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Evaluation of Thermo-oxidative Stability of Biodiesel Elton L Savi, Leandro S. Herculano, Gustavo V. B. Lukasievicz, Alex S. Torquato, Mauro Luciano Baesso, Nelson Guilherme Castelli Astrath, and Luis C Malacarne Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b00696 • Publication Date (Web): 27 Jun 2017 Downloaded from http://pubs.acs.org on July 2, 2017
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Evaluation of Thermo-oxidative Stability of Biodiesel Elton L. Savi,† Leandro S. Herculano,‡ Gustavo V. B. Lukasievicz,‡ Alex S. Torquato,‡ Mauro L. Baesso,† Nelson G. C. Astrath,† and Luis C. Malacarne∗,† †Departamento de Física, Universidade Estadual de Maringá, 87020-900, Maringá, PR, Brazil ‡Departamento de Física, Universidade Tecnológica Federal do Paraná, 85884-000, Medianeira, PR, Brazil E-mail:
[email protected] Abstract The biodiesel susceptibility to oxidation is one of the major problems concerning its use as an alternative to diesel fuel. Although well characterized, the oxidation process cannot be completely prevented since it can be affected by a large number of factors, as fuel composition, storage conditions, contaminants, temperature and presence of air and light. In this work, we propose the Fourier Transform Infrared Spectroscopy (FTIR) in association with Principal Components Analysis (PCA) and hierarchical cluster analysis (HCA) as a method for monitoring the extent of oxidation degree of biodiesel in the low rate phase, before the end of the induction period, in which the changes in the physical properties as viscosity, mass density, and chain composition of the sample remain almost undetectable. A detailed investigation of thermo-oxidation of biodiesel is reported for a mixture of 50/50 percent of soybean oil and animal fat biodiesels. The biodiesel degradation was accelerated maintaining the temperature of the sample at 110o C under
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constant air flux for different times. Oil stability index, mass density, viscosity, gross caloric value, esters composition, UV-VIS and FTIR spectra were measured in order to analyze the degree of degradation of each sample. The multivariate analysis in the FTIR spectra clearly shows the discrimination of the samples in the first stage of the degradation process. These results could be useful as a method for monitoring the fuel quality during the storage, helping among fuel producers, suppliers, and users.
Introduction Biodiesel derived from vegetable oil or animal fats is an alternative source of energy to substitute petroleum fuels. The main advantage of biodiesel is its sustainable eco-friendly nature reducing the environmental impact in comparison with conventional diesel fuel, presenting a possible net negative carbon dioxide balance. 1 Biodiesel is non-toxic and presents high viscosity, providing better lubrication to engines than mineral diesel. Although biodiesel produces about 10% less energy than petroleum diesel, its actual performance in the engine is practically the same in terms of power output and torque. Biodiesel consists of esters produced by transesterification of vegetable oils or animal fat triglycerides. Oxidation process is one of the major issues influencing biodiesel oxidative stability, and can be affected by a large number of factors including fuel composition, storage conditions, contaminants, temperature and presence of air and light. Various aspects of biodiesel stability have been reported describing the significance of oxidation stability, its oxidation chemistry, the methods used for characterizing stability, the factors known to influence stability, and consequences of biodiesel oxidation in diesel engines. 2–4 The oxidation could be in principle observed by measuring a number of physical properties such as mass density, viscosity, gross caloric value, peroxide index, esters composition, etc. In terms of oxidative evaluation, the Rancimat method is one of the most popular methods used to determine the oxidation stability by accelerating the aging process of the sample by exposing it to heat and increased volumes of air. The method measures the time that 2 ACS Paragon Plus Environment
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passes until oxidation takes place at a high rate - the induction time or oxidation stability index (OSI). However, the oxidation process characterization involves the study of full modification in the samples properties and composition. As this process is non-linear, the simple measurement of a specific property do not necessarily describe the degree of degradation. The early stages of oxidation typically follow first order reaction kinetics, in which quality parameters such as mass density, acid values, and viscosity remain almost unchanged. At the final phase, where the oxidation takes high rate, the changes in the physical parameters are significant and easily detected. Maintaining and monitoring the biodiesel fuel quality during storage presents a concern among fuel producers, suppliers, and users. In this direction, the availability of quick tests for the determination of the degradation degree represents an important step towards the improvement of biodiesel handling and trading. Raman, IR, and UV-Vis spectroscopies have already become very widespread techniques in the field of characterization and analysis of biofuels. For instance, 5,6 FTIR was used in conjunction with principal components analysis (PCA) and hierarchical cluster analysis (HCA) to classify biodiesels produced from different vegetable oils. The results showed that it is possible to develop a reliable and rapid methodology to identify used vegetable oils with raw materials in biodiesel production by applying the unsupervised techniques of multivariate analysis to the data. HCA and PCA were also used in the analysis of gas chromatography as a tool to classify/analyze biodiesels for chemical information. 7,8 Multivariate analysis was also used for predicting water content in biodiesel, 9 to monitor and quantify transesterification reaction, 10 in H-NMR spectra of fatty esters and biodiesels to infer the corresponding cetane number, 11,12 to associate and discriminate samples for potential use in forensic and environmental applications, 13 and for biodiesel/diesel blend classification. 14,15 Recently, the change of the dielectric property was found to be consistent with the Rancimat conductivity, infrared peak area, ultraviolet absorbance, and the residual mass during the degradation process. 16 In this work, FTIR spectroscopy in association with multivariate analysis is used to
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differentiate the degradation degree of a commercial biodiesel in the low rate phase, before the end of the induction period. In this phase, the changes in the physical properties such as viscosity, mass density, and chain composition of the sample remain almost undetectable. The accelerated degradation is induced at the temperature of 110o C under constant air flux for different time periods. A set of physical properties is determined in order to analyze the degree of degradation of each sample. Measurements of OSI, mass density, viscosity, caloric power, esters composition, UV-VIS/FTIR spectra are performed and the results used to analyze the oxidation stability of biodiesels. The PCA shows that the first three components are sufficient for a complete discrimination of the degradation dynamics, especially in the low rate phase of the degradation process. So far as we know, similar work has not yet been reported.
Experimental Section Samples of commercial biodiesel were provided by BSBios Inc. with composition of 50/50 percent of soybean oil and waste animal fat from meat-processing industries. This biodiesel presents mostly fatty acid group with 16- and 18-carbon chain lengths (17.4% of palmitic acid, 31.3% of oleic acid, 30.6% of linoleic acid). The effects of the oxidation process were investigated maintaining ten samples under accelerated degradation conditions for different times. The thermo-degradation was carried out at 110o C under constant air flux of 10L/h for 1, 2, 3, 5, 7, 9, 12, 15 and 18 hours using the Rancimat method (892 Professional Rancimat, Metrohm). The high temperature accelerated the biodiesel degradation due to the enhancement in the rate of oxidation. These samples were used as stock for analysis. The oil stability index (OSI) or induction time was measured by the Rancimat method. The method is based on the plot of conductivity versus time and the inflection point is used to define the OSI time, according to the technical norm EN14112. The mass density and the viscosity were recorded by a densimeter (Aton-paar DMA 5000)
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and a rheometer (Brookfield DV-III) coupled to a heat controller, respectively, according to the technical norms ASTM D4052 and D445. The gross calorific value or combustion power of the samples was obtained using a calorimeter (IKA Works C-2000) following the ASTM D240 norm. The tests were performed with approximately 0.5g of sample, which was analyzed in dynamic mode at 40o C and 15 bars of oxygen pressure with an accuracy of 0.1o C. Fatty acid methyl esters of the biodiesel were separated by gas chromatography (GC) (Perkin Elmer Clarus 680) equipped with a flame ionization detector (FID) and a fused-silica capillary column (100m, 0.25mm i.d. and 0.25µm of polysiloxane, Select FAME CP-7420, Agilent Technologies). The operation parameters were as follows: detector temperature, 275o C; injection port temperature, 240o C. Initially, the column temperature was held at 80o C for 1min. Subsequently, the temperature was increased to 160o C at a rate of 20o C/min, and then to 198o C at a rate of 1o C/min. After this period, it was once again raised to 250o C at a rate of 5o C/min for 5min, totalizing 58min of chromatographic run. The carrier gas flow (helium) was 1.1mL/min. The sample split ratio was 1 : 100. For identification, the retention times of the fatty acids were compared to those of standard methyl esters (Sigma, St. Louis, MO) and commercial oils of known composition, such as chia and soybean oils. Retention times and peak area percentages were automatically computed by a software (TotalChrom, Perkin Elmer). The main fatty acids compositions of all samples are shown in Table 1. The UV-Vis spectra were recorded by a spectrophotometer (T90+UV/Vis, PG Instruments Limited) with a precision of 0.3 nm from 300 nm to 700 nm with a step of 0.5 nm at 25o C. The samples were held in a 0.2 mm thick quartz cuvette. A FTIR spectrometer (PerkinElmer model Spectrum 400) was used to detect the infrared absorption of biodiesel using a Universal Attenuated Total Reflectance (UATR-FTIR) sensor, from 4, 000 cm−1 to 600 cm−1 , with a resolution of 4 cm−1 and 32 scans. To remove noise the spectra were then treated using first derivative procedure with a first-order polynomial. Mean-centered data were used as pre-processing tools for multivariate analysis. To obtain
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a simplified and comprehensive two-dimensional view of the relationships that exist among various thermo-degraded samples, PCA 17,18 and HCA were carried out in this work. Both PCA and HCA were performed with Mathematica 7.0 software by using the Multivariate Statistics Package and Hierarchical Clustering Package. For PCA and HCA the Agglomerate method to find clustering hierarchically, with the Chessboard distance, was used.
Results and Discussion The oxidation induction time for the undegraded sample was measured following the standard technical norm EN14112 based on the analysis by the Rancimat instrument at 110o C. This value was calculated as the maximum change in the rate of oxidation defined by the maximum of the second derivative of the conductivity versus time curve, as showed in the inset of Fig. 1. At about 12h, the oxidation starts at a high rate - a period whose termination is defined by the detection of secondary decomposition products. The OSI time measured using the Rancimat method as a function of temperature is plotted in Fig. 1 (a) and in logarithm scale in (b). The results follow the model ln(OSI) = B0 + B1 T −1 , where T is the absolute temperature in K and B0 and B1 are constants. 19 The parameter B1 is related to the reaction activation energy, Ea (kJ/mol), by Ea = Rg B1 , in which Rg is the gas constant. The regression analysis shows a linear correlation (R2 = 0.99), yielding Ea = 77.8kJ/mol, which is in agreement with the literature value for fatty acids and ester obtained by isothermal differential scanning calorimetry. 20 The result provides a correlation for estimating OSI as a function of temperature, although an extrapolation of OSI estimation to reasonable storage temperatures is more problematic. 19 Figure 2 presents the values of mass density, kinematic viscosity, and gross calorific value for all the samples. All the properties present almost no variation for the samples under thermo-degradation time of up to 9 hours. After 9 hours, the changes in mass density and viscosity become apparent. At 12 hours, the measured values are outside the limit
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Figure 1: Rancimat test for cell conductivity with time displaying oxidations stability time for the fresh biodiesel. (a) The OSI time measured using the Rancimat method for the undegraded sample as a function of temperature. (b) OSI in logarithm scale. Inset shows Rancimat test for cell conductivity in time at 110o C, following the EN14112 norm. values allowed for commercial biodiesel, according to the technical norm EN14214:2012. A decreasing of gross calorific value after 9 hours of thermo-degradation is also observed. As biodiesel is oxidized, there is a loss of hydrogen molecules or addition of oxygen molecules to the fuel that contributes to the fast decreasing in the combustion power or the amount of energy released per mass unit. The same slow change in the early stage of oxidation followed by a fast change in the second stage of oxidation is observed as for the density and viscosity results. The slow change in the physical properties during the initial period of oxidation is a wellknown result. 21 During the initial stages of the oxidation of biodiesel, the methylene allyl and bis allyl groups are more active and interact more with the double bonds to produce a carbon free radical. The resulting radicals interact with oxygen causing the formation of peroxides for the propagation step. Peroxides propagate through the continuous abstraction of hydrogen from a carbon to form another carbon radical and a hydroperoxide (ROOH). The newly formed carbon free radicals are again combined with oxygen and the propagation 7 ACS Paragon Plus Environment
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process continues. This is a continuous chain process that concludes in the termination step; the reaction terminates when two free radicals react with each other to yield stable products. In the induction period, the concentration of hydroperoxide remains very low, given the oxidation stability of the fatty oil or biodiesel under stress conditions. After this period the ROOH level increases rapidly and properties of fatty oils and biodiesel fuels are
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depicted in Fig. 3. Table 1: Main esters composition of all thermo-degraded samples obtained by CG-FID analysis. Analitic 0h 17.4 11.7 30.6 31.3 3.5
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Figure 3: Principal changes in the hydrocarbon chain composition for the thermo-degraded samples obtained by gas chromatography with flame ionization detection - CG-FID. After the end of the induction period a large decreasing of linoleic and linolenic acids and a corresponding increasing in palmitic, stearic and oleic composition is observed. Although slight changes are noticeable in the physical properties in the first stage of the oxidation process, no clear information regarding the biodiesel degree of oxidation is ascribed. In this direction, a quick test to monitor the quality of biodiesel fuel during storage, especially in the first stage of oxidation, represents an important factor for the improvement of biodiesel 9 ACS Paragon Plus Environment
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handling, trading and use. The UV-Vis absorption results are shown in Fig. 4. The thermo-degraded time influence on the evolution of the absorption bands is prominent. The strong absorption in the region of 400−500 nm is predominantly a result of carotenoids present in the biodiesel samples. 22,23 The decreasing of absorption in the first stage of degradation, as shown in the inset for 450 nm and 480 nm, indicates a bleaching by carotenoid loss in the samples. Despite the reduction of the optical absorption in the first stage of oxidation, the use of UV-Vis spectroscopy for identification of oxidative stability depends on the feedstock of the corresponding biodiesel. For this particular composition, the absorption measurements in the range of 400 − 500 nm seems to represent an easy, fast and non-expensive method to monitor the fuel quality during the storage period. However, the degradation of carotenoids in the sample could not necessarily give a direct correlation with the biodiesel oxidation, especially since the biodiesel degradation can be affected by a large number of factors, not only by thermal degradation. 3.0
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Figure 4: UV-Vis spectra of thermo-degraded biodiesel for different times. The arrow represents the increasing degradation time (0, 1, 2, 3, 5, 7, 9, 12, 15 and 18 h). The inset shows the decreasing of absorption in the first stage of degradation for the 450 nm and 480 nm, indicating a bleaching by carotenoid loss.
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FTIR spectroscopy gives the characteristics of functional groups that constitute the components in the samples. For qualitative analysis, the mid-IR region (4000 − 400 cm−1 ) gives a fingerprint of functional groups present in the biodiesel. However, instead of a detailed analysis of each specific peak, a global analysis considering the whole spectrum can be obtained with the chemometric method. For instance, the mid-IR region spectroscopy is found to be efficient in the classification of oils and can be used as a rapid and simple discriminant analysis for oils and fats. 24 Here, we show that FTIR spectroscopy associated with chemometric analysis is also a powerful tool for monitoring or investigating biodiesel oxidation. It allows for the assessment of the relative oxidative state of a biodiesel sample, including the first stage, in which the main physical properties present slow variation. FTIR spectra are presented in Fig. 5. The curves are quite similar to one another, making it difficult to identify differences among the samples by simple inspection. This characteristic situation can commonly be addressed using principal components analysis. Additionally, hierarchical cluster analysis can also be used to monitor the biodiesel degree of oxidation. 100 Transmittance (%)
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Figure 6 shows the results from PCA analysis. The PCA is a statistical technique that uses an orthogonal transformation to convert a large amount of observations in a set of non 11 ACS Paragon Plus Environment
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correlated values, known as principal components. The PCA scores plot, PC1 vs. PC2 (PC1 contains 77% of the variance between the data sets and PC2 12% of variance), gives a clear characteristic discrimination from samples in the first stage process of degradation (negative values of PC1) from samples in the second stage of degradation (samples with large variation in physical properties). The two stages appear to be well separated from one another, suggesting that the degradation after the first stage has significant changes in chemical bonds compared to that observed in the second stage of degradation. In addition, the plot of PC1 versus PC3 (5% of variance) gives a increasing discrimination for the sample in the first stage of degradation, in which the change in the physical properties as viscosity, density, and chain composition of the sample remain almost undetectable. Note that the three first components contain 94% of the total variance, showing that with this orthogonal transformation of the PCA method almost all information of FTIR spectra are captured in the first components. A simple spectroscopic analysis taking a specific peak, as performed in Ref., 16 was not able to discriminate the degradation evolution in the low rate phase.
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Figure 6: PCA scores plot (P C2 × P C1 and P C3 × P C1) obtained from FTIR spectra of thermo-degraded biodiesel for different times at 110o C. Negative values of P C1 and increasing values of P C3 discriminate the samples in the low rate phase of the degradation process. Figure 7 shows the dendrogram plot of the statistical distance for the correlation matrix 12 ACS Paragon Plus Environment
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for all FTIR spectra. One can observe the increasing statistical distance (vertical amplitude in the plot) from the sample before the fast degradation process (0h to 9h) to the full degraded times (12h-18h). The results are in total agreement with the PCA scores plot, and is an additional tool for monitoring the dynamic evolution of thermo-degradation process. Note that this method also takes a global information from the FTIR spectrum without the need for analysis of specific peaks. The cluster analysis technique for data classification was used. Data elements are partitioned into groups called clusters that represent proximate collections of data elements based on a distance function. The partition data into exactly n lists of similar elements is found by clustering hierarchically. Increasing n leads to an increasing classification in the degradation. For instance, the gray area in Fig. 7 represents high light level n = 4. Additional sub-options methods are available to allow for more control over the clustering. For a given set of data and distance function, the choice of the best number of clusters may be unclear. A Significance Test can be used to determine statistically significant clusters to help choose an appropriate number. A possible value of Significance Test is Silhouette. The Silhouette test subdivides the data into successively more clusters looking for the first minimum of the silhouette statistic.
Figure 7: Dendrogram plot of a Hierarchical Cluster Analysis obtained from FTIR spectra of thermo-degraded biodiesel showing the statistical distance between samples. The increasing in the hierarchical distance is observed in function of thermo-degradation time.
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Conclusions To summarize, the chemometric techniques in association with FTIR spectroscopy proved to be a useful tool to monitor the evolution of the degradation process in biodiesel by taking an overall description of the evolution of the degradation. Measurements of OSI time, mass density, viscosity, gross calorific value, FTIR and UV-Vis spectra were employed to study thermo-degraded biodiesel. Upon comparing the samples at different thermo-degradation times, it becomes evident that it is not possible to determine the degradation evolution in the low rate phase only by monitoring the physical changes on the samples. The application of principal component analysis allows us to locate the thermo-degradation classification of the biodiesel samples, giving a clear discrimination on the stage of degradation. The spectral fingerprints generated by FTIR in addition to the chemometric techniques of PCA and HCA are sufficient information to differentiate the biodiesel stages of degradation and may help maintaining and monitoring fuel quality of biodiesel during the storage. The present paper suggests that it is possible to develop a methodology to identify the degree of degradation for biodiesel sample helping among fuel producers, suppliers, and users.
Acknowledgement The authors acknowledge the support from the Brazilian agencies CAPES, CNPq, and Fundação Araucária, and thank BSBios Inc. for providing the samples.
References (1) Demirbas, A. Political, Economic and Environmental Impacts of Biofuels: A Review. Appl. Energy 2009, 86, S108-S117. (2) Siddharth, J.; Sharma, M. P. Review of Different Test Methods for the Evaluation of Stability of Biodiesel. Renew. Sustain. Energy Rev. 2010, 14, 1937-1947. 14 ACS Paragon Plus Environment
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