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Biodiesel from fish waste oil: synthesis via supercritical methanol and thermodynamic optimization

Biodiesel from fish waste oil: synthesis via supercritical methanol and thermodynamic optimization Keywords: bioenergy; supercritical methanol; fish waste oil; biodiesel; transesterification; response surface methodology Received: 14 October 2020; Accepted: 20 February 2021 © The Author(s) 2021. Published by Oxford University Press on behalf of National Institute of Clean-and-Low-Carbon Energy This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http:// creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 188 | Clean Energy, 2021, Vol. 5, No. 2 The addition of a cosolvent improves the mass transfer Introduction between oil and alcohol by increasing the solubility and Recently, among renewable sources, biodiesel has drawn the creation of a single phase [15]. In this study, the utilized the attention of researchers and engineers as one of alcohol for biodiesel production has a high degree while the practical and promising solutions for energy issues triglyceride has a low degree of polarity. As a result, the and as a replacement choice for traditional fossil-based cosolvent should have a medium level of polarity [16]. The fuels. The biodiesel is normally synthesized through the yield in biodiesel obtained in the present study utilized transesterification reaction of vegetable oils, animal fats or hexane as a cosolvent, as it has a medium level of polarity waste oils with short-chain alcohols [ ]. In a typical method, 1 [17], with 20% hexane (v/v) [18]. due to the slow formation of the two phases of oil and al- The primary motivation and novelty of this study is cohol, the presence of a catalyst (an alkaline substance such the “efficient production of the biodiesel from fish waste as sodium hydroxide or potassium hydroxide) in biodiesel oil and methanol under supercritical conditions” to reduce production is essential. Applying the catalyst presents a significant costs of producing biodiesel in comparison series of restrictions and disadvantages, including the re- with conventional approaches, which typically need pre- quirement for excessive energy consumption for complex treatment of the raw materials at very high costs (please purification operations and the production of undesirable see the graphical abstract). The novelty relies on the ap- side reactions that are not able to provide an acceptable plication of supercritical methanol transesterification conversion rate [2 ]. To provide a practical solution, Saka and (SCMT) and the use of fish waste. However, supercritical Dadan [3] proposed a new breakthrough in catalyst-free conditions have been applied to other types of oil such production for biodiesel under supercritical conditions. This as vegetable oil, but fish waste as a source of oil was not innovation promises a lot of advantages including no need considered in other studies. This paper also relies on for a catalyst, separation with less complexity and higher a feasibility study of using local fish waste in Iran as a reaction rates without producing wastewater [ ]. Basicall 4 y, source of biodiesel. There exists a remarkable potential methanol under supercritical conditions turns into a won- for the utilization of fish oil as biodiesel in Iran, as its derful solvent that dissolves the feedstock. Therefore, potential is great among other renewables in Iran. Fish these molecules of the reactant react simply without any waste amounted to 300 000 tons in the Persian Gulf and particular catalyst [ ]. 5 The fact that the alcohol is present ~33 000 tons in the Caspian Sea, with an overall rate of under pressurized conditions in the reaction medium leads ~442 000 tons throughout the year 2003 [10]. Another ob- to higher solubility of the substrate, increasing the reaction jective of this paper is to investigate the use of local fish rates and ester yields []. 6 The use of supercritical methanol waste oil in Iran as a raw material in the economical and has potential in the economical conversion of low-quality easy production of biodiesel fuel. feedstock and oils with a high free-fatty-acid (FFA) con- The transesterification reaction was carried out in a tent, such as waste oils []. 7 Biodiesel holds many advan- continuous reactor under supercritical conditions and the tages over conventional petroleum diesel, such as high transesterification of fish waste oil was performed via super- biodegradability, high cetane index, and significant reduc- critical methanol. The response surface methodology (RSM) tions of engine exhaust emissions of carbon monoxide and method was applied to analyse the effect of four param- hydrocarbons as compared to petroleum diesel [ ]. The 8 only eters, including temperature ( ), T pressure (P), the molar ratio limitation of using this fuel may be its high cost in com- of alcohol to oil (W ) and the feed flow rate (F ) on the yield of parison with that of conventional diesel fuel. This high cost the biodiesel production in supercritical methanol. of biodiesel production is because of the high price of the feedstock in this process [9 ]. To reduce these costs, waste animal fats can be used as a potential feedstock. Some oils 1 Materials and methods of low quality, including of trap grease, cooking oils (con- 1.1 Materials tains 2–7% FFAs) and animal oils (contains 5–30% FFAs), are used as feedstocks in biodiesel production [10]. The fish The fish waste oil was purchased from Arman Jonoub Co. industry poses a high potential threat to the environment Normal hexane and methanol (purity >99%) w ere ordered if their waste is not disposed of properly, which provides from Iran Chemicals Co. and Shiraz Petrochemical Co., re- an opportunity to use waste fish oil as a source of renew- spectively. The fatty-acid compositions of the fish waste able fuel for cleaner power generation [11]. A pretreatment oils are listed in Table 1. step is needed to reduce the FFA level. Consequently, a low amount of the FFA in pretreated oil can be transesterified, 1.2 Apparatus and experimental design converting the triglycerides into biodiesel, using an alkali catalyst [12]. In a recent study focusing on biodiesel from Schematics of the experimental set-up to perform the re- vegetable oils, the effects of various types of vegetables action are depicted in Fig. 1. Because of the supercritical on the characteristics of biodiesel fuel were investigated treatment conditions and in order to sustain high levels of [13]. In another study, the authors synthesized fatty-acid pressure and temperature, a tubular reactor was placed in methyl ester using oil from viscera fish through an en- an oven. It comprised 316 tubes made from stainless steel zymatic catalysis and analysed the biodiesel in terms of with internal diameter of 0.74 cm and length of 0.55 m. After physico-chemical charactristics [14]. temperature stabilization, the feed consisting of fish waste Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 Espootin et al. | 189 Table 1: Fatty-acid composition of fish waste oil Fatty acid wt% Result Myristic acid (C14:0) 10.3 ± 3.4 Palmitic acid (C16:0) 38.5 ± 5.8 Oleic acid (C18:1) 28.6 ± 6.3 Stearic acid (C18:0) 7.7 ± 3.9 Eicosapentaenoic acid (C20:5) 6.2 ± 0.2 Docosahexaenoic acid (C22:6) 8.8 ± 3.1 Fig. 1: Schematic diagram of the apparatus oil, methanol and hexane as a cosolvent was pumped into the system using a high-pressure pump (model PU-980, and interaction coefficients, respectively. The coded values, JASCO Co.), with the pressure set by the back-pressure con- as well as the real values corresponding to each code, are troller (model BP 1580–81, JASCO Co.) and at a predefined given in Table 3. The sequence of the experiments was flow rate. For each set of experimental parameters, sam- random and a central point was performed in seven rep- ples were in an immersed vial in a cold trap while Crushed licates to evaluate the repeatability. Minitab 17 was used Pyrex Glass (CPG) filled up the tubular reaction chamber. for the statistical analysis of the experimental runs in A  selective CPG with a mesh range varying from 20 to 40 which the significance evaluation for the developed poly- was used in the following experiments. In order to measure nomial function was carried out using analysis of variance the amount of the produced methyl esters in the final bio- (ANOVA) and determination of the correlation coefficient. diesel product, a gas-chromatography (GC) analyser system together with an installed flame ionization detector (FID) was applied (model 3420, BEIFEN, China). Moreover, the ca- 2 Results and discussion pillary column (HP-5, i.d.  =  0.32  mm, length  =  30  m, film The general quadratic function represented by Equation thickness  =  0.25 µm) and argon gas with purity (99.99%) (2a) is the expanded version of Equation (1), which was em- as a carrier gas were used. Moreover, the GC analysis was ployed to derive a model for regression based on a polyno- carried out using temperature programming with a set ini- mial after fitting the output from the series of experiments: tial oven temperature of 70°C and held for 2 min. Then, the o o –1 temperature was raised to 310 C with a rate of 20C min . Y = β + β X + β X + β X + β X + β X X 0 1 1 2 2 3 3 4 4 12 1 2 The injection port and the detector temperature were set o o + β X X + β X X + β X X + β X X + β X X 12 1 2 13 1 3 14 1 4 23 2 3 24 2 4 at 315 C and 325 C, respectively. Also, in order to assure the 2 2 2 2 exit of all species in the injected samples into the column, + β X X + β X + β X + β X + β X 34 3 4 11 22 33 44 1 2 3 4 (2a) the temperature was held for 5 min. Minitab 17 and ANOVA were then used to determine values for the coefficient of correlation and the standard deviation to verify the suitability of the developed model. 1.3 Experimental design Based on the outcomes obtained by running the experi- An experimental procedure was designed for the process to ments, the biodiesel reaction yield varies with various pre- study the effective variables in the esterification reaction. defined variables according to: This method was performed using the central composite design (CCD), which takes into account four independent Y = 89.063 + 2.734T + 0.759P + 7.786F + 1.557W − 0.658T thermo-physical variables including the methanol-to-fish- 2 2 2 waste-oil-weight ratio (W), feed flow rate (F), reaction tem- − 0.843P − 2.888F − 0.787W + 0.110T.P − 1.172T.F perature (T) and reaction pressure (P) at five coded levels − 0.335T.W − 0.008P.F + 0.485P.W − 0.815F.W (2b) (–2, –1, 0, 1, 2). These ranges were selected based on sev- eral prior experiments and, consequently, the rest of the experiments, as depicted in Table 2, were carried out ac- 2.1 The model fitting cording to the analysis of the design matrix. In the next Rotatable CCD and response values (yield of produced step, after completing all the experiments, the obtained biodiesel) are presented in Table 4. Considering a con- results as the biodiesel yield were modelled by the RSM via fidence level of 95%, the parameters with P <  0.001 and a quadratic polynomial interpolation as: P  <  0.05 were characterized as very effective and ef- n n n n fective parameters, respectively. The results of the valid- Y = b + b X + b X + b X X i i ii i ij i j(1) ation of the model that was performed by the ANOVA are i=1 i=1 i=1 j>1 shown in Table 5. The results indicated that the linear In Equation (1), Y is the outcome, n shows the number of terms including W , T, F as well as the squared term of investigated parameters and optimal variables in the ex- F (P  <  0.001) were coded as the most effective param- perimental runs,X and X are the coded independent vari- eters. Furthermore, the linear term of the , squar P ed ables and b , b , b and b are the intercept, linear, quadratic term of W, T and P as well as cross terms W-time and o i ii ij Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 190 | Clean Energy, 2021, Vol. 5, No. 2 T-time (P <  0.05) were coded as effective parameters in R or the coefficient of determination, is considered for the proposed model based on the coded variables. The the analysis. Coefficient R represents the level of quality determination coefficient (R ) and the corrected de- for fitting where a polynomial model function is used. termination coefficient (Adj-R ) were estimated to be For this study, the coefficient was obtained to be 98.5%, 98.99% and 97.35%, respectively. These results indicate which reveals a great correlation among , T F, P and W that the appropriate precision of the proposed model with the response (Fig. 2). for correlating the experimental data was successfully achieved. Each of the coefficients in the equation has 2.2 GC analysis been determined where the significant coefficients of the developed quadratic models were calculated using The recorded chromatogram for the GC analyser system analysis of the standard deviation (Table). 6 The value of equipped with an FID detector was applied for quantita- P shows the probability for the situation in which a co- tive measurement. The detector response of the FID with efficient becomes 0.  This value is <5% if the confidence regard to different compounds is not the same in the re- level is assumed to be 0.95. Moreover, another indicator, corded chromatogram. This can be attributed to several reasons, such as the number of unequal injections and the Table 2: Coded experimental design conditions speed of the unequal injections, which have an effect on the peak integral area. To solve this problem and to reduce –1 a Run no. T (˚C) P (bar) F (mL min ) W mo the uncertainty in the chromatography methods, the in- 1 1 1 1 1– ternal standard (IS) and the peak area normalization were 2 1– 1– 1 1 used. To calculate the percentage value of each compound 3 1 1– 1– 1– from the peak area of the chromatogram, the peak area of 4 1– 1– 1 1– one of the compounds that was not participating in the 5 1– 1– 1– 1 reaction was used as the IS. Equation (3) was applied to in- 6 1– 1 1 1 crease the accuracy of the method. The RRF is the relative 7 1 1– 1 1 responses factor: 8 1 1– 1 1– 9 0 0 0 0 RRF×Area A Area IS 10 1– 1 1 1– A %=  × 100 (3) RRF×Area A Area IS 11 0 0 0 2 12 0 0 0 0 The recorded chromatogram of the biodiesel under super - 13 0 0 0 0 critical conditions is depicted in Fig. 3. After analysing the 14 0 0 0 0 fatty-acid methyl ester (FAME) content using the GC tech- 15 1 1 1 1 nique, the following results were obtained for the fish-oil 16 0 0 0 0 biodiesel for the ratio and retention time (RT): 17 0 2– 0 0 18 0 0 0 2– • oleic acid methyl ester (C-18:1) where RT = 13.88; 19 1 1 1– 1– • palmitic acid methyl ester (C-16:0) where R= T 12.38; 20 0 2 0 0 • eicosapentaenoic acid methyl ester (C-20:0) where 21 0 0 0 0 RT = 14.55; 22 0 0 2 0 • stearic acid methyl ester (C-18:0) where R= T 14.10;  23 2 0 0 0 • docosahexaenoic acid (C-22:6) where RT = 16.35. 24 1– 1 1– 1 25 0 0 2– 0 The related peaks confirm that the biodiesel was success- 26 0 0 0 0 fully synthesized [19]. Furthermore, Equation (4) was used 27 2– 0 0 0 for calculation of the yield value: 28 1 1 1– 1 29 1 1– 1– 1– Wight of Methyl Ester 30 1– 1 1– 1– Yield %= × 100 Weight of total oil in sample 31 1– 1– 1– 1– (4) Table 3: Coded levels and real values of experimental variables Variable Symbol Coded levels and real values 2 1 0 –1 –2 Temperature (C) T 320 270 220 170 120 Pressure (bar) P 140 120 100 80 60 –1 Flow rate (mL min ) F 2.5 2 1.5 1 0.5 Methanol to oil mass ratio M 30 25 20 15 10 Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 Espootin et al. | 191 Table 4: Experimental biodiesel-production yields according to the experimental matrix design for a three-level-four factors CCD Variables –1 a Run no. T (˚C) P (bar) F (mL min ) W Yield% mo 1 270 120 2 15 93.7 2 170 80 2 25 90.6 3 270 80 1 15 77.2 4 170 80 2 15 87.8 5 170 80 1 25 72.4 6 170 120 2 25 92.1 7 270 80 2 25 93.0 8 270 80 2 15 92.8 9 220 100 1.5 20 87.7 10 170 120 2 15 89.8 11 220 100 1.5 30 88.3 12 220 100 1.5 20 89.8 13 220 100 1.5 20 90.3 14 220 100 1.5 20 90.6 15 270 120 2 25 96.3 16 220 100 1.5 20 89.1 17 220 60 1.5 20 85.1 18 220 100 1.5 10 83.3 19 270 120 1 15 78.7 20 220 140 1.5 20 86.1 21 220 100 1.5 20 88.4 22 220 100 2.5 20 91.6 23 320 100 1.5 20 90.0 24 270 120 1 25 76.4 25 220 100 0.5 20 63.1 26 220 100 1 1.5 87.5 27 120 100 1.5 20 82.4 28 270 120 1 25 83.7 29 270 80 1 25 80.9 30 170 120 1 15 68.8 31 170 80 1 15 68.5 The weight ratio of methanol to oil. A generic chromatogram of the methyl esters for the Table 5: Regression coefficients, T-value and P-value for the model estimated by Minitab software for the transesterification selected sample with optimal values is shown in Fig. 3. reaction Biodiesel yield (%) 3 Investigation of the effects of the Term Coefficient T-value P-value process parameters Constant 89.063 1760.3 0 To investigate the different operating parameters such T 2.734 10.01 0 as P, F, W and T on the biodiesel-production efficiency, P 0.759 2.78 0.013 RSM diagrams were plotted. These diagrams were used to F 7.786 28.49 0 describe the effects of two variables on response values W 1.557 5.7 0 while the other two variables were constant. The bio- T –0.658 –2.63 0.018 diesel response graph (Yield%) as a function of the two P –0.843 –3.37 0.004 parameter values of the reaction in a 3D graph is depicted F –2.888 –11.54 0 in Fig. 4. W –0.787 –3.14 0.006 TW –0.335 –1 0.033 TF –1.172 –3.5 0.003 3.1 Effect of the temperature (T) and pressure (P) TP 0.11 0.33 0.747 WF –0.815 –2.44 0.027 To investigate the effect of the pressure, the yield as a func- WP 0.485 1.45 0.167 tion of the T and P values of the reaction was researched. In FP –0.008 –0.02 0.982 this study, F and W were selected to have constant values Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 192 | Clean Energy, 2021, Vol. 5, No. 2 Table 6: Analysis of the variance of the proposed models for the efficiency of the biodiesel production Source Degree of freedom Sum of square Mean square F P Regression 14 1998.81 142.77 79.68 0 Linear variables 4 1706.27 426.57 238.05 0 Square variables 4 254.17 63.54 35.46 0 Mutual variables 6 38.38 6.4 3.57 0.019 Error 16 28.67 1.79 Lack of fit 10 19.45 1.94 1.27 0.402 Net error 6 9.22 1.54 Total 30 2027.48   Fig. 3: Chromatogram of the biodiesel under supercritical methanol Fig. 2: Predicted values with respect to the experimental percentage conditions values of the biodiesel (R = 0.985) to a reduced amount of produced biodiesel due to the lack –1 of 1.5  mL  min and 20:1, respectively. The reaction pres- of sufficient time for a reaction between the alcohol and sure in the interval 60–140 bar varies directly and propor - the feed [22]. Due to the F value increasing, the likelihood tionally with the amount of biodiesel produced. According of degradation of the methyl esters increases, so the bio- to Fig. 4a, increasing the pressure up to an optimal amount diesel yield is reduced. Therefore, there is a slight reduc- (~112.7  bar) enhanced the solubility of the oil in alcohol tion in the amount of biodiesel produced at high values of to form a more homogeneous mixture [20]. Moreover, an F and W (Fig. 4b). increase in collisions between molecules of the alcohol Several experiments under different conditions have and oil leads to an increase in the amount of methyl ester been conducted with the methanol-to-fish-waste-oil- production, while a further increase in the pressure leads weight ratio in the range of 10:1 to 30:1 in order to investi- to enhancement of the dilution of the reactants and pre- gate the impact of its variation on the amount of produced vents the reaction between them. Therefore, the efficiency biodiesel. Table 3 shows the results obtained from ANOVA rate decreases at higher pressures [20]. According to Fig. 4a, in which the process response is significantly affected by increasing the pressure over an optimal level at low tem- the methanol-to-fish-waste-oil-weight ratio. Higher levels peratures results in a further decrease in the amount of of excessive methanol reduce the temperatures of the crit- methyl ester produced and the yield of the production of ical products in the reaction products. The reason for this the biodiesel. is that the critical state of the methanol is smaller in com- Pressure affects the thermo-physical properties as parison with the conditions of the constituents of the mix- well as the hydrogen bonding, especially around the ture. If the critical temperatures of the components in the fluid’s critical point. Hence, the higher the pressure, the product are reduced, the FAME decompositions will im- higher the fluid density, which results, at a specific reac- prove and, as a result, the amount of produced biodiesel tion temperature, in stronger interaction among the par - will decrease [23]. ticles [21]. 3.3 Effect of the methanol-to-fish-waste-oil- weight ratio (W) and temperature (T) 3.2 Effect of the feed flow rate (F) and methanol- to-fish-waste-oil-weight ratio (W) In Fig. 4c, the yield value has been shown as a function To investigate the effects of the F value on the biodiesel of the W and T values of the reaction. The P and F values –1 yield with T and P constant at values of 220°C and 100 bar, have constant values of 100 bar and 1.5 mL min, respect- this parameter was studied within the range of 0.5– ively. Increasing the W value leads to an increase in the –1 2.0 mL min . At high W values, increasing the F value leads alcohol and oil contact levels, resulting in more products. Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 Espootin et al. | 193 Fig. 4: The biodiesel response graph (Yield%) Furthermore, increasing the W value reduces the critical Therefore, at high values of T and W, the biodiesel yield temperature of the reaction mixture. At higher T and W goes down slightly [23]. values, by lowering the critical temperature of the reaction The temperature of the reaction plays an important mixture, the biodiesel-production efficiency is decreased role in biodiesel-production efficiency under supercrit- due to the decomposition of the produced methyl esters. ical conditions, as it instantly impacts the stabilization of Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 194 | Clean Energy, 2021, Vol. 5, No. 2 the FAME production [20]. It is known that, by increasing shown in Fig. 4e–h. Similar observations have been re- the temperature of the reaction significantly up to 270 C, ported by recent studies when transesterification has FAME achieves stability; however, beyond this level, de- been carried out at higher levels of reaction tempera- composition begins as a result of isomerization between ture [26]. cis- and trans-forms [20]. So, with higher T and W values, the biodiesel-production efficiency is decreased due to the decomposition of the produced methyl esters. Therefore, 3.5 Optimal level of variables the yield of the produced biodiesel reduces slightly at high Using Minitab and its response optimizer package, the values of T and W [22]. If the volumetric ratio of methanol optimal levels of the selected reaction variables were to oil increases to a certain value, the biodiesel impurity achieved. The optimum operating conditions were de- will decrease, as was reported by similar observations in termined and summarized by the RSM method (Table 7 ). the literature [24]. Under optimum conditions, the predicted maximum yield was estimated to be 95.2%. To verify the predicted yield by the model developed, the optimal levels for the response 3.4 Effect of the feed flow rate (F) and reaction variables were analysed for the predicted optimal condi- temperature (T) tions. Finally, the yield of biodiesel production was cal- The effect of the T and F values of the reaction on the culated to be 94.6%, which is close to the predicted yield yield with W and P constant at values of 20:1 and 100 bar (95.2%). was studied. As can be seen in Fig. 4d, a high reaction Table 8 provides a comparison of the best results temperature leads to increasing the chance of collision obtained in this study with the results reported by between the materials and, consequently, the speed of Aboelazayem et  al. [27], García-Martínez et  al. [ 28] and the reaction is increased. So, an increase in the yield Samniang et  al. [29], including the experimental condi- value is achieved by the temperature increasing up to tions and FAME. an optimum value of 270°C. At higher temperatures, the decomposition of unsaturated methyl ester of the fatty acid leads to a slight decrease in the yield value. Similar 4 Conclusions results have been observed by researchers in Ref. [25], in which it is reported that, if the reaction temperature To sum up, the production of biodiesel fuel from fish increases to >271 C, the efficiency of the biodiesel pro- waste oil was investigated using a transesterification re- duction will start to reduce. Furthermore, the F value is action under supercritical conditions of methanol in a effective on the biodiesel-production efficiency. At low continuous system. The conventional catalytic methods F values, due to the prolongation of the reaction time, caused some problems due to the sensitivity of the FFAs the possibility of producing side reactions of the de- and the water present in the primary oil. Unlike these composition of the produced methyl esters is increased. methods, the supercritical-alcohol method performs the Consequently, biodiesel-production efficiency is de- transesterification reaction without the need for a catalyst, creased [20]. The related contour plots for this study are which eliminates catalyst-consumption problems and the need for separation and purification of the products from the catalyst. The operating conditions were optimized Table 7: Optimum operating conditions determined by the by designing the experiments using the CCD method. RSM According to the optimal operating conditions calculated by the RSM, the values of W (22.3), T (270°C), P (112.7 bar) Variables Optimum value –1 and F (2.0  mL  min ) were achieved. The maximum effi- M = methanol-to-oil-weight ratio 22.3 ciency predicted by the RSM was estimated to be 95.2%. T = temperature 270°C The experimental yield of the biodiesel production under P = pressure 112.7 bar the optimum conditions was calculated to be 94.6%, which −1 F = flow rate 2.0 mL min is close to the predicted yield (95.2%). Table 8: Optimum operating conditions determined by the RSM Alcohol Experimental conditions FAME (wt%) Reference –1 Methanol 22.3:1 methanol-to-oil-weight ratio; 270°C; 112.7 bar; 2.0 mL min 94.6% This work Methanol 37:1 methanol-to-oil-weight ratio; 253.5°C; 198.5 bar 91% Aboelazayem et al. [27] Methanol 43:1 methanol-to-tobacco-oil molar ratio; 300°C; 90 min 92.8% García-Martínez et al. 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Production and characterization of biodiesel from oil Comparison of biodiesel production from crude Jatropha oil of fish waste by enzymatic catalysis. Renewable Energy, 2020, and Krating oil by supercritical methanol transesterification. 153:1346–1354. Renewable Energy, 2014, 68:351–355. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Clean Energy Oxford University Press

Biodiesel from fish waste oil: synthesis via supercritical methanol and thermodynamic optimization

Clean Energy , Volume 5 (2) – Jun 1, 2021

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Copyright © 2021 National Institute of Clean-and-Low-Carbon Energy
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10.1093/ce/zkab003
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Abstract

Keywords: bioenergy; supercritical methanol; fish waste oil; biodiesel; transesterification; response surface methodology Received: 14 October 2020; Accepted: 20 February 2021 © The Author(s) 2021. Published by Oxford University Press on behalf of National Institute of Clean-and-Low-Carbon Energy This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http:// creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 188 | Clean Energy, 2021, Vol. 5, No. 2 The addition of a cosolvent improves the mass transfer Introduction between oil and alcohol by increasing the solubility and Recently, among renewable sources, biodiesel has drawn the creation of a single phase [15]. In this study, the utilized the attention of researchers and engineers as one of alcohol for biodiesel production has a high degree while the practical and promising solutions for energy issues triglyceride has a low degree of polarity. As a result, the and as a replacement choice for traditional fossil-based cosolvent should have a medium level of polarity [16]. The fuels. The biodiesel is normally synthesized through the yield in biodiesel obtained in the present study utilized transesterification reaction of vegetable oils, animal fats or hexane as a cosolvent, as it has a medium level of polarity waste oils with short-chain alcohols [ ]. In a typical method, 1 [17], with 20% hexane (v/v) [18]. due to the slow formation of the two phases of oil and al- The primary motivation and novelty of this study is cohol, the presence of a catalyst (an alkaline substance such the “efficient production of the biodiesel from fish waste as sodium hydroxide or potassium hydroxide) in biodiesel oil and methanol under supercritical conditions” to reduce production is essential. Applying the catalyst presents a significant costs of producing biodiesel in comparison series of restrictions and disadvantages, including the re- with conventional approaches, which typically need pre- quirement for excessive energy consumption for complex treatment of the raw materials at very high costs (please purification operations and the production of undesirable see the graphical abstract). The novelty relies on the ap- side reactions that are not able to provide an acceptable plication of supercritical methanol transesterification conversion rate [2 ]. To provide a practical solution, Saka and (SCMT) and the use of fish waste. However, supercritical Dadan [3] proposed a new breakthrough in catalyst-free conditions have been applied to other types of oil such production for biodiesel under supercritical conditions. This as vegetable oil, but fish waste as a source of oil was not innovation promises a lot of advantages including no need considered in other studies. This paper also relies on for a catalyst, separation with less complexity and higher a feasibility study of using local fish waste in Iran as a reaction rates without producing wastewater [ ]. Basicall 4 y, source of biodiesel. There exists a remarkable potential methanol under supercritical conditions turns into a won- for the utilization of fish oil as biodiesel in Iran, as its derful solvent that dissolves the feedstock. Therefore, potential is great among other renewables in Iran. Fish these molecules of the reactant react simply without any waste amounted to 300 000 tons in the Persian Gulf and particular catalyst [ ]. 5 The fact that the alcohol is present ~33 000 tons in the Caspian Sea, with an overall rate of under pressurized conditions in the reaction medium leads ~442 000 tons throughout the year 2003 [10]. Another ob- to higher solubility of the substrate, increasing the reaction jective of this paper is to investigate the use of local fish rates and ester yields []. 6 The use of supercritical methanol waste oil in Iran as a raw material in the economical and has potential in the economical conversion of low-quality easy production of biodiesel fuel. feedstock and oils with a high free-fatty-acid (FFA) con- The transesterification reaction was carried out in a tent, such as waste oils []. 7 Biodiesel holds many advan- continuous reactor under supercritical conditions and the tages over conventional petroleum diesel, such as high transesterification of fish waste oil was performed via super- biodegradability, high cetane index, and significant reduc- critical methanol. The response surface methodology (RSM) tions of engine exhaust emissions of carbon monoxide and method was applied to analyse the effect of four param- hydrocarbons as compared to petroleum diesel [ ]. The 8 only eters, including temperature ( ), T pressure (P), the molar ratio limitation of using this fuel may be its high cost in com- of alcohol to oil (W ) and the feed flow rate (F ) on the yield of parison with that of conventional diesel fuel. This high cost the biodiesel production in supercritical methanol. of biodiesel production is because of the high price of the feedstock in this process [9 ]. To reduce these costs, waste animal fats can be used as a potential feedstock. Some oils 1 Materials and methods of low quality, including of trap grease, cooking oils (con- 1.1 Materials tains 2–7% FFAs) and animal oils (contains 5–30% FFAs), are used as feedstocks in biodiesel production [10]. The fish The fish waste oil was purchased from Arman Jonoub Co. industry poses a high potential threat to the environment Normal hexane and methanol (purity >99%) w ere ordered if their waste is not disposed of properly, which provides from Iran Chemicals Co. and Shiraz Petrochemical Co., re- an opportunity to use waste fish oil as a source of renew- spectively. The fatty-acid compositions of the fish waste able fuel for cleaner power generation [11]. A pretreatment oils are listed in Table 1. step is needed to reduce the FFA level. Consequently, a low amount of the FFA in pretreated oil can be transesterified, 1.2 Apparatus and experimental design converting the triglycerides into biodiesel, using an alkali catalyst [12]. In a recent study focusing on biodiesel from Schematics of the experimental set-up to perform the re- vegetable oils, the effects of various types of vegetables action are depicted in Fig. 1. Because of the supercritical on the characteristics of biodiesel fuel were investigated treatment conditions and in order to sustain high levels of [13]. In another study, the authors synthesized fatty-acid pressure and temperature, a tubular reactor was placed in methyl ester using oil from viscera fish through an en- an oven. It comprised 316 tubes made from stainless steel zymatic catalysis and analysed the biodiesel in terms of with internal diameter of 0.74 cm and length of 0.55 m. After physico-chemical charactristics [14]. temperature stabilization, the feed consisting of fish waste Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 Espootin et al. | 189 Table 1: Fatty-acid composition of fish waste oil Fatty acid wt% Result Myristic acid (C14:0) 10.3 ± 3.4 Palmitic acid (C16:0) 38.5 ± 5.8 Oleic acid (C18:1) 28.6 ± 6.3 Stearic acid (C18:0) 7.7 ± 3.9 Eicosapentaenoic acid (C20:5) 6.2 ± 0.2 Docosahexaenoic acid (C22:6) 8.8 ± 3.1 Fig. 1: Schematic diagram of the apparatus oil, methanol and hexane as a cosolvent was pumped into the system using a high-pressure pump (model PU-980, and interaction coefficients, respectively. The coded values, JASCO Co.), with the pressure set by the back-pressure con- as well as the real values corresponding to each code, are troller (model BP 1580–81, JASCO Co.) and at a predefined given in Table 3. The sequence of the experiments was flow rate. For each set of experimental parameters, sam- random and a central point was performed in seven rep- ples were in an immersed vial in a cold trap while Crushed licates to evaluate the repeatability. Minitab 17 was used Pyrex Glass (CPG) filled up the tubular reaction chamber. for the statistical analysis of the experimental runs in A  selective CPG with a mesh range varying from 20 to 40 which the significance evaluation for the developed poly- was used in the following experiments. In order to measure nomial function was carried out using analysis of variance the amount of the produced methyl esters in the final bio- (ANOVA) and determination of the correlation coefficient. diesel product, a gas-chromatography (GC) analyser system together with an installed flame ionization detector (FID) was applied (model 3420, BEIFEN, China). Moreover, the ca- 2 Results and discussion pillary column (HP-5, i.d.  =  0.32  mm, length  =  30  m, film The general quadratic function represented by Equation thickness  =  0.25 µm) and argon gas with purity (99.99%) (2a) is the expanded version of Equation (1), which was em- as a carrier gas were used. Moreover, the GC analysis was ployed to derive a model for regression based on a polyno- carried out using temperature programming with a set ini- mial after fitting the output from the series of experiments: tial oven temperature of 70°C and held for 2 min. Then, the o o –1 temperature was raised to 310 C with a rate of 20C min . Y = β + β X + β X + β X + β X + β X X 0 1 1 2 2 3 3 4 4 12 1 2 The injection port and the detector temperature were set o o + β X X + β X X + β X X + β X X + β X X 12 1 2 13 1 3 14 1 4 23 2 3 24 2 4 at 315 C and 325 C, respectively. Also, in order to assure the 2 2 2 2 exit of all species in the injected samples into the column, + β X X + β X + β X + β X + β X 34 3 4 11 22 33 44 1 2 3 4 (2a) the temperature was held for 5 min. Minitab 17 and ANOVA were then used to determine values for the coefficient of correlation and the standard deviation to verify the suitability of the developed model. 1.3 Experimental design Based on the outcomes obtained by running the experi- An experimental procedure was designed for the process to ments, the biodiesel reaction yield varies with various pre- study the effective variables in the esterification reaction. defined variables according to: This method was performed using the central composite design (CCD), which takes into account four independent Y = 89.063 + 2.734T + 0.759P + 7.786F + 1.557W − 0.658T thermo-physical variables including the methanol-to-fish- 2 2 2 waste-oil-weight ratio (W), feed flow rate (F), reaction tem- − 0.843P − 2.888F − 0.787W + 0.110T.P − 1.172T.F perature (T) and reaction pressure (P) at five coded levels − 0.335T.W − 0.008P.F + 0.485P.W − 0.815F.W (2b) (–2, –1, 0, 1, 2). These ranges were selected based on sev- eral prior experiments and, consequently, the rest of the experiments, as depicted in Table 2, were carried out ac- 2.1 The model fitting cording to the analysis of the design matrix. In the next Rotatable CCD and response values (yield of produced step, after completing all the experiments, the obtained biodiesel) are presented in Table 4. Considering a con- results as the biodiesel yield were modelled by the RSM via fidence level of 95%, the parameters with P <  0.001 and a quadratic polynomial interpolation as: P  <  0.05 were characterized as very effective and ef- n n n n fective parameters, respectively. The results of the valid- Y = b + b X + b X + b X X i i ii i ij i j(1) ation of the model that was performed by the ANOVA are i=1 i=1 i=1 j>1 shown in Table 5. The results indicated that the linear In Equation (1), Y is the outcome, n shows the number of terms including W , T, F as well as the squared term of investigated parameters and optimal variables in the ex- F (P  <  0.001) were coded as the most effective param- perimental runs,X and X are the coded independent vari- eters. Furthermore, the linear term of the , squar P ed ables and b , b , b and b are the intercept, linear, quadratic term of W, T and P as well as cross terms W-time and o i ii ij Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 190 | Clean Energy, 2021, Vol. 5, No. 2 T-time (P <  0.05) were coded as effective parameters in R or the coefficient of determination, is considered for the proposed model based on the coded variables. The the analysis. Coefficient R represents the level of quality determination coefficient (R ) and the corrected de- for fitting where a polynomial model function is used. termination coefficient (Adj-R ) were estimated to be For this study, the coefficient was obtained to be 98.5%, 98.99% and 97.35%, respectively. These results indicate which reveals a great correlation among , T F, P and W that the appropriate precision of the proposed model with the response (Fig. 2). for correlating the experimental data was successfully achieved. Each of the coefficients in the equation has 2.2 GC analysis been determined where the significant coefficients of the developed quadratic models were calculated using The recorded chromatogram for the GC analyser system analysis of the standard deviation (Table). 6 The value of equipped with an FID detector was applied for quantita- P shows the probability for the situation in which a co- tive measurement. The detector response of the FID with efficient becomes 0.  This value is <5% if the confidence regard to different compounds is not the same in the re- level is assumed to be 0.95. Moreover, another indicator, corded chromatogram. This can be attributed to several reasons, such as the number of unequal injections and the Table 2: Coded experimental design conditions speed of the unequal injections, which have an effect on the peak integral area. To solve this problem and to reduce –1 a Run no. T (˚C) P (bar) F (mL min ) W mo the uncertainty in the chromatography methods, the in- 1 1 1 1 1– ternal standard (IS) and the peak area normalization were 2 1– 1– 1 1 used. To calculate the percentage value of each compound 3 1 1– 1– 1– from the peak area of the chromatogram, the peak area of 4 1– 1– 1 1– one of the compounds that was not participating in the 5 1– 1– 1– 1 reaction was used as the IS. Equation (3) was applied to in- 6 1– 1 1 1 crease the accuracy of the method. The RRF is the relative 7 1 1– 1 1 responses factor: 8 1 1– 1 1– 9 0 0 0 0 RRF×Area A Area IS 10 1– 1 1 1– A %=  × 100 (3) RRF×Area A Area IS 11 0 0 0 2 12 0 0 0 0 The recorded chromatogram of the biodiesel under super - 13 0 0 0 0 critical conditions is depicted in Fig. 3. After analysing the 14 0 0 0 0 fatty-acid methyl ester (FAME) content using the GC tech- 15 1 1 1 1 nique, the following results were obtained for the fish-oil 16 0 0 0 0 biodiesel for the ratio and retention time (RT): 17 0 2– 0 0 18 0 0 0 2– • oleic acid methyl ester (C-18:1) where RT = 13.88; 19 1 1 1– 1– • palmitic acid methyl ester (C-16:0) where R= T 12.38; 20 0 2 0 0 • eicosapentaenoic acid methyl ester (C-20:0) where 21 0 0 0 0 RT = 14.55; 22 0 0 2 0 • stearic acid methyl ester (C-18:0) where R= T 14.10;  23 2 0 0 0 • docosahexaenoic acid (C-22:6) where RT = 16.35. 24 1– 1 1– 1 25 0 0 2– 0 The related peaks confirm that the biodiesel was success- 26 0 0 0 0 fully synthesized [19]. Furthermore, Equation (4) was used 27 2– 0 0 0 for calculation of the yield value: 28 1 1 1– 1 29 1 1– 1– 1– Wight of Methyl Ester 30 1– 1 1– 1– Yield %= × 100 Weight of total oil in sample 31 1– 1– 1– 1– (4) Table 3: Coded levels and real values of experimental variables Variable Symbol Coded levels and real values 2 1 0 –1 –2 Temperature (C) T 320 270 220 170 120 Pressure (bar) P 140 120 100 80 60 –1 Flow rate (mL min ) F 2.5 2 1.5 1 0.5 Methanol to oil mass ratio M 30 25 20 15 10 Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 Espootin et al. | 191 Table 4: Experimental biodiesel-production yields according to the experimental matrix design for a three-level-four factors CCD Variables –1 a Run no. T (˚C) P (bar) F (mL min ) W Yield% mo 1 270 120 2 15 93.7 2 170 80 2 25 90.6 3 270 80 1 15 77.2 4 170 80 2 15 87.8 5 170 80 1 25 72.4 6 170 120 2 25 92.1 7 270 80 2 25 93.0 8 270 80 2 15 92.8 9 220 100 1.5 20 87.7 10 170 120 2 15 89.8 11 220 100 1.5 30 88.3 12 220 100 1.5 20 89.8 13 220 100 1.5 20 90.3 14 220 100 1.5 20 90.6 15 270 120 2 25 96.3 16 220 100 1.5 20 89.1 17 220 60 1.5 20 85.1 18 220 100 1.5 10 83.3 19 270 120 1 15 78.7 20 220 140 1.5 20 86.1 21 220 100 1.5 20 88.4 22 220 100 2.5 20 91.6 23 320 100 1.5 20 90.0 24 270 120 1 25 76.4 25 220 100 0.5 20 63.1 26 220 100 1 1.5 87.5 27 120 100 1.5 20 82.4 28 270 120 1 25 83.7 29 270 80 1 25 80.9 30 170 120 1 15 68.8 31 170 80 1 15 68.5 The weight ratio of methanol to oil. A generic chromatogram of the methyl esters for the Table 5: Regression coefficients, T-value and P-value for the model estimated by Minitab software for the transesterification selected sample with optimal values is shown in Fig. 3. reaction Biodiesel yield (%) 3 Investigation of the effects of the Term Coefficient T-value P-value process parameters Constant 89.063 1760.3 0 To investigate the different operating parameters such T 2.734 10.01 0 as P, F, W and T on the biodiesel-production efficiency, P 0.759 2.78 0.013 RSM diagrams were plotted. These diagrams were used to F 7.786 28.49 0 describe the effects of two variables on response values W 1.557 5.7 0 while the other two variables were constant. The bio- T –0.658 –2.63 0.018 diesel response graph (Yield%) as a function of the two P –0.843 –3.37 0.004 parameter values of the reaction in a 3D graph is depicted F –2.888 –11.54 0 in Fig. 4. W –0.787 –3.14 0.006 TW –0.335 –1 0.033 TF –1.172 –3.5 0.003 3.1 Effect of the temperature (T) and pressure (P) TP 0.11 0.33 0.747 WF –0.815 –2.44 0.027 To investigate the effect of the pressure, the yield as a func- WP 0.485 1.45 0.167 tion of the T and P values of the reaction was researched. In FP –0.008 –0.02 0.982 this study, F and W were selected to have constant values Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 192 | Clean Energy, 2021, Vol. 5, No. 2 Table 6: Analysis of the variance of the proposed models for the efficiency of the biodiesel production Source Degree of freedom Sum of square Mean square F P Regression 14 1998.81 142.77 79.68 0 Linear variables 4 1706.27 426.57 238.05 0 Square variables 4 254.17 63.54 35.46 0 Mutual variables 6 38.38 6.4 3.57 0.019 Error 16 28.67 1.79 Lack of fit 10 19.45 1.94 1.27 0.402 Net error 6 9.22 1.54 Total 30 2027.48   Fig. 3: Chromatogram of the biodiesel under supercritical methanol Fig. 2: Predicted values with respect to the experimental percentage conditions values of the biodiesel (R = 0.985) to a reduced amount of produced biodiesel due to the lack –1 of 1.5  mL  min and 20:1, respectively. The reaction pres- of sufficient time for a reaction between the alcohol and sure in the interval 60–140 bar varies directly and propor - the feed [22]. Due to the F value increasing, the likelihood tionally with the amount of biodiesel produced. According of degradation of the methyl esters increases, so the bio- to Fig. 4a, increasing the pressure up to an optimal amount diesel yield is reduced. Therefore, there is a slight reduc- (~112.7  bar) enhanced the solubility of the oil in alcohol tion in the amount of biodiesel produced at high values of to form a more homogeneous mixture [20]. Moreover, an F and W (Fig. 4b). increase in collisions between molecules of the alcohol Several experiments under different conditions have and oil leads to an increase in the amount of methyl ester been conducted with the methanol-to-fish-waste-oil- production, while a further increase in the pressure leads weight ratio in the range of 10:1 to 30:1 in order to investi- to enhancement of the dilution of the reactants and pre- gate the impact of its variation on the amount of produced vents the reaction between them. Therefore, the efficiency biodiesel. Table 3 shows the results obtained from ANOVA rate decreases at higher pressures [20]. According to Fig. 4a, in which the process response is significantly affected by increasing the pressure over an optimal level at low tem- the methanol-to-fish-waste-oil-weight ratio. Higher levels peratures results in a further decrease in the amount of of excessive methanol reduce the temperatures of the crit- methyl ester produced and the yield of the production of ical products in the reaction products. The reason for this the biodiesel. is that the critical state of the methanol is smaller in com- Pressure affects the thermo-physical properties as parison with the conditions of the constituents of the mix- well as the hydrogen bonding, especially around the ture. If the critical temperatures of the components in the fluid’s critical point. Hence, the higher the pressure, the product are reduced, the FAME decompositions will im- higher the fluid density, which results, at a specific reac- prove and, as a result, the amount of produced biodiesel tion temperature, in stronger interaction among the par - will decrease [23]. ticles [21]. 3.3 Effect of the methanol-to-fish-waste-oil- weight ratio (W) and temperature (T) 3.2 Effect of the feed flow rate (F) and methanol- to-fish-waste-oil-weight ratio (W) In Fig. 4c, the yield value has been shown as a function To investigate the effects of the F value on the biodiesel of the W and T values of the reaction. The P and F values –1 yield with T and P constant at values of 220°C and 100 bar, have constant values of 100 bar and 1.5 mL min, respect- this parameter was studied within the range of 0.5– ively. Increasing the W value leads to an increase in the –1 2.0 mL min . At high W values, increasing the F value leads alcohol and oil contact levels, resulting in more products. Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 Espootin et al. | 193 Fig. 4: The biodiesel response graph (Yield%) Furthermore, increasing the W value reduces the critical Therefore, at high values of T and W, the biodiesel yield temperature of the reaction mixture. At higher T and W goes down slightly [23]. values, by lowering the critical temperature of the reaction The temperature of the reaction plays an important mixture, the biodiesel-production efficiency is decreased role in biodiesel-production efficiency under supercrit- due to the decomposition of the produced methyl esters. ical conditions, as it instantly impacts the stabilization of Downloaded from https://academic.oup.com/ce/article/5/2/187/6245790 by DeepDyve user on 27 April 2021 194 | Clean Energy, 2021, Vol. 5, No. 2 the FAME production [20]. It is known that, by increasing shown in Fig. 4e–h. Similar observations have been re- the temperature of the reaction significantly up to 270 C, ported by recent studies when transesterification has FAME achieves stability; however, beyond this level, de- been carried out at higher levels of reaction tempera- composition begins as a result of isomerization between ture [26]. cis- and trans-forms [20]. So, with higher T and W values, the biodiesel-production efficiency is decreased due to the decomposition of the produced methyl esters. Therefore, 3.5 Optimal level of variables the yield of the produced biodiesel reduces slightly at high Using Minitab and its response optimizer package, the values of T and W [22]. If the volumetric ratio of methanol optimal levels of the selected reaction variables were to oil increases to a certain value, the biodiesel impurity achieved. The optimum operating conditions were de- will decrease, as was reported by similar observations in termined and summarized by the RSM method (Table 7 ). the literature [24]. Under optimum conditions, the predicted maximum yield was estimated to be 95.2%. To verify the predicted yield by the model developed, the optimal levels for the response 3.4 Effect of the feed flow rate (F) and reaction variables were analysed for the predicted optimal condi- temperature (T) tions. Finally, the yield of biodiesel production was cal- The effect of the T and F values of the reaction on the culated to be 94.6%, which is close to the predicted yield yield with W and P constant at values of 20:1 and 100 bar (95.2%). was studied. As can be seen in Fig. 4d, a high reaction Table 8 provides a comparison of the best results temperature leads to increasing the chance of collision obtained in this study with the results reported by between the materials and, consequently, the speed of Aboelazayem et  al. [27], García-Martínez et  al. [ 28] and the reaction is increased. So, an increase in the yield Samniang et  al. [29], including the experimental condi- value is achieved by the temperature increasing up to tions and FAME. an optimum value of 270°C. At higher temperatures, the decomposition of unsaturated methyl ester of the fatty acid leads to a slight decrease in the yield value. Similar 4 Conclusions results have been observed by researchers in Ref. [25], in which it is reported that, if the reaction temperature To sum up, the production of biodiesel fuel from fish increases to >271 C, the efficiency of the biodiesel pro- waste oil was investigated using a transesterification re- duction will start to reduce. Furthermore, the F value is action under supercritical conditions of methanol in a effective on the biodiesel-production efficiency. At low continuous system. The conventional catalytic methods F values, due to the prolongation of the reaction time, caused some problems due to the sensitivity of the FFAs the possibility of producing side reactions of the de- and the water present in the primary oil. Unlike these composition of the produced methyl esters is increased. methods, the supercritical-alcohol method performs the Consequently, biodiesel-production efficiency is de- transesterification reaction without the need for a catalyst, creased [20]. The related contour plots for this study are which eliminates catalyst-consumption problems and the need for separation and purification of the products from the catalyst. The operating conditions were optimized Table 7: Optimum operating conditions determined by the by designing the experiments using the CCD method. RSM According to the optimal operating conditions calculated by the RSM, the values of W (22.3), T (270°C), P (112.7 bar) Variables Optimum value –1 and F (2.0  mL  min ) were achieved. The maximum effi- M = methanol-to-oil-weight ratio 22.3 ciency predicted by the RSM was estimated to be 95.2%. T = temperature 270°C The experimental yield of the biodiesel production under P = pressure 112.7 bar the optimum conditions was calculated to be 94.6%, which −1 F = flow rate 2.0 mL min is close to the predicted yield (95.2%). Table 8: Optimum operating conditions determined by the RSM Alcohol Experimental conditions FAME (wt%) Reference –1 Methanol 22.3:1 methanol-to-oil-weight ratio; 270°C; 112.7 bar; 2.0 mL min 94.6% This work Methanol 37:1 methanol-to-oil-weight ratio; 253.5°C; 198.5 bar 91% Aboelazayem et al. [27] Methanol 43:1 methanol-to-tobacco-oil molar ratio; 300°C; 90 min 92.8% García-Martínez et al. 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Journal

Clean EnergyOxford University Press

Published: Jun 1, 2021

References