Delonix regia heterogeneous catalyzed two-step biodiesel production from Pongamia pinnata oil using methanol and 2-propanol

Journal of Cleaner Production 255 (2020) 120313

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Delonix regia heterogeneous catalyzed two-step biodiesel production from Pongamia pinnata oil using methanol and 2-propanol Bisheswar Karmakar , Sucharita Samanta , Gopinath Halder * Department of Chemical Engineering, National Institute of Technology, Durgapur, India

a r t i c l e i n f o

a b s t r a c t

Article history: Received 4 September 2019 Received in revised form 29 December 2019 Accepted 28 January 2020 Available online 29 January 2020

The study described here was focussed on preparing heterogeneous catalysts (acid and base) by H2SO4 and KOH wet impregnation technique from raw Delonix regia pods after carbonization and steam activation, which was used in converting free fatty acids and glycerides in karanja oil into fuel-grade esters. Resistance to thermal degradation of the precursor material was evaluated by TGA analysis, while catalyst characterization was done through BET, EDAX, FT-IR, SEM and XRD. These helped in estimating efficient surface modification and efficient doping of functional groups. Optimization of both esterification and transesterification steps is done through L16 Taguchi matrices, with the following process parameters: agitation speed, alcohol to oil ratio, catalyst concentration, reaction duration, reaction temperature. With a maximum FFA conversion of 99.86%, the biodiesel yield was 99.39%. Fuel characterization tests and GC analyses for residual glycerides showed that the fuel has acceptable physicochemical properties according to ASTM standards with low residual glycerides. Catalysts show significant reusability with sulfonated (H2SO4 impregnated) catalyst retaining efficiency up to 3 uses and base catalyst (KOH doped) up to 7 uses. A cost analysis of catalyst preparation shows that the indigenously developed catalysts reduce production costs by a significant margin, proving to be lucrative for commercialization. © 2020 Elsevier Ltd. All rights reserved.

Handling editor: Jun Bi Keywords: Biodiesel production Catalyst reusability Delonix regia Heterogeneous two-step production Pongamia pinnata Taguchi L16

1. Introduction Biodiesel being one of the renewable, biodegradable alternatives to fossil energy, researchers made use of various edible and non-edible oils from plants as well as waste oils and animal fats over a wide range of approaches for the development of commercially usable biodiesel (AI-Nimr and AI-Dafaie, 2014; Magno et al., 2015; Ramkumar and Kirubakaran, 2016). In addition to being physico-chemically similar to petro-diesel and being compatible with diesel engines, biodiesel has the advantages of having higher thermal stability, proving to be safer for transportation. Due to low sulphur content, greenhouse gas emissions are also lower. The range of feedstock available as well as the techniques that are available for exploitation in the field of biodiesel production are wide. The production of fuel-grade esters from free fatty acids and glycerides (mono-, di- and tri-) involves esterification with acids

* Corresponding author. Department of Chemical Engineering, National Institute of Technology Durgapur, M.G. Avenue, Durgapur, 713209, West Bengal, India. E-mail addresses: [email protected] (B. Karmakar), sucharita.samanta111@ gmail.com (S. Samanta), [email protected] (G. Halder). https://doi.org/10.1016/j.jclepro.2020.120313 0959-6526/© 2020 Elsevier Ltd. All rights reserved.

and transesterification with acids, bases or enzymes (biocatalysts). Edible oils are not used to avoid straining food sources. Animal fats are hard to process and are still used in skincare products due to their long shelf life. Oils from non-edible plants like karanja (Pongamia pinnata), Croton megalocarpus, physic nut (Jatropha curcas), rubber seed (Hevea brasiliensis), mahua (Madhuca indica), castor (Ricinus communis), etc. can be grown in relatively harsh climatic conditions and in areas that are either unsuitable for food crop production or for decorative purposes. From the family Leguminaceae, karanja (Pongamia pinnata) grown in India, is a glabrous tree of medium size that can grow in tidal forests, coastal areas, riverbanks and even roadsides (Sharma and Singh, 2008), making production of biodiesel feasible. The increased viscosity of oils is primarily because of glycerides (mono-, di- and tri-) being present in large quantities and thus transesterification with alcohols is needed to convert these glycerides into their alkyl esters that have diesel-like properties (Sharma and Singh, 2008). Oils with high FFA (free fatty acid) content or traces of water in them cannot be base transesterified because saponification occurs with the FFA, while presence of water causes hydrolysis of triglycerides into FFA (Karmakar and Halder, 2019). Therefore, such oils need to be

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converted into their esters through a two-step mechanism that involves FFA esterification (acid catalyst) and subsequent glyceride transesterification (base catalyst) to yield the final product. Over the past few years, many researchers have made use of a wide range of feedstock for biodiesel production using a myriad of catalysed approaches. These approaches have centred on using homogeneous or heterogeneous catalysts, with many researchers opting to use inert supports to dope functional groups such as acid or base groups or even heavy metals that can act as a catalyst in a transesterification. While some relied on acid or base single step conversions, some others have utilized transition metals doped on inert carbonaceous supports as catalysts. Karmakar et al. and Dhawane et al. used H2SO4 in a homogeneous system for conversion of castor oil and waste cooking oil into biodiesel with 90.38% and 95.376% yield, respectively (Karmakar et al., 2018; Dhawane et al., 2018). High FFA (~15% w/w) Calophyllum inophyllum oil was converted by Dawodu et al. in a single step using methanol with carbonized C. inophyllum cake which were HSO3 doped, resulting in around 99% w/w yield of fuel (Dawodu et al., 2014). Biodiesel had also been prepared from Mesua ferrea linn (MFL) seed oil with methanol using carbonized MFL seed shells impregnated with H2SO4 which resulted in a 95.57% yield of fuel (Bora et al., 2018). Also, another work has been reported by Karmakar et al. which involved using carbonized and H2SO4 doped Delonix regia pods, which was used to obtain a 97.04% yield from high-FFA Madhuca indica oil using methanol (Karmakar et al., 2020). In primarily base catalysed approaches involving oils with negligible FFA or pretreated oils free of FFA, some works have also been reported. Dhawane et al. had previously reported in separate works of converting rubber seed oil into biodiesel; carbonized Delonix regia char was separately used after impregnation with KOH or Fe(II) along with methanol. The biodiesel yields were: 96.31% for Fe(II) doped carbon (Dhawane et al., 2016b) and 89.81% for KOH doped carbon (Dhawane et al. 2016a). Homogeneous CaO catalyst developed from calcined chicken manure was used in the transesterification of waste cooking oil using methanol with over 90% FAME yield (Maneerung et al., 2016). The ‘one-variable-at-a-time’ (OVAT) approach is an optimization technique needing a large number of experiments. This makes the process both wasteful and costly, since it is laborious, timeconsuming and unnecessarily repetitive. Hence, software guided approaches such as Factorial and Response Surface Methodology (RSM) are preferable that provide outputs based on mathematical models. Backed with statistical analysis, the optimum levels for a given set of reaction parameters can be evaluated very precisely. Being a factorial approach, the Taguchi OA can incorporate higher number of process parameters with very less number of resulting runs and the data fed as a response is sufficient in predicting the optimum reaction conditions. Thus for the present approach Taguchi L16 matrix was used for optimization of the two-step process. The present study provides insight into a novel approach utilizing a dual step conversion of karanja oil that attempted to and was successful in converting FFAs using acid esterification and glycerides (mono-, di- and tri) using base transesterification for biodiesel synthesis. For the first time, instead of methanol, 2propanol was used as a better reactant (due to its low polarity resulting in better miscibility with the oil) during the base catalysed conversion. Additionally, the catalysts developed were based on a carbonaceous support that is inert in nature, as well as reusable as discussed later. Raw Delonix regia (flamboyant) pods were collected and used as the precursor material for developing a carbon support. The raw material is evaluated by thermo-gravimetric (TGA) analysis for ascertaining optimal carbonization temperature and then carbonized accordingly, followed by physical (steam

activation) to enhance surface properties. Both the acid and base catalysts are made by wet impregnation of H2SO4 and KOH respectively. Characterization of the steam activated char and the wet impregnated char (both acid and base type) is done to determine changes before and after modification. The surface modification is analysed by scanning electron microscopy (SEM), analysis of elemental composition by EDAX (energy dispersive X-ray spectroscopy), presence of functional groups by FT-IR (Fourier Transform Infrared Spectroscopy) and XRD (X-ray Diffraction) analysis, modification of porosity and surface area by functional group impregnation using BET (BrunauereEmmetteTeller) analysis. The first step is acid esterification of FFA in the presence of methanol to form FAME. The esterified oil, free of FFA is then base transesterified using KOH-impregnated char in the presence of 2-propanol. Both processes are optimized using L16 Taguchi orthogonal array (OA) approach. Fuel characterization tests conducted show whether the product obtained meets the standard criteria to be used as a fuel. Both the catalysts are studied for their reusability and the cost of preparation was estimated to determine if the developed process can be scaled up for commercial level biodiesel production. During scale-up, it can be expected that the cost of oil procurement from local mills would be constant. Since catalyst costs are expected to be high due to the use of laboratory grade reagents, the reusability of these catalysts is of huge benefit to the applicability of this process on a commercial level. Since industrial grade chemicals are far cheaper compared to the laboratory grade chemicals used in this study, the large scale production costs, when computed, are expected to be much lower than computed here. 2. Materials and procedure 2.1. Materials required For the preparation of the heterogeneous catalysts, raw Delonix regia pods were collected from the local areas both within and around the institute campus at Durgapur, West Bengal, India. Karanja oil was obtained from a local oil mill. The oil was freed of residual water and impurities by heating above 80
C and filtration respectively. For the study, reagents of analytical grade were utilized. For the acid esterification, methanol (99.50%; Merck, India) was preferred due to its low boiling point as well as its low carbon chain length compared to 2-propanol (99.50%, Merck, India) which as used for the base transesterification due to high miscibility of branched chain alcohols with the oil. Concentrated H2SO4 of min. 98% strength is used for the sulfonation of the carbon support to develop the acid catalyst while KOH is used for the development of the base catalyst by wet impregnation process as well as a titration standard for the determination of FFA in both the oil and the acid esterified product. For FFA estimation, 2-propanol is also used with phenolphthalein as the end point indicator. Arium-611 DI ultrapure water system (Sartorius A.G., Gottingen, Germany) was used to get deionized water used throughout the experiments. 2.2. Preparation of heterogeneous catalyst The accrued flamboyant pods were cleaned by water for removing dust particles as well as other impurities. Thereafter, they were subjected to additional cleaning by deionised water for removing residual ions, after which they were dried in a hot air oven; this removes the moisture. The pods were ground for size reduction, and subsequently carbonized in a muffle furnace (CSMF136Z, N.R. Enterprise, Kolkata, India). The carbonization temperature was determined prior to the process by TGA of the raw pods to determine the temperature at which the mass loss was negligible resulting in a steady residual mass. The obtained

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temperature used for carbonization was thus 500
C with continuous flow of N2 for 1 h. The carbonized pods need physical activation for enhancement of surface properties and therefore steam was passed under 1.5e2 kg/cm2 at 350
C for 1.5 h (Dhawane et al., 2015). This enhancement enables the inert carbon support to display better adsorption properties during the wet impregnation of both H2SO4 and KOH and is dubbed as ‘activated carbon (AC)’. For H2SO4 impregnation, the AC was ‘sulfonated’ as follows: 40 ml of conc. H2SO4 (98% min.) was loaded with 5 g of AC and run at 120
C for 10h under 550 rpm agitation12. In order for KOH impregnation onto the surface of the AC, a 10N aqueous solution of KOH was prepared and 20g of AC was loaded onto 200 ml of the 10N solution. The mixture thus obtained was then kept in an incubator at 30
C under orbital shaking at 200 rpm for 24 h (Dhawane et al., 2016a). For removal of the excess H2SO4 or KOH from their respective mixtures, the prepared catalysts were repeatedly washed using deionized water and filtered, then dried. This results in the obtainment of acid and base heterogeneous catalysts that has a carbonaceous, inert support with high thermal resistance.

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which is calibrated to provide an output of energy contained per unit mass of sample. The estimation of AV and FFA involves the titration of a specific quantity of sample dissolved in 10 ml of 2propanol against KOH solution of specific strength, while the end point indicator used was phenolphthalein (Karmakar et al., 2020). Estimation was done in triplicates and the mean value was considered. Eqs. (1) and (2) are used to calculate FFA content and AV:

FFA% ¼

AV ¼

28:2  N  t m

56:1  N  t m

(1)

(2)

Here, 28.2 is the standard weight taken for oleic acid, 56.1 is molar weight of KOH, titre value is denoted by t, N is the strength of KOH solution (expressed in normality), m is the mass of oil used (Karmakar et al., 2018).

2.3. Characterization of raw pod and developed catalysts

2.5. Design of experiments (DOE) for optimization

Initial TGA analysis of the pods establishes the percentage of non-volatile components in the raw material and the carbonization temperature. For TGA analysis, an instrument DTG-60H, synchronized DTA-TG apparatus (Shimadzu, model C30574700290, Japan) was used. TGA was performed under 30
to 700
C temperature range with 10
C/min increment, N2 based purging at 19.8 ml/min (flow rate). For studying the modification in surface properties after steam activation and H2SO4 or KOH impregnation, the 3 types of Delonix regia char were characterized using a SEM (JEOL JSM- 6030, India) and to identify incorporation of specific functional groups on the samples, FT-IR was used. BET analysis identifies each sample’s physical properties by estimating its pore volume and surface area using an instrument Smart Sorb 92e93 (Smart Instruments, India). The operating temperature was maintained at 77K and surface properties were estimated by N2 desorption-adsorption method. An X-ray Diffractometer (D8 ADVANCE BRUKER AXS, Germany) is used for XRD analysis. It is useful in obtaining the crystalline structure of a given sample, such as before and after functional group impregnation; such changes in the crystalline structure are recorded as distinctive ‘peaks’ (in the plot). Parallel beam Cu Ka radiation was used over a 10e50
2q range, with 0.02 step size and results obtained were compared with JSDPS standard library. To detect inorganic elements, an EDAX instrument (OXFORD INCAXsight) was used.

For both the acid esterification and base transesterification steps, five reaction parameters need to be optimized for maximum FFA conversion or biodiesel yield and therefore the Taguchi orthogonal array (OA) design devised by Dr. Genichi Taguchi is the preferred approach. This technique relies on a statistical prediction that elucidates the optimum conditions of every process parameter based on the mean and variance of every output generated (Sathish Kumar et al., 2015). The results are in the form of individual parametric effect on product yield and all other parameters are retained at baseline levels. From Eq. (1), an N number of experiments are required, relying on P number of experimental parameters, while L number of levels for each chosen parameter in a relation as given in Eq. (3): N ¼ (L - 1) P þ 1

(3)

Based on this, the L16 OA chosen gives a total of only 16 runs for 4 levels of each of the five process parameters. The parameters chosen were agitation speed, catalyst concentration, alcohol (methanol/2-propanol) to oil ratio, reaction temperature and reaction time. (Tables S1 and S2). Design Expert software version 11.0.0.1 was used for developing the matrix and evaluating the results.

2.4. Preliminary analysis of oil

2.6. Two-step fuel production

Pongamia pinnata oil needed to be characterized via standard ASTM tests for insight into its properties. Physico-chemical traits like kinematic viscosity, relative density, water content, calorific value as well as acid value (corresponding to FFA content) were tested. Relative density is presented as mass per unit volume of sample relative to that of water. Kinematic viscosity (KV) of the oil was estimated using a redwood viscometer following standardized ASTM D445 testing procedure which measures the time taken by a fixed amount of oil to flow through an orifice at a certain temperature. The KV can differ based on the temperature. The weights of the oil before and after drying at 80
C were considered and computed for difference, presented as moisture/water content. Calorific value of the sample is estimated using a bomb calorimeter (Parr 1672 calorimetric thermometer). The sample is loaded into the bomb and then combustion of the sample aided by O2 supply leads to a temperature change in the surrounding water bath,

The reactor used for the present study was a flat bottom, 3 necked flask of 2 L capacity. The side necks were fitted with a thermometer and a reflux condenser. The heating and stirring of the reaction mixture is by means of a hotplate magnetic stirrer, allowing alteration of both plate temperature and rpm. The reactor is charged with a fixed amount of sample (oil or esterified oil), to which a recommended quantity of alcohol is added followed by the required amount of heterogeneous catalyst (acid/base) after the desired temperature is reached. The mixture is cooled to below 20
C to quench the reaction. After filtration, the catalyst is washed and kept for reusability tests, while the mixture is heated for alcohol recovery and then left in a separating funnel for the separation of water (formed from acid esterification), glycerol and impurities. The product is washed with water to remove leached acidic or basic functional groups before being subjected to standard ASTM tests for characterization.

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2.7. Empirical model equation and analysis of variance (ANOVA) The mean response compared to SD is the basis for calculating the signal to noise ratio (SNR) and optimize the process. However, for elucidation of the effect of discrete reaction parameter on responses, a statistical ANOVA (analysis of variance) is done (Kumar et al., 2015). Then, the influence of every reaction variable that is deemed significant in the processes is represented as sum of squares (SS) value, and can be converted into individual contribution% based on Eq. (4):

% contribution of factor ¼

SSf  100 SST

(4)

In this equation, the sum of squares of a particular factor is denoted by SSf while the sum of squares of the model is denoted as SST, the total. A regression equation developed by using the fed data can then be confirmed for accuracy by conducting experiments under optimal conditions predicted. 2.8. Fuel characterization For the estimation of physico-chemical traits, both the esterified oil as well as transesterified biodiesel were analysed by standard ASTM tests. Viscosity (using Redwood viscometer) of a fuel is an indication of the ease with which it can be atomized by spraying for combustion in an engine. At flash point, the fuel generates ignitable vapours enough for a brief flash, while at a relatively higher temperature the vapours formed are sufficient enough for sustaining a flame. A Pensky Martens apparatus (closed cup) was used for the measurement of fire and flash point. Sample is charged into the chamber of the apparatus and a flame injector can be rotated such that it dips into the chamber for ignition. When the temperature is sufficient for vapour formation, upon introduction of the flame, the vapour mixture spontaneously ignites giving either a brief flash or a continuous flame for about 10 s. Higher values are indicative of thermal stability, thereby storage and transportation of the fuel are easy (Canoira et al., 2010). Acid value and FFA% can be estimated using a titrimetric assay as discussed in Section 2.4. (Dhawane et al., 2015). Measurement of aniline point of the biodiesel gives an estimate of the aromatic hydrocarbon content, such as paraffins, and higher is preferable. Cetane number and calorific value are also important quality parameters for the product obtained. The fuel is also visually checked for cloudiness, which is observed due to the presence of moisture. 3. Results and discussion 3.1. Analysis of raw materials The fatty acid profile of karanja oil is presented in Table 1. Preliminary analysis of the Pongamia pinnata oil was performed for establishing the physical and chemical properties, listed in Table 6. Water content of the oil is low; but a high kinematic viscosity of

Table 1 Fatty acid compositional profile of Karanja oil. Fatty acid

Chemical name

Formula

Structure

Weight%

Palmitic Stearic Oleic Linoleic Arachidic Behenic Lignoceric

Hexadecanoic Octadecanoic Cis-9-octadecenoic Cis-9, cis-12-octadecenoic Eicosanoic Docosanoic Tetracosanoic

C16H32O2 C18H36O2 C18H34O2 C18H32O2 C20H40O2 C22H44O2 C24H48O2

16:0 18:0 18:1 18:2 20:0 22:0 24:0

10e11 6e7 48e49 18e19 4e5 4.5e5.5 2.5-3.5

24.71 mm2/s was noted which is typical of bio-oils and therefore cannot be used directly as fuel in diesel engines. High calorific value noted can be considered favourable towards expectations of energy rich esters after transesterification. FFA and AV are high (8.46% w/w and 16.83 mg KOH/g), hence acid esterification (pre-treatment) of the oil is necessary (Karmakar and Halder, 2019). Table 2 summarizes the raw flamboyant pod proximate analysis results, which reveal a significant amount of fixed carbon content (46.89%) which is economical enough for developing a porous inert carbonaceous support, proving the chosen precursor material to be suitable for H2SO4 or KOH impregnation. Thermal stability of the pods was determined using thermo-gravimetric analysis (TGA). From Fig. 1 it is clear that all of the volatile matter is lost when the temperature is raised up to 500
C. Further rise in temperature till 700
C does not affect the mass loss considerably, and the residual mass is constant at around 54%. Therefore, the carbonization temperature is set at 500
C (Dhawane et al., 2017). The derivative of weight loss percentage derived from the TGA data is plotted as a DTG (Derivative of Thermo-gravimetry) curve and the increase in thermal degradation (dW/dt) is seen to be occurring in 2 phases, the first being a curve above 60
C that corresponds to loss of water molecules which occurs up to 150e220
C (Chaudhary et al., 2016). With further rise in temperature, the other peak noted between 300
and 500
C is due to the loss of volatile organic components (VOCs) (Karmakar et al., 2020). It is also seen from separate TGA plots of the steam activated carbon as well as the H2SO4 doped acid catalyst and the KOH doped base catalyst that there is practically no mass loss for the entire selected temperature range. This shows the efficiency of carbonization as well as the thermal stability of prepared catalyst. Therefore, the Delonix regia char once prepared and steam activated, can be used for a long time for development of both acid and base catalysts. 3.2. Characterization of catalysts The activated, sulfonated and KOH impregnated carbon were subjected to BET analysis in order to analyse their pore volume and surface area, the results of which are as follows: AC has a pore volume ¼ 0.3246 cm3/g and surface area ¼ 811.5 m2/g while pore volume and surface area for SC are 0.0721 cm3/g and 330.62 m2/g respectively; the KOH doped carbon (KC) has a pore volume ¼ 0.0263 cm3/g and surface area ¼ 215.38 m2/g. A change in surface area with a corresponding decrease in pore volume is seen in both the catalysts developed implying effective doping of the carbon support by H2SO4 and KOH. This can be further confirmed by the SEM images shown in Fig. 2a-d. From Fig. 2a, it is seen that the carbonized char has a surface that is extremely rough in appearance with ridges and a poorly formed porous structure varying in size, which are modified and mostly enlarged after activation by steam as seen in Fig. 2b. Fig. 2c shows that H2SO4 doping effectively blocks the pores due to proper doping of H2SO4 on the surface of the char. This results in an effective acid catalyst. A similar observation is noted for Fig. 2d, where KOH doping has a similar effect on the surface morphology of the carbon support. EDAX analysis of the synthesized catalysts showed the presence of different elements in the prepared catalysts. For the sulfonated

Table 2 Proximate analysis of raw Delonix regia. Content name

Percentage

Moisture Volatile organic matter Ash Fixed carbon

8.05 41.85 3.21 46.89

B. Karmakar et al. / Journal of Cleaner Production 255 (2020) 120313

Fig. 1. Thermo-gravimetric analysis (TGA) and derivative thermo-gravimetry (DTG) of raw Delonix regia pods.

Fig. 2. SEM image of (a) carbonized Delonix regia (b) steam activated Delonix regia (c) H2SO4 impregnated Delonix regia (d) KOH impregnated Delonix regia.

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catalyst (Fig. S1a) a high concentration of S and O is seen, while for the KOH-doped catalyst (Fig. S1b), a very high amount of K is seen, which confirms effective doping. FT-IR and XRD analysis confirm presence of various functional groups. Spectral data from the FT-IR analyses of the samples are shown in Fig. S2 where the presence and modification of characteristic peaks at specific wavenumbers confirm the success of the physical activation as well as the changes caused in the surface structure of the catalyst support due to wet impregnation processes for both H2SO4 and KOH. For each sample, various characteristics peaks were obtained. For steam activated carbon: 3512 cm1 denotes a OeH phenol group, 3438 cm1 denotes a secondary NeH amine stretch (Dhawane et al., 2017), 3394 cm1 denotes OeH carboxylic acid group, 1610 cm1 and 1646 cm1 denote C]C alkene stretches, 1590 cm1 denotes a secondary NeH amide bend (Dhawane et al., 2015) and 930 cm1 denotes CeH alkene stretches (Dhawane et al., 2016b). For sulfonated carbon: 3609 cm1 denotes an OeH alcohol group (free), 3482 cm1 and 3421 cm1 denote NeH primary and secondary amine stretches correspondingly (Roldan et al., 2012), 3226 cm1 is formed due to an OeH alcohol group (H-bonded), 1636 cm1 and 1616 cm1 show C]C weak alkene stretches, 1368 cm1 denotes a S]O sulfone group while 1194 cm1 confirms H2SO4 adsorption (Bora et al., 2018) and 1050 cm1 denotes a sulfoxide group. For KOH doped catalyst, similar peaks are also noted, with minor changes in the peak positions. The peaks noted for base catalyst were at: 3618 cm1, 3510 cm1, 3226 cm1, 1639 cm1, 1620 cm1, 1501 cm1 and 930 cm1. The results obtained from the XRD analysis help us comprehend the presence and structure of the polycyclic rings of aromatic carbon. Their presence results in the effective surface doping of H2SO4 or KOH on the activated carbon support (Budarin et al., 2006; Lokman et al., 2016; Yu et al., 2010; Zong et al., 2007). The peaks observed within the 2q range of 10
e30
can be seen in Fig. S3, with peaks at 24
, 40.38
confirm a carbonaceous support. Also shown in Fig. S3 is the diffraction pattern for sulfonated carbon. The intensities of the peaks are seen to increase in the 2q range 20
e30
and 40
e50
which corresponds to effective doping of H2SO4 (Konwar et al., 2014). When KOH is impregnated on the activated char, its dispersion on the surface of the char as seen in Fig. S3 can be ascertained by the 2q peaks seen at 12.28
, 23.74
and 28.26
. Among these, a peak noted at a 2q value of 12.28
confirms that the support surface has been doped by KOH. All the values for the diffraction data can be related to their characteristic structures by referring to the standard JCPDS library (Dhawane et al., 2015). Thus it can be confirmed that the process of steam activation and doping of H2SO4 and KOH on to the inert carbonaceous support was successful, with resistance to leaching resulting in high reusability shown in Section 4. 3.3. ANOVA of the two-step production process Optimization of the biodiesel production was done with the use of L16 Taguchi matrices, one for the acid esterification process that is focussed on converting FFA to FAME, while the other matrix is for biodiesel production from the esterified oil using 2-propanol. The response obtained for each combination of parametric conditions can be useful in the determination of the process’s optimum conditions. For the acid esterification process the drop in acid value represents the formation of FFA into their corresponding methyl esters, as seen in Table 3 and the base transesterification process is concerned with the conversion of the triglycerides into FAPE as shown in Table 4 (Dhawane et al., 2018). The ANOVA technique being vigorous, it can be used to develop a mathematical model equation and to examine the model’s acceptability for process optimization. Statistical analysis of both

the esterification and transesterification techniques can be performed by ANOVA studies of the response in each case. For each model thus developed, values for the sum of squares, the F-value (Fisher’s exact test) and the p-value (probability) describe its significance in process optimization and how each process variable impacts the response. ANOVA results for both processes have been reported in Table S3 and S5. From the ANOVA results of FFA esterification, it is seen that the F-value is 13.24 with a p-value of 0.028, indicating that the model terms are significant. Similarly from the ANOVA results of glyceride transesterification, it is seen that the Fvalue is 38.65 with a p-value of 0.0059. The sum of squares (SS) values for both the processes are also listed, and for each process, the SS values of each process parameter can be computed into its corresponding contribution factor for the reaction using Eq. (4). The contribution factors for every significant process parameter both the esterification and transesterification processes are represented in Table 5. These show that for the esterification process, agitation speed had the highest controlling effect on the reaction, while for the transesterification process, it was reaction time. For the estimation of fit characteristics of the model, the predicted R2 value should be close to the adjusted R2 value, with a maximum difference of 0.2. When the difference is higher than 0.2, it is most likely that this is caused by a large block effect or an error with the data or more likely, the model chosen. Also, the adequate precision value which tests the ratio of signal to noise (SNR) should be high enough, the minimum desired value being 4 (Dhawane et al., 2016b; Kilic et al., 2013). For both the processes, the values are in reasonable agreement for the model to be acceptable, as is represented in Tables S4 and S6. 3.4. Regression model equation and experimental validation The regression model equation developed from the ANOVA studies is useful in interpreting the significance of individual parameters upon the process response, and the coefficients associated with each of the different levels considered for every factor in the equation are useful in understanding the relative impact on the overall process. For both the acid esterification and the base transesterification processes, two separate model equations were developed that depicted the response in terms of FFA conversion and biodiesel yield, as shown in Eqs. (5) and (6): FFA Conversion (%) ¼ 71.14 þ 1.36  A[1] þ 7.49  A[2] - 4.96  A [3] þ 4.78  C[1] þ 6.98  C[2] e 6.81  C[3] þ 0.7488  D [1] þ 4.14  D[2] þ 5.22  D[3] e 8.02  E[1] e 5.67  E [2] þ 9.03  E[3] (5) Biodiesel yield (%) ¼ 97.34e0.5094  A[1] e 0.0044  A [2] þ 0.7456  A[3] e 1.82  B[1] þ 0.6681  B[2] þ 0.4631  B[3] e 0.8219  C[1] þ 0.6281  C[2] þ 0.4431  C[3] þ 0.0706  E [1] þ 0.7706  E[2] e 0.8619  E[3] (6) For Eqs. (5) and (6) (wherever applicable), A represents reaction temperature, B represents reaction time (duration), C is the catalyst concentration, D refers to the alcohol:oil ratio (methanol for esterification and 2-propanol for transesterification) and E refers to the agitation speed. 1, 2 and 3 refer to the levels of each process parameter that affect the reaction in each case. According to Figs. 3 and 4, the one factor model graphs show the optimum levels for each significant process variable (a to d) that is included in the model equations for FFA conversion and biodiesel yield. Thus, the figures clearly show that the coded equations are efficient in precise prediction of the required response (Dhawane et al., 2015). From the ANOVA analysis and the factors coded in the model equation, the set of reaction parameters at their optimum levels can be

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Table 3 L16 experimental matrix for esterification depicting FFA conversion. Run No.

Temperature (
C)

Time (min)

Catalyst (w/w %)

Methanol: oil molar ratio

Agitation Speed (rpm)

FFA conversion (%)

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

60 50 70 60 70 40 40 70 60 60 50 40 40 50 70 50

180 180 45 135 135 90 135 90 90 45 45 45 180 135 180 90

3 4.5 6 1.5 3 3 4.5 4.5 6 4.5 3 1.5 6 6 1.5 1.5

6:1 9:1 9:1 9:1 15:1 9:1 12:1 6:1 12:1 15:1 12:1 6:1 15:1 6:1 12:1 15:1

900 600 900 1050 600 750 900 1050 600 750 1050 600 1050 750 750 900

83.33 68.33 72.67 81.17 57.5 78.96 81.36 66.84 59.44 40.77 92.67 67.19 62.5 70.19 71.97 83.33

Table 4 L16 experimental matrix for transesterification depicting biodiesel yield. Run No.

Temperature (
C)

Time (min)

Catalyst (w/w %)

Methanol: oil molar ratio

Agitation Speed (rpm)

Biodiesel yield (%)

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

50 40 60 40 50 70 50 60 40 60 50 60 40 70 70 70

150 150 60 60 90 150 120 150 120 120 60 90 90 60 90 120

6 8 6 2 2 2 8 4 6 2 4 8 4 8 6 4

8:1 12:1 12:1 6:1 12:1 10:1 6:1 6:1 10:1 8:1 10:1 10:1 8:1 8:1 6:1 12:1

600 900 700 600 800 700 700 800 800 900 900 600 700 800 900 600

98.53 97.12 97.31 94.41 96.15 97.76 98.47 98.69 96.89 97.74 96.18 98.59 98.89 94.17 98.39 98.1

Table 5 Parametric contribution percentage and optimum values for FFA conversion%. Parameter (unit)

Agitation speed (rpm) Alcohol: oil ratio Catalyst Concentration% (w/w) Reaction temperature (
C) Reaction time (h)

FFA Conversion (Acid esterification)

Biodiesel production (Base transesterification)

Contribution Factor (%)

Optimum value

Contribution Factor (%)

Optimum value

34.03 25.08 (with methanol) 24.24 16.65 Insignificant

900 12:1 3 50 45

16.81 Insignificant (with 2-propanol) 16.62 10.89 55.67

700 6:1 4 60 90

Table 6 Analysis of karanja oil and biodiesel obtained. Parameter (unit)

Karanja oil

Biodiesel obtained

Testing Procedure

Relative density (at 25
C) Acid Value (mg KOH/g) Free Fatty Acid (%) Kinematic viscosity (mm2/s) Water content (%) Calorific value (MJ/kg) Flash Point (
C) Fire Point (
C) Aniline Point (
C) Cetane Number Diesel Index

0.89 16.83 8.46 24.71 0.21 36.5 -

0.754 0.024 0.012 2.3 0.02 39.8 179 190 49 56.1 64.03

ASTM ASTM ASTM ASTM ASTM ASTM ASTM ASTM ASTM -

D4253 D974 D445 D3172 D240 6450 6450 D611 D613

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Fig. 3. Impact of reaction parameter on FFA conversion: (a) Reaction temperature (b) Catalyst concentration (c) Methanol:oil ratio and (d) Agitation speed.

obtained. However, for establishment of the accuracy of the mathematical prediction, the reaction conditions need to be experimentally validated. For validation, experimental runs are carried out and the response tallied against the predicted results. The predicted versus actual values can then be plotted as shown in Figs. S4 and S5, which show good correlation with negligible differences, confirming the model’s accuracy in response prediction, for both FFA conversion and biodiesel yield.

transesterification. Both esterification and transesterification processes depend on the variation of process parameters that have their individual as well as combined effects. This study was directed at optimization of reaction parameters for both processes, listed as: agitation speed, reaction temperature, catalyst load in the reaction mixture, molar ratio of alcohol to oil and reaction duration. Optimal levels corresponding to their values for both FFA conversion and biodiesel yield are summarily reported in Table 5.

3.5. Parametric analysis of two-step conversion

3.5.1. Impact of reaction temperature A temperature at which the reaction is allowed to take place is a key factor in determining the reaction efficiency since low temperatures provide insufficient energy towards product formation, while high temperatures lead to product degradation with reactant losses. When methanol is used for esterification, temperatures higher than the boiling point of ethanol (64.7
C) are usually

Separate experiments were conducted using 2-propanol for acid pre-treatment. The 2-propanol greatly improves acid transesterification but doesn’t react with the FFAs at all, hence the product degrades within 48e72 h. Hence, the alcohol added is methanol for acid esterification and 2-propanol for base

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Fig. 4. Impact of reaction parameter on FFA conversion: (a) Reaction temperature (b) Reaction time (c) Catalyst concentration and (d) Agitation speed.

unfavourable since most of the methanol will exist in vapour form and therefore will be unable to react with the oil. The same goes for base transesterification with 2-propanol, however, in this case increased miscibility between the reactants means that the required temperature for maximum product can be expectedly moderate enough. For the esterification process, the reaction temperature was changed through 4 levels between 40
and 70
C. According to the conclusions drawn from Fig. 3a, the yield improved up to 50
C, declining rapidly on further increase. As mentioned earlier, rapid evaporation of methanol is common at higher temperatures and methanol vapours cannot react with the oil. Comparable observations were noted from various other experiments (Dhawane et al., 2017, 2018; Halder et al., 2015; Karmakar et al., 2018; Neeharika et al., 2017). Similarly, for base transesterification, the reaction temperatures were also varied at 4 levels between 40
C and 70
C, and the graph presented in Fig. 4a

also represents a similar finding, when 2-propanol was used as the reacting alcohol. The yield improved till 60
C followed by a mild decline on further increase to 70
C. This can be due to the increase in backward reaction favored by increased vaporization of the alcohol. 3.5.2. Impact of reaction time For a reaction to be complete, the reactants should have enough residence time so that the molecules can interact as long as required for the desired products to be formed. With a high reaction rate, the duration needed is low (Bokhari et al., 2016). When the reactants are in the same phase but are immiscible, reaction duration can expectedly be higher (as in acid esterification), with miscibility leading to faster reaction rates (as in base transesterification) For FFA conversion, the reaction duration was varied at 4 levels between 45 min and 180 min, and 45 min was sufficient,

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indicating a rapid reaction. Analogous results were obtained by Medina-Valtierra et al., with catalyst developed from pyrolyzed rubber tyre waste (Medina-Valtierra et al., 2017) and by Dhawane et al., who converted rubber seed oil in their experiments using Fe(II) as well as KOH doped carbonaceous catalyst in separate studies (Dhawane et al., 2016a, 2016b). For the base-catalysed transesterification using 2-propanol, the reaction duration was varied at 4 levels between 60 min and 150 min at 30 min intervals. Fig. 4b depicts the results, where it is discernible that the yield of propyl esters was seen to increase considerably till 90 min, with further increase having an insignificant effect. This is due to the high reaction rate since 2-propanol and oil are miscible. In other works with lower alcohols, various researchers reported results that were similar, showing the impact of reaction duration on the optimization of biodiesel yield using both acid and base catalysed approaches (Bokhari and Chuah, 2016; Bora et al., 2018; Dhawane et al., 2015; Goyal et al., 2012; Halder et al., 2015). 3.5.3. Impact of alcohol to oil ratio In a typical transesterification and esterification, 3 mol of alcohol convert a triglyceride into 3 fatty acid esters (biodiesel), while 1 mol of alcohol is required to convert an FFA mole in the oil to its ester (Bokhari and Chuah, 2016). In this study, methanol was chosen for esterification since secondary alcohols with higher carbon chain length do not react with FFAs due to low polarity of the alkyl group and steric hindrance. While the alcohol provided should be in excess of the stoichiometrically required amount, a large excess leads to dilution, inhibiting reaction progress (Dhawane et al., 2017). In the esterification step, it was noted from Fig. 3c that highest FFA conversion occurred at ratio of 12:1. Thus, methanol is required in a large excess than is dictated by stoichiometric ratios. Since the esterification reaction is easily reversible, this excess helps in keeping the reaction equilibrium towards product formation. From Table 5 it can be seen that this parameter has a significant contribution of 24.24% in the FFA conversion process. Studies reported by many others (Berrios et al., 2007; Neeharika et al., 2017; Ramachandran et al., 2011; Wan Omar et al., 2009) are in agreement with our reported conclusions. For the base catalysed transesterification using 2-propanol, the resistance in diffusion is negligible. Therefore the lowest amount of 2-propanol is sufficient in providing optimum biodiesel yield with the optimization approach (L16 Taguchi OA) showing the insignificance of this process parameter on the biodiesel yield. Hence, the lowest level of this parameter, i.e., a 6:1 M ratio is chosen, keeping cost-effectiveness in mind. 3.5.4. Impact of catalyst concentration Catalyst concentration is seen to be influential in the FFA reduction, since a significant catalyst quantity is required to facilitate esterification as seen from Fig. 3b. Since the catalyst is heterogeneous, this would mean that 3% w/w is chosen (due to being economical) for further experiments. From Table 5, it is seen that catalyst concentration has a significant contribution in FFA conversion, by a percentage of 24.24%. Studies by Bora et al. using sulfonated MFL char on MFL oil into biodiesel resulted in similar conclusions (Bora et al., 2018). In some other studies using H2SO4 in a direct-homogeneous system (Agra et al., 1996; Banani et al., 2015; Bokhari and Chuah, 2016; Goyal et al., 2012) it was shown that increase in acid catalyst concentration had trivial impact on the FFA conversion or biodiesel yield. During the second stage using base catalyst (KOH impregnated char), the catalyst concentration at 4% w/w was seen from Fig. 4c to have the highest biodiesel yield. This can also be explained due to the leaching of the KOH into the system from the carbon support and thereby causing minor amounts of saponification with the

residual FFA in the oil, which can therefore attribute to the drop in biodiesel yield. Studies on Hevea brasiliensis oil using flamboyant pod support for KOH impregnated base catalyst and Fe(II) doped metal catalyst have been reported by Dhawane et al. with similar conclusions (Dhawane et al., 2016a,b, 2017). 3.5.5. Impact of agitation speed Even when the oil and alcohol are mixed and heated to a suitable temperature, the FFA esterification or triglyceride transesterification do not occur unless external agitation is provided to the reactants. Most reported literature works reported before have considered a set agitation speed for carrying out their experimental works; however, it should be considered for optimization. From the acid esterification data depicted in Table 3 and Fig. 3d when optimization of FFA conversion is carried within a range of 600 rpme1050 rpm, it is seen that optimal ester yield was at 900 rpm, while additional escalation caused a fall in ester conversion. The reported results are congruent to our other works (Karmakar et al., 2018), to the observed trend reported by Aldo et al. and Ramachandran et al. (Aldo et al., 2010; Ramachandran et al., 2011). Similarly, for base transesterification as seen in Fig. 4d, when the variation of the mixing intensity was done within the range of 600 rpme900 rpm, an increase in biodiesel yield was noted from 600 to 700 rpm, after which the yield dropped abruptly at 800 rpm, with better yields at 900 rpm. Hence the agitation speed of 700 rpm is considered optimal. For both acid esterification and base transesterification reactions, if the mixing intensity is extreme, the reactants do not get sufficient contact time for the reaction to proceed. The rapid collisions between reactant molecules that results from extreme agitation not only results in damage of the structural integrity of the catalyst, but also inefficient product formation. Similar results were observed by Dhawane et al. in their works (Dhawane et al., 2016b, 2017). 3.6. Fuel characterization The acid esterified oil must have a low FFA content (as signified by its low AV) for the base transesterification process. Also, physico-chemical properties of the biodiesel must be tested for suitability as fuel. Characterization was done through standardized ASTM tests and found to adhere to required specifications. These included tests for residual AV and FFA% content for both the esterified oil and the biodiesel, while other tests such as flash point, aniline point, cetane number, diesel index (DI), fire point, kinematic viscosity (KV), molecular weight, relative density, calorific value and water content. All of these were tested and reported summarily in Table 6. Fire point and flash point tests showed high thermal stability of the fuel, since flash point is 179
C. Residual AV and FFA are noted to be 0.64 and 0.32 respectively, indicating the fuel’s non-corrosive nature. KV of the fuel is 2.3 mm2/s, indicating good fuel fluidity resulting in improved spray characteristics (Ahmad et al., 2019). Calorific value was also tested and the value indicates that high amount of heat energy from the fuel can be obtained. The high aniline point noted can be attested to a high paraffinic content. High amounts of paraffin are desired and sometimes even added to enhance the combustion of the fuel. This also corresponds to the diesel index (DI) of the fuel being high, and the fuel can be expected to show low ignition delay resulting from a higher cetane number when compared to petro-diesel (values within 45e48). Every value tested for each property was found to be adhering to the ASTM limits set for commercial biodiesel, with some values that were better than known for petro-diesel. These values for the fuel alongside the values for those of the raw karanja oil are shown in

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Table 6. Hence it is clear that the fuel obtained through the recommended two-step production process when performed under optimal conditions can be used in diesel engines (when blended suitably) since it is better than commercially recommended biodiesel.

11

4. Raw material drying cost (DC) ¼ Time in hours  units consumed  cost per unit ¼ 12  2  $0.065 ¼ $1.56 5. Carbonization costs (CC) ¼ IEC þ HC ¼ $ (0.044 þ 0.58) ¼ $0.624 where IEC is the inert environment creation cost. IEC ¼ N2 flow ¼ $0.044

4. Catalyst reusability After the first use, the heterogeneous acidic and basic catalyst were collected by filtration and washed with acetone for the removal of oil and impurities, then dried in a hot air oven. Catalysts were reused in different concentrations (other parameters at optimal levels) for evaluation of the reusability and to check the efficiency of functional group retention by the carbon support, as in Table S7. When the drop in FFA conversion or biodiesel yield was significant enough, the carbon support was again impregnated with H2SO4 or KOH as described in Section 2.2. From analysis of the products of the esterification and transesterification processes, it was seen that catalytic activity of the sulfonated carbon decreased significantly after 3 reuses while the KOH doped carbon retained its efficiency till 7 reuses. This is due to functional group leaching (both H2SO4 and KOH) during the reaction as well as from the structural damage of the inert support due to agitation (Dhawane et al., 2016a). The prepared catalysts thus are able to remain efficient till quite a number of reuses, while the structural integrity of the carbon support is not compromised even after many reuses. When combined with the ease of recovery and reuse (filtration followed by washing), the catalysts show tremendous potential in large scale applications where bulk quantities of catalyst can be easily prepared with the right equipment as well as reuse for cost effectiveness is also a major advantage. 5. Cost analysis for catalyst preparation For the presented work, catalyst preparation cost assessment is useful for understanding if the process is appropriate for commercialization. Among all factors, most of the cost is due to factors like source of raw material, preparation technique, required treatment process and especially reusability. In the preparation of 1 kg each of sulfonated and KOH-doped catalyst, the following were our observations, which have been calculated in USD ($). 1. Raw material cost (RMC) ¼ $0 (waste material, locally available). For commercial production, 10% overhead cost allotted collection labour charge. 2. Size reduction cost (SRC) ¼ $0 for batch studies since reduction was manual. For commercial production, 10% overhead cost allotted (machine grinding). 3. Cost for raw material washing ¼ HC þ WC ¼ $0.064 where WC is the water cost since distilled water acquired from distilled water setup available in laboratory is used and HC is the heating cost involved in obtainment of the distilled water. HC ¼ (unit cost for 1 L water  units consumed) ¼ $0.065  1 ¼ $0.065 WC ¼ $0 (water cost already included in HC)

HC ¼ Time in hours  units consumed  cost per unit ¼ 1.5  6  $0.065 ¼ $0.58 6. Steam activation cost (AC) ¼ SC þ HC ¼ $ (0.065 þ 0.38) ¼ $0.445, where SC refers to steam preparation cost and HC is the heating cost. SC ¼ Time in hours  units consumed  cost per unit ¼ 1  1  $0.065 ¼ $0.065 HC ¼ Time in hours  units consumed  cost per unit ¼ 1.5  4  $0.065 ¼ $0.38  Therefore raw material creation cost: CC þ DC þ WC þ SRC þ RMC þ AC ¼ $0.624 þ $1.56 þ $0 þ $0 þ$0 þ $0.445 ¼ $2.629 7. Cost of impregnation (IC) ¼ AGC þ CCH ¼ $(8.45 þ 103.536) ¼ $111.986, where AGC refers to the cost of agitation, while CCH is the cost for chemicals required for impregnation. AGC ¼ Time in hours  units consumed  cost per unit ¼ (10  1  $0.065) þ (24  5  $0.065) ¼ $8.45 CCH ¼ [amount of H2SO4 needed (in litre)  cost per litre] þ [amount of KOH needed (in kg)  cost per kg] ¼ (4  $10.47) þ (5.6  $11.01) ¼ $103.536  Net cost involved ¼ CC þ DC þ WC þ SRC þ RMC þ IC þ AC ¼ $2.629 þ $111.986 ¼ $114.615  Total cost ¼ Net cost þ Overhead charges (10% of net cost) ¼ $114.615 þ $11.462 ¼ $126.077 From the cost analysis shown above, two things are quite clear: 1. The cost of preparation of raw material is quite negligible in bulk. 2. More than 90% of the catalyst preparation cost comes from the cost of chemicals required for impregnation. Under optimum conditions and maximum reuse, the lowest yield of 95.61% is reasonably significant. From the reusability studies, it was also seen that while the sulfonated carbon can be reused 3 times, the KOH doped carbon is more stable in retaining the functional groups in its matrix and can be reused very efficiently till 7 times. Hence, using 2 kg of sulfonated carbon and 1.33 kg of KOH-doped carbon catalysts, an approximate amount of 267 kg biodiesel can be developed, with catalyst cost accounting for an amount of $211 in total, or only $0.79 per kg. The sole factor for this drastic cost reduction is the reusability. According to recent sources, market price of commercial grade AC is over $14.5, which

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is very high compared to our $1.38 spent in AC preparation. Hence it is apparent that the process has a lucrative scope for commercialization owing to the low costs incurred in carbon support preparation as well as the relatively simple catalyst preparation process. The recovery and reuse of the catalysts is also simple enough on a large scale with the right equipment, and since the carbon support prepared is structurally very capable of retaining functional groups as well as not damaged during the reaction and washing, Delonix regia based catalysts are definitely a rewarding approach towards large scale catalysed biodiesel production.

6. Conclusions A new technique was adopted for production of a low-corrosion biodiesel using a two-step catalytic conversion using steam activated Delonix regia as inert support for both acid (H2SO4 doped) and base catalysts (KOH doped). Raw material used as feedstock for the process is karanja oil. Using L16 Taguchi DOE, both esterification and transesterification processes are optimized. For both processes, the following parameters were considered: catalyst load, reaction duration, reaction temperature, molar ratio of oil to alcohol and agitation speed. Raw pods were analysed using TGA for determination of fixed carbon and carbonization temperature. Activated char and developed catalysts were characterized using SEM, EDAX, FT-IR, XRD and BET. The produced biodiesel was characterized by standard ASTM tests for physico-chemical suitability of the product. The developed catalysts were also tested for reusability, and base catalyst showed more stability in functional group retention than the acid catalyst. Finally an analysis of cost for preparation of the catalyst was calculated. Maximum FFA conversion using methanol was 99.86%; maximum biodiesel production using 2propanol was 99.39%. Biodiesel production reaches a maximum of 99.39% at 60
C for 90 min with 4% w/w catalyst under 700 rpm using 6:1 2-propanol: oil ratio. Catalyst reusability experiments showed good FFA conversion till 3 re-uses and high biodiesel yield till 7 re-uses. Cost analysis showed that catalyst support when indigenously prepared, is much more economical compared to activated carbon that is available commercially. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence that work reported in paper.

CRediT authorship contribution statement Bisheswar Karmakar: Conceptualization, Methodology, Investigation, Software, Validation. Sucharita Samanta: Formal analysis, Data curation, Writing - original draft. Gopinath Halder: Supervision, Project administration, Writing - review & editing. Acknowledgements We express our sincere gratitude to the Ministry of Science and Technology, Govt. of India for their financial aid through research project no. EEQ/2016/000243.

Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.jclepro.2020.120313.

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