A novel biobased heterogeneous catalyst derived from Musa acuminata peduncle for biodiesel production – Process optimization using central composite design

Energy Conversion and Management 189 (2019) 118–131

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A novel biobased heterogeneous catalyst derived from Musa acuminata peduncle for biodiesel production – Process optimization using central composite design Muthusamy Balajii, Subramaniapillai Niju

T

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Department of Biotechnology, PSG College of Technology, Coimbatore 641004, India

ARTICLE INFO

ABSTRACT

Keywords: Ceiba pentandra oil Red banana peduncle Response surface methodology Transesterification Biodiesel

The present research work focused towards the utilization of Musa acuminata Colla ‘Red’ banana peduncle for the development of a novel, low-cost, green, and highly efficient heterogeneous catalyst for the conversion of Ceiba pentandra oil (CPO) into C. pentandra methyl esters (CPME). The calcined red banana peduncle (CRBP) was characterized by Fourier Transform Infrared Spectroscopy (FTIR), X-ray diffraction (XRD), Brunauer-EmmettTeller (BET), scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDS), and techniques. BET analysis revealed that the catalyst surface area was 45.99 m2 g−1 with pore diameter of 9.77 nm. EDS analysis on CRBP showed the presence of various minerals and potassium was found to be the major active ingredient responsible for high catalytic activity. The biodiesel production process parameters such as CRBP concentration (1.5–3.5 wt%), methanol to esterified CPO (E-CPO) molar ratio (6:1–14:1), and transesterification time (40–120 min) was optimized using central composite design (CCD) based response surface methodology (RSM). Among the three parameters studied, CRBP concentration was found to be the most significant parameter in maximizing the CPME conversion since it exhibited huge multi-minerals and high surface area. A maximum experimental CPME conversion of 98.73 ± 0.50% was achieved at the process conditions of 2.68 wt% CRBP concentration, 11.46 methanol to E-CPO molar ratio, and 106 min transesterification time while the temperature and stirrer speed was maintained at 65 °C and 450 rpm respectively. Also, the properties of synthesized CPME were evaluated and the studies on catalyst reusability were also performed.

1. Introduction In 2017, the global primary energy consumption was increased by 2.2% owing to the increasing energy use in buildings (29%), industries (> 50%), and transportation (20%) sectors. A total of 13,511.2 million tonnes of oil equivalents (Mtoe) of primary energy were consumed globally by utilizing various types of fuels in which crude oil holds a maximum share of about 34.20% followed by coal (27.62%), natural gas (23.36%), hydroelectric (6.80%), nuclear energy (4.41%) and renewables (3.61%). This huge consumption resulted in the emission of 33,444.0 million tonnes of carbon dioxide [1]. Hence, the focus on developing diverse alternative renewable energy sources has been intensified in recent years. Biofuels especially biodiesel is regarded as a potential candidate for replacing the conventional fossil-based diesel fuel. The usage of biodiesel will equalize the progress among agriculture, environment, and economy [2]. Among the available production methods, the most

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easiest and cost-effective method is transesterification in which the triglycerides present in any kind of lipid feedstock (edible, non-edible oils, waste cooking oils, and animal fat) was allowed to react with methanol in the presence of a catalyst to form fatty acid methyl esters (product) and glycerol (by-product) [3,4]. Non-edible oils have become the pin interest for biodiesel production since the feedstocks are lowvalued, locally available throughout the year, and doesn’t create food vs fuel conflicts. Ceiba pentandra (Silk cotton or Kapok tree) is a large, erect, deciduous and buttressed tree belongs to Malvaceae family which is native to tropical America, Africa, Caribbean, Southeast Asia, Sri Lanka, and India. The tree usually bears oblong-ellipsoid, pendulous shaped capsules comprising plentiful brown coloured seeds embedded with silky hairs [5]. The seeds of C. pentandra contain 25–28% of oil in each fruit [6] and various researchers have stated its potential to use as a feedstock for biodiesel production. Employment of homogeneous catalysts in biodiesel production raises several issues such as impossible catalyst recovery, requirement

Corresponding author. E-mail address: [email protected] (S. Niju).

https://doi.org/10.1016/j.enconman.2019.03.085 Received 27 December 2018; Received in revised form 27 March 2019; Accepted 28 March 2019 0196-8904/ © 2019 Published by Elsevier Ltd.

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of costly purification and catalyst removal steps, equipment corrosion, and huge generation of wastewater thereby making the entire process not an environmentally benign [7,8]. To overcome the above-said problems, the environmentally benign and cost-effective heterogeneous catalysts were utilized for biodiesel production since it is neither dissolved nor consumed in the reaction thereby makes the transesterification process more efficient [9]. Based on chemical composition, the heterogeneous catalyst includes a wide range of catalyst species [10–12]. In recent years, the biomass-based heterogeneous catalyst is attaining increased attention due to its high availability and activity for biodiesel production. Few researchers reported the biodiesel production using various biomass ash as heterogeneous catalyst such as cocoa pod husk [13], palm kernel fronds [14], Musa paradisiacal peel [15], Musa ‘Gross Michel’ peels [16], ripe plantain peels [17], Musa balbisiana Colla peels and underground stem [18–20], tucumã peels [21], banana peels and cocoa pod husk [22], Musa acuminata peel [23], coconut waste [24], wood ash [25], Lemna perpusilla Torrey [26], rubber seed shell [27], camphor tree [28], gasifier bottom ash [29], and rice husk ash [30,31]. In India, banana is cultivated under 858,000 Ha of area which accounts for an annual production of 29,163,000 MT during 2016–2017 [32]. More than 75 species of wild banana varieties found are native to the humid tropical and sub-tropical countries that extend from India to the Pacific [33,34]. The banana plant generates huge quantities of organic-based post-harvest residues such as pseudo-stems, bulbs, rachis, leaf sheath and peduncles comprising 70% weight of total fresh plant which remains unutilized [35]. Potassium, a major macronutrient plays a significant role in plant growth and development and is abundantly available in banana plantains [36]. These agri-residues were often dumped or burnt in the farm fields and to some extent, it was size reduced using machinery to use as green manure. However, the practice of dumping and burning such large amounts of residue leads to environmental pollution by the release of greenhouse gases. Among different banana residues, the peduncle constitutes about 13 wt% of the harvested banana cluster, is considered as waste and was often discarded, burnt, and decomposed in the farm fields [34]. The peduncle is a part of banana crop commonly the stalk that supports the inflorescence from which the female flowers developed into fruits [37,38]. Red banana, the largest herbaceous flowering plant can grow from 6 to 6.7 m tall [33] and it is the highly prized and most relished variety of Tamil Nadu and Kerala. It is also cultivated in Andhra Pradesh, Karnataka, and to some extents in Western and Central India. In Bihar and other surrounding regions, it is popularly known as Lal Velchi while in Karnataka, it is Chandra Bale. The colour of the fruit rind, midrib, petiole, and pseudostem is purplish red. This robust plant has fruit bunches weighing between 20 and 30 kg and its fruits are sweet and orange-yellow coloured [39]. In earlier days, the traditional one factor at a time (OFAT) method has been employed for optimizing the process. However, it is timeconsuming, laborious, and economically unfeasible since it includes a huge number of experiments to evaluate the optimal points [40]. To overcome the above-said problems, response surface methodology (RSM) came into existence which is a multivariate statistical tool appropriate for modeling the complex processes [41]. This tool is highly applicable when an experimental response is influenced by numerous variables and hence, it can be applied to optimize the biodiesel production process [42]. From the statistical analysis of variance, the influence of each parameter on maximizing the biodiesel production can be determined [43]. Also, it enables researchers to predict the most influential parameter in the transesterification process [44,45]. In this work, the unexploited red banana peduncle (RBP) has been utilized for the synthesis of eco-friendly heterogeneous base catalyst for

biodiesel production owing to its abundant availability in local fruit markets, and high mineral content especially potassium. A low-cost, non-corrosive green catalyst has been synthesized by high-temperature calcination technique and was characterized by various techniques. The underutilized C. pentandra oil (CPO) was subjected to two-step esterification and transesterification process to reduce the acid value. So far, minimum reports are available on the statistical optimization of transesterification process catalyzed by biomass-derived heterogeneous catalyst [15,16,22]. Also, very few reports are prevailing in the literature pertaining to the heterogeneous catalyst assisted biodiesel production from CPO [46,47]. Hence, in this research, the influence of transesterification reaction parameters such as reaction time, CRBP concentration (wt%), methanol to esterified Ceiba oil molar ratio, and transesterification time (min) was examined using central composite design (CCD) of RSM to amplify the C. pentandra methyl ester (CPME) conversion. Also, reusability studies have been carried out using the synthesized catalyst to examine the stability of the catalyst for commercial viability. Furthermore, the fuel properties of the synthesized CPME was also evaluated. 2. Materials and methods 2.1. Materials The red banana peduncle (RBP) (Cultivar Name: Musa acuminata Colla ‘Red’, Cultivar Group: AAA) was obtained from the local market in Coimbatore while the Ceiba pentandra oil (CPO) was procured from Tamil Traders, Coimbatore, Tamil Nadu, India. The suspended particles present in the raw CPO was removed by filtration using normal filter paper and it was subsequently preheated to remove moisture using hot air oven (Make: Scientek) at 105 °C until constant weight was attained. The preheated CPO was then stored in an airtight container for further use. The acid value, free fatty acid (FFA) and water content of CPO were found to be 14 ± 0.36 mg of KOH g−1 oil, 7 ± 0.18% and 0.05 ± 0.01 wt% respectively. Sulfuric acid (≥97%), potassium hydroxide (KOH, ≥85%) was purchased from HiMedia Laboratories Pvt. Ltd., Mumbai while methanol, ethanol, and phenolphthalein solution (pH indicator) were purchased from S.D. Fine-Chem Limited, Bangalore. All the chemicals used in the experiments were of analytical grade. The fatty acid composition of CPME (Fig. 1) was determined by Gas Chromatography-Mass Spectroscopy (GC–MS) (Model: Scion 436GC, Make: Bruker, Germany) and BR-5MS (5% Diphenyl/95% Dimethyl polysiloxane) column was used. AOCS Official Method Ce 2–66 [48] was employed for the preparation of methyl esters from CPO for the better identification of compounds. Helium was employed as a carrier gas with 2 µl sample injected having a 10:1 split ratio and the gas flow rate was fixed at 1 ml/min. The oven temperature was initially maintained at 110 °C and held for 3.50 min. Further, the oven temperature was increased to 200 °C at a heating rate of 10 °C/min (no hold) and then, it was increased to 280 °C at a heating rate of 5 °C/min and held for 12 min. The injector temperature was set at 280 °C. The inlet line temperature of MS (TQ Quadrupole) was set at 290 °C with the source temperature being operated at 250 °C and the mass scan (m/z) was done at a frequency range of 50–500 amu. The library NIST Version-11 was used to identify the compounds present. From GC–MS results, the major fatty acid present in the form of methyl esters were found to be methyl linoleate (39.27%, Retention time, RT-16.98), methyl oleate (23.71%, RT-17.08), and methyl tridecanoate (20%, RT-14.73). Similarly, Sivakumar et al. [49] reported the fatty acid composition of CPO and observed the presence of linoleic (35.11%), oleic (29.69%), palmitic (23.20%), and stearic (5.68%). Also, the authors determined the initial acid value of raw CPO and found to be 28.71 mg of KOH g−1 which was higher than the present work. Also, Silitonga et al. [6] examined the

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Fig. 1. GC–MS profile of CPME.

fatty acid composition of CPO employed in their study and reported the major fatty acid constituents such as linoleic acid (39.7%), palmitic acid (19.2%), malvalic acid (18.5%), oleic acid (17.4%) and others (5.2%). The difference in acid value and fatty acid composition was majorly influenced by the soil or plant growth conditions, geographical location, and the employed oil extraction procedure.

(≤0.425 mm). The finely sieved RBP was then calcined in a programmable muffle furnace (Make: VB Ceramic Consultants, Chennai, India) at 700 °C for 4 h with 5 °C/min of linear heating rate. After cooling down the furnace temperature to below 300 °C, the calcined red banana peduncle (CRBP) was carefully transferred to a desiccator to avoid reaction with the moisture and atmospheric air. The resultant CRBP was further stored in a 30 ml flat bottom glass tubes (Make: Borosil) and it can be directly used as a renewable heterogeneous catalyst without further modifications.

2.2. Catalyst preparation The collected RBP (shown in Fig. 2a) was initially washed with deionized water to remove the adhered sand particles followed by size reduction using a knife and the resultant (Fig. 2b) was dried in a hot air oven at 65 °C for 4 days. The dried RBP was further size reduced using a mixer grinder and sieved using ASTM 40 mesh size sieve

2.3. Catalyst characterization The surface morphology and elemental composition of both the uncalcined red banana peduncle (URBP) and calcined red banana

Fig. 2. (a and b). Red banana peduncle used in the present study.

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peduncle (CRBP) were examined by high-resolution field emission electron microscopy (FESEM, CARL ZEISS SIGMA IV, Germany) equipped with energy dispersive X-ray (EDX, Oxford X-Act) spectroscopy. Prior to analysis, the samples were subjected to gold (Au) coating using sputter coating machine (Quorum Q150R S) and then, the samples were loaded on the stub containing carbon tape. Further, the unwanted particles were removed manually using the blower. The surface area of URBP and CRBP was evaluated by multi-point BrunauerEmmett-Teller (BET) analysis using fully automated Quantachrome instruments (Nova 2200e, USA). The samples (URBP and CRBP) were degassed at 150 °C for 8 h to remove moisture. Nitrogen gas was used as adsorbate. The pore volume and pore diameter were determined by the Barrett-Joyner-Halenda (BJH) method using adsorption and desorption isotherm. The crystalline phase and diffraction pattern of both the URBP and CRBP was studied using powder X-ray diffractometer (XRD, PANalytical X’Pert3, Netherland) coupled with Cu – Kα radiation generating electron beam at 40 kV and 30 mA, in the scanning angle (2θ) ranging between 10 and 90° with 0.0130° increasing step size. The functional groups present in the samples (URBP and CRBP) between the wavenumber 4000 and 600 cm−1 were identified by Fourier transform infrared spectroscopy (FTIR, Nicolet 6700 Thermo Scientific, USA) with potassium bromide (KBr) as a matrix.

phase). Lower glycerol phase was drained off while the upper phase containing CPME was stored in an airtight container for further analysis. The percentage (%) conversion of CPO to CPME was calculated using Eq. (1) given by Knothe [50].

% CPME Conversion = 100 ×

2AME 3A CH2

(1)

where %CPME conversion = percentage conversion of triglycerides to methyl esters. The factors 2 and 3 were derived from the number of attached protons at the α-carbonyl methylene and methoxy carbons, respectively. AME = integration value of methoxy groups of methyl esters at chemical shift of 3.7 ppm. A CH2 = integration value of α – carbonyl methylene groups in fatty ester derivatives at chemical shift of 2.3 ppm. 3. Results and discussion 3.1. Catalyst characterization 3.1.1. FTIR analysis The FTIR pattern of both URBP and CRBP was presented in Fig. 3(a and b). In URBP, a major absorption peak was observed at 1039.31 cm−1 belongs to CeO stretching of carbohydrate (cellulose, and hemicellulose) and lignin matrix or it may be appeared due to the CeOeC stretching in cellulose and hemicellulose present in the peduncle [51]. A broad absorption band at 3384.67 cm−1 and a minor band at 666 cm−1 could be ascribed to the eOH stretching and bending vibration of water molecules [16,52]. Furthermore, the minor peak appeared in URBP at 2894.37 cm−1 may be assigned to CeH stretching while the presence of sharp bands at 1410 and 1594.38 cm−1 represents aromatic ring vibration and CeH bonding deformation of lignin [51,53]. In addition, distinct and minor sharp peaks were seen in URBP at 666, 716.58, 777, 1247.77, 1334.58, 1410.62, and 3741.76 cm−1. The strong band at 1247.77 cm−1 represents the C]O stretching vibration in xylan, lignin and ester groups. A similar trend of absorption spectra was reported by Karim et al. [36] in raw banana peduncle (Musa species). Manimaran et al. [33] investigated the chemical composition of RBP fibers and reported a high cellulose content of 72.90 wt% followed by lignin (15.99 wt%), and hemicellulose (11.01 wt%). The major absorption bands of URBP existing at 1039.31, 1594.38, and 3384.67 cm−1 was almost disappeared in CRBP which clearly indicates the effectiveness of selected calcination temperature which degraded the complex carbohydrate-lignin matrix. The prominent absorption bands in CRBP were observed at 875.80, 999.34, 1130.28, 1259.51, 1352.14, and 1456.42 cm−1. The low intense band at 700 cm−1 signifies the presence of the phosphate group in CRBP which is in good agreement with the EDS results. The high-intensity absorption peak at 999.34 cm−1 could be ascribed to SieOeSi stretching vibration [18,21,54] while the sharp band at 1130.28 cm−1 and a minor band at 1790.02 cm−1 and 875.80 cm−1 denoted the presence of carbonates due to the atmospheric CO2 adsorption onto mineral oxides [18,25,55]. The high-intensity spectra observed at 1259.51 cm−1 could be attributed to the presence of organic phosphates (P]O) stretch. The band observed at 875.80 cm−1 may also be assigned to aromatic phosphates (PeOeC) stretch [55]. The low-intensity peaks at 700.83 and 751.69 cm−1 could be associated with the presence of tetragonal shaped potassium and hexagonal shaped silicon compounds [56]. From the FTIR observations on both URBP and CRBP, the change in intensity and shift of absorption peaks confirmed the existence of structural changes during the calcination process.

2.4. Biodiesel production 2.4.1. Esterification reaction The procured CPO was subjected to two-step process i.e. esterification followed by transesterification reaction since the determined acid value (14.0 mg of KOH g−1 oil) was found to be higher and is beyond the satisfactory limit. Hence, concentrated sulfuric acid was employed as catalyst to reduce the CPO’s acid value. The reduction of CPO’s acid value was carried out using 250 ml three-necked round bottom flask kept in a constant temperature water bath operated at 60 °C while the stirrer fitted at the middle neck was operated at 450 rpm. On the other two necks, a water-cooled condenser which is connected to a cryostat being operated at 10 °C and a temperature indicator was fitted. After performing the esterification reaction, the excess methanol present in the reaction was completely removed by heating and then, the resultant was allowed to settle down overnight for clear phase separation using separating funnel. The bottom layer (water and other impurities) was drained off while the top layer containing esterified oil was separated and stored in an air-tight container for acid value determination and further use in the transesterification reaction. 2.4.2. Transesterification reaction The esterified CPO (E-CPO) possessing minimal acid value was subjected to transesterification reaction to find the effectiveness of CRBP with the same experimental setup employed during the esterification reaction. Based on the previous studies, the reaction temperature and stirrer speed were kept constant at 65 °C and 450 rpm, respectively for all the transesterification experiments. Initially, the calculated amount of methanol and an estimated amount of CRBP was added to the batch reactor and the mixture was continuously stirred and then, 25 g of preheated E-CPO was added to the batch reactor to initialize the transesterification reaction. Once the reaction time was completed, the resultant mixture was subjected to heating for a particular time period inorder to remove the excess methanol followed by separation of catalyst from the reaction mixture. An overnight clear separation was performed by keeping the separating funnel undisturbed for distinct phase partition of CPME (upper phase) and glycerol (lower

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Fig. 3. FTIR spectra (a) URBP and (b) CRBP.

3.1.2. XRD analysis The peduncle samples (URBP and CRBP) were characterized by XRD technique to determine the crystallinity. Fig. 4(a and b) represents the XRD pattern of URBP and CRBP samples respectively and the peaks observed in diffractogram were matched with the Joint Committee on Powder Diffraction Standards (JCPDS) database. In URBP, most of the peaks were unidentified due to the interference caused by carbohydrate – lignin matrix. By comparing the XRD patterns of URBP and CRBP, it is evident that distinct peaks were observed in CRBP between 2θ = 10–80° and it can be attributed to the effectiveness of chosen calcination temperature which facilitates the removal of the above-said matrix. In CRBP diffractogram, the peaks at 19.26°, 27.27°, 28.42°, 37.30°, 38.49°, 39.08°, 40.59°, 41.65°, 56.23°, 58.65°, 62.90°, 66.44° and 68.47° can be ascribed to the presence of tetragonal structured potassium which was found to be the major phase of catalyst. Furthermore, the minor peak corresponds to minerals such as hexagonal structured calcium and silicon, and the cubic structured magnesium

was observed in CRBP. After calcination, the element silicon was observed as magnesium silicide (cubic) and calcium silicide (hexagonal). The prevalence of minerals (K, Si, Ca and Mg) in peduncle can be directly ascribed to the nature of the soil and the manure or fertilizers provided at the time of growth. From XRD observations, it is clearly seen that the selected calcination process successfully extracted and increased the availability of minerals in the catalyst which subsequently enhances the catalytic activity. 3.1.3. SEM analysis To examine the surface characteristics and physical impact of the calcination process on RBP, the samples (URBP and CRBP) was scanned using FESEM. From Fig. 5(a–c), the URBP exhibited irregular cracks and asymmetrically distorted cell organelles due to the manual size reduction process. Also, the highly disrupted URBP illustrated the absence of pores and perforations on its heterogeneous surface. The rough surface of URBP can be attributed over the carbohydrate – lignin matrix and

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Fig. 4. XRD spectra (a) URBP and (b) CRBP.

upon calcination at 700 °C for 4 h, a highly smooth textured ash (i.e. CRBP) was recovered. The calcination process extracted the light green coloured ash possessing high mineral content by degrading the carbohydrate – lignin matrix and the extracted ash can be employed directly as a solid base heterogeneous catalyst for biodiesel production. From Fig. 5(d–f), the CRBP showed relatively ordered, flat and smooth surface having a lot of pores and perforations. This increased porosity significantly enhances the biodiesel conversion owing to its increased surface area. From the overall SEM observations, the calcination process significantly changes the morphology of RBP.

samples (URBP and CRBP) depicted large amounts of potassium (K). In addition, some trace amounts of magnesium (Mg), silica (Si), phosphorous (P), sulphur (S), and calcium (Ca) were observed. The potassium content in URBP was found to be 25.63 wt% whereas, in CRBP, it was 42.23 wt%. This increase in K content can be attributed over the effectiveness of the calcination process as it efficiently extracts the minerals present in RBP through degradation of the lignin-carbohydrate matrix. Similarly, the composition of other minerals such as Mg, Si, and P was also increased after calcination. The minerals such as S and Ca was not detected in URBP whereas, in CRBP, it was found to be 0.68 wt % and 1.70 wt% respectively. This absence of minerals can be ascribed to the negligible presence in URBP and also by the camouflage of the above-mentioned matrix. The EDS results were in accordance with the XRD results. However, the peaks corresponding to the mineral S was not observed in XRD diffractogram of CRBP owing to its negligible

3.1.4. EDS analysis The elemental composition of both URBP and CRBP was represented in Fig. 6(a and b) respectively and it was obtained using the energy vs signal (relative abundance) histogram of EDS. It is evident that the

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(a)

(b)

(c)

(d)

(e)

(f)

Fig. 5. SEM images (a, b, and c) URBP and (d, e, and f) CRBP.

Fig. 6. EDS images (a) URBP and (b) CRBP.

presence. From the EDS observation, it was very clearly seen that the calcination process effectively extracted the minerals from the URBP sample. Table 1 summarizes the elemental composition of previously reported biomass ash based catalyst. Pazmiño-Hernandez et al. [34] utilized Musa cavendishii banana peduncle for biofuel production and reported the presence of various minerals such as P (481.6 mg/L), K

(34,445.5 mg/L), Ca (1.9 mg/L), Mg (502.3 mg/L), Si (97.3 mg/L), Na (15.5 mg/L), NOx-N (462.6 mg/L), and S (477.5 mg/L) in the extracted juice. The authors also observed a high amount of K in the peduncle juice which is in accordance with the present study. Karim et al. [57] produced mineral rich biochar from the banana peduncle and reported higher levels of potassium and sulfur content. 124

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Table 1 Comparison of elemental composition reported on various biomass ash. Elements

Aluminum Silicon Phosphorous Sulphur Chlorine Potassium Calcium Manganese Iron Zinc Rubidium Strontium Magnesium Sodium Carbon Oxygen Lead (mg kg−1) Cobalt (mg kg−1) Copper Chromium Titanium

Symbol

Al Si P S Cl K Ca Mn Fe Zn Rb Sr Mg Na C – Pb Co Cu Cr Ti

% Mass fraction Calcinated plaintain peels [15]

Wood ash [25]

Calcined wood ash catalyst (CWC800) [25]

Activated wood ash catalyst (AKWC1) [25]

Rice husk ash [30]

Lemna perpusilla Torrey ash [26]

Musa Gross Michel peel ash [16]

Musa balbisiana Colla peel ash [18]

Tucuma peels [21]

Paw paw peel ash [58]

Musa acuminata peel ash [23]

URBP (Present study)

CRBP (Present study)

3.42 33.01 1.99 0.67 4.89 54.73 1.13 0.05 0.04 0.01 0.04 0.03 – – – – – – – – –

9.0 17.6 1.15 – – 7.3 14.7 – – – – – 2.9 0.6 – – – – – – –

1.2 21.5 0.50 – – 5.7 17.8 – – – – – 4.5 5.7 – – – – – – –

1.1 31.9 0.55 – – 36.8 10.5 – – – – – 3.0 8.5 – – – – – – –

– 38.21 – – – 0.90 – – – – – – – – 4.34 56.55 – – – – –

– 82.51 – – 1.10 11.32 – – – – – – – 0.53 5.10 – 3.77 6.35 – – –

– – – – – 99.73 0.03 0.01 0.01 0.004 – – 0.03 0.19 – – 0.001 – 0.00002 – –

– – – – – 41.37 36.08 – – 0.12 – – 12.02 10.41 – – – – – – –

0.32 0.45 12.67 2.58 0.35 63.81 12.28 0.09 0.26 0.11 0.10 – 6.69 – – – – – 0.18 0.09 –

0.44 – 4.38 2.75 5.67 30.17 4.13 – – – – – 1.91 – – 50.55 – – – – –

0.737 10.864 6.068 2.857 2.070 65.110 7.787 0.227 1.152 0.114 0.123 0.134 2.472 0.145 – – – – 0.192 0.036 0.086

– 0.56 0.78 – – 25.63 – – – – – – 0.97 – – 72.06 – – – – –

– 1.54 1.91 0.68 – 42.23 1.70 – – – – – 1.39 – – 50.54 – – – – –

3.1.5. BET analysis For any kind of solid base heterogeneous catalyst, the catalytic activity was strongly influenced by the surface area and porosity of the catalyst in addition to the mineral content. The samples (URBP and CRBP) was characterized by the BET method (surface area) and BJH desorption summary (pore volume and pore diameter) to check the efficiency of the calcination process. The BET surface area of URBP and CRBP was found to be 24.46 and 45.99 m2 g−1 respectively. Also, the

pore volume and pore diameter of samples (URBP and CRBP) were determined as 0.083 cc g−1, 11.75 nm, and 0.14 cc g−1, 9.77 nm respectively. The increase in specific surface area values indicates the efficiency of the calcination process on peduncle sample. A summary on BET results reported on various biomass as a catalyst source was presented in Table 2. From the reported literature, the synthesized CRBP catalyst showed high surface area among ash based solid catalyst and it can be attributed to the performed size reduction and sieving process,

Table 2 Comparison of surface area, pore volume, and pore radius reported previously on various biomass. Catalyst Source/Catalyst/Catalyst Support

Surface area (m2 g−1)

Pore volume (cc g−1)

Pore diameter or radius (nm)

Biodiesel yield or conversion (%)

References

Mesua ferrea Linn seed derived char Mesua ferrea Linn seed derived AC Mesua ferrea Linn seed derived sulfonated carbon Date pits powder Date pits derived carbon catalyst (C3) Flamboyant pods derived carbon catalyst Char Wood char catalyst Pomelo peel biochar catalyst Wood ash Calcined wood ash catalyst (CWC800) Activated wood ash catalyst (AKWC1) Lemna perpusilla Torrey ash Musa ‘Gross Michel’ peel ash Tucuma peel ash Musa balbisiana Colla peel Musa balbisiana Colla peel ash URBP CRBP

23.419 333.833 150.326

7.5206 115.63 55.32

– – –

– – –

[59] [59] [59]

432 211 820 354 337 6.7 9.38 3.72 0.65 9.622 4.442 1.0 10.176 14.036 24.466 45.992

0.22C 0.14C 0.3534C 0.34C 0.24C 24.4MM – – – 2.170 × 10−8 0.020C – 0.065 0.074 0.083 0.145

6.62D 5.98D – 3.8R 2.7R – 25P 26P 53P 4.512 × 10−9 17.864D – 1.60R 2.603R 11.754D 9.770D

– 91.6 89.81 – 96 98 40.2 98.7 99 89.43 98.5 97.3 – 100 – 98.73 ± 0.50

[60] [60] [61] [62] [62] [8] [25] [25] [25] [26] [16] [21] [18] [18] (Present Study) (Present Study)

M

R

– Pore radius. – Pore radius expressed in m. D – Pore Diameter. S – Particle Size expressed in µm. C – Pore Volume expressed in cm3 g−1. M – Pore Volume expressed in m3 g−1. MM – Pore Volume expressed in mm3 g−1. R,M

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USA) was exercised for statistical assessment of transesterification experimental data. Of several transesterification parameters, the CRBP concentration (A), methanol to E-CPO molar ratio (B), and transesterification time (C) have been selected as the input parameters (Table 3) for CRBP catalyzed transesterification process. A total of seventeen experimental runs based on the CCD matrix (Table 4) with three center points was experimented to analyze the impact of individual independent variables on the CPME conversion. The interaction impact of transesterification parameters such as CRBP concentration (1.5–3.5 wt %), methanol to esterified CPO molar ratio (6–14 M ratio), and transesterification time (40–120 min) was investigated and the optimal conditions of process parameters were achieved using the analysis of variance (ANOVA). The experimental CPME conversion shown in Table 4 represents the conversion of CPO to CPME acquired from the transesterification runs evaluated by 1H NMR analysis while the predicted CPME conversion signifies the biodiesel conversion obtained from quadratic polynomial equation represented in Eq. (2). The p-value was employed to evaluate the significance of each model terms. The significance of the corresponding regression coefficient is inversely proportional to its p-value. From the ANOVA table presented in Table 5 clearly indicates that the selected quadratic model was statistically significant at 95% confidence interval owing to its low p-value (< 0.0001) and high F-value (83.81). Also, the selected transesterification parameters (A, B, and C) was found to be statistically significant since all the opted terms exhibits low p-value. Among the three selected parameters, the term CRBP concentration (A) was the most significant parameter in CPME conversion since it exhibits the highest

Table 3 Range and levels of transesterification process parameters. Name

Units

Alpha (−)

Low

Middle

High

Alpha (+)

CRBP concentration Methanol to E-CPO ratio Transesterification time

wt% molar min

0.82 3.27 12.73

1.5 6 40

2.5 10 80

3.5 14 120

4.18 16.73 147.27

and the selected calcination temperature (700 °C for 4 h). However, few carbon-based solid catalyst or catalyst support exhibited very high surface area which can be ascribed to the catalyst synthesis procedure. 3.2. Esterification process Based on several preliminary studies performed on our laboratory, the acid value of the CPO was reduced from 14 to 3.20 mg of KOH g−1 of oil under the optimal esterification conditions such as 1 vol.% sulfuric acid concentration, 1:4 methanol to CPO volumetric ratio, 1 h reaction time, and 450 rpm stirrer speed operated at a reaction temperature of 60 °C. The upper esterified layer was separated from the reaction mixture by removing the excess methanol and other impurities and stored in an airtight container for further use in transesterification experiments. 3.3. CCD based RSM optimization of transesterification process Design Expert 11 software package (STAT-EASE Inc., Minneapolis, Table 4 Central composite design matrix. Std

Run

A:CRBP concentration wt%

B:Methanol to E-CPO ratio molar

C:Transesterification time min

Experimental CPME Conversion %

Predicted CPME Conversion %

14 9 7 8 15 6 10 2 5 3 11 17 12 1 4 13 16

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

2.5 0.818207 1.5 3.5 2.5 3.5 4.18179 3.5 1.5 1.5 2.5 2.5 2.5 1.5 3.5 2.5 2.5

10 10 14 14 10 6 10 6 6 14 3.27283 10 16.7272 6 14 10 10

147.272 80 120 120 80 120 80 40 120 40 80 80 80 40 40 12.7283 80

79.93 52.23 46.39 97.06 96.03 91.45 97.22 48.11 62.93 57.53 58.59 95.44 88.77 41.46 93.72 49.67 97.54

76.85 49.14 48.99 99.95 96.48 90.31 97.83 47.27 65.20 60.42 59.94 96.48 84.94 40.33 93.21 50.27 96.48

Table 5 ANOVA table for the central composite design. Source

Sum of Squares

df

Mean Square

F-value

p-value

Model A-CRBP concentration B-Methanol to E-CPO ratio C-Transesterification time AB AC BC A2 B2 C2 Residual Lack of Fit Pure Error Cor Total

7633.62 2861.78 754.46 852.51 333.98 165.17 659.03 745.18 814.45 1527.24 70.84 68.49 2.35 7704.46

9 1 1 1 1 1 1 1 1 1 7 5 2 16

848.18 2861.78 754.46 852.51 333.98 165.17 659.03 745.18 814.45 1527.24 10.12 13.70 1.17

83.81 282.79 74.55 84.24 33.00 16.32 65.12 73.64 80.48 150.92

< 0.0001 < 0.0001 < 0.0001 < 0.0001 0.0007 0.0049 < 0.0001 < 0.0001 < 0.0001 < 0.0001

significant

11.68

0.0808

not significant

126

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Fig. 8. Interaction effect of CRBP concentration and methanol to E-CPO molar ratio on CPME conversion.

Fig. 7. Experimental vs predicted CPME conversion.

middle level (80 min). Increasing the parameter A and maintaining the parameter B at low level (6:1) significantly enhances the CPME conversion upto certain limit. But, increasing the parameter A alone beyond 3 wt% results in the reduction of CPME conversion and this can be associated with the requirement of excess methanol to shift the equilibrium. Mendonça et al. reported a similar decrease in biodiesel conversion with increasing catalyst loading on ash based heterogeneous catalyst derived from waste tucumã peels [21]. As seen in ANOVA (Table 5), the parameter A was found to be highly statistically significant since it holds very low p-value and very high F-value. Conversely, increasing the parameter B by keeping parameter A at low level (1.5 wt%) influences the CPME conversion to a certain extent. In general, the rate of triglycerides to methyl ester conversion was highly influenced when the methanol to oil molar ratio was increased above stoichiometric value [63]. However, increasing the parameter B beyond

F-value (282.79) and low p-value (< 0.0001). n

n

Y%CPME conversion = m 0 +

n 1

i=1

n

mii xi2 +

mi xi + i=1

mijxixj i=1 j=i+1

(2)

The quality of the selected quadratic model is ascertained by the coefficient of determination (R2) and the estimated R2 for the selected model was found to be 0.9908 which suggests that the model can illustrate 99.08% variability and affirms the consistency to achieve the predicted values. Furthermore, the predicted R2 (0.9305) is in reasonable agreement with the adjusted R2 (0.9790) value. To measure the signal to noise ratio of the selected model, the value of adequate precision should be higher than 4 and the corresponding value was found to be 24.43 which indicates an adequate signal thereby the selected model can be used to navigate the design space. The F-value (11.68) of lack of fit implies that the model fitness was good. Fig. 7 depicts the experimental against the predicted CPME conversion and the observation depicted the high correlation between actual and predicted values since the data points lies close to the diagonal line. The second-order polynomial equation illustrated in Eq. (3) is acquired to authenticate a mathematical relationship between the response (CPME conversion) and the selected input parameters (A, B, and C).

CPME conversion(%) = + 96.48 + 14.48A + 7.43B + 7.90C + 6.46AB + 4.54AC

9.08BC

8.13A2

8.50B2

11.64C2

(3)

where A is CRBP concentration (wt%), B is methanol to E-CPO ratio (molar), and C is transesterification time (min). This equation is exploited to examine the CPME conversion using multiple regression analysis. 3.4. Interactive effects of transesterification parameters on CPME conversion The 3D response surface plot (Fig. 8) displays the impact of interaction between CRBP concentration (A) and methanol to E-CPO molar ratio (B) on the CPME conversion. The parameter A was varied from 1.5 wt% to 3.5 wt% and the parameter B was varied from 6:1 to 14:1 M ratio while the transesterification time (C) was kept constant at the

Fig. 9. Interaction effect of CRBP concentration and transesterification time on CPME conversion. 127

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parameter B. This highest CPME conversion can be attributed to the high concentration of basic sites [16,63]. Mendonça et al. employed different methanol to oil molar ratios (10:1, 15:1, and 20:1) to increase the soybean oil based biodiesel conversion and reported 15:1 ratio as optimum ratio [21]. From the ANOVA table, it is found that there is a significant interaction between CRBP concentration (A) and methanol to E-CPO molar ratio (B) since the corresponding p-value (0.0007) was found to be lower. Fig. 9 illustrates the impact of interaction between the parameters CRBP concentration (A) and the transesterification time (C) on the CPME conversion while the methanol to E-CPO molar ratio (B) was kept constant at 10:1. At low levels of both A and C, the graph displays a minimum CPME conversion (< 60%) and this can be associated to the low availability of active sites and insufficient time for the conversion of triglycerides to methyl esters [18]. Increasing the parameter A alone upto a certain limit drastically increases the CPME conversion and this can be attributed to the high surface area (45.992 m2 g−1) of CRBP which represents the high availability of active sites in the catalyst [16]. Pathak et al. studied the influence of Musa acuminata peel ash catalyst on transesterification of soybean oil and reported an increase in biodiesel yield from 72% to 98.95% when the catalyst loading was increased from 0.3% to 0.7% [23]. Similarly, Mendonça et al. observed an increase in biodiesel conversion from 62.5 to 95.7% when the tucumã peels derived ash catalyst loading was increased from 1 to 5 wt% at 2 h reaction time [21]. However, increasing the parameter A beyond 3 wt% with respect to minimum time (40 min) results in the reduction of CPME conversion and it signifies the increasing viscosity of the reaction mixture due to the high solid catalyst loading which leads to poor mixing of reactants [43]. Similarly, Betiku et al. varied the loading of banana peel ash catalyst from 1.6 to 4.4 wt% and observed a slight decrease in biodiesel yield beyond 3.5 wt% [16]. However, varying the parameter C alone upto middle level (80 min) and keeping the parameter A at low-level influences the CPME conversion. It is noted that increasing the parameter beyond 80 min results in a gradual decrease in

Fig. 10. Interaction effect of methanol to E-CPO molar ratio and transesterification time on CPME conversion.

the middle level (10:1) decreases the CPME conversion. This reduction in conversion can be attributed to the excess methanol present in the reaction mixture which prevents the catalytic active sites to access the triglyceride molecule present in CPO. Also, it may be occurred due to reverse transesterification i.e. conversion of methyl esters into monoglycerides and diglycerides. A similar trend of reduction in methyl ester yield was reported with transesterification of waste cooking oil using Musa balbisiana Colla peel ash based catalyst [18]. As seen in the 3-D plot (Fig. 8), the highest conversion of CPME was observed between 2.5 wt% and 3 wt% of parameter A, and between 10:1 and 12:1 of

Fig. 11. 1H NMR spectra of CPME produced under optimal transesterification conditions. 128

129

(Present study) 98.73 ± 0.50 450 106 65 11.46:1

S* – Stirring rate was not mentioned.

Ceiba pentandra oil 700 °C for 4 h

2.68

[65] [19] 91.4 98 S* 650 120 60 60 275 6:1 9:1 Soybean oil Jatropha curcas oil 800 °C for 4 h 550 °C for 2 h

1 5

94.87 97.3 S* S* 90 240 60 80 0.3 (v/v) 15:1 500 °C for 3.5 h 800 °C for 4 h

Musa paradisiacal peel Astrocaryum aculeatum Meyer peels Cocoa pod husk Musa balbisiana Colla underground stem Musa acuminata Colla ‘Red’ peduncle

3 1

[26] [13] [27] [18] [16] 89.43 99.3 83.06 100 98.5 68.07 rad/s – 400 600 S* 300 57 60 180 69.02 65 ± 5 65 60 60 65 9:1 0.73 (v/v) 0.20 (v/v) 6:1 7.6:1

Jatropha curcas oil Azadirachta indica oil Rubber seed oil Waste cooking oil Bauhinia monandra seed oil Thevetia peruviana oil Soybean oil

5 0.65 2.2 g 2 2.75

Methanol to oil ratio (molar) Catalyst concentration (wt%)

Transesterification Process Parameters

550 ± 5 °C for 2 h 700 °C for 4 h 800 °C for 3 h 700 °C for 4 h 700 °C for 4 h

Table 6 represents the comparison of CRBP catalyst over the existing biomass-derived heterogeneous catalyst. From Table 6, it was evident that the present study showed comparatively high biodiesel conversion

Lemna perpusilla Torrey Cocoa pod husk Rubber seed shell Musa balbisiana Colla peel Musa ‘Gross Michel’ peel

3.6. Comparison of various biomass derived heterogeneous catalyst employed for biodiesel production

Lipid Feedstock

Based on the CCD of RSM, the optimal conditions for attaining maximum CPME conversion was obtained by the numerical optimization tool provided in the Design Expert software [52]. The software predicted a maximum CPME conversion of 99.23% at the process conditions of 2.68 wt% CRBP concentration, 11.46 methanol to E-CPO molar ratio, and 106 min transesterification time. The software prediction was validated by conducting additional experiments (triplicate) at the above-mentioned conditions. The percentage conversion of CPO to CPME was determined as 98.73 ± 0.50% using Eq. (1) and the corresponding 1H NMR spectra were presented in Fig. 11. The peaks at 2.3 ppm (α-methylene proton) and 3.66 ppm (methoxy proton) confirmed the conversion of CPO into CPME [40]. The peak observed between 0.8 and 0.9 ppm may be ascribed to terminal methyl group proton. A prominent peak at 1.25 ppm and 1.60 ppm can be attributed to the presence of carbon chain methylene proton and carbonyl methylene proton [64].

Calcination temperature & time

3.5. Optimization of transesterification process parameters

Catalyst Source

Table 6 Comparison of synthesized catalyst over other biomass derived heterogeneous catalyst.

Reaction temperature (°C)

Reaction time (min)

Stirrer speed (rpm)

Biodiesel conversion or yield (%)

Ref.

CPME conversion and it can be ascribed to the occurrence of esters hydrolysis thereby soap formation takes place. From the 3-D plot (Fig. 9), it is clearly seen that the maximum CPME conversion was acquired around the middle levels of parameter A (2.5–3 wt%) and C (70–90 min). As seen in the ANOVA table, it is observed that the interaction impact between parameter A and C are statistically significant due to its low p-value (0.0049). Fig. 10 displays the impact of interaction between the parameters methanol to E-CPO molar ratio (B) and transesterification time (C) on the CPME conversion while the CRBP concentration (A) was kept constant at the middle level (2.5 wt%). Methanol to E-CPO molar ratio is an important parameter in the transesterification of E-CPO [63]. At a low level of parameter B and a minimum level of parameter C, a low CPME conversion (< 60%) was observed and this signifies the preference of excess methanol to drive the transesterification reaction forward. A gradual increase in CPME conversion was observed when the parameter B alone was increased from 6:1 ratio to 12:1 ratio and it can be ascribed over the availability of surplus methanol which appreciably moves the reaction towards product formation. A similar increase in biodiesel yield was observed by Pathak et al. [23] when the methanol to oil molar ratio was increased from 3:1 to 12:1. Increasing the parameter C alone drastically enhances the CPME conversion when the parameter B was fixed at low level. The increase in contact time between CRBP catalyst and reactants enhances the prospect of collision thereby increases the CPME conversion. Similar observations were reported on the transesterification of Elaeis guineensis oil with Ky(MgCa)2xO3 heterogeneous catalyst [63]. However, increasing the parameter B beyond 12:1 at a minimum time (40 min) reveals a decrease in CPME conversion. At high methanol to oil molar ratios, decreased interactions between CRBP catalyst and reactants takes place due to diluted reactants [21]. Similarly, at the conditions of the high level of both parameters B and C resulted in decreased CPME conversion and this reduction can be associated to the occurrence of glycerol solubilization in the reaction mixture and also the dilution of catalyst concentration at high methanol presence. From the 3-D plot (Fig. 10), it is clearly seen that the highest CPME conversion was observed between 10:1 and 12:1 of parameter B, and 80 and 120 min of parameter C. The interaction impact between parameter B and C were found to be highly statistically significant than the previous interactions owing to its very low p-value (< 0.0001) and high F-value (65.12).

[15] [21]

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of 98.73% under the optimal transesterification conditions such as 2.68 wt% catalyst loading, and 11.46:1 methanol to oil molar ratio in 106 min at 65 °C. Onoji et al. employed calcined rubber seed shell as solid base catalyst for the conversion of rubber seed oil to biodiesel and observed a reasonable biodiesel yield of 83.06% using 2.2 g catalyst, and 0.20 (v/v) methanol to oil ratio in 1 h at 60 °C [27]. Chouhan and Sarma utilized L. perpusilla Torrey ash as heterogeneous catalyst for the biodiesel production from Jatropha oil and reported a moderate conversion of 89.43% using 5 wt% catalyst, and 9:1 methanol to oil ratio at 65 ± 5 °C in 5 h [26]. This moderate biodiesel yield can be attributed to the mineral composition of the biomass and the selected calcination temperature. However, biomass such as cocoa pod husk [13], Musa balbisiana Colla peel [18] and Musa ‘Gross Michel’ peel [16] calcined at 700 °C for 4 h yielded a very high biodiesel conversion of 99.3%, 100%, and 98.5% respectively.

4. Conclusion The present work examined the synthesis of a novel heterogeneous base catalyst via high-temperature calcination of red banana peduncle and its utilization in the transesterification of CPO for biodiesel production. The characterization results indicated that the selected calcination temperature (700 °C for 4 h) drastically extracts the minerals from the peduncle by degrading the carbohydrate-lignin matrix. The synthesized CRBP catalyst exhibited a high catalytic activity due to its increased surface area and the existence of mixed mineral oxides. The transesterification parametric effect on CPME conversion was studied using CCD based RSM and the selected quadratic model was found to be significant. The model predicted a maximum CPME conversion of 99.23% under the optimal conditions of 2.68 wt% of CRBP concentration, 11.46:1 methanol to E-CPO molar ratio, and 106 min of reaction time. The CPME conversion of 98.73 ± 0.50% obtained from the experimental results are in accordance with the model predicted value. Therefore, CRBP- a biobased catalyst derived from RBP has a strong potential to be used as a highly efficient, low-cost heterogeneous for biodiesel production.

3.7. Fuel properties of synthesized CPME To evaluate the quality of synthesized CPME, the physiochemical properties were determined and compared with the ASTM and EN standards. The free fatty acid content of fuel can be predicted by determining acid value. To reduce the corrosion in the fuel system, the acid value of fuel should be very minimum. The kinematic viscosity predicts fuel behavior in cold conditions. Density plays a significant role in biodiesel as it predicts the fuel amount required to inject for generating particular engine power. The acid value, density (at 15 °C), and kinematic viscosity (at 40 °C) of the synthesized CPME was found to be 0.23 mg KOH g−1 oil, 885 kg m−3, and 4.23 mm2 s−1 respectively. The higher flash point value of CPME (165 °C) allows safer storage and transport of fuel even at high-temperature conditions [46]. The cloud point of CPME was found to be 2 °C which is higher than the conventional petro diesel. However, all the observed values were within the limit mentioned in the ASTM D6751 and EN 14214 standards. The above-observed values of CPME are in close agreement with the earlier reported values of CPME produced using KOH [49] and nano-sized heterogeneous acid catalyst [47].

Conflict of interest None. Acknowledgments SN is grateful to SERB-DST, New Delhi, India for Early Career Research Award (ECR/2015/000036) and MB is thankful to SERB-DST for the award of Junior Research Fellowship (JRF). References [1] Statistical review of world energy. Br Pet 2018. https://www.bp.com/en/global/ corporate/energy-economics/statistical-review-of-world-energy.html (accessed November 26, 2018). [2] Meher LC, Sagar DV, Naik SN. Technical aspects of biodiesel production by transesterification – a review. Renewable Sustainable Energy Rev 2006;10:248–68. https://doi.org/10.1016/j.rser.2004.09.002. [3] Ma F, Hanna MA. Biodiesel production: a review. Bioresour Technol 1999;70:1–15. [4] Gerpen JVan. Biodiesel processing and production. Fuel Process Technol 2005;86:1097–107. https://doi.org/10.1016/j.fuproc.2004.11.005. [5] Lim TK. Edible medicinal and non-medicinal plants 2012;Volume 1. https://doi. org/10.1007/978-90-481-8661-7. [6] Silitonga AS, Ong HC, Mahlia TMI, Masjuki HH, Chong WT. Characterization and production of Ceiba pentandra biodiesel and its blends. Fuel 2013;108:855–8. https://doi.org/10.1016/j.fuel.2013.02.014. [7] Anwar M, Rasul MG, Ashwath N. Production optimization and quality assessment of papaya (Carica papaya) biodiesel with response surface methodology. Energy Convers Manage 2018;156:103–12. https://doi.org/10.1016/j.enconman.2017.11. 004. [8] Zhao C, Lv P, Yang L, Xing S, Luo W, Wang Z. Biodiesel synthesis over biochar-based catalyst from biomass waste pomelo peel. Energy Convers Manage 2018;160:477–85. https://doi.org/10.1016/j.enconman.2018.01.059. [9] Balajii M, Niju S. Biodiesel production using biochar as a heterogeneous catalyst. Non-Soil Biochar Appl. New York: Nova Science Publishers, Inc.; 2018. p. 177–212. [10] Chouhan APS, Sarma AK. Modern heterogeneous catalysts for biodiesel production: a comprehensive review. Renewable Sustainable Energy Rev 2011;15:4378–99. https://doi.org/10.1016/j.rser.2011.07.112. [11] Da Silva DA, Santisteban OAN, De Vasconcellos A, Silva Paula A, Aranda DAG, Giotto MV, et al. Metallo-stannosilicate heterogeneous catalyst for biodiesel production using edible, non-edible and waste oils as feedstock. J Environ Chem Eng 2018;6:5488–97. https://doi.org/10.1016/j.jece.2018.08.047. [12] Ruhul AM, Kalam MA, Masjuki HH, Fattah IMR, Reham SS, Rashed MM. State of the art of biodiesel production processes: A review of the heterogeneous catalyst. RSC Adv 2015;5:101023–44. https://doi.org/10.1039/c5ra09862a. [13] Betiku E, Etim AO, Pereao O, Ojumu TV. Two-step conversion of neem (Azadirachta indica) seed oil into fatty methyl esters using a heterogeneous biomass-based catalyst: an example of cocoa pod husk. Energy Fuels 2017;31:6182–93. https://doi. org/10.1021/acs.energyfuels.7b00604. [14] Ameen OM, Adekola FA, Adebayo GB, Adekola OF, Belewu MA, Rahman SG. Conversion of Jatropha curcas oil to biodiesel using potash from cocoa pod husk (CPH) and palm kernel frond (PKF) as catalyst. Niger J Pure Appl Sci 2014;27:2515–23. [15] Betiku E, Ajala SO. Modeling and optimization of Thevetia peruviana (yellow

3.8. Catalyst reusability Catalyst reusage is one of the major advantages in using a heterogeneous catalyst for biodiesel production and it significantly reduces the biodiesel production cost [21]. Reusability studies enable authors in predicting the economic viability of biodiesel production at commercial scale. The synthesized CRBP catalyst was recycled at the above mentioned optimal transesterification conditions. Prior to every cycle, the catalyst was washed with methanol followed by hexane to remove the adhered impurities and then, it was subjected to drying in vacuum oven at 100 °C for 6 h [23]. The results showed that the CPME conversion was above 90% at the end of three consecutive runs. This reduction in CPME conversion may be attributed to the blockage of active sites present in the CRBP catalyst due to the agglomeration of esters and glycerol [18,23]. Also, it may be ascribed to the possible loss of minerals present in the catalyst during the consecutive cycles due to leaching [18]. However, significant loss of catalyst amount was observed at the end of each cycle due to the difficulties in catalyst transfer from the reactor. Mendonça et al. reused the tucumã peels derived ash catalyst and reported a 17% decrease in catalytic activity at the end of the 4th cycle [21]. Pathak et al. performed reusability studies on ash based heterogeneous catalyst derived from Musa acuminata banana peel and observed a decrease in biodiesel conversion from 98.95% to 52.16% at the end of the fourth cycle [23]. Gohain et al. examined the recycling potency of Musa balbisiana Colla peel derived catalyst for the biodiesel production from waste cooking oil and reported a decrease in biodiesel conversion from 100% to 50% at the end of the 5th cycle [18]. 130

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