factor (LCSF) influences both oxidative stability (OS) and cold response of biodiesel. The LCSF, OS, APE and BAPE were within the range of the biodiesel standards. The oxidative stability of microalgal biodiesel is another important parameter, especially in places with warm climate. The oxidative stability depends upon the number of double bond and existence of allylic and bis-allylic hydrogen [39]. The fuel with large amount of unsaturation is more susceptible to oxidation than those having more saturated fatty acid. OS significantly influenced by the conditions such as storage, transport, and handling and can be modified by anti-oxidant additives [40]. The biodiesel from C. vulgaris resulted high degree of unsaturation, hence process of oxidation started at low temperature. While, APE and BAPE were highly influenced by number and position of carbon double bond. In BAPE presence of one bis-allylic position at C-11 in linoleic acid and two bis-allylic positions at C-11 and C-14 in linolenic acid were more prone to auto oxidation than APE [41]. The lowest temperature at which crystals grow and become visible is known as cloud point. The highest temperature at which the crystal fused together and agglomerates which restrict flow of fuel and hinder operability of diesel engine is called as pour point. The flow properties including CP and PP have value of 3.1 C and 9 C respectively, which meets the biodiesel standards which ranges from 3 to 15 and -5 to 10 respectively. The CP and PP properties are affected by i) chain length longer carbon chain increases melting point and decreases the performance at lower temperature ii) double bond with cis configuration improve biodiesel cold properties than trans configuration [42]. However, the problem associated with reliable cold flow properties can be overcome by blending with an appropriate depressants. Therefore, the biodiesel produced from C. vulgaris using CaO catalyst obtained from waste eggshells can be utilized as substitute fuel for commercial diesel. 4. Conclusion The experiment results showed that CaO catalyst derived from egg shell waste was successfully used for the direct conversion of microalgae biomass to biodiesel. The parameters such as catalyst loading, reaction time and stirring rate were evaluated, where biodiesel yield was significantly affected by the investigated variables. The transesterification reaction kinetics were investigated by using RSM based CCD matrix and a 92.03% microalgae biodiesel yield was reported at optimal reaction conditions, of 1.39% (wt/wt)
Table 5 Fuel properties of microalgal biodiesel. Biodiesel properties
ASTM -6751 biodiesel standard
EN-14214 biodiesel standard
Degree of Unsaturation (DU) Saponification Value (SV) Iodine Value (IV) g I2 100/g Cetane Number (CN) Long Chain Saturated Factor (LCSF) Cloud Point (CP) C Pour point (PP) Allylic Position Equivalents (APE) Bis Allylic Position Equivalents (BAPE) Oxidation Stability (OS) (hours) Higher Heating Value (HHV) Kinematic Viscosity (U) (mm2/s) Density (r) (g/cm3)
e e e 47-65 e 3 to 15 5 to 10 e e 3 min 127, 042 1.9e6.0 0.86
e e 120 51e120 e e e e e 6 min e 3.5e5 0.85e0.90
Fuel values C. vulgaris 88.7 233.71 88.5 50.0 14.5 9.2 3.1 75.3 33.6 7.4 44.7 4.5 0.9
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catalyst concentration, reaction time 3 (h) and stirring rate 140 (rpm) at constant 75 C temperature and 1:10 (wt/vol) biomass/ methanol ratio. The reusability study revealed that the catalyst was stable upto three cycles and conferms to an average of 85.22% microalgae biodiesel yield. The fuel properties of microalge biodiesel as obtained were found to be closely related to the biodiesel standards.
[17]
[18]
[19]
Acknowledgments The authors expresses thanks to Centre for Nanoscience and Nanotechnology (Jamia Millia Islamia, New Delhi) for assistance with instruments (TEM and SEM) facility, BIT Bangalore for BET analysis and the Central University of Gujarat for providing the research facilities to carry out the present research study.
[20]
[21] [22]
[23]
Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.renene.2019.01.047. References [1] P. Patil, H. Reddy, T. Muppaneni, S. Ponnusamy, Y. Sun, P. Dailey, P. Cooke, U. Patil, S. Deng, Bioresource Technology Optimization of microwaveenhanced methanolysis of algal biomass to biodiesel under temperature controlled conditions, Bioresour. Technol. 137 (2013) 278e285, https:// doi.org/10.1016/j.biortech.2013.03.118. [2] S. Wahidin, A. Idris, S. Raehanah, M. Shaleh, Rapid Biodiesel Production Using Wet Microalgae via Microwave Irradiation, 2018, pp. 3e5. [3] Y. Zhang, Y. Li, X. Zhang, T. Tan, Bioresource Technology Biodiesel Production by Direct Transesterification of Microalgal Biomass with Co-solvent, vol. 196, 2015, pp. 712e715. [4] P. Hidalgo, G. Ciudad, S. Schober, M. Mittelbach, R. Navia, Improving the FAME Yield of in Situ Transesteri Fi Cation from Microalgal Biomass through Particle Size Reduction and Cosolvent Incorporation, 2014, https://doi.org/10.1021/ ef5023303. [5] P. Hidalgo, G. Ciudad, M. Mittelbach, R. Navia, Biodiesel production by direct conversion of Botryococcus braunii lipids : reaction kinetics modelling and optimization, Fuel 153 (2015) 544e551, https://doi.org/10.1016/ j.fuel.2015.03.039. [6] H. Im, H. Lee, M.S. Park, J. Yang, J.W. Lee, Bioresource Technology Concurrent extraction and reaction for the production of biodiesel from wet microalgae 152 (2014) 534e537. [7] J.G.M. Orta, S.B. Lee, A. Harvey, Alkaline in Situ Transesterification of Chlorella Vulgaris, vol. 94, 2012, pp. 544e550, https://doi.org/10.1016/ j.fuel.2011.11.045. [8] E.A. Ehimen, Z. Sun, G.C. Carrington, Use of ultrasound and Co-solvents to improve the in-situ transesterification of microalgae biomass, Proced. Environ. Sci. 15 (2012) 47e55, https://doi.org/10.1016/j.proenv.2012.05.009. [9] G. Ma, W. Hu, H. Pei, L. Jiang, Y. Ji, R. Mu, Study of KOH/Al 2 O 3 as heterogeneous catalyst for biodiesel production via in situ transesterification from microalgae, Environ. Technol. 36 (2015) 622e627, https://doi.org/10.1080/ 09593330.2014.954629. [10] A.M. Doyle, Z.T. Alismaeel, T.M. Albayati, A.S. Abbas, High Purity FAU-type Zeolite Catalysts from Shale Rock for Biodiesel Production High Purity FAUtype Zeolite Catalysts from Shale Rock for Biodiesel Production, 2017, https://doi.org/10.1016/j.fuel.2017.02.098. [11] M. Alsharifi, H. Znad, S. Hena, M. Ang, Biodiesel production from canola oil using novel Li/TiO 2 as a heterogeneous catalyst prepared via impregnation method, Renew. Energy 114 (2017) 1077e1089, https://doi.org/10.1016/ j.renene.2017.07.117. [12] A.M. Doyle, T.M. Albayati, A.S. Abbas, Z.T. Alismaeel, Biodiesel Production by Esteri Fi Cation of Oleic Acid over Zeolite Y Prepared from Kaolin, vol. 97, 2016, pp. 19e23. [13] T.M. Albayati, A.M. Doyle, Encapsulated Heterogeneous Base Catalysts onto SBA-15 Nanoporous Material as Highly Active Catalysts in the Transesterification of Sunflower Oil to Biodiesel, vol. 17, 2015, pp. 1e10, https:// doi.org/10.1007/s11051-015-2924-6. [14] T.A. Hassan, V.K. Rangari, R.K. Rana, S. Jeelani, Ultrasonics sonochemistry sonochemical effect on size reduction of CaCO3 nanoparticles derived from waste eggshells, Ultrason. Sonochem. 20 (2013) 1308e1315, https://doi.org/ 10.1016/j.ultsonch.2013.01.016. [15] M.D. Putra, Y. Ristianingsih, R. Jelita, C. Irawan, I.F. Nata, Potential waste from palm empty fruit bunches and eggshells as a heterogeneous catalyst for biodiesel production, RSC Adv. 7 (2017) 55547e55554, https://doi.org/ 10.1039/C7RA11031F. [16] A. Buasri, N. Chaiyut, V. Loryuenyong, C. Wongweang, S. Khamsrisuk,
[24]
[25]
[26]
[27]
[28]
[29]
[30] [31]
[32]
[33] [34] [35]
[36] [37]
[38]
[39]
[40]
[41]
[42]
845
Application of eggshell wastes as a heterogeneous catalyst for biodiesel production, Sustain. Energy 1 (2013) 7e13, https://doi.org/10.12691/rse-1-2-1. P.R. Pandit, M.H. Fulekar, Egg shell waste as heterogeneous nanocatalyst for biodiesel production : optimized by response surface methodology, J. Environ. Manag. 198 (2017) 319e329, https://doi.org/10.1016/j.jenvman.2017.04.100. K. Kanaga, A. Pandey, S. Kumar, Bioresource Technology Multi-objective optimization of media nutrients for enhanced production of algae biomass and fatty acid biosynthesis from Chlorella pyrenoidosa, NCIM 2738 (200) (2016) 940e950. G. Knothe, Analyzing biodiesel: standarts and other methods, JAOCS (J. Am. Oil Chem. Soc.) 83 (2006), https://doi.org/10.1007/s11746-006-5033-y. A. Linggawati, S. Anita, T.A. Amri, Preparation and Characterization of Calcium Oxide Heterogeneous Catalyst Derived from Anadara Granosa Shell for Biodiesel Synthesis, 2016, 2016, pp. 1e8, https://doi.org/10.18502/keg.v1i1.494. Y.Y. Margaretha, H.S. Prastyo, A. Ayucitra, S. Ismadji, Calcium Oxide from Pomacea Sp . Shell as a Catalyst for Biodiesel Production, 2012, pp. 1e9. N. Viriya-empikul, P. Krasae, B. Puttasawat, B. Yoosuk, N. Chollacoop, K. Faungnawakij, Bioresource Technology Waste Shells of Mollusk and Egg as Biodiesel Production Catalysts, vol. 101, 2010, pp. 3765e3767, https://doi.org/ 10.1016/j.biortech.2009.12.079. R. Ljupkovi, M. Tehnicki, M. Pupin, N. Radulovi, A. Boji, Significance of the Structural Properties of CaO Catalyst in the Production of Biodiesel : an Effect on the Reduction of, 2014, https://doi.org/10.2298/HEMIND130612063L. R. Anr, A.A. Saleh, S. Islam, S. Hamdan, A. Maleque, Biodiesel Production from Crude Jatropha Oil Using a Highly Active Heterogeneous Nanocatalyst by Optimizing Transesteri Fi Cation Reaction Parameters, 2015, https://doi.org/ 10.1021/acs.energyfuels.5b01899. Z. Mirghiasi, F. Bakhtiari, E. Darezereshki, Journal of Industrial and Engineering Chemistry Preparation and Characterization of CaO Nanoparticles from Ca ( OH ) 2 by Direct Thermal Decomposition Method, vol. 20, 2014, pp. 113e117. P. Boey, G. Pragas, S. Abd, Bioresource Technology Biodiesel Production via Transesterification of Palm Olein Using Waste Mud Crab ( Scylla serrata ) Shell as a Heterogeneous Catalyst, vol. 100, 2009, pp. 6362e6368, https://doi.org/ 10.1016/j.biortech.2009.07.036. H. Liu, L. Su, Y. Shao, L. Zou, Biodiesel production catalyzed by cinder supported CaO/KF particle catalyst, Fuel 97 (2012) 651e657, https://doi.org/ 10.1016/j.fuel.2012.02.002. W. Widayat, T. Darmawan, R.A. Rosyid, H. Hadiyanto, Biodiesel production by using CaO catalyst and ultrasonic assisted, J. Phys. Conf. Ser. 877 (2017), https://doi.org/10.1088/1742-6596/877/1/012037. G. Chen, R. Shan, J. Shi, B. Yan, Ultrasonic-assisted production of biodiesel from transesterification of palm oil over ostrich eggshell-derived CaO catalysts, Bioresour. Technol. 171 (2014), https://doi.org/10.1016/ j.biortech.2014.08.102. M. Mathiyazhagan, a Ganapathi, Factors affecting biodiesel production, Res. Plant Biol. 1 (2011) 1e5. I. Istadi, U. Mabruro, B.A. Kalimantini, L. Buchori, D.D. Anggoro, Reusability and stability tests of calcium oxide based catalyst (K2O/CaO-ZnO) for transesterification of soybean oil to biodiesel, Bull. Chem. React. Eng. Catal. 11 (2016) 34e39, https://doi.org/10.9767/bcrec.11.1.413.34-39. R. Anr, A.A. Saleh, M.S. Islam, S. Hamdan, M.A. Maleque, Biodiesel production from crude jatropha oil using a highly active heterogeneous nanocatalyst by optimizing transesterification reaction parameters, Energy Fuels 30 (2016) 334e343, https://doi.org/10.1021/acs.energyfuels.5b01899. G. Knothe, Analyzing biodiesel : standards and other methods 83 (2006) 823e833. S. Niju, K.M.M.S. Begum, N. Anantharaman, Modification of Egg Shell and its Application in Biodiesel Production, 2014, pp. 702e706. ~o, A.G. Ferreira, Determination of M.R. Monteiro, A.R.P. Ambrozin, L.M. Lia biodiesel blend levels in different diesel samples by 1 H NMR 88 (2009) 691e696, https://doi.org/10.1016/j.fuel.2008.10.010. O. Download, P. Export, Waste Capiz ( Amusium Cristatum ) Shell as a New Heterogeneous Catalyst for Biodiesel Production, 2017, pp. 2012e2014. L.F. Ramírez-Verduzco, J.E. Rodríguez-Rodríguez, A.D.R. Jaramillo-Jacob, Predicting cetane number, kinematic viscosity, density and higher heating value of biodiesel from its fatty acid methyl ester composition, Fuel 91 (2012) 102e111, https://doi.org/10.1016/j.fuel.2011.06.070. Y.H. Chen, B.Y. Huang, T.H. Chiang, T.C. Tang, Fuel properties of microalgae (Chlorella protothecoides) oil biodiesel and its blends with petroleum diesel, Fuel 94 (2012) 270e273, https://doi.org/10.1016/j.fuel.2011.11.031. L.M.D.S. Freire, I.M.G. Dos Santos, J.R. De Carvalho Filho, A.M.T.D.M. Cordeiro, L.E.B. Soledade, V.J. Fernandes, A.S. De Araujo, A.G. De Souza, Influence of the synthesis process on the properties of flow and oxidative stability of biodiesel from Jatropha curcas biodiesel, Fuel 94 (2012) 313e316, https://doi.org/ 10.1016/j.fuel.2011.10.054. E.G. Giakoumis, A statistical investigation of biodiesel physical and chemical properties, and their correlation with the degree of unsaturation, Renew. Energy 50 (2013) 858e878, https://doi.org/10.1016/j.renene.2012.07.040. Pe rez, Influence of fatty M.J. Ramos, C.M. Fern andez, A. Casas, L. Rodríguez, A. acid composition of raw materials on biodiesel properties, Bioresour. Technol. 100 (2009) 261e268, https://doi.org/10.1016/j.biortech.2008.06.039. G. Knothe, Biodiesel: current trends and properties, Top. Catal. 53 (2010) 714e720, https://doi.org/10.1007/s11244-010-9457-0.