Snail (Helix pomatia) Shells as a Catalyst for Biodiesel Synthesis

Snail (Helix pomatia) Shells as a Catalyst for Biodiesel Synthesis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Snail ( Helix pomatia ) Shells as a Catalyst for Biodiesel Synthesis Eglė Sendžikienė, Gediminas Gokas, Ieva Gaidė, Milda Gumbytė, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6811110/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Biodiesel is an alternative to conventional diesel. The use of heterogeneous catalysts in biodiesel production is promising, as it is easier to separate it from the product than homogeneous ones. It was determined that the calcined grape snail ( Helix pomatia ) shells show good catalytic efficiency in rapeseed oil transesterification process with methanol. It was determined that the CaO concentration in calcined grape snail ( Helix pomatia ) shells was 97.74 ± 0.12%. Using the response surface methodology, the biodiesel production process was optimised. The influence of interaction of independent variables and optimal conditions for the synthesis of rapeseed oil methyl ester were determined: an alcohol to oil molar ratio of 10.6:1, a catalyst concentration of 5.7 wt % and a reaction duration of 7.8 h at a temperature of 64°C. The physical and chemical properties of produced biodiesel at optimal process conditions are presented, their compliance with the requirements of biodiesel standard EN 14214 are discussed. The produced biodiesel using snail shells which are food processing waste meets the requirements of the EN 14214 standard and can be used in diesel engines during the summer period. Earth and environmental sciences/Environmental sciences Physical sciences/Chemistry transesterification heterogeneous catalysis snail shells response surface methodology methylester biodiesel Figures Figure 1 Figure 2 1. Introduction Population growth leads to a high demand for energy and, at the same time, dependence on limited fossil energy resources [ 1 ], the use of which pollutes the environment and increases global warming. It is predicted that in 2040 global energy consumption will increase by 56% compared with 2010 level [ 2 ] In the transport sector, a large share of vehicles are those that use mineral diesel. Biodiesel is an alternative to conventional diesel. The advantages of biodiesel over diesel are better biodegradability, it has a higher combustion efficiency, and less harmful substances are released during combustion, such as aromatic hydrocarbons, etc. [ 3 , 4 ]. Another advantage is that biodiesel is miscible with mineral diesel in any ratio, so replacing at least part of mineral diesel with biodiesel reduces environmental pollution and increases energy independence on countries exporting oil or mineral fuels. It would also bring us closer to the Kyoto Protocol (1997) and the Paris Agreement (2015), which encourage the reduction of fossil fuel consumption and aim to implement one of the goals of the European Green Deal - reducing the negative impact to environment of transport. Biodiesel is obtained from renewable resources - oils or fats, by transesterifying it with alcohols and using catalysts to accelerate the process. Catalysts are divided into homogeneous and heterogeneous. Homogeneous catalysts such as NaOH or KOH are most often used in industrial biodiesel production due to their good catalytic activity and cheapness [ 5 ]. However, the disadvantage of homogeneous catalysts is the inevitable waste generated during the washing process, which cannot be reused, and most often during homogeneous reactions, several transesterification cycles are required to obtain high-quality biodiesel [ 6 ]. Acidic homogeneous (H 2 SO 4 , H 2 SO 3 , HCl) catalysts are most often used when the acidity of the oil is higher than 2%, but the acidic nature of these catalysts accelerates equipment corrosion, and they are also used once [ 7 ]. Multiple uses, better reaction rate and selectivity, easier catalyst separation from final product and low cost are the advantages of heterogeneous catalysts. Due to these factors, more and more attention is paid to the search for solid-phase catalysts. Immobilized lipases are environmentally friendly materials that can be used in biodiesel synthesis, but their disadvantages are that lipases work most efficiently at temperatures of 40–45 o C, at higher temperatures denaturation processes begin. And the transesterification process is most efficient when the temperature is close to the boiling point of alcohol [ 8 , 9 ]. What is more, transesterification is more efficient when excess alcohol is used, which can inactivate lipases [ 10 ]. As heterogeneous catalysts, alkali oxides, alkaline earth metal oxides are most often used. One of the oxides - CaO is poorly soluble in methanol, easily available and cheap, and is also stable for a long time when used in biodiesel production [ 11 ]. It is promising to extract CaO from natural waste sources, which are large amounts of calcium carbonate [ 12 ]. There are many food production wastes, most of which consist of calcium carbonate. In biodiesel synthesis, heterogeneous catalysts can be - oyster shells [ 13 ], crab shells [ 14 ], mussel shells [ 15 ], shrimp shells [ 16 ], eggshells [ 17 , 18 ]. Snails belong to the class Gastropoda and Phylum Mollusca. Every year, more and more snails are consumed worldwide. In 2014, the market was valued at approximately $ 12 billion, and the total consumption reached about 450,000 tons [ 19 ]. The value of the Lithuanian snail market in 2023 reached $ 3.7 million [ 20 ]. In Lithuania, grape snails grow in nature, they are collected, sold, and consumed. The development of the snail market is driven by the growing consumer interest in gourmet food, the recognition of the nutritional benefits of snails, and the increasing attention to sustainable food sources. After snails are consumed, the shells remain a waste, therefore research related to its use is relevant. The aim of this study was to optimize the transesterification process of rapeseed oil with methanol using response surface methodology (RSM) and calcined grape snail ( Helix pomatia ) shells as a heterogeneous catalyst. In order to assess the influence of three independent variables on the biodiesel yield, multiple regression and correlation analysis were applied. The interaction effect of three independent variables – alcohol to oil molar ratio, concentration of the catalyst and process duration – on the ester yield was evaluated. Furthermore, the optimal conditions were determined, under which the maximum ester yield meeting the requirements of the standard was obtained. 2. Materials and Methods 2.1 Preparation of the Catalyst Grape snails ( Helix pomatia ) were collected in Lithuania, Panevezys distr. Snail shells are a natural material consisting mainly of calcium carbonate. When calcium carbonate is heated, it decomposes into calcium oxide and carbon dioxide. Snail shells were prepared according to the studies conducted by Gaide and colleagues. Snails were calcined in a muffle furnace (AB UMEGA SNOL 8.2 /1100, Utena, Lithuania) for 5 hours at 850°C [ 21 ]. Before calcination, snail shells were crushed, sieved through a sieve, and a 0.315–0.1 mm fraction was used for the experiment. 2.2. Determination of calcium oxide in Snail Shells Crushed snail shells were dissolved in royal water (a mixture of nitric and hydrochloric acid in a 1:3 volume ratio). 25 ml of the test solution was poured into a conical flask, 60–70 ml of H 2 O and 10 ml of KOH (2 mol/l) were added. After mixing well, the indicator of calcium carboxylic acid was added to the flask, mixed and titrated with Trilon B. Color change from raspberry to blue was observed. Eq. (1) was used for the calculation of the CaO content: \(\:\:\:\:\:\:\:\:\text{C}\text{a}\text{O}\:=\frac{V\:\times\:\:\text{K}\:\times\:0.0014\:\times\:\:250}{\text{m}\:\times\:\:25}\:\times\:\:100\text{%}\) (1), where: V – volume of trilon B used for calcium titration, mL; m – mass of the snail shells sample, g; K – trilon B correction factor. 2.3. Oil transesterification process Rapeseed oil purchased from a local market was used for transesterification. It met the requirements for edible oil. The transesterification process was carried out in a laboratory reactor equipped with mixing and heating elements and a reflux condenser. Before adding methanol (Analytical pure Lach-Ner - REVISION) and the prepared catalyst, the oil was heated to the temperature required for the reaction, then the required amount of catalyst and alcohol was added. The experiments were performed at 64 o C, i.e. close to the boiling point of methanol, which is most often chosen for research, because increasing the temperature is associated with an increase in the reaction rate, but higher than the boiling point is undesirable due to possible alcohol losses and increased energy consumption. After the reaction, the resulting mixture was filtered through cellulose paper, washed once with H 3 PO 4 (5%) (10% of the volume of the mixture) and twice with distilled water (10% of the volume of the mixture), after which the aqueous part was separated. A rotary evaporator (COMPANY, MANUFACTURER) was used to separate the excess alcohol and water residues. 2.4. Determination of ester content The content of rapeseed oil methyl ester in the product obtained during the synthesis was analyzed by gas chromatography methods using a Clarus 500 chromatograph (Perkin Elmer) with flame ionization detector. The content of methyl ester up to 80% was determined according to the methodology given in the standard EN 14105. The analysis conditions for determining the content of partial (mono-, di-, triglyceride) glycerides were as follows: Restek MXT Biodiesel TG capillary column (14 m – 0.53 mm – 0, and 16 µm); initial thermostat temperature 50°C, held for 1 minute. Then the temperature was raised by 15°C/min to 180°C, then 7°C/min to 230°C and 30°C/min to 370°C, held for 5 minutes; detector temperature − 380°C; carrier gas - hydrogen, the flow rate of which was 4 ml/min. The ester yield (%) was calculated based on the determined amount of partial glycerides [ 22 ]. In the case of ester content of more than 80% in a final product, determination was done based on the requirements of the EN 14103 standard. The following conditions were used for the analysis: Alltech AT-FAME capillary column (30 m-0.25 mm-0.25 µm), the initial oven temperature was 210°C, held for 5 min, then at a rate of 20°C/min it was raised to 230°C and held for 12 min; the carrier gas (H 2 ) flow rate was 3 ml/min; the injector and detector temperature was 250°C. 2.5 Response surface analysis Optimization and statistical analysis of the transesterification process In order to optimize the transesterification process and determine the influence of the molar ratio of methanol to rapeseed oil (A), catalyst loading (B) and reaction duration (C) (Table 1 ) on the ester yield, a 3-factor experiment was performed using Central composite design (CCD). The CCD experiment consisted of 17 trials (Table 2 ). The ester yield (%) was used as a response indicator in the model. The obtained data were analyzed by variance (ANOVA) and graphical analysis using Design-Expert 13 (Stat-Ease, Minneapolis) software. The experimental data (Table 2 ) were analyzed using the response surface regression (RSREG) method of the Statistical Analysis System (SAS). This method is based on a second-order polynomial model (Eq. 3). The RSREG methodology includes canonical analysis to determine the stationary values of each factor. Based on the fitted model, response surface contour plots were constructed for each pair of factors under study, fixing the third factor at its calculated stationary value. To validate the model, an optimization procedure of the reaction conditions was performed using combinations of independent variables that were not included in the original experimental design. Table 1 Independent variables used in the Central composite design for the synthesis of rapeseed oil methyl ester Factors Name Units Low Actual High Actual A: Molar ratio of methanol to rapeseed oil mol/mol 5 15 B: Catalyst loading (from oil mass) wt% 4 10 C: Reaction duration h 4 10 Table 2 Central composite design matrix with three independent variables and experimental and predicted results. No. Alcohol to oil molar ratio, mol/mol Catalyst concentration (from oil mass), wt% Reaction duration, h Ester yield, % Experimental results Predicted results 1 10 7 7 96.94 96.37 2 5 4 4 18.22 16.86 3 15 10 10 99.81 100.16 4 10 7 7 99.15 100.27 5 5 10 10 29.54 28.75 6 15 10 10 28.95 30.56 7 3 7 7 45.64 48.39 8 10 2.8 2.8 67.25 70.79 9 5 10 10 70.33 70.67 10 10 7 7 97.8 96.37 11 10 11.2 11.2 81.99 80.50 12 15 4 4 39.21 37.87 13 15 4 4 98.4 98.18 14 10 7 7 27.78 28.71 15 10 7 7 96.49 96.37 16 17 7 7 84.44 83.74 17 5 4 4 52.11 49.49 The quadratic polynomial regression equation was used to estimate the model parameters and predict the response: \(\:Y=\:{\beta\:}_{0}+\:\sum\:_{i=1}^{3}{\beta\:}_{i}{X}_{i}\:+\:\sum\:_{i=1}^{3}{\beta\:}_{ii}{X}_{i}^{2}+\:\sum\:_{i=1}^{2}\:\sum\:_{j=i+1}^{3}{\beta\:}_{ij}{X}_{i}{X}_{j}\) (2), where: Y – the response (dependent variable); X i , X j – the independent variables; β 0 , β i , β ii bei β j , β ij – constant coefficients. 2.6. Studies of the physical and chemical properties of biodiesel The physical and chemical properties of obtained biodiesel were evaluated based on the requirements of the EN 14214 standard. 3. Results and Discussions 3.1. Concentration of calcium oxide in snail shells It was found that the CaO concentration in uncalcined snail shells ( Helix pomatia ) was 47.14 ± 0.22%, while after calcination at 850 o C for 5 h it reaches 97.74 ± 0.12%. A slightly lower CaO content was obtained in snail shells of Helix Aspersa Maxima calcined under the same conditions (91.69 ± 0.43%) [ 11 ]. Similar results were obtained by Laskar el al., where snail shells ( Pila spp .) were dried in an oven at 100 o C for 12 h before calcination (4 h at temperature 900 o C), and CaO content reached 98.017% [ 23 ]. Mohammed et al. obtained the optimal conditions for the preparation of snail shells at 900 o C and 3.5 h [ 24 ]. Trisupakitti et al. studied golden apple cherry snail shells ( Pomacea canaliculata ), they calcined crushed shells at 1050 o C for 2 h and determined 98.6% of CaO [ 25 ]. A lower CaO content of 70.113% was obtained by heating river snail shells at 800 o C for 4 h [ 26 ]. It is believed that the lower concentration of CaO was obtained because the calcination temperature was lower. However, Phewphong et al. investigated shells of golden apple snails ( Pomacea canaliculata ) and used a calcination temperature of 800 o C, it was obtained that CaO concentration reaches 100% in treated snail shells with acid before calcination and 95.05% of CaO in untreated snail shells [ 27 ]. Trisupakitti et al., investigated golden apple cherry snail shells and obtained CaO of 99.5%. However, before calcination deproteination was done (ground shell was agitated with 4%w/v NaOH at 60 o C for 1 h and then allowed to precipitate, the filtrate was washed with distilled water until the pH of the wash water was neutral, dried in an oven at 100 o C for 1 h, decolorized by boiling in acetone for 1 h, filtered and washed with methanol and dried at 100 o C for 1 h) [ 25 ]. Phewphong et al. [ 27 ] and Trisupakitti et al. [ 25 ] studies prove that treatment of snail shells before calcination leads to a 1–5% higher CaO concentration, nevertheless, additional reagents and energy costs are used during treatment stage. 3.2. Optimal Reaction Conditions Modeling and Determination Using Response Surface Methodology Response Surface Analysis It is known that the main parameters determining the efficiency of biodiesel production are the molar ratio of alcohol to oil (A; mol/mol), catalyst concentration (B; wt%) and reaction duration (C; h). In order to evaluate the interaction effects (the total effect of these factors), experiments were carried out by varying the physical parameters according to the experimental design (Table 2 ). Multiple regression analysis applied to the data in Table 2 allowed the experimental results obtained according to the full factorial central composition design to be approximated by a second-order polynomial Eq. (2). The resulting regression model describing the synthesis of rapeseed methyl ester is presented in Eq. (3), where the response variable (Y, ester yield; %) is expressed as the sum of the products of the independent variables and the regression coefficients. Y = -182.02 + 13.90A + 19B + 27.40C – 0.32AB + 0.46AC + 0,26BC – 0.62A 2 – 1.17B 2 – 1.81C 2 (3) where: Y – ester yield, %; A – alcohol to oil molar ratio, mol/mol; B – catalyst loading, wt%; C – reaction duration, h. Positive (+) coefficients indicate a positive correlation with the response variable, and negative (-) coefficients indicate a negative correlation. To assess the variance (ANOVA) and to check the adequacy of the empirical model, a statistical analysis of the model was performed. Table 3 summarizes the ANOVA results obtained after applying the second-order response surface model using the mean squares method. The significance of the coefficients of the response surface model, as defined in Eq. (4), was also assessed. The statistical significance of each coefficient was determined based on the P values (probabilities, Prob > F), which also indicate the strength of the interaction of each parameter. Based on the data in Table 3 , the P value of the model is less than 0.0001, which indicates a high statistical significance of the model for predicting response values and the adequacy of the derived model. The probability that such a high F value of the model would be random (due to noise or natural variability) is only 0.01%. The high F value of the model (F = 273.49) and the correspondingly low P value (P < 0.0001) confirm the high statistical significance of the constructed model. The "Lack of Fit" test assesses whether the selected model adequately describes the relationship between the independent variables and the response variable, or whether there is a systematic bias that the model misses. If the model imprecision is statistically significant (small P value), this would indicate that the model is inappropriate and does not describe the data well enough, possibly because the model was too simple or important factors were omitted. An assessment of the discrepancy between the residual errors and the net error (F value 18.25) showed that the model imprecision is not statistically significant (P = 0.0528 > 0.05). This result is desirable as it confirms that the selected second-order polynomial model is appropriate and adequately describes the experimental data, without significant systematic bias. The statistical significance of all model coefficients was determined by P values and is presented in Table 3 . Table 3 Result of experimental design matrix for ester yield Source of variation Sum of squares Degrees of freedom (df) Mean squares F value p-value Prob > F Model 14527.03 9 1614.11 273.49 < 0.0001 Significant A-molar ratio 1899.94 1 1899.94 321.92 < 0.0001 B-catalyst 143.28 1 143.28 24.28 0.0017 C-Duration 7786.11 1 7786.11 1319.26 < 0.0001 AB 184.22 1 184.22 31.21 0.0008 AC 383.23 1 383.23 64.93 < 0.0001 BC 43.11 1 43.11 7.30 0.0305 A 2 1742.11 1 1742.11 295.18 < 0.0001 B 2 814.71 1 814.71 138.04 < 0.0001 C 2 1927.91 1 1927.91 326.66 < 0.0001 Residual 41.31 7 5.90 Lack of Fit 40.43 5 8.09 18.25 0.0528 not significant Pure Error 0.8861 2 0.4430 Cor Total 14568.34 16 C.V. % = 3.64 R 2 = 0,9972 Adeq Precision = 44.764 R 2 Adj = 0.9935 R 2 Pred = 0.9781 A higher F value and a lower P value indicate that the corresponding parameters are significant. p-values "P > F" less than 0.05 mean that the model components are significant. In this model, A, B, C, AB, AC, BC, A 2 , B 2 and C 2 are statistically significant model components. A low coefficient of variation (CV) value (3.64%) indicates minimal data dispersion around the mean value, which indicates high experimental precision and model reliability. The coefficient of determination (R 2 ) defines the proportion of the variance of the response variable that is explained by the regression model. The range of R 2 values is from 0 to 1, where a value closer to 1 reflects a better fit of the model to the empirical data. Ideally, R 2 = 1 would mean complete explanation of the response variation by the model, while R 2 = 0 – complete failure of the model to explain the variation. The resulting R 2 value (0.9972) is extremely high, and indicates that the model explains 99.72% of the variation in the response variable, indicating an excellent fit of the model to the experimental data (Fig. 1 ). The adjusted coefficient of determination (R 2 Adj ) is a modification of R 2 that adjusts the indicator for the number of independent variables in the model. Since R 2 tends to increase artificially with increasing number of variables, even if the newly added variables are not statistically significant, R 2 Adj introduces a correction factor that re-analyses the addition of unnecessary variables. For this reason, R 2 Adj is considered a more reliable indicator of model fit, especially in models with a larger number of variables. For a good model, the value of R 2 Adj should be close to the value of R 2 . The obtained R 2 Adj value (0.9935) is extremely high and close to R 2 (0.9972), which confirms the model fit and indicates that the model is not overfitted with insignificant variables. A high R 2 Adj value reinforces the conclusion that the model is well-fitting, even considering the complexity of the model. The predicted coefficient of determination (R 2 Pred ) assesses the model's ability to predict response values for new, independent data. It is desirable that the R 2 Pred value be positive and close to the R 2 and R 2 Adj values. The obtained R 2 Pred value (0.9781) is high and close to R 2 and R 2 Adj , which indicates that the model has good predictive properties and can accurately predict response values for new data. The Adeq Precision value, reaching 44.764, shows a high signal-to-noise ratio, indicating that the model is statistically significant and reliable. This indicator allows us to conclude that the model is suitable for predicting response values and can be effectively used for optimizing reaction conditions. The high Adeq Precision value confirms the validity of the model and its value for further research. Figure 1 shows the accuracy of the predictive model, assessed by comparing the experimentally determined and model-predicted values of ester yield. The visual graphical analysis presented shows the good fit and high predictive power of the regression model. The arrangement of the data points, close to the line of perfect fit, confirms the excellent fit of the model to the experimental data and the accuracy of the predicted values. 3.3. Interaction of independent variables on ester yield Based on the results of the primary analysis, three-dimensional (3D) contour plots were constructed to visualize and identify the optimal conditions for the ester yield, as illustrated in Fig. 2 (A), (B), (C). Each plot analyses the dependencies between the process response (ester yield ((%)) and the independent variables - catalyst concentration, alcohol to oil molar ratio and reaction duration. Contour plots are constructed by fixing one independent variable at a stationary point and varying the remaining two independent variables on the X and Y axes to visually identify the conditions under which the response value is maximum. Figure 2 depicts the response surfaces for the ester yield, reflecting: Fig. 2 A. the interaction between alcohol to oil molar ratio and catalyst concentration; Fig. 2 B shows the interaction between alcohol to oil molar ratio and the reaction duration; Fig. 2 d shows the interaction between the catalyst loading and the reaction duration. The analysis of Fig. 2 A, where the reaction duration is fixed at 6.94 hours, shows the interaction effect of the alcohol to oil molar ratio and catalyst loading on the ester yield. The graph shows that the ester yield increases with increasing both the alcohol to oil molar ratio and the catalyst loading. This direct relationship between catalyst loading and ester yield is a fundamental property of heterogeneous catalysis, and the contour plots of the surface response methodology provide a detailed visual analysis of the efficiency of the snail shells CaO catalyst. The snail shells CaO catalyst acts as a solid material, and the catalytic reaction occurs on its surface. A higher catalyst loading in the reaction mixture means that a larger amount of solid catalyst particles is introduced into the system. These particles obtained after calcination are characterized by a porous structure and a large specific surface area [ 11 ]. The active catalytic sites responsible for the transesterification reaction (most often basic CaO surface sites, such as O 2 − ions) are located precisely on this surface. Therefore, increasing the catalyst loading proportionally increases the total surface area of the catalyst in the reaction mixture, and with it the total number of available active sites on which the reacting oil and alcohol molecules can adsorb and the transesterification reaction takes place. As a result, the reaction rate accelerates, and a larger portion of the oil is converted to ester during the same reaction time. Higher alcohol to oil molar ratio pushes the reaction equilibrium in the direction of ester formation according to Le Chatelier's principle, also increasing the probability of collision of the reactants with the catalyst [ 12 ]. The highest yield, exceeding 98%, are achieved at the highest tested alcohol amount and catalyst loading, confirming the synergistic effect of these parameters, and the shape of the contour lines in the graph highlights this interaction, consistent with trends reported in the scientific literature for heterogeneous catalysis. For example, Trisupakitti et al. [ 25 ] obtained a biodiesel yield of 95.2% with a golden apple snail shells catalyst using a 0.8 wt% catalyst loading and a 12:1 methanol to oil molar ratio, while Laskar et al. [ 23 ] reached a 98% ester yield with a Pila spp. snail shells catalyst using a 3 wt% catalyst loading and a 6:1 methanol to oil molar ratio, highlighting the potential of snail shells as a promising catalyst source. These quantitative values show a direct correlation between catalyst loading, alcohol to oil molar ratio, and ester yield, emphasizing the critical role of catalyst loading for an efficient transesterification process. The effect of the alcohol to oil molar ratio and the reaction duration on the ester yield, where the catalyst laoding is fixed at 4.24%, is given (Fig. 2 B). It can be seen that the ester yield increases in both cases, with increasing the alcohol to oil molar ratio and the reaction duration. The effect of reaction duration is particularly important in heterogeneous catalysis, where the reaction takes place on the catalyst surface. A longer reaction duration provides more time for molecules of the oil and alcohol to diffuse into the catalyst pores, adsorb on the active sites, and react, especially when the catalyst concentration is relatively low [ 14 ]. A higher alcohol to oil molar ratio, as in Fig. 2 A, further shifts the reaction equilibrium towards the formation of esters. The highest ester yield, exceeding 99%, are again achieved at the highest tested reaction duration values, emphasizing that the longer reaction duration compensates for the lower catalyst concentration, allowing to obtain high ester yield. The shape of the contour lines and the localization of the highest ester yield in the graph emphasize the synergistic effect of the parameters and are consistent with the trends described in the scientific literature for heterogeneous catalysis in biodiesel production. Kaewdaeng et al. [ 26 ] achieved 92.5% oil conversion to ester after a 1-hour of reaction with a river snail shells catalyst, while Birla et al. [ 28 ] obtained the optimal reaction duration of 7 hours, achieving 99.58% conversion with a snail shell catalyst. It can be noticed that the reaction duration is one of the essential parameters to achieve a high ester yield, especially when using heterogeneous catalysts. The effect of catalyst loading and reaction duration, when the alcohol to oil molar ratio is fixed at 8.4 mol/mol on the ester yield is presented in Fig. 2 C. It can be seen that the ester yield increases with increasing both catalyst loading and reaction duration, and optimal conditions are achieved by combining these parameters. When the alcohol content is fixed, catalyst loading and reaction duration become the main factors determining the ester yield. Higher catalyst loading increases the number of active sites, while longer reaction duration provides sufficient time for the reaction to proceed to completion, especially when the alcohol content is limited [ 11 ]. The highest ester yield, exceeding 98%, are again achieved at the highest tested catalyst loading, close to 9–10 wt%, and reaction duration reaching 9–10 hours, confirming the synergistic effect of these parameters. For example, Kaewdaeng et al. investigated the use of a river snail shells catalyst for synthesis of fatty acid methyl ester [ 26 ]. The optimal catalyst loading of 3 wt% and a reaction time of 1 hour, allowed to achieve 92.5% of fatty acid methyl ester yield, and subsequent optimization tests showed that the ester yield can reach up to 98.19%. Karkal et al. (2023) optimized the process with a crab shell as a heterogeneous catalyst, achieving a biodiesel yield of 88.56 wt% with a catalyst loading of 3 wt% and a reaction duration of 60 minutes, demonstrating efficiency even in short reaction duration [ 14 ]. Alsabi et al. (2024) achieved an extremely high, 99.36%, fatty acid methyl ester yield with a mussel shell as a catalyst, optimizing the methanol to oil molar ratio to 18:1, a catalyst loading of 6 wt% and a reaction duration of 6 hours [ 15 ]. Laskar et al. (2018) obtained biodiesel yield of 98%, while using snail shells a catalyst (3 wt%), a reaction took 7 hours, and the methanol to oil molar ratio was 6:1 [ 23 ]. 3.4. Optimization of rapeseed oil methyl ester synthesis process The influence of three independent variables on the rapeseed oil methyl ester yield was evaluated and the process was optimized. The optimal conditions were determined (process temperature is 64°C): methanol to oil molar ratio 10.6:1, snail shells loading 5.7 wt%, reaction duration 7.8 h. The predicted ester yield was 99.81 wt%, and the experimentally determined ester content was slightly lower at 98.80 ± 0.30 wt%, while the obtained experimental ester content was 97.15 ± 0.25 wt%, however it meets the requirements of the standard REN 14214. The data are presented in Table 4 . Table 4 Optimum parameters for rapeseed oil methyl ester production, predicted and experimental ester yield Methanol-to-oil molar ratio, mol/mol Snail shells concentration, wt% (from oil mass) Reaction duration, h Predicted ester yield, wt% Experimental ester yield, wt% Experimental ester content, wt% 10.6:1 5.7 7.8 99.81 98.80 ± 0.30 97.15 ± 0.25 Table 5 presents comparative results of studies by scientists who analyzed the process of transesterification of oil with methanol using snail shells as a catalyst. Different oils were used. Rapeseed oil was used in this research and Gaide et al. [ 11 ] study, soybean oil was used by Laskar et al., [ 23 ] Das et. al. [ 29 ] and Ouafi et al. [ 30 ]. Transesterification of palm oil was studied by Viriya-empikul et al. [ 31 ] Phewphong et al. [ 27 ], Birla et al. [ 28 ]. Kaewdaeng et al. [ 26 ], Mohammed et al. [ 24 ] produced fatty acid methyl ester from waste frying/ cooking oil. The obtained ester yield ranged from 85.5 to 98.15 wt%. Many researchers have performed the synthesis of methyl esters at 60–65 o C, in this research, 64 o C was used. It is believed that temperatures close to the boiling point of methanol (64.7 o C) were chosen, as it is known that transesterification reactions are most efficient under temperatures close to alcohols boiling. Only Laskar et al. synthesized biodiesel at a low temperature of 28 o C and obtained ester yield of 98 wt% [ 23 ]. For the transesterification reaction to proceed a minimum methanol to oil molar ratio of 3:1 is required, all researchers (Table 5 ) used a excess of methanol to oil molar ratio from 21:5 (4.2:1) [ 24 ] to 12:1 [ 25 , 27 , 30 , 31 ]. In this study, the optimal methanol to oil molar ratio was found to be 10.6:1. Table 5 Comparison of optimum condition for biodiesel production when different snail shells as heterogeneous catalyst is used Oil Snail Temperature, °C Snail shells amount, wt% Reaction duration, h Methanol-to-oil molar ratio, mol/mol Ester yield, content*wt% Reference Waste frying oil Snail from the banks of the river Ganges in Varanasi, India 60 2 8 6.03:1 87.28 [ 28 ] Palm olein oil Golden apple snail 60 10 2 12:1 93.2 [ 31 ] Used cooking oil River snail 65 3 1 9:1 92.5 [ 26 ] Palm oil Golden apple snail 65 0.8 6 12:1 92.5 [ 25 ] Soybean oil Pila spp 28 3 7 6:1 98 [ 23 ] Palm oil Golden apple snail Pomacea canaliculata (calcination and acid treatment process.) 65 5 2,5 12:1 87.5 [ 27 ] Waste cooking oil 65 5 2.5 12:1 85.5 Waste cooking oil Snail from Iraq 62.2 9.8 4.8 21:5 95* [ 24 ] Rapessed oil Helix Aspersa Maxima 64 6.06 8 7.5:1 98.15* [ 11 ] Soybean oil Snaill “ chengkawl sawl ” 70 6,0 3 8:1 96.1 [ 29 ] Soybean oil Snail shells powder after the copper Cu(II) removal 60 2 1 12:1 93 [ 30 ] Rapessed oil Helix pomatia 64 5.7 7.8 10.6:1 98.80 97.15* This work *Ester content Very different data were obtained by other researchers when determining the optimal amount of catalyst and process duration. Trisupakitti et al (2018) obtained 92.5 wt% of ester yield in 6 h, while using 0.8 wt% of Golden apple snail shells [ 25 ]. While the same snails were used by Viriya-empikul et al. [ 31 ] however the optimal catalyst amount was 10 wt%, although the process duration was 2 h and a similar ester yield of 93.2 wt% was obtained. In this study, optimum reaction duration was 7.8 h and 5.7 wt% of Helix pomatia snail shells. Although in this study optimized process conditions were similar to the optimal conditions described in the literature, significantly higher ester yield (98.80 wt%) was achieved and ester content (97.15 wt%), exceeding the requirements of the EN 14214 standard. 3.5. Physical and chemical properties of obtained rapeseed oil methyl ester Biofuels can be used in the transport sector if they meet the requirements of the standard EN 14214. The compliance of physical and chemical properties of the produced methyl ester and their comparison with the requirements of the standard are presented in Table 6 . Table 6 The physical and chemical properties of rapeseed oil methyl ester Parameter Units EN 14214 requirements Rapeseed oil methyl ester (RME) Ester content % min 96.5 97.15 ± 0.25 Density at 15°C kgm − 3 min 860 max 900 885 ± 2.00 Viscosity at 40°C mm 2 s − 1 min 3.50 max 5.00 4.70 ± 0.10 Acid value mg KOHg − 1 max 0.5 0.22 ± 0.05 Moisture content mgkg − 1 max 500 305 ± 2.10 Iodine value g J 2 100 − 1 g − 1 max 120 115 ± 0.20 Linolenic acid methyl ester content % max 12.0 8.86 ± 0.10 Monoglyceride content % max 0.8 0.27 ± 0.03 Diglyceride content % max 0.2 0.05 ± 0.02 Triglyceride content % max 0.2 0.06 ± 0.01 Free glycerol content % max 0.02 0.007 ± 0.00 Total glycerol content % max 0.25 0.19 ± 0.10 Methanol content % max 0.2 0.10 ± 0.05 Phosphorus content, ppm 10 7.5 ± 0.10 Metals II (Ca/Mg) mg kg − 1 max 5 3.5 ± 0.25 Oxidation stability 110°C H min 8 8.5 ± 0.15 Cetane number - min 51 52 ± 0.20 Cold filter plugging point °C -5°C (in summer) -32°C (in winter) -9.8 ± 0.04 The ester content shows how many fatty acid methyl esters were formed from triglycerides. The ester content of the obtained biodiesel 97.15 ± 0.25 wt% meets the requirements of the standard (not less than 96.5%). The density of biodiesel is higher (885 ± 2.00 kgm - 3) than that of mineral diesel and meets the requirements of the standard (860–900 kgm -3 ) (at 15°C). Viscosity affects the fuel supply and combustion process. It should be 3.5-5.0 mm 2 s -1 (at 40°C), obtained value is 4.70 ± 0.10 mm 2 s -1 . Acid value in the European standard max 0.5 mg KOHg -1 . If biodiesel contains a higher number of acids, engine corrosion and sediment formation may occur, the resulting RME acid value is 0.22 ± 0.05 mg KOHg -1 . Water in biodiesel can cause microbiological processes, during which the sludge formed can clog filters. Moisture content must be max 500 mgkg -1 , in this study the RME moisture content obtained is 305 ± 2.10 mgkg -1 . Iodine value and linolenic acid methyl ester content depend on the fatty acid composition of the oils or fats used, it is determined that if biodiesel consists of a large amount of mono- and polyunsaturated acids, it polymerizes when heated and sediment is formed. Iodine value should be max 120 g J 2 100 -1 g -1 , obtained value – 115 ± 0.20 g J 2 100 -1 g -1 , linolenic acid methyl ester content should be max 12%, obtained 8.86 ± 0.10%. Monoglyceride, diglyceride, triglyceride, free and total glycerol content should be no less than 0.8%, 0.2%, 0.2%, 0.02% and 0.25%, obtained values are: 0.27 ± 0.03%, 0.05 ± 0.02%, 0.06 ± 0.01%, 0.007% and 0.19 ± 0.10% respectively. If these indicators are exceeded, sediment may form, and they also directly affect the increase in viscosity. Excess methanol is used for transesterification, so its removal is a very important stage of the biodiesel purification process. Methanol content should not exceed 0.2%, in the resulting biodiesel – 0.10 ± 0.05%. Another indicator that depends on the oil used is the phosphorus content. Phosphorus in esters may remain due to phospholipids contained in the raw material. Phosphorus content is limited to 10 ppm, determined value is 7.5 ± 0.10 ppm. The content of alkali metals must not exceed 5 mgkg -1 , obtained 3.5 ± 0.25 mgkg -1 . Since snail shells calcined to CaO were used as catalysts in this study, it is very important that the biodiesel is purified well, and no calcium remains. It is important that the fuel maintains the required properties during storage and transportation, as oxidation processes occur when it comes into contact with oxygen, and the properties of the fuel change. Oxidation stability, must be min 8 h at 110°C, obtained 8.5 ± 0.15 h. Cetane number determines combustion quality, according to the standard requirements min 51, obtained 52 ± 0.20. Low-temperature properties are very important to use the fuel not only in summer, but also in the cold period. In different countries, depending on climatic conditions, different requirements apply for cold filter plugging point. In this study, the RME cold filter plugging point obtained is -9.8 ± 0.04°C. The cold filter plugging point of fuels used in the summer period is min − 5°C in Lithuania The produced biodiesel meets the requirements of the EN 14214 standard and can be used in diesel engines during the summer period. Conclusions Calcium oxide is a suitable catalyst for biodiesel synthesis. CaO concentration was 97.74 ± 0.12% in calcined for 4 hours at 850°C grape snail shells ( Helix pomatia ). Transesterification studies were performed by varying three independent variables (methanol to oil molar ratio, loading of catalyst and reaction duration) in order to determine their influence on the efficiency of the transesterification process and to select optimal conditions. The studies were performed at a temperature of 64 o C. The optimal conditions for the synthesis of rapeseed oil methyl ester were determined by using the response surface methodology: alcohol to oil molar ratio 10.6:1, loading of catalyst 5.7 wt % and process duration 7.8 h. Under the determined optimal conditions the ester yield reached 97.15 wt %. The produced biodiesel meets the requirements of the EN 14214 standard and can be used in diesel engines during the summer period. Declarations Author Contributions Eglė Sendžikienė: Conceptualization; Data curation; Formal analysis; Methodology; Funding acquisition; Resources; Validation; Project administration; Visualization; Supervision; Roles/Writing - original draft; and Writing - review & editing Gediminas Gokas: Investigation; Software. Ieva Gaidė: Data curation; Investigation; Writing – original draft. Milda Gumbytė: Data curation; Formal analysis; Investigation; Methodology; Software; Visualization; Roles/Writing - original draft. Kiril Kazancev: Investigation. Violeta Makarevičienė : Conceptualization; Formal analysis; Validation; Supervision; Roles/Writing - original draft; and Writing - review & editing. Funding / Acknowledgements. This project has received funding from the Ministry of Education, Science and Sports of the Republic of Lithuania and Research Council of Lithuania (LMTLT) under the Program ‘University Excellence Initiative’ Project ‘Development of the Bioeconomy Research Center of Excellence’ (BioTEC), agreement No S-A-UEI-23-14. Declaration of interests We have nothing to declare. Data availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Aghbashlo, M. et al. Machine learning technology in biodiesel research: a review. Prog Energy Combust. Sci. 85 , 100904. https://doi.org/10.1016/j.pecs.2021.100904 (2021). CEEC the future. https://www.ceecthefuture.org/resources/world-energy-use-to-rise-by-56-percent-driven-by-growth-in-the-developing-world Outili, N., Kerras, H., Nekkab, C., Merouani, R. & Meniai, A. H. Biodiesel production optimization from waste cooking oil using green chemistry metrics. Renew. Energy . 145 , 2575–2586. https://doi.org/10.1016/j.renene.2019.07.152 (2020). Gaide, I., Grigas, A., Makareviciene, V. & Sendzikiene, E. Life cycle assessment and biodegradability of biodiesel produced using different alcohols and heterogeneous catalysts. Green. Chem. Lett. Rev. 17 (1), 2394503. https://doi.org/10.1080/17518253.2024.2394503 (2024). Mandari, V. & Devarai, S. K. Biodiesel Production Using Homogeneous, Heterogeneous, and Enzyme Catalysts via Transesterification and Esterification Reactions: a Critical Review. Bioenerg Res. 15 , 935–961. https://doi.org/10.1007/s12155-021-10333-w (2022). Karčauskiene, D. et al. False flax ( Camelina sativa L .) as an alternative source for biodiesel production Zemdirbyste , 101 (2), 161–168 (2014). Mukhtar, A. S. et al. Current status and challenges in the heterogeneous catalysis for biodiesel production. Renew. Sustain. Energy Rev. 157 , 112012, 1364–0321. https://doi.org/10.1016/j.rser.2021.112012 (2022). Zhao, X., Qi, F., Yuan, C., Du, W. & Liu, D. Lipase-catalyzed process for biodiesel production: Enzyme immobilization, process simulation and optimization. Renew. Sustain. Energy Rev. 44 , 182–197. https://doi.org/10.1016/j.rser.2014.12.021 (2015). Xia, S., Lin, J., Sayanjali, S., Shen, C. & Cheong, L. Z. Lipase-catalyzed production of biodiesel: a critical review on feedstock, enzyme carrier and process factors. Biofuels Bioprod. Biorefin . 18 (1), 291–309. https://doi.org/10.1002/bbb.2561 (2024). Gumbytė, M., Makareviciene, V. & Sendzikiene, E. Enzymatic Transesterification of Atlantic Salmon (Salmo salar) Oil with Isoamyl Alcohol Materials . 16 (3) 185. (2023). https://doi.org/10.3390/ma16031185 Gaide, I., Makareviciene, V., Sendzikiene, E. & Kazancev, K. Snail Shells as a Heterogeneous Catalyst for Biodiesel Fuel Production. Processes 11 (1) 260. (2023). https://doi.org/10.3390/pr11010260 Mazaheri, H. H. C. et al. An Overview of Biodiesel Production via Calcium Oxide Based Catalysts: Current State and Perspective. Energies 14 (13), 3950. (2021). https://doi.org/10.3390/en14133950 De la Cruz-De, M. et al. Using discarded oyster shells to obtain biodiesel. Agro Productividad . https://doi.org/10.32854/agrop.v15i1.2019 (2022). Karkal, S. S., Rathod, D. R., Jamadar, A. S., Shivaramu, M. S. & Kudre, T. G. Production optimization, scale-up, and characterization of biodiesel from marine fishmeal plant oil using Portunus sanguinolentus crab shell derived heterogeneous catalyst. Biocatal. Agric. Biotechnol. 47 102571.https://doi.org/10.1016/j.bcab.2022.102571 (2023). Alsabi, H. A. et al. From Waste to Catalyst: Transforming Mussel Shells into a Green Solution for Biodiesel Production from Jatropha curcas Oil. Catalysts 14 (1) 59. (2024). https://doi.org/10.3390/catal14010059 Karkal, S. S., Rathod, D. R., Jamadar, A. S., Shivaramu, M. S. & Kudre, T. G. Exploitation of freshwater fish waste as feedstock and Fenneropeneus indicus shrimp shell as catalyst source for biodiesel production. Biofuels 15 (1), 1–15 (2023). Gaide, I., Makareviciene, V., Sendzikiene, E. & Gumbytė, M. Rapeseed Oil Transesterification Using 1-Butanol and Eggshell as a Catalyst. Catalysts 13 (2), 302. https://doi.org/10.3390/catal13020302 (2023). Gaide, I., Makareviciene, V. & Sendzikiene, E. Effectiveness of Eggshells as Natural Heterogeneous Catalysts for Transesterification of Rapeseed Oil with Methanol. Catalysts 12, 246. (2022). https://doi.org/10.3390/catal12030246 https:// touchstonesnailfranchise.com/snail-market/?utm_source (see 2025 02 25). Indexbox Lithuania -. Snails (Except Sea Snails) - Market Analysis, Forecast, Size, Trends and Insights Please mention the Source: https://www.indexbox.io/store/lithuania-snails-except-sea-snails-market-analysis-forecast-size-trends-and-insights/?utm_source Gaide, I., Makareviciene, V., Sendzikiene, E. & Kazancev, K. Natural Rocks–Heterogeneous Catalysts for Oil Transesterification in Biodiesel Synthesis. Catalysts 11(3) 384. (2021). https://doi.org/10.3390/catal11030384 Bailer, J. et al. Handbook of analytical methods for fatty acid methyl esters used as diesel fuel substitutes. (ed. Fichte) 36–38 Vienna: Research Institute for Chemistry and Technology of Petroleum Products, University of Technology, (1994). Laskar, I. B. et al. Waste snail shell derived heterogeneous catalyst for biodiesel production by the transesterification of soybean oil. RSC Adv. 8 , 20131. https://doi.org/10.1039/C8RA02397B (2018). Mohammed, K., Alkhafaje, Z. A. & Rashid, I. M. Heterogeneously catalyzed transesterification reaction using waste snail shell for biodiesel production. Heliyon 9 (6), e17094. https://doi.org/10.1016/j.heliyon.2023.e17094 (2023). Trisupakitti, S., Ketwong, C., Senajuk, W., Phukapak, C. & Wiriyaumpaiwong, S. Golden apple cherry snail shell as catalyst for heterogeneous transesterification of biodiesel. Braz J. Chem. Eng. 35 , 1283–1291 (2018). Kaewdaeng, S., Sintuya, P. & Nironsin R.Biodiesel production using calcium oxide from river snail shell ash as catalyst. Energy Procedia . 138 , 937–942 (2017). Phewphong, S. et al. Biodiesel production process catalyzed by acid-treated golden apple snail shells (Pomacea canaliculata)-derived CaO as a high-performance and green catalyst. Eng. Technol. Appl. Sci. Res. 49 (1), 36–46 (2021). https://ph01.tci-thaijo.org/index.php/easr/article/view/243515 Birla, A., Singh, B., Upadhyay, S. N. & Sharma, Y. C. Kinetics studies of synthesis of biodiesel from waste frying oil using a heterogeneous catalyst derived from snail shell. Bioresour Technol. 106 , 95–100 (2012). Das, S., Anal, J. M. H., Kalita, P., Saikia, L. & Rokhum, S. L. Process Optimization of Biodiesel Production Using Waste Snail Shell as a Highly Active Nanocatalyst. Int. J. Energy Res. 1 , 6676844. https://doi.org/10.1155/2023/6676844 (2023). Ouafi, R. et al. Waste snail shells-derived mixed oxide catalyst for efficient transesterification of vegetable oil: Towards sustainable biodiesel production. Mater. Today Commun. 39 , 109128. https://doi.org/10.1016/j.mtcomm.2024.109128 (2024). Viriya-empikul, N., Krasae, P., Nualpaeng, W., Yoosuk, B. & Faungnawakij, K. Biodiesel production over Ca-based solid catalysts derived from industrial wastes. Fuel 92 , 239–244 (2012). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6811110","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":472092972,"identity":"4b64f97b-4a5a-4f09-9dc9-f41e1d4eeaaa","order_by":0,"name":"Eglė Sendžikienė","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIie3Rv0sDMRTA8RcOdDNrbqn/wpOD4iD6ryQUOopQkA6CdwTiUnSto//BidA54UG7HHTN4FARnG/scKhnXfzBpY4O+S4P8vjwhgDEYv+yJP+clmmQ7eQACHAWIuwHSfMPgvgXAslmot1COL8rVtAcne4tSeNq/NjL/GAmAJtOkk6fNDIzHKXWaSmrl6zvh+cidAW9M4LlpEpXaKsMqVlV9YPkxLurNTRvqiTWkle6fJhsIcgLA7BjVTlnWqqcJO5OwkR4poUyA3VbMY1yTgfThRkdSsw6Cb8hV9fNsbpeLp7T9QXtc53c+3rc6yQgJGx+8Hu/X76esaFtLBaLxdreAWIdXUga+r+6AAAAAElFTkSuQmCC","orcid":"","institution":"Vytautas Magnus University","correspondingAuthor":true,"prefix":"","firstName":"Eglė","middleName":"","lastName":"Sendžikienė","suffix":""},{"id":472092973,"identity":"47146e83-06c4-4c5e-a8f1-75fa0da67449","order_by":1,"name":"Gediminas Gokas","email":"","orcid":"","institution":"Vytautas Magnus University","correspondingAuthor":false,"prefix":"","firstName":"Gediminas","middleName":"","lastName":"Gokas","suffix":""},{"id":472092974,"identity":"8a346181-0d9c-43d9-aa9e-ac9132177718","order_by":2,"name":"Ieva Gaidė","email":"","orcid":"","institution":"Vytautas Magnus University","correspondingAuthor":false,"prefix":"","firstName":"Ieva","middleName":"","lastName":"Gaidė","suffix":""},{"id":472092975,"identity":"5da744fc-2cbb-49a5-8dd6-793f3f58fbef","order_by":3,"name":"Milda Gumbytė","email":"","orcid":"","institution":"Vytautas Magnus University","correspondingAuthor":false,"prefix":"","firstName":"Milda","middleName":"","lastName":"Gumbytė","suffix":""},{"id":472092976,"identity":"6c892aaf-ec74-4e2e-bd9e-338c70ecf6a3","order_by":4,"name":"Kiril Kazancev","email":"","orcid":"","institution":"Vytautas Magnus University","correspondingAuthor":false,"prefix":"","firstName":"Kiril","middleName":"","lastName":"Kazancev","suffix":""},{"id":472092977,"identity":"9c112fc4-70c9-42a1-87b5-dd3cd6f68a38","order_by":5,"name":"Violeta Makarevičienė","email":"","orcid":"","institution":"Vytautas Magnus University","correspondingAuthor":false,"prefix":"","firstName":"Violeta","middleName":"","lastName":"Makarevičienė","suffix":""}],"badges":[],"createdAt":"2025-06-03 12:08:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6811110/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6811110/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84862349,"identity":"c8a1dad9-bb03-4478-b570-9d392e2536ca","added_by":"auto","created_at":"2025-06-18 07:18:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":20557,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of actual and predicted ester yield data\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6811110/v1/5682245ea1a5631a19fafc33.png"},{"id":84862350,"identity":"3e7ac50c-7f4e-44a5-90bc-6fe66f2e0e46","added_by":"auto","created_at":"2025-06-18 07:18:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":365521,"visible":true,"origin":"","legend":"\u003cp\u003eDependence of the ester yield on two independent variables: a) alcohol to oil molar ratio and catalyst loading; b) alcohol to oil molar ratio and reaction duration; c) catalyst loading and reaction duration\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6811110/v1/d12edaa2a04cde8bfbb71913.png"},{"id":89464129,"identity":"54dd5113-3a86-4575-b030-75fe023bec0c","added_by":"auto","created_at":"2025-08-20 08:17:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1764066,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6811110/v1/3c9321d5-62ef-4e74-8cae-844f2c975516.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eSnail (\u003cem\u003eHelix pomatia\u003c/em\u003e) Shells as a Catalyst for Biodiesel Synthesis\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePopulation growth leads to a high demand for energy and, at the same time, dependence on limited fossil energy resources [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], the use of which pollutes the environment and increases global warming. It is predicted that in 2040 global energy consumption will increase by 56% compared with 2010 level [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] In the transport sector, a large share of vehicles are those that use mineral diesel.\u003c/p\u003e \u003cp\u003eBiodiesel is an alternative to conventional diesel. The advantages of biodiesel over diesel are better biodegradability, it has a higher combustion efficiency, and less harmful substances are released during combustion, such as aromatic hydrocarbons, etc. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Another advantage is that biodiesel is miscible with mineral diesel in any ratio, so replacing at least part of mineral diesel with biodiesel reduces environmental pollution and increases energy independence on countries exporting oil or mineral fuels. It would also bring us closer to the Kyoto Protocol (1997) and the Paris Agreement (2015), which encourage the reduction of fossil fuel consumption and aim to implement one of the goals of the European Green Deal - reducing the negative impact to environment of transport.\u003c/p\u003e \u003cp\u003eBiodiesel is obtained from renewable resources - oils or fats, by transesterifying it with alcohols and using catalysts to accelerate the process. Catalysts are divided into homogeneous and heterogeneous. Homogeneous catalysts such as NaOH or KOH are most often used in industrial biodiesel production due to their good catalytic activity and cheapness [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, the disadvantage of homogeneous catalysts is the inevitable waste generated during the washing process, which cannot be reused, and most often during homogeneous reactions, several transesterification cycles are required to obtain high-quality biodiesel [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Acidic homogeneous (H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e, H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e3\u003c/sub\u003e, HCl) catalysts are most often used when the acidity of the oil is higher than 2%, but the acidic nature of these catalysts accelerates equipment corrosion, and they are also used once [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMultiple uses, better reaction rate and selectivity, easier catalyst separation from final product and low cost are the advantages of heterogeneous catalysts. Due to these factors, more and more attention is paid to the search for solid-phase catalysts. Immobilized lipases are environmentally friendly materials that can be used in biodiesel synthesis, but their disadvantages are that lipases work most efficiently at temperatures of 40\u0026ndash;45 \u003csup\u003eo\u003c/sup\u003eC, at higher temperatures denaturation processes begin. And the transesterification process is most efficient when the temperature is close to the boiling point of alcohol [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. What is more, transesterification is more efficient when excess alcohol is used, which can inactivate lipases [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. As heterogeneous catalysts, alkali oxides, alkaline earth metal oxides are most often used. One of the oxides - CaO is poorly soluble in methanol, easily available and cheap, and is also stable for a long time when used in biodiesel production [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. It is promising to extract CaO from natural waste sources, which are large amounts of calcium carbonate [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. There are many food production wastes, most of which consist of calcium carbonate. In biodiesel synthesis, heterogeneous catalysts can be - oyster shells [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], crab shells [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], mussel shells [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], shrimp shells [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], eggshells [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e Snails belong to the class Gastropoda and Phylum Mollusca. Every year, more and more snails are consumed worldwide. In 2014, the market was valued at approximately \u003cspan\u003e$\u003c/span\u003e12\u0026nbsp;billion, and the total consumption reached about 450,000 tons [ \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e ]. The value of the Lithuanian snail market in 2023 reached \u003cspan\u003e$\u003c/span\u003e3.7\u0026nbsp;million [ \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e ]. In Lithuania, grape snails grow in nature, they are collected, sold, and consumed. The development of the snail market is driven by the growing consumer interest in gourmet food, the recognition of the nutritional benefits of snails, and the increasing attention to sustainable food sources. After snails are consumed, the shells remain a waste, therefore research related to its use is relevant. \u003c/p\u003e \u003cp\u003eThe aim of this study was to optimize the transesterification process of rapeseed oil with methanol using response surface methodology (RSM) and calcined grape snail (\u003cem\u003eHelix pomatia\u003c/em\u003e) shells as a heterogeneous catalyst. In order to assess the influence of three independent variables on the biodiesel yield, multiple regression and correlation analysis were applied. The interaction effect of three independent variables \u0026ndash; alcohol to oil molar ratio, concentration of the catalyst and process duration \u0026ndash; on the ester yield was evaluated. Furthermore, the optimal conditions were determined, under which the maximum ester yield meeting the requirements of the standard was obtained.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Preparation of the Catalyst\u003c/h2\u003e\n \u003cp\u003eGrape snails (\u003cem\u003eHelix pomatia\u003c/em\u003e) were collected in Lithuania, Panevezys distr. Snail shells are a natural material consisting mainly of calcium carbonate. When calcium carbonate is heated, it decomposes into calcium oxide and carbon dioxide. Snail shells were prepared according to the studies conducted by Gaide and colleagues. Snails were calcined in a muffle furnace (AB UMEGA SNOL 8.2 /1100, Utena, Lithuania) for 5 hours at 850\u0026deg;C [\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e]. Before calcination, snail shells were crushed, sieved through a sieve, and a 0.315\u0026ndash;0.1 mm fraction was used for the experiment.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2. Determination of calcium oxide in Snail Shells\u003c/h2\u003e\n \u003cp\u003eCrushed snail shells were dissolved in royal water (a mixture of nitric and hydrochloric acid in a 1:3 volume ratio). 25 ml of the test solution was poured into a conical flask, 60\u0026ndash;70 ml of H\u003csub\u003e2\u003c/sub\u003eO and 10 ml of KOH (2 mol/l) were added. After mixing well, the indicator of calcium carboxylic acid was added to the flask, mixed and titrated with Trilon B. Color change from raspberry to blue was observed. Eq. (1) was used for the calculation of the CaO content:\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:\\:\\:\\:\\:\\:\\:\\text{C}\\text{a}\\text{O}\\:=\\frac{V\\:\\times\\:\\:\\text{K}\\:\\times\\:0.0014\\:\\times\\:\\:250}{\\text{m}\\:\\times\\:\\:25}\\:\\times\\:\\:100\\text{%}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e(1),\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003ewhere:\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eV \u0026ndash; volume of trilon B used for calcium titration, mL;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003em \u0026ndash; mass of the snail shells sample, g;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\"\u003eK \u0026ndash; trilon B correction factor.\u003cbr\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Oil transesterification process\u003c/h2\u003e\u003cp\u003eRapeseed oil purchased from a local market was used for transesterification. It met the requirements for edible oil. The transesterification process was carried out in a laboratory reactor equipped with mixing and heating elements and a reflux condenser.\u003c/p\u003e\u003cp\u003eBefore adding methanol (Analytical pure Lach-Ner - REVISION) and the prepared catalyst, the oil was heated to the temperature required for the reaction, then the required amount of catalyst and alcohol was added. The experiments were performed at 64 \u003csup\u003eo\u003c/sup\u003eC, i.e. close to the boiling point of methanol, which is most often chosen for research, because increasing the temperature is associated with an increase in the reaction rate, but higher than the boiling point is undesirable due to possible alcohol losses and increased energy consumption.\u003c/p\u003e\u003cp\u003eAfter the reaction, the resulting mixture was filtered through cellulose paper, washed once with H\u003csub\u003e3\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e (5%) (10% of the volume of the mixture) and twice with distilled water (10% of the volume of the mixture), after which the aqueous part was separated. A rotary evaporator (COMPANY, MANUFACTURER) was used to separate the excess alcohol and water residues.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e\u003cem\u003e2.4. Determination of ester content\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eThe content of rapeseed oil methyl ester in the product obtained during the synthesis was analyzed by gas chromatography methods using a Clarus 500 chromatograph (Perkin Elmer) with flame ionization detector. The content of methyl ester up to 80% was determined according to the methodology given in the standard EN 14105. The analysis conditions for determining the content of partial (mono-, di-, triglyceride) glycerides were as follows: Restek MXT Biodiesel TG capillary column (14 m \u0026ndash; 0.53 mm \u0026ndash; 0, and 16 \u0026micro;m); initial thermostat temperature 50\u0026deg;C, held for 1 minute. Then the temperature was raised by 15\u0026deg;C/min to 180\u0026deg;C, then 7\u0026deg;C/min to 230\u0026deg;C and 30\u0026deg;C/min to 370\u0026deg;C, held for 5 minutes; detector temperature \u0026minus;\u0026thinsp;380\u0026deg;C; carrier gas - hydrogen, the flow rate of which was 4 ml/min. The ester yield (%) was calculated based on the determined amount of partial glycerides [\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the case of ester content of more than 80% in a final product, determination was done based on the requirements of the EN 14103 standard. The following conditions were used for the analysis: Alltech AT-FAME capillary column (30 m-0.25 mm-0.25 \u0026micro;m), the initial oven temperature was 210\u0026deg;C, held for 5 min, then at a rate of 20\u0026deg;C/min it was raised to 230\u0026deg;C and held for 12 min; the carrier gas (H\u003csub\u003e2\u003c/sub\u003e) flow rate was 3 ml/min; the injector and detector temperature was 250\u0026deg;C.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 \u003cem\u003eResponse surface analysis\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eOptimization and statistical analysis of the transesterification process\u003c/p\u003e\u003cp\u003eIn order to optimize the transesterification process and determine the influence of the molar ratio of methanol to rapeseed oil (A), catalyst loading (B) and reaction duration (C) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) on the ester yield, a 3-factor experiment was performed using Central composite design (CCD). The CCD experiment consisted of 17 trials (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The ester yield (%) was used as a response indicator in the model. The obtained data were analyzed by variance (ANOVA) and graphical analysis using Design-Expert 13 (Stat-Ease, Minneapolis) software. The experimental data (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) were analyzed using the response surface regression (RSREG) method of the Statistical Analysis System (SAS). This method is based on a second-order polynomial model (Eq.\u0026nbsp;3). The RSREG methodology includes canonical analysis to determine the stationary values of each factor. Based on the fitted model, response surface contour plots were constructed for each pair of factors under study, fixing the third factor at its calculated stationary value. To validate the model, an optimization procedure of the reaction conditions was performed using combinations of independent variables that were not included in the original experimental design.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eIndependent variables used in the Central composite design for the synthesis of rapeseed oil methyl ester\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\"\u003e\u003cp\u003eFactors\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\"\u003e\u003cp\u003eName\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\"\u003e\u003cp\u003eUnits\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\"\u003e\u003cp\u003eLow Actual\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\"\u003e\u003cp\u003eHigh Actual\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003eA:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003eMolar ratio of methanol to rapeseed oil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003emol/mol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003eB:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003eCatalyst loading (from oil mass)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003ewt%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003eC:\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003eReaction duration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003eh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCentral composite design matrix with three independent variables and experimental and predicted results.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" rowspan=\"2\"\u003e\u003cp\u003eNo.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" rowspan=\"2\"\u003e\u003cp\u003eAlcohol to oil molar ratio, mol/mol\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" rowspan=\"2\"\u003e\u003cp\u003eCatalyst concentration (from oil mass), wt%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" rowspan=\"2\"\u003e\u003cp\u003eReaction duration, h\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\"\u003e\u003cp\u003eEster yield, %\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\"\u003e\u003cp\u003eExperimental results\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\"\u003e\u003cp\u003ePredicted results\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e96.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e96.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e18.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e16.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e99.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e100.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e99.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e100.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e29.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e28.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e28.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e30.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e45.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e48.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e2.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e2.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e67.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e70.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e70.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e70.67\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e97.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e96.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e81.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e80.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e39.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e37.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e98.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e98.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e27.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e28.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e96.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e96.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e84.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e83.74\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e52.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\"\u003e\u003cp\u003e49.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\u003cp\u003eThe quadratic polynomial regression equation was used to estimate the model parameters and predict the response:\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u0026nbsp;\u003cspan class=\"mathinline\"\u003e\\(\\:Y=\\:{\\beta\\:}_{0}+\\:\\sum\\:_{i=1}^{3}{\\beta\\:}_{i}{X}_{i}\\:+\\:\\sum\\:_{i=1}^{3}{\\beta\\:}_{ii}{X}_{i}^{2}+\\:\\sum\\:_{i=1}^{2}\\:\\sum\\:_{j=i+1}^{3}{\\beta\\:}_{ij}{X}_{i}{X}_{j}\\)\u003c/span\u003e\u0026nbsp;\u003c/span\u003e (2),\u003c/p\u003e\u003cp\u003ewhere:\u003c/p\u003e\u003cp\u003eY \u0026ndash; the response (dependent variable);\u003c/p\u003e\u003cp\u003e\u003cem\u003eX\u003c/em\u003e \u003csub\u003e\u0026nbsp;\u003cem\u003ei\u003c/em\u003e\u0026nbsp;\u003c/sub\u003e, \u003cem\u003eX\u003c/em\u003e\u003csub\u003e\u003cem\u003ej\u003c/em\u003e\u003c/sub\u003e \u0026ndash; the independent variables;\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e \u003csub\u003e\u0026nbsp;\u003cem\u003e0\u003c/em\u003e\u0026nbsp;\u003c/sub\u003e, \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003eii\u003c/em\u003e\u003c/sub\u003e bei \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003ej\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003e\u0026beta;\u003c/em\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e \u0026ndash; constant coefficients.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6. \u003cem\u003eStudies of the physical and chemical properties of biodiesel\u003c/em\u003e\u003c/h2\u003e\u003cp\u003eThe physical and chemical properties of obtained biodiesel were evaluated based on the requirements of the EN 14214 standard.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results and Discussions","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e3.1. \u003cem\u003eConcentration of calcium oxide in snail shells\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eIt was found that the CaO concentration in uncalcined snail shells (\u003cem\u003eHelix pomatia\u003c/em\u003e) was 47.14 ± 0.22%, while after calcination at 850 \u003csup\u003eo\u003c/sup\u003eC for 5 h it reaches 97.74 ± 0.12%. A slightly lower CaO content was obtained in snail shells of \u003cem\u003eHelix Aspersa Maxima\u003c/em\u003e calcined under the same conditions (91.69 ± 0.43%) [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. Similar results were obtained by Laskar el al., where snail shells (\u003cem\u003ePila spp\u003c/em\u003e.) were dried in an oven at 100 \u003csup\u003eo\u003c/sup\u003eC for 12 h before calcination (4 h at temperature 900 \u003csup\u003eo\u003c/sup\u003eC), and CaO content reached 98.017% [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. Mohammed et al. obtained the optimal conditions for the preparation of snail shells at 900 \u003csup\u003eo\u003c/sup\u003eC and 3.5 h [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]. Trisupakitti et al. studied golden apple cherry snail shells (\u003cem\u003ePomacea canaliculata\u003c/em\u003e), they calcined crushed shells at 1050 \u003csup\u003eo\u003c/sup\u003eC for 2 h and determined 98.6% of CaO [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eA lower CaO content of 70.113% was obtained by heating river snail shells at 800 \u003csup\u003eo\u003c/sup\u003eC for 4 h [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. It is believed that the lower concentration of CaO was obtained because the calcination temperature was lower. However, Phewphong et al. investigated shells of golden apple snails (\u003cem\u003ePomacea canaliculata\u003c/em\u003e) and used a calcination temperature of 800 \u003csup\u003eo\u003c/sup\u003eC, it was obtained that CaO concentration reaches 100% in treated snail shells with acid before calcination and 95.05% of CaO in untreated snail shells [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]. Trisupakitti et al., investigated golden apple cherry snail shells and obtained CaO of 99.5%. However, before calcination deproteination was done (ground shell was agitated with 4%w/v NaOH at 60 \u003csup\u003eo\u003c/sup\u003eC for 1 h and then allowed to precipitate, the filtrate was washed with distilled water until the pH of the wash water was neutral, dried in an oven at 100 \u003csup\u003eo\u003c/sup\u003eC for 1 h, decolorized by boiling in acetone for 1 h, filtered and washed with methanol and dried at 100 \u003csup\u003eo\u003c/sup\u003eC for 1 h) [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. Phewphong et al. [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e] and Trisupakitti et al. [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e] studies prove that treatment of snail shells before calcination leads to a 1–5% higher CaO concentration, nevertheless, additional reagents and energy costs are used during treatment stage.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003e3.2. \u003cem\u003eOptimal Reaction Conditions Modeling and Determination Using Response Surface Methodology\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eResponse Surface Analysis\u003c/p\u003e\n\u003cp\u003eIt is known that the main parameters determining the efficiency of biodiesel production are the molar ratio of alcohol to oil (A; mol/mol), catalyst concentration (B; wt%) and reaction duration (C; h). In order to evaluate the interaction effects (the total effect of these factors), experiments were carried out by varying the physical parameters according to the experimental design (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Multiple regression analysis applied to the data in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e allowed the experimental results obtained according to the full factorial central composition design to be approximated by a second-order polynomial Eq.\u0026nbsp;(2). The resulting regression model describing the synthesis of rapeseed methyl ester is presented in Eq.\u0026nbsp;(3), where the response variable (Y, ester yield; %) is expressed as the sum of the products of the independent variables and the regression coefficients.\u003c/p\u003e\n\u003cp\u003eY = -182.02 + 13.90A + 19B + 27.40C – 0.32AB + 0.46AC + 0,26BC – 0.62A\u003csup\u003e2\u003c/sup\u003e – 1.17B\u003csup\u003e2\u003c/sup\u003e – 1.81C\u003csup\u003e2\u003c/sup\u003e (3)\u003c/p\u003e\n\u003cp\u003ewhere:\u003c/p\u003e\n\u003cp\u003eY – ester yield, %;\u003c/p\u003e\n\u003cp\u003eA – alcohol to oil molar ratio, mol/mol;\u003c/p\u003e\n\u003cp\u003eB – catalyst loading, wt%;\u003c/p\u003e\n\u003cp\u003eC – reaction duration, h.\u003c/p\u003e\n\u003cp\u003ePositive (+) coefficients indicate a positive correlation with the response variable, and negative (-) coefficients indicate a negative correlation.\u003c/p\u003e\n\u003cp\u003eTo assess the variance (ANOVA) and to check the adequacy of the empirical model, a statistical analysis of the model was performed. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e summarizes the ANOVA results obtained after applying the second-order response surface model using the mean squares method. The significance of the coefficients of the response surface model, as defined in Eq.\u0026nbsp;(4), was also assessed. The statistical significance of each coefficient was determined based on the P values (probabilities, Prob \u0026gt; F), which also indicate the strength of the interaction of each parameter. Based on the data in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, the P value of the model is less than 0.0001, which indicates a high statistical significance of the model for predicting response values and the adequacy of the derived model. The probability that such a high F value of the model would be random (due to noise or natural variability) is only 0.01%. The high F value of the model (F = 273.49) and the correspondingly low P value (P \u0026lt; 0.0001) confirm the high statistical significance of the constructed model. The \"Lack of Fit\" test assesses whether the selected model adequately describes the relationship between the independent variables and the response variable, or whether there is a systematic bias that the model misses. If the model imprecision is statistically significant (small P value), this would indicate that the model is inappropriate and does not describe the data well enough, possibly because the model was too simple or important factors were omitted. An assessment of the discrepancy between the residual errors and the net error (F value 18.25) showed that the model imprecision is not statistically significant (P = 0.0528 \u0026gt; 0.05). This result is desirable as it confirms that the selected second-order polynomial model is appropriate and adequately describes the experimental data, without significant systematic bias. The statistical significance of all model coefficients was determined by P values and is presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eResult of experimental design matrix for ester yield\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eSource of variation\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eSum of squares\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eDegrees of freedom (df)\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eMean squares\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eF value\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003ep-value Prob \u0026gt; F\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eModel\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e14527.03\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1614.11\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e273.49\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eSignificant\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eA-molar ratio\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1899.94\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1899.94\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e321.92\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eB-catalyst\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e143.28\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e143.28\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e24.28\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0017\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eC-Duration\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e7786.11\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e7786.11\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1319.26\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eAB\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e184.22\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e184.22\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e31.21\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0008\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eAC\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e383.23\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e383.23\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e64.93\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eBC\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e43.11\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e43.11\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.30\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0305\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eA\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1742.11\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1742.11\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e295.18\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eB\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e814.71\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e814.71\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e138.04\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eC\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1927.91\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e1927.91\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e326.66\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt; 0.0001\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eResidual\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e41.31\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.90\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eLack of Fit\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e40.43\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.09\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e18.25\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.0528\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003enot significant\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003ePure Error\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.8861\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.4430\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eCor Total\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e14568.34\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eC.V. % = 3.64\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e = 0,9972\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eAdeq Precision = 44.764\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eAdj\u003c/sub\u003e = 0.9935\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ePred\u003c/sub\u003e = 0.9781\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eA higher F value and a lower P value indicate that the corresponding parameters are significant. p-values \"P \u0026gt; F\" less than 0.05 mean that the model components are significant. In this model, A, B, C, AB, AC, BC, A\u003csup\u003e2\u003c/sup\u003e, B\u003csup\u003e2\u003c/sup\u003e and C\u003csup\u003e2\u003c/sup\u003e are statistically significant model components. A low coefficient of variation (CV) value (3.64%) indicates minimal data dispersion around the mean value, which indicates high experimental precision and model reliability. The coefficient of determination (R\u003csup\u003e2\u003c/sup\u003e) defines the proportion of the variance of the response variable that is explained by the regression model. The range of R\u003csup\u003e2\u003c/sup\u003e values is from 0 to 1, where a value closer to 1 reflects a better fit of the model to the empirical data. Ideally, R\u003csup\u003e2\u003c/sup\u003e = 1 would mean complete explanation of the response variation by the model, while R\u003csup\u003e2\u003c/sup\u003e = 0 – complete failure of the model to explain the variation. The resulting R\u003csup\u003e2\u003c/sup\u003e value (0.9972) is extremely high, and indicates that the model explains 99.72% of the variation in the response variable, indicating an excellent fit of the model to the experimental data (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The adjusted coefficient of determination (R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eAdj\u003c/sub\u003e) is a modification of R\u003csup\u003e2\u003c/sup\u003e that adjusts the indicator for the number of independent variables in the model. Since R\u003csup\u003e2\u003c/sup\u003e tends to increase artificially with increasing number of variables, even if the newly added variables are not statistically significant, R\u003csup\u003e2\u003c/sup\u003eAdj introduces a correction factor that re-analyses the addition of unnecessary variables. For this reason, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eAdj\u003c/sub\u003e is considered a more reliable indicator of model fit, especially in models with a larger number of variables. For a good model, the value of R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eAdj\u003c/sub\u003e should be close to the value of R\u003csup\u003e2\u003c/sup\u003e. The obtained R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eAdj\u003c/sub\u003e value (0.9935) is extremely high and close to R\u003csup\u003e2\u003c/sup\u003e (0.9972), which confirms the model fit and indicates that the model is not overfitted with insignificant variables. A high R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eAdj\u003c/sub\u003e value reinforces the conclusion that the model is well-fitting, even considering the complexity of the model. The predicted coefficient of determination (R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ePred\u003c/sub\u003e) assesses the model's ability to predict response values for new, independent data. It is desirable that the R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ePred\u003c/sub\u003e value be positive and close to the R\u003csup\u003e2\u003c/sup\u003e and R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eAdj\u003c/sub\u003e values. The obtained R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ePred\u003c/sub\u003e value (0.9781) is high and close to R\u003csup\u003e2\u003c/sup\u003e and R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eAdj\u003c/sub\u003e, which indicates that the model has good predictive properties and can accurately predict response values for new data. The Adeq Precision value, reaching 44.764, shows a high signal-to-noise ratio, indicating that the model is statistically significant and reliable. This indicator allows us to conclude that the model is suitable for predicting response values and can be effectively used for optimizing reaction conditions. The high Adeq Precision value confirms the validity of the model and its value for further research.\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the accuracy of the predictive model, assessed by comparing the experimentally determined and model-predicted values of ester yield. The visual graphical analysis presented shows the good fit and high predictive power of the regression model. The arrangement of the data points, close to the line of perfect fit, confirms the excellent fit of the model to the experimental data and the accuracy of the predicted values.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003ch2\u003e3.3. \u003cem\u003eInteraction of independent variables on ester yield\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eBased on the results of the primary analysis, three-dimensional (3D) contour plots were constructed to visualize and identify the optimal conditions for the ester yield, as illustrated in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e (A), (B), (C). Each plot analyses the dependencies between the process response (ester yield ((%)) and the independent variables - catalyst concentration, alcohol to oil molar ratio and reaction duration. Contour plots are constructed by fixing one independent variable at a stationary point and varying the remaining two independent variables on the X and Y axes to visually identify the conditions under which the response value is maximum. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e depicts the response surfaces for the ester yield, reflecting: Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA. the interaction between alcohol to oil molar ratio and catalyst concentration; Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB shows the interaction between alcohol to oil molar ratio and the reaction duration; Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003ed shows the interaction between the catalyst loading and the reaction duration.\u003c/p\u003e\n\u003cp\u003eThe analysis of Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA, where the reaction duration is fixed at 6.94 hours, shows the interaction effect of the alcohol to oil molar ratio and catalyst loading on the ester yield. The graph shows that the ester yield increases with increasing both the alcohol to oil molar ratio and the catalyst loading. This direct relationship between catalyst loading and ester yield is a fundamental property of heterogeneous catalysis, and the contour plots of the surface response methodology provide a detailed visual analysis of the efficiency of the snail shells CaO catalyst. The snail shells CaO catalyst acts as a solid material, and the catalytic reaction occurs on its surface. A higher catalyst loading in the reaction mixture means that a larger amount of solid catalyst particles is introduced into the system. These particles obtained after calcination are characterized by a porous structure and a large specific surface area [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. The active catalytic sites responsible for the transesterification reaction (most often basic CaO surface sites, such as O\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e−\u003c/sup\u003e ions) are located precisely on this surface. Therefore, increasing the catalyst loading proportionally increases the total surface area of the catalyst in the reaction mixture, and with it the total number of available active sites on which the reacting oil and alcohol molecules can adsorb and the transesterification reaction takes place. As a result, the reaction rate accelerates, and a larger portion of the oil is converted to ester during the same reaction time. Higher alcohol to oil molar ratio pushes the reaction equilibrium in the direction of ester formation according to Le Chatelier's principle, also increasing the probability of collision of the reactants with the catalyst [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]. The highest yield, exceeding 98%, are achieved at the highest tested alcohol amount and catalyst loading, confirming the synergistic effect of these parameters, and the shape of the contour lines in the graph highlights this interaction, consistent with trends reported in the scientific literature for heterogeneous catalysis. For example, Trisupakitti et al. [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e] obtained a biodiesel yield of 95.2% with a golden apple snail shells catalyst using a 0.8 wt% catalyst loading and a 12:1 methanol to oil molar ratio, while Laskar et al. [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e] reached a 98% ester yield with a Pila spp. snail shells catalyst using a 3 wt% catalyst loading and a 6:1 methanol to oil molar ratio, highlighting the potential of snail shells as a promising catalyst source. These quantitative values show a direct correlation between catalyst loading, alcohol to oil molar ratio, and ester yield, emphasizing the critical role of catalyst loading for an efficient transesterification process.\u003c/p\u003e\n\u003cp\u003eThe effect of the alcohol to oil molar ratio and the reaction duration on the ester yield, where the catalyst laoding is fixed at 4.24%, is given (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB). It can be seen that the ester yield increases in both cases, with increasing the alcohol to oil molar ratio and the reaction duration. The effect of reaction duration is particularly important in heterogeneous catalysis, where the reaction takes place on the catalyst surface. A longer reaction duration provides more time for molecules of the oil and alcohol to diffuse into the catalyst pores, adsorb on the active sites, and react, especially when the catalyst concentration is relatively low [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e]. A higher alcohol to oil molar ratio, as in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA, further shifts the reaction equilibrium towards the formation of esters. The highest ester yield, exceeding 99%, are again achieved at the highest tested reaction duration values, emphasizing that the longer reaction duration compensates for the lower catalyst concentration, allowing to obtain high ester yield. The shape of the contour lines and the localization of the highest ester yield in the graph emphasize the synergistic effect of the parameters and are consistent with the trends described in the scientific literature for heterogeneous catalysis in biodiesel production. Kaewdaeng et al. [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e] achieved 92.5% oil conversion to ester after a 1-hour of reaction with a river snail shells catalyst, while Birla et al. [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e] obtained the optimal reaction duration of 7 hours, achieving 99.58% conversion with a snail shell catalyst. It can be noticed that the reaction duration is one of the essential parameters to achieve a high ester yield, especially when using heterogeneous catalysts.\u003c/p\u003e\n\u003cp\u003eThe effect of catalyst loading and reaction duration, when the alcohol to oil molar ratio is fixed at 8.4 mol/mol on the ester yield is presented in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC. It can be seen that the ester yield increases with increasing both catalyst loading and reaction duration, and optimal conditions are achieved by combining these parameters. When the alcohol content is fixed, catalyst loading and reaction duration become the main factors determining the ester yield. Higher catalyst loading increases the number of active sites, while longer reaction duration provides sufficient time for the reaction to proceed to completion, especially when the alcohol content is limited [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. The highest ester yield, exceeding 98%, are again achieved at the highest tested catalyst loading, close to 9–10 wt%, and reaction duration reaching 9–10 hours, confirming the synergistic effect of these parameters. For example, Kaewdaeng et al. investigated the use of a river snail shells catalyst for synthesis of fatty acid methyl ester [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]. The optimal catalyst loading of 3 wt% and a reaction time of 1 hour, allowed to achieve 92.5% of fatty acid methyl ester yield, and subsequent optimization tests showed that the ester yield can reach up to 98.19%. Karkal et al. (2023) optimized the process with a crab shell as a heterogeneous catalyst, achieving a biodiesel yield of 88.56 wt% with a catalyst loading of 3 wt% and a reaction duration of 60 minutes, demonstrating efficiency even in short reaction duration [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e]. Alsabi et al. (2024) achieved an extremely high, 99.36%, fatty acid methyl ester yield with a mussel shell as a catalyst, optimizing the methanol to oil molar ratio to 18:1, a catalyst loading of 6 wt% and a reaction duration of 6 hours [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. Laskar et al. (2018) obtained biodiesel yield of 98%, while using snail shells a catalyst (3 wt%), a reaction took 7 hours, and the methanol to oil molar ratio was 6:1 [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003ch2\u003e3.4. \u003cem\u003eOptimization of rapeseed oil methyl ester synthesis process\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe influence of three independent variables on the rapeseed oil methyl ester yield was evaluated and the process was optimized. The optimal conditions were determined (process temperature is 64°C): methanol to oil molar ratio 10.6:1, snail shells loading 5.7 wt%, reaction duration 7.8 h. The predicted ester yield was 99.81 wt%, and the experimentally determined ester content was slightly lower at 98.80 ± 0.30 wt%, while the obtained experimental ester content was 97.15 ± 0.25 wt%, however it meets the requirements of the standard REN 14214. The data are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\n\u003ctable id=\"Tab4\" border=\"1\" style=\"width: 1004px;\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eOptimum parameters for rapeseed oil methyl ester production, predicted and experimental ester yield\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" style=\"width: 121px;\"\u003e\n\u003cp\u003eMethanol-to-oil\u003c/p\u003e\n\u003cp\u003emolar ratio, mol/mol\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\" style=\"width: 206px;\"\u003e\n\u003cp\u003eSnail shells\u003c/p\u003e\n\u003cp\u003econcentration, wt% (from oil mass)\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\" style=\"width: 117px;\"\u003e\n\u003cp\u003eReaction duration, h\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\" style=\"width: 152px;\"\u003e\n\u003cp\u003ePredicted ester yield, wt%\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\" style=\"width: 175px;\"\u003e\n\u003cp\u003eExperimental ester yield, wt%\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\" style=\"width: 189.544px;\"\u003e\n\u003cp\u003eExperimental ester content, wt%\u003c/p\u003e\n\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" style=\"width: 121px;\"\u003e\n\u003cp\u003e10.6:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\" style=\"width: 206px;\"\u003e\n\u003cp\u003e5.7\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\" style=\"width: 117px;\"\u003e\n\u003cp\u003e7.8\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\" style=\"width: 152px;\"\u003e\n\u003cp\u003e99.81\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\" style=\"width: 175px;\"\u003e\n\u003cp\u003e98.80 ± 0.30\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\" style=\"width: 189.544px;\"\u003e\n\u003cp\u003e97.15 ± 0.25\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e presents comparative results of studies by scientists who analyzed the process of transesterification of oil with methanol using snail shells as a catalyst. Different oils were used. Rapeseed oil was used in this research and Gaide et al. [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e] study, soybean oil was used by Laskar et al., [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e] Das et. al. [\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e] and Ouafi et al. [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. Transesterification of palm oil was studied by Viriya-empikul et al. [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e] Phewphong et al. [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e], Birla et al. [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e]. Kaewdaeng et al. [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e], Mohammed et al. [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e] produced fatty acid methyl ester from waste frying/ cooking oil. The obtained ester yield ranged from 85.5 to 98.15 wt%.\u003c/p\u003e\n\u003cp\u003eMany researchers have performed the synthesis of methyl esters at 60–65 \u003csup\u003eo\u003c/sup\u003eC, in this research, 64 \u003csup\u003eo\u003c/sup\u003eC was used. It is believed that temperatures close to the boiling point of methanol (64.7 \u003csup\u003eo\u003c/sup\u003eC) were chosen, as it is known that transesterification reactions are most efficient under temperatures close to alcohols boiling. Only Laskar et al. synthesized biodiesel at a low temperature of 28\u003csup\u003eo\u003c/sup\u003eC and obtained ester yield of 98 wt% [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eFor the transesterification reaction to proceed a minimum methanol to oil molar ratio of 3:1 is required, all researchers (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e) used a excess of methanol to oil molar ratio from 21:5 (4.2:1) [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e] to 12:1 [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. In this study, the optimal methanol to oil molar ratio was found to be 10.6:1.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\n\n\u003ctable id=\"Tab5\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eComparison of optimum condition for biodiesel production when different snail shells as heterogeneous catalyst is used\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eOil\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eSnail\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eTemperature, °C\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eSnail shells amount, wt%\u003c/p\u003e\n\u003c/th\u003e\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eReaction duration, h\u003c/p\u003e\n\u003c/th\u003e\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMethanol-to-oil\u003c/p\u003e\n\u003cp\u003emolar ratio, mol/mol\u003c/p\u003e\n\u003c/th\u003e\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eEster yield,\u003c/p\u003e\n\u003cp\u003econtent*wt%\u003c/p\u003e\n\u003c/th\u003e\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eWaste frying oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eSnail from the banks of the river Ganges in Varanasi, India\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e6.03:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e87.28\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003ePalm olein oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eGolden apple snail\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e12:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e93.2\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eUsed cooking oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eRiver snail\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e9:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e92.5\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003ePalm oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eGolden apple snail\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.8\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e12:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e92.5\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eSoybean oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003ePila spp\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e6:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e98\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003ePalm oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eGolden apple snail Pomacea canaliculata (calcination and acid treatment process.)\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e2,5\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e12:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e87.5\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eWaste cooking oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e65\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e2.5\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e12:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e85.5\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eWaste cooking oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eSnail from Iraq\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e62.2\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.8\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e4.8\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e21:5\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e95*\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eRapessed oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eHelix Aspersa Maxima\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.06\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e7.5:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e98.15*\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eSoybean oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eSnaill “\u003cem\u003echengkawl sawl\u003c/em\u003e”\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e70\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e6,0\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e8:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e96.1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eSoybean oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eSnail shells powder after the copper Cu(II) removal\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e60\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e12:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e93\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eRapessed oil\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eHelix pomatia\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.7\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e7.8\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e10.6:1\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e98.80\u003c/p\u003e\n\u003cp\u003e97.15*\u003c/p\u003e\n\u003c/td\u003e\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eThis work\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"12\"\u003e*Ester content\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eVery different data were obtained by other researchers when determining the optimal amount of catalyst and process duration. Trisupakitti et al (2018) obtained 92.5 wt% of ester yield in 6 h, while using 0.8 wt% of Golden apple snail shells [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. While the same snails were used by Viriya-empikul et al. [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e] however the optimal catalyst amount was 10 wt%, although the process duration was 2 h and a similar ester yield of 93.2 wt% was obtained. In this study, optimum reaction duration was 7.8 h and 5.7 wt% of Helix pomatia snail shells.\u003c/p\u003e\n\u003cp\u003eAlthough in this study optimized process conditions were similar to the optimal conditions described in the literature, significantly higher ester yield (98.80 wt%) was achieved and ester content (97.15 wt%), exceeding the requirements of the EN 14214 standard.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003ch2\u003e3.5. \u003cem\u003ePhysical and chemical properties of obtained rapeseed oil methyl ester\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eBiofuels can be used in the transport sector if they meet the requirements of the standard EN 14214. The compliance of physical and chemical properties of the produced methyl ester and their comparison with the requirements of the standard are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\n\u003ctable id=\"Tab6\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eThe physical and chemical properties of rapeseed oil methyl ester\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eParameter\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eUnits\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eEN 14214 requirements\u003c/p\u003e\n\u003c/th\u003e\u003cth align=\"left\"\u003e\n\u003cp\u003eRapeseed oil methyl ester (RME)\u003c/p\u003e\n\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eEster content\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e%\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emin 96.5\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e97.15 ± 0.25\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eDensity at 15°C\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003ekgm\u003csup\u003e− 3\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emin 860\u003c/p\u003e\n\u003cp\u003emax 900\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e885 ± 2.00\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eViscosity at 40°C\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emm\u003csup\u003e2\u003c/sup\u003es\u003csup\u003e− 1\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emin 3.50\u003c/p\u003e\n\u003cp\u003emax 5.00\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.70 ± 0.10\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eAcid value\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emg KOHg\u003csup\u003e− 1\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emax 0.5\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.22 ± 0.05\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eMoisture content\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emgkg\u003csup\u003e− 1\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emax 500\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e305 ± 2.10\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eIodine value\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eg J\u003csub\u003e2\u003c/sub\u003e100\u003csup\u003e− 1\u003c/sup\u003eg\u003csup\u003e− 1\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emax 120\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e115 ± 0.20\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eLinolenic acid methyl ester\u003c/p\u003e\n\u003cp\u003econtent\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e%\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emax 12.0\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.86 ± 0.10\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eMonoglyceride content\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e%\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emax 0.8\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.27 ± 0.03\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiglyceride content\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e%\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emax 0.2\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.05 ± 0.02\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eTriglyceride content\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e%\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emax 0.2\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.06 ± 0.01\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eFree glycerol content\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e%\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emax 0.02\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.007 ± 0.00\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal glycerol content\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e%\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emax 0.25\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.19 ± 0.10\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eMethanol content\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e%\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emax 0.2\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.10 ± 0.05\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003ePhosphorus content, ppm\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.5 ± 0.10\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eMetals II (Ca/Mg)\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emg kg\u003csup\u003e− 1\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emax 5\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.5 ± 0.25\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eOxidation stability 110°C\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eH\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emin 8\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.5 ± 0.15\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eCetane number\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003emin 51\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e52 ± 0.20\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003eCold filter plugging point\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e°C\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e-5°C (in summer)\u003c/p\u003e\n\u003cp\u003e-32°C (in winter)\u003c/p\u003e\n\u003c/td\u003e\u003ctd align=\"left\"\u003e\n\u003cp\u003e-9.8 ± 0.04\u003c/p\u003e\n\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe ester content shows how many fatty acid methyl esters were formed from triglycerides. The ester content of the obtained biodiesel 97.15 ± 0.25 wt% meets the requirements of the standard (not less than 96.5%). The density of biodiesel is higher (885 ± 2.00 kgm\u003csup\u003e-\u003c/sup\u003e3) than that of mineral diesel and meets the requirements of the standard (860–900 kgm\u003csup\u003e-3\u003c/sup\u003e) (at 15°C). Viscosity affects the fuel supply and combustion process. It should be 3.5-5.0 mm\u003csup\u003e2\u003c/sup\u003es\u003csup\u003e-1\u003c/sup\u003e (at 40°C), obtained value is 4.70 ± 0.10 mm\u003csup\u003e2\u003c/sup\u003es\u003csup\u003e-1\u003c/sup\u003e. Acid value in the European standard max 0.5 mg KOHg\u003csup\u003e-1\u003c/sup\u003e. If biodiesel contains a higher number of acids, engine corrosion and sediment formation may occur, the resulting RME acid value is 0.22 ± 0.05 mg KOHg\u003csup\u003e-1\u003c/sup\u003e. Water in biodiesel can cause microbiological processes, during which the sludge formed can clog filters. Moisture content must be max 500 mgkg\u003csup\u003e-1\u003c/sup\u003e, in this study the RME moisture content obtained is 305 ± 2.10 mgkg\u003csup\u003e-1\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIodine value and linolenic acid methyl ester content depend on the fatty acid composition of the oils or fats used, it is determined that if biodiesel consists of a large amount of mono- and polyunsaturated acids, it polymerizes when heated and sediment is formed. Iodine value should be max 120 g J\u003csub\u003e2\u003c/sub\u003e100\u003csup\u003e-1\u003c/sup\u003eg\u003csup\u003e-1\u003c/sup\u003e, obtained value – 115 ± 0.20 g J\u003csub\u003e2\u003c/sub\u003e100\u003csup\u003e-1\u003c/sup\u003eg\u003csup\u003e-1\u003c/sup\u003e, linolenic acid methyl ester content should be max 12%, obtained 8.86 ± 0.10%. Monoglyceride, diglyceride, triglyceride, free and total glycerol content should be no less than 0.8%, 0.2%, 0.2%, 0.02% and 0.25%, obtained values are: 0.27 ± 0.03%, 0.05 ± 0.02%, 0.06 ± 0.01%, 0.007% and 0.19 ± 0.10% respectively. If these indicators are exceeded, sediment may form, and they also directly affect the increase in viscosity. Excess methanol is used for transesterification, so its removal is a very important stage of the biodiesel purification process. Methanol content should not exceed 0.2%, in the resulting biodiesel – 0.10 ± 0.05%. Another indicator that depends on the oil used is the phosphorus content. Phosphorus in esters may remain due to phospholipids contained in the raw material. Phosphorus content is limited to 10 ppm, determined value is 7.5 ± 0.10 ppm. The content of alkali metals must not exceed 5 mgkg\u003csup\u003e-1\u003c/sup\u003e, obtained 3.5 ± 0.25 mgkg\u003csup\u003e-1\u003c/sup\u003e. Since snail shells calcined to CaO were used as catalysts in this study, it is very important that the biodiesel is purified well, and no calcium remains. It is important that the fuel maintains the required properties during storage and transportation, as oxidation processes occur when it comes into contact with oxygen, and the properties of the fuel change. Oxidation stability, must be min 8 h at 110°C, obtained 8.5 ± 0.15 h. Cetane number determines combustion quality, according to the standard requirements min 51, obtained 52 ± 0.20. Low-temperature properties are very important to use the fuel not only in summer, but also in the cold period. In different countries, depending on climatic conditions, different requirements apply for cold filter plugging point. In this study, the RME cold filter plugging point obtained is -9.8 ± 0.04°C. The cold filter plugging point of fuels used in the summer period is min − 5°C in Lithuania\u003c/p\u003e\n\u003cp\u003eThe produced biodiesel meets the requirements of the EN 14214 standard and can be used in diesel engines during the summer period.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eCalcium oxide is a suitable catalyst for biodiesel synthesis. CaO concentration was 97.74 ± 0.12% in calcined for 4 hours at 850°C grape snail shells (\u003cem\u003eHelix pomatia\u003c/em\u003e). Transesterification studies were performed by varying three independent variables (methanol to oil molar ratio, loading of catalyst and reaction duration) in order to determine their influence on the efficiency of the transesterification process and to select optimal conditions. The studies were performed at a temperature of 64 \u003csup\u003eo\u003c/sup\u003eC. The optimal conditions for the synthesis of rapeseed oil methyl ester were determined by using the response surface methodology: alcohol to oil molar ratio 10.6:1, loading of catalyst 5.7 wt % and process duration 7.8 h. Under the determined optimal conditions the ester yield reached 97.15 wt %. The produced biodiesel meets the requirements of the EN 14214 standard and can be used in diesel engines during the summer period.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEglė Sendžikienė:\u0026nbsp;\u003c/strong\u003eConceptualization; Data curation; Formal analysis; Methodology; Funding acquisition; Resources; Validation; Project administration; Visualization; Supervision; Roles/Writing - original draft; and Writing - review \u0026amp; editing \u0026nbsp;\u003cstrong\u003eGediminas Gokas:\u003c/strong\u003e Investigation; Software. \u0026nbsp; \u003cstrong\u003eIeva Gaidė:\u003c/strong\u003e Data curation; Investigation; Writing – original draft. \u0026nbsp;\u003cstrong\u003eMilda Gumbytė:\u003c/strong\u003e Data curation; Formal analysis; Investigation; Methodology; Software; Visualization; Roles/Writing - original draft. \u003cstrong\u003eKiril Kazancev:\u003c/strong\u003e Investigation. \u003cstrong\u003eVioleta Makarevičienė\u003c/strong\u003e: Conceptualization; Formal analysis; Validation; Supervision; Roles/Writing - original draft; and Writing - review \u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding / Acknowledgements.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project has received funding from the Ministry of Education, Science and Sports of the Republic of Lithuania and Research Council of Lithuania (LMTLT) under the Program ‘University Excellence Initiative’ Project ‘Development of the Bioeconomy Research Center of Excellence’ (BioTEC), agreement No S-A-UEI-23-14.\u003c/p\u003e\n\u003ch3\u003eDeclaration of interests\u003c/h3\u003e\n\u003cp\u003eWe have nothing to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAghbashlo, M. et al. 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Biodiesel production over Ca-based solid catalysts derived from industrial wastes. \u003cem\u003eFuel\u003c/em\u003e \u003cb\u003e92\u003c/b\u003e, 239\u0026ndash;244 (2012).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"transesterification, heterogeneous catalysis, snail shells, response surface methodology, methylester, biodiesel","lastPublishedDoi":"10.21203/rs.3.rs-6811110/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6811110/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBiodiesel is an alternative to conventional diesel. The use of heterogeneous catalysts in biodiesel production is promising, as it is easier to separate it from the product than homogeneous ones. It was determined that the calcined grape snail (\u003cem\u003eHelix pomatia\u003c/em\u003e) shells show good catalytic efficiency in rapeseed oil transesterification process with methanol. It was determined that the CaO concentration in calcined grape snail (\u003cem\u003eHelix pomatia\u003c/em\u003e) shells was 97.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12%. Using the response surface methodology, the biodiesel production process was optimised. The influence of interaction of independent variables and optimal conditions for the synthesis of rapeseed oil methyl ester were determined: an alcohol to oil molar ratio of 10.6:1, a catalyst concentration of 5.7 wt % and a reaction duration of 7.8 h at a temperature of 64\u0026deg;C. The physical and chemical properties of produced biodiesel at optimal process conditions are presented, their compliance with the requirements of biodiesel standard EN 14214 are discussed. The produced biodiesel using snail shells which are food processing waste meets the requirements of the EN 14214 standard and can be used in diesel engines during the summer period.\u003c/p\u003e","manuscriptTitle":"Snail (Helix pomatia) Shells as a Catalyst for Biodiesel Synthesis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-18 07:18:02","doi":"10.21203/rs.3.rs-6811110/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7d547f34-a200-426c-9aff-5b4e1aa7b269","owner":[],"postedDate":"June 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":50221499,"name":"Earth and environmental sciences/Environmental sciences"},{"id":50221500,"name":"Physical sciences/Chemistry"}],"tags":[],"updatedAt":"2025-08-20T08:08:40+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-18 07:18:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6811110","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6811110","identity":"rs-6811110","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}