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Green chromatography determination of fatty acid methyl esters in biodiesel a

b

b

Carlos Molina Mayo , Andrea Brito Alayón , María Teresa García Rodríguez , Ana Isabel a

a

Jiménez Abizanda & Francisco Jiménez Moreno a

Departamento de Química Analítica, Nutrición y Bromatología, Facultad de Química, Universidad de La Laguna (ULL), Avenida Astrofísico Francisco Sánchez, s/n. 38201 La Laguna (Tenerife, Islas Canarias), España; b

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Departamento de Ingeniería Química y Tecnología Farmacéutica, Facultad de Química, Universidad de La Laguna (ULL), Avenida Astrofísico Francisco Sánchez, s/n. 38201 La Laguna (Tenerife, Islas Canarias), España Accepted author version posted online: 10 Feb 2015.Published online: 10 Mar 2015.

To cite this article: Carlos Molina Mayo, Andrea Brito Alayón, María Teresa García Rodríguez, Ana Isabel Jiménez Abizanda & Francisco Jiménez Moreno (2015): Green chromatography determination of fatty acid methyl esters in biodiesel, Environmental Technology, DOI: 10.1080/09593330.2015.1016121 To link to this article: http://dx.doi.org/10.1080/09593330.2015.1016121

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Environmental Technology, 2015 http://dx.doi.org/10.1080/09593330.2015.1016121

Green chromatography determination of fatty acid methyl esters in biodiesel Carlos Molina Mayoa , Andrea Brito Alayónb , María Teresa García Rodríguezb , Ana Isabel Jiménez Abizandaa and Francisco Jiménez Morenoa∗ a Departamento

de Química Analítica, Nutrición y Bromatología, Facultad de Química, Universidad de La Laguna (ULL), Avenida Astrofísico Francisco Sánchez, s/n. 38201 La Laguna (Tenerife, Islas Canarias), España; b Departamento de Ingeniería Química y Tecnología Farmacéutica, Facultad de Química, Universidad de La Laguna (ULL), Avenida Astrofísico Francisco Sánchez, s/n. 38201 La Laguna (Tenerife, Islas Canarias), España

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(Received 27 November 2014; accepted 18 January 2015 ) This work proposes a green, simple and rapid chromatographic methodology for separation and determination of a group of 13 fatty acids methyl esters (FAMEs) by using a capillary gas chromatography with a flame ionization detector. The method was successfully applied for the determination of FAMEs in biodiesel samples from commercial and waste cooking oils, synthesized by homogeneous catalysis. Detection and quantification limits were in the μg L−1 level. Direct injection of sample solution was compared with solid-phase extraction and solid-phase microextraction procedures, giving similar results. The lower analysis time represent considerable improvement compared with other papers. The described methodology is especially suitable for process control applications. The samples analysed showed total contents of FAMEs higher than 96.5%, which verifies the European regulations. Keywords: biodiesel; fatty acids methyl esters; gas chromatography; transesterification; flame ionization detector

1. Introduction The critical situation regarding energetic resources that have been widespread and worldwide all along the last years, due to the diminution of natural resources and the increase of the environmental problems, has led to the search for alternative fuels, which should be easily available, environmentally sustainable and friendly, and technically and economically competitive.[1–4] For the so-called developed countries, fuels with a biological origin, such as alcohols, vegetable oils, biomass, biogas, synthetic fuels and so on, are becoming increasingly important. Therefore, it seems necessary to develop alternative fuels, which must present similar features to conventional fuels, such as diesel, which is largely utilized in the transport, agriculture, commercial, domestic and industrial sectors for the generation of power or mechanical energy.[5] Between these alternative fuels, biodiesel obtained from vegetable oils is a promising, eco-friendly alternative to diesel fuel, and contributes to the reduction of greenhouse gases emissions, as well as other harmful emissions.[2,5–8] Biodiesel is a biodegradable, renewable and non-toxic diesel fuel, and typically produces less sulphur dioxide and about 60% less net carbon dioxide emissions than petroleum-based diesel. Furthermore, biodiesel reduces black smoke normally associated with diesel vehicles and other particulate matter emissions that cause respiratory tract damage.[9,10]

*Corresponding author. Email: [email protected] © 2015 Taylor & Francis

According to American Society for Standard Testing and Material (ASTM) specifications, biodiesel can be defined as the mono-alkyl fatty acid esters of long chain derived from renewable lipids such as vegetable or greasy oils of animals, which is used in compression ignition engines (diesel engines) or in heating boilers.[11] The main by-product of the transesterification reaction is glycerol, which is a valuable by-product, usually sold to the cosmetic industry in order to be used in soaps and other products.[12] There are several choices for vegetable oil sources,[13] such as sunflower, peanut, soybean, rapeseed, palm, olive, cottonseed, linseed, jatropha, coconut, pongamia, rubberseed, jojoba, waste cooking oil and so on.[14–17] Vegetable oils, which are composed of 98% triglycerides and small amounts of mono- and diglycerides, naturally fix the solar energy, have low sulphur contents and are renewable and widely available from a variety of sources. Triglycerides are esters formed by three molecules of fatty acids, with different carbon chain length and number of double bonds, and one molecule of glycerol, and they contain substantial amounts of oxygen in their structure.[18,19] Methyl esters from vegetable oils are the best substitutes for diesel since they do not require any adaptation in the diesel engine and present a high energetic yield.[20,21]

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Due to the increasing interest and use of alternative fuels, the assurance of their properties and quality has gained great interest for the successful commercialization and market acceptance of biodiesel.[22] Accordingly, biodiesel standards have been established or are being developed in various countries and regions around the world, including the ASTM (ASTM D 6751), European Standard (EN 14214, EN 14103), etc.[11,23,24] Thus, the European standard EN 14103 established that the esters total content in a biodiesel must be 96.5%, in order to be suitable for diesel engines. In the case of Spain, biodiesel is regulated in Real Decreto (RD) 61/2006, of 31 January,[25] which describes the specifications of gasoline, diesel, industrial gases and liquefied petroleum. In this RD, the composition and properties are defined according to the standard EN 14214, with the exception of the iodine index, whose maximum value is found to be in 140 g iodine per 100 g of sample.[25] Several analytical methods have been developed for fuel quality assessment and production monitoring during the transesterification reaction for biodiesel production and characterization.[26,27] The most intensively studied methods have been gas chromatography (GC), highperformance liquid chromatography (HPLC), nuclear magnetic resonance (NMR) and Fourier transform infrared spectroscopy. Thus, Jin et al. reported a method to identify the methanolysis products of triglycerides with NMR technology,[28] while Oliveira et al. developed calibration models based on Fourier transform near infrared and Fourier transform infrared-attenuated total reflectance combined with partial least squares and artificial neural network analysis to determine the methyl ester contents in biodiesel blends.[29] Several authors have proposed analysis of biodiesel mixtures using non-aqueous reverse phase HPLC with different detection systems, such as ultraviolet spectroscopy,[30] refractive index[31] or evaporative light-scattering detector,[32] to carry out the separation and quantification of main fatty acids methyl esters (FAMEs) of biodiesel produced from vegetable and animal oils. GC has been the most widely used method for analysis of FAMEs in biodiesel samples, due to its higher accuracy in quantifying minor components. A GC-Mass Spectrometry technique has been used to analyse the composition of biodiesel samples, with the aim to optimize the synthesis process [33] and to identify fatty acids.[34] Even though the mass spectrometer is a highly selective detector, this type of instrumentation is costly and cannot be afforded by many laboratories. Therefore, the method most commonly used for the analysis of FAMEs in biodiesel samples is GC with a flame ionization detector (GC-FID). This technique has been used for the analysis of FAMEs existing on biodiesel produced from commercial and waste cooking oil in order to compare different transesterification conditions [35–37] or to study the kinetics of the biodiesel production reaction.[38] Modifications of the GC-FID methodology

by means of combination with solid-phase microextraction (SPME) [39] or ionic liquids [40–42] have also been reported, but these preconcentration methodologies imply longer sample preparation times. The aim of this work is the development of a simple, rapid and green method for the determination of FAMEs composition in biodiesel, avoiding any sample pretreatment, based on the GC-FID technique that can be used for quality control as well as for the characterization of biodiesel, which does not require special preliminary sample preparation. The analysis of complex matrices usually required tedious sample preparation procedures or the use of sophisticated techniques. In this study, an effective method for quantification of FAMEs is proposed using a small amount of samples that can be directly injected into the chromatographic system. Thus, the method requires less solvent and is not time-consuming since both chromatogram times are reduced and derivatization is not necessary. The method is applied for determination of FAMEs in biodiesel samples from different commercial and waste cooking oils. 2.

Experimental

2.1. Chemicals, reagents and standards Methanol ( > 99%), sodium hydroxide ( > 99%), orthophosphoric acid ( > 85%) and MgSO4 ( > 98%) were purchased from Merck (Darmstadt, Germany). All aqueous solutions were prepared using ultrapure water (18.2 M cm−1 ) from a Milli-Q system A10 (Millipore, Bedford, MA, USA). Table 1 shows FAMEs studied as well as the internal standard (methyl undecanoate). Liquid standard solutions of 10,000 mg L−1 were purchased from Accu-Standard (New Haven, USA), and were used without further purification ( > 99.0%). Standard solutions of 100 mg L−1 were prepared in n-hexane (Scharlau Chemie, Barcelona, Spain). Standard working solutions were prepared daily and then diluted with n-hexane up to the final concentration. The stock solutions and diluted standard solutions were stored in the dark at 4°C. 2.2. Oil samples Olive, sunflower, seeds, rape, corn and mixtures (soy– sunflower, olive–sunflower and olive–sunflower–corn) oils were studied. Two kinds of oil feedstock were used: commercial oil and waste cooking oil. Commercial oils were obtained from local markets, whereas waste cooking oils were collected from different sites: particular kitchens, restaurant kitchens of Chemistry Faculty and Pharmacy Faculty of La Laguna University (Tenerife, Canary Island, Spain) and restaurant kitchens of several schools (Tenerife, Canary Island, Spain). All oil samples were homogenized and vacuum filtered to remove food residues and solid precipitate before using. Waste oil samples were dehydrated

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Table 1.

Fatty acids methyl esters (FAMEs) studied.

Peak IUPAC name

Common name

Acronymun

1

Methyl decanoate

Methyl caprate

C10:0

*

Methyl undecanoate

Methyl undecanoate

C11:0

2

Methyl dodecanoate

Methyl laurate

C12:0

3

Methyl tetradecanoate

Methyl myristate

C14:0

4

Methyl hexadecanoate Methyl palmitate

C16:0

5

Methyl cis-9hexadecenoate

Methyl palmitoleate

C16:1

6

Methyl octadecanoate

Methyl stearate

C18:0

7

Methyl cis-9octadecenoate

Methyl oleate

C18:1

8

Methyl cis,cis-9,12octadecadienoate

Methyl linoleate

C18:2

9

Methyl cis-ciscis-9,12,15octadecatrienoate

Methyl linolenate

C18:3

10

Methyl arachidate

Methyl arachidate

C20:0

11

Methyl cis-11eicosenoate

Methyl eicosenoate

C20:1

12

Methyl docosanoate

Methyl behenate

C22:0

13

Methyl cis-13docosenoate

Methyl erucate

C22:1

Chemical formula

Note: *Internal standard.

with anhydrous MgSO4 to remove water from the frying process and vacuum filtered again in order to eliminate suspended matter and rest of MgSO4 . 2.3. Biodiesel synthesis Biodiesel was synthesized by transesterification with homogeneous alkaline catalysis from oil samples at atmospheric pressure and 65°C, by using a batch reactor that allows thermostatizing the process, equipped with a reflux condenser to avoid methanol losses. Thus, 600 ± 1 g of each oil sample was accurately weighed and placed into a

dry reaction flask cylindrical reactor. The catalyst consisted of a sodium methoxide solution, prepared by mixing 168 mL of methanol and 6 g of sodium hydroxide. This solution was prepared daily, in order to preserve the catalytic activity and to avoid dampness absorption. Oil samples were stirred and heated at 65°C in a water thermostatic bath, to keep the temperature constant throughout the reaction. Once this temperature was reached, the prepared catalyst was added into the reaction flask. The mixture was maintained at 65°C and stirred continuously at 1000 rpm for a predetermined reaction time of 80 min. The reaction flask was then removed from the water bath and reaction

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products were allowed to settle for 24 hours, in order to separate two immiscible liquid phases, the upper phase contains the synthetized products and the lower one contains rest of reagents which lacks interest for this study. The top phase is composed of biodiesel obtained (methyl esters), not reacted oil, methanol and catalyst in excess, glycerol, and a small amount of soap produced during the process. To remove the excess of catalyst, the crude ester was washed several times with a mixture of deionized water and phosphoric acid 5% (30 mL), until the washing water became clear. Excess of methanol and water in the ester were then removed by evaporation at atmospheric pressure in a centrifugal evaporator at 80°C. 2.4. Instrumentation A capillary gas-chromatographic system Varian 3900 (Palo Alto, CA, USA) was used to analyse the FAMEs, using a Varian Autosampler CP-8410 to carry out the injection of the samples, as well as a FID as a detection system. Separations were performed by using a CP SIL 88 column, from Varian (Palo Alto, CA, USA), with 50 m length, 0.25 mm internal diameter and 0.25 μm film thicknesses. Chromatographic signals were registered and processed using the Star Chromatography Workstation, version 6.00 software. 2.5. Chromatographic conditions Chromatographic operating conditions were the following: the injection was performed following split mode with a ratio of 1:20 and a sample size of 0.1 μL; helium was employed as the carrier gas, at a flow rate of 1 mL min−1 , while nitrogen was used as make up (30 mL min−1 ), with a constant column pressure of 28.1 psi; the detector and injector temperature were set at 250°C for all the experiments. Initially, the column temperature was set at 160°C for 1 min, and then a temperature program was applied. Firstly, the temperature was increased up to 170°C, by a temperature slope of 3°C min−1 , with a remaining time of 5 min. Then, 30°C min−1 temperature slope was applied up to 200°C and kept for 5 min, and finally, 10°C min−1 temperature slope was applied up to 210°C and kept for 5 min. Total run time was 19.25 min. 2.6. Statistics Statistical analyses, that is, linear regression and tests for intercept, slope, intra-day and inter-day repeatability were performed by the Statistica.[43] 3. Results and discussion 3.1. Chromatographic operating conditions In order to separate and determine simultaneously the FAMEs present in biodiesel samples obtained after

methanolysis reactions of vegetable oils (commercial and used) by capillary GC, with a FID, several experiments were carried out to find the suitable values of those parameters affecting the chromatographic separation, such as column head pressure, injector and detector temperature, injection volume and oven temperature program. An nhexane solution containing 100 μg mL−1 of each of the 13 FAMEs and 100 μg mL−1 of methyl undecanoate as an internal standard was prepared. A volume of 0.1 μL was injected into the chromatographic system. The effect of the column head pressure was assessed by the Van Deemter equation, which relates the column efficiency, expressed in terms of theoretical plate equivalent to height (H ) as a function of the average linear carrier gas velocity (¯u). The carrier gas velocity was varied between 18.5 and 140 cm s−1 , which is equivalent to a column head pressure between 30 and 230 kPa. Column head pressures higher than 100 kPa provided the lowest H values in most of the FAMEs studied. Therefore, 66.84 cm s−1 (100 kPa) was found as column head pressure for further experiments, since it provided a satisfactory column efficiency, with a low baseline noise and a good resolution. This column head pressure (100 kPa) involves a gas flow through the chromatographic column of 1.00 mL min−1 . The temperature in the injection area and in the FID detector must be maintained at a high enough value to avoid sample condensation, but being carefully controlled in order not to break thermally unstable components in the injection and not to damage the detector and increase the baseline noise. This parameter can affect retention times and peak areas. For injector, temperature was modified between 200°C and 280°C, and for FID between 200°C and 300°C. Retention times remained unaffected in both cases, while the peak areas increased when the injector temperature was increased up to 250°C, and from this temperature value decreased slowly. Therefore, a temperature of 250°C was selected for injector and for FID detector in order to obtain high sensitivity and low noise levels. Different sample aliquots from 0.1 to 1 μL were injected into the GC system. A volume of 0.1 μL was selected because this small sample volume allowed achieving a good sensitivity and a low baseline noise and it is very convenient for routine analysis as a small amount of solvents are required, which result in a lower cost and as well as a lower analysis time. Several experiments were carried out in order to find an oven temperature program that provided a quantitative separation of the 13 FAMEs studied, including the internal standard (methyl undecanoate). Steps and main features of the three temperature programs assayed are summarized in Table 2 and chromatograms obtained are shown in Figure 1. In Figure 1(a), chromatogram with Program 1, it can be noticed that methyl linolenate (peak 9) and methyl eicosenoate (peak 11) appear to overlap, so this temperature program did not lead to a baseline separation

Environmental Technology Table 2. Oven temperature programs.

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Program Step Ti (°C) Tf (°C) T (°C)/min 1

1 2 3

150 150 170

− 170 200

2

1 2 3

160 160 170

− 170 200

3

1 2 3 4

160 160 170 200

− 170 200 210

− 4 2 Total run time − 3 3 Total run time − 3 30 10 Total run time

5

(a) Remaining t (min) 1 5 5 30 1 5 5 20 1 5 5 5 19.25

(b)

Notes: Ti , initial temperature and Tf , final temperature.

of the FAMEs studied. Besides, methyl behenate (peak 12) and methyl erucate (peak 13) appear after more than 20 min, implying a large analysis time. The following temperature program tested gives the chromatogram of Figure 1(b). The short analysis time did not allow the identification of all the FAMEs studied, since the chromatogram finished before peaks 12 and 13 appeared, probably because not a high enough temperature is reached. Furthermore, methyl linolenate (peak 9) and methyl eicosenoate (peak 11) appear to overlap again. A chromatogram obtained under the third temperature program, including a new step in which the temperature rises to 210°C, is shown in Figure 1(c). As it can be noticed, the separation of the 13 FAMEs, together with the internal standard, achieved, under these chromatographic experimental conditions, provided a satisfactory resolution between peaks and high efficiencies for an analysis time less than 17 min. This analysis time is considerably less than those proposed by other authors.[34,35] Therefore, this oven temperature program was found for further experiments on biodiesel samples.

3.2.

Analytical characteristics of the chromatographic method The relative peak area (detector response) was linearly dependent on sample concentration over the range of concentration studied. Calibration curves were obtained by injecting three replicates of seven different levels of standard solutions of each FAMEs at a working range of 0.5–500 mg L−1 (0.5, 50, 100, 200, 300, 400 and 500 mg L−1 ). All solutions contained 100 mg L−1 of internal standard (methyl undecanoate). The figures of merit of the calibration graphs obtained by applying lineal regression are shown in Table 3. A satisfactory linearity, with correlation coefficients (R2 ) higher than 0.9989, was observed in all cases.

(c)

Figure 1. Chromatograms obtained under the oven temperature programs in Table 2. (a) Program 1; (b) Program 2; and (c) Program 3.

As in this chromatographic method, the signal from the blank was negligible, limits of detection (LODs) and limits of quantification (LOQs) were calculated by multiplying by 3 and 10, respectively, the standard deviation obtained by injecting 10 replicates of the solution with the lowest concentration used to find the calibration curves. LODs and LOQs for each FAME, given in Table 3, show that LOD was between 133 μg L−1 for methyl eicosenoate and 233 μg L−1 for methyl stearate, and LOQ between 443 μg L−1

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Table 3. Figures of merit for the calibration lines (y = a + bx) for the GC-FID developed method. Peak

FAME

tR (min)

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

C10:0 C12:0 C14:0 C16:0 C16:1 C18:0 C18:1 C18:2 C18:3 C20:0 C20:1 C22:0 C22:1

4.933 5.766 7.211 8.910 9.548 10.791 11.528 12.741 14.220 13.242 14.070 15.913 16.873

(b ± S b) ·10−3 11.5 11.5 10.7 10.6 10.2 8.9 9.2 8.9 8.6 8.8 9.3 7.6 7.8

± ± ± ± ± ± ± ± ± ± ± ± ±

0.3 0.2 0.4 0.3 0.2 0.3 0.3 0.3 0.1 0.3 0.3 0.1 0.2

(a ± S a) ·10−3

S y/x

R2

LOD (μg L−1 )

LOQ (μg L−1 )

± ± ± ± ± ± ± ± ± ± ± ± ±

0.1316 0.0967 0.1498 0.1091 0.0975 0.1265 0.1127 0.1360 0.0546 0.1234 0.1223 0.0570 0.0825

0.9985 0.9986 0.9982 0.9989 0.9986 0.9985 0.9994 0.9987 0.9992 0.9986 0.9986 0.9989 0.9988

136 137 138 177 164 233 202 197 154 212 133 141 175

453 458 460 591 547 776 674 657 515 707 443 469 583

99 46 141 102 81 142 77 130 70 138 94 75 92

1 7 11 8 8 10 9 11 4 10 9 4 6

Notes: tr , internal standard = 5.29 min. tR , migration time; S y/x , standard deviation of regression; R2 , determination coefficient; LOD, limit of detection; and LOQ, limit of quantification. Table 4. Precision and accuracy for the GC-FID developed method. Intra-day (repeatability) % RSD (n = 3)

Inter-day (reproducibility) % RSD (n = 9)

Peak

FAME

Spiked amount (μgL−1 )

tr

Area

tr

Area

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

C10:0 C12:0 C14:0 C16:0 C16:1 C18:0 C18:1 C18:2 C18:3 C20:0 C20:1 C22:0 C22:1

170 200 205 175 200 300 290 350 345 270 170 190 240

0.03 0.03 0.04 0.05 0.05 0.05 0.04 0.05 0.05 0.04 0.04 0.05 0.05

1.9 2.5 2.2 2.2 2.1 2.6 2.7 2.6 1.9 2.4 2.3 1.9 2.3

0.07 0.10 0.13 0.07 0.07 0.11 0.12 0.08 0.13 0.07 0.09 0.10 0.10

3.0 5.1 5.5 4.6 6.2 6.3 6.6 6.7 5.0 4.8 6.7 5.6 5.1

for methyl behenate and 776 μg L−1 for methyl stearate, which represent a suitable approach to this kind of analysis. The precision of the chromatographic method developed was expressed in terms of relative standard deviation (% RSD). The performance of the method was tested by a repeatability and reproducibility study at three concentration levels (5, 25 and 75 mg L−1 ), carrying out three consecutive injections of a standard solution of FAMEs in the same day (n = 3) and three different days (n = 9). The results obtained for a concentration of 25 mg L−1 are shown in Table 4. As it can be seen, % RSD values were less than 0.05% for retention times and less than 2.6% for peak areas in intra-day study (repeatability). In the case of inter-day study, % RSD values were less than 0.13% for retention times and less than 6.7% for peak areas (i.e. reproducibility). Therefore, it can be stated that the chromatographic method developed presents an acceptable repeatability and reproducibility.

Recovery (R) (%) 98.3 97.6 98.8 99.2 97.4 100.9 98.2 102.2 100.3 99.5 98.6 97.7 100.6

± ± ± ± ± ± ± ± ± ± ± ± ±

0.1 0.2 0.2 0.1 0.3 0.1 0.2 0.1 0.1 0.2 0.2 0.3 0.1

The accuracy of the method was assessed by carrying out a recovery test of the 13 FAMEs, which was performed by adding known amounts of the FAME standards to biodiesel samples obtained after the transesterification reaction. FAMEs spiked amounts, as well as the mean recoveries (%) and % RSD values obtained, are summarized in Table 4. Satisfactory recoveries were obtained, ranging between 97.4% for methyl palmitoleate and 102.2% for methyl linoleate. Finally, uncertainty was calculated following the guidance of European Analytical Group contained in the document ‘Guide for the expression of uncertainty in measurement’.[44] The estimated uncertainty was ± 3.2%, calculated for a coverage factor of 95% (k = 1). All the previous parameters are in accordance with the European Rule, EN-14103.[24] The previous results are lower than those reported by other authors for the determination of FAMEs in biodiesel samples by GC-FID. Table 5 summarizes some of the

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Environmental Technology Table 5.

Comparison of the main features of the proposed method with the literature.

Technique HPLC-RID HPLC-ELSD HS-SPME-GC GC-FID GC-FID UPLC-ELSD GC-FID GC-FID

V (μL)

Number of FAMEs

t (min)

LOD (mg L−1 )

RSD (%)

R (%)

Reference

20 50

6 13 6 9 13 11 30 13

14 36 35 8 10 5 30 19

2.0–4.0 0.11–1.10 0.3–0.6 5.2 1.1–2.8 13–580 0.28–0.93 0.13–0.23

0.15–3.2 3.0–10.0 6.9–16 2.9–6.1 2.3–4.5 2.1–6.4

98–105

[31] [32] [40] [45] [46] [47] [48] This paper

1 1 2 2 0.1

0.13–6.7

70–106 98 97–101 91–98 97–103 97–102

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Notes: GC-FID, gas chromatography-flame ionization detector; HPLC-RID, high-performance liquid chromatographyrefractive index detector; HPLC-ELSD, high-performance liquid chromatography-evaporative light-scattering detector; HS-SPME-GC, head space-solid-phase microextraction-gas chromatography; and UPLC-ELSD, ultra-performance liquid chromatography-evaporative light-scattering detection.

main features of analytical methods described in the literature. It can be seen that results obtained in this work are lower in all cases than those obtained by other authors, probably because of the proper optimization of the experimental conditions, and overall the small volume (0.1 μL) of sample injected without any pretreatment.

3.3.

(a)

Application to biodiesel samples

The chromatographic separation developed was applied to carry out the analysis of the FAMEs contained in different biodiesel samples, obtained from the alkali-catalysed transesterification reaction with methanol, as it was described in Section 2. Some experiments were carried out in order to find the best conditions to extract the FAMEs to be determined. Thus, solid-phase extraction (SPE), SPME and direct injection of the samples were compared. SPE allows both preconcentration and purification of samples. Oasis-HLB and Sep-Pak-Plus SPE cartridges were tested, with different conditions for activation and dry, as well as for the elution of FAMEs retained. Sep-Pak-Plus gave the highest percentages. In the case of SPME, three kinds of fibres were assayed, polydimethylsiloxane-divinylbenzene, polydimethylsiloxane (PDMS) and polyamide, corresponding to the best results of the PDMS fibre. Figure 2 shows the chromatograms obtained for the direct injection in the chromatographic system of 0.1 mL of biodiesel sample diluted in n-hexane (1:16) (Figure 2(a)), and after the treatment with the Sep-Pak-Plus cartridge for SPE (Figure 2(b)) and PDMS fibre for SPME (Figure 2(c)). As can be seen, results obtained were similar in all the cases, so the use of SPE and SPME was discarded because extraction time was high in both cases and there are no significant improvements in the percentages of FAMEs obtained. One hundred micro litre of biodiesel samples prepared from commercial and waste cooking oil were diluted appropriately with n-hexane (1:16), and 0.1 μL were directly injected into the chromatographic system.

(b)

(c)

Figure 2. Chromatograms obtained for a biodiesel sample: (a) Direct injection; (b) Sep-Pak-Plus SPE cartridge; and (c) PDMA SPME fibre (*Internal standard).

The chromatograms obtained for biodiesel produced from commercial oils (sunflower and olive samples) are shown in Figure 3(a). It can be seen that in the biodiesel obtained

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(a)

(b)

Figure 3. Chromatograms obtained for biodiesel samples prepared from: (a) commercial olive and sunflower oils and (b) waste cooking olive and sunflower oils.

from olive oil the main ester is methyl oleate (peak 7), followed by methyl palmitate (peak 4) and traces of methyl palmitoleate (peak 5), methyl stereate (peak 6) and methyl linoleate (peak 8), while biodiesel from sunflower oil is formed mainly by four FAMEs, namely methyl palmitate (peak 4), methyl oleate (peak 7) and methyl linoleate (peak 8), and in less proportion methyl stereate (peak 6). Figure 3(b) shows the chromatograms corresponding to biodiesel samples from waste cooking olive and sunflower oils. It can be noticed that profiles of chromatograms of commercial and used oils from the same source are practically the same, although in the biodiesel sample from waste cooking olive oil there are traces of methyl palmitoleate (peak 5) and methyl linolenate (peak 9). These results are in accordance with the major fatty acids present in commercial oils. According to the calibration curves, FAME contents were calculated and expressed as a mass fraction of the total FAME content (%). The percentages of each of the FAMEs in biodiesel samples from commercial and waste cooking olive (O), sunflower (SF), seeds (S), rape (R), corn

(C) and mixtures (soy–sunflower, SSF, olive–sunflower, OSF and olive–sunflower–corn, OSFC) oils are shown in Table 6. The same behaviour, concerning the biodiesel from commercial and waste cooking oils, observed in chromatograms in Figure 3 is observed in all types of biodiesel studied, and percentages of FAMEs in biodiesel from commercial oil are slightly higher than those from waste cooking oils. Thus, in biodiesels from olive oil, as it can be expected, the main FAME is methyl oleate (C18:1), with percentages of 84.7 and 84.1 for biodiesel from commercial and waste cooking oil, respectively. In biodiesel mixtures involving olive oil, this ester is also the most abundant (69.7% for OSF and 78.2% for OSFC). Methyl palmitoleate (C16:1) and methyl linolenate (C18:3) only have been found in those biodiesels and methyl linolenate (C18:3) also in the biodiesels from SSF*. FAME found at higher concentration in the rest of biodiesel was the methyl linoleate (C18:2) with values around 60% in all cases. Methyl palmitate (C16:0) is present in all the biodiesels, and has values from 5.83% in SF* to 10.85% in S*. Methyl stereate has percentages between 0.55 and 2.18. Methyl arachidate (C20:0) presents percentages underneath 0.83% and is only present in biodiesels involving olive and soy oils. Finally, methyl behenate (C22:0) only has been found in biodiesels from seeds oil, 0.12% when the biodiesel derived from commercial oil, and 0.85% in the case of used oil (these data were not included in Table 6). Table 6 also summarized the total percentage of FAMEs in biodiesels, showing that the FAMEs content were always higher than 99%, with the exception of the biodiesel from used rape oil and olive–sunflower oil. Total percentages in all cases surpassed the values found in EN 14103:2003.[24] This fact highlights the esterification reaction that has been almost complete and it can be related to a performance for the biodiesel synthesis above 80% (last column in Table 6). 4. Conclusions A GC-FID method that permitted the quick and feasible determination of FAMEs in biodiesel samples obtained by the alkali-catalysed transesterification reaction of vegetable and waste cooking oils is proposed. The method allows separating a group of 13 FAMEs with a baseline resolution, by direct injection of the sample, without any previous treatment, with the analysis time of 17 min. The direct injection of a very small volume of sample without any tedious pretreatment often required for these complex matrices entails not only shorter analysis times but also reduction of potentially toxic reagents, so the method can be considered suitable for the environment. Furthermore, the detection limits obtained as well as the accuracy, precision and percentages of recuperation improve those given by other authors, which represent a suitable approach to

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Environmental Technology

Table 6. Composition, expressed as % (mean ± standard deviation, n = 3), obtained for the different biodiesel samples analysed by the GC-FID method. FAME (%) C16:0

C16:1

C18:0

C18:1

C18:2

C18:3

C20:0

C20:1

4

5

6

7

8

9

10

11

0.12 ± 0.03 0.21 ± 0.02 – – – – – – – – – 0.15 ± 0.01 0.75 ± 0.03 0.86 ± 0.02

– – ± ± ± ± ± ± ± ± ± ± ± ±

0.15 ± 0.01 0.35 ± 0.02 – – – – 0.18 ± 0.01 0.83 ± 0.02 – – 0.51 ± 0.01 0.43 ± 0.02 0.12 ± 0.01 0.21 ± 0.02

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Peak Oil O O* SF SF* S S* R R* C C* SSF SSF* OSF* OSFC*

9.5 9.1 6.59 5.83 9.04 10.85 10.79 8.21 10.79 7.53 10.83 9.46 8.8 9.6

± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.3 0.4 0.07 0.05 0.03 0.01 0.06 0.09 0.04 0.09 0.07 0.09 0.9 0.1

0.26 ± 0.04 0.19 ± 0.03 – – – – – – – – – – 0.36 ± 0.05 0.26 ± 0.03

1.47 1.61 1.52 0.94 1.34 1.63 0.87 0.55 0.89 0.83 1.95 2.18 1.82 0.75

± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.03 0.04 0.05 0.02 0.02 0.07 0.04 0.06 0.02 0.04 0.08 0.05 0.07 0.01

84.7 84.1 25.4 30.5 25.6 27.5 26.9 25.3 28.2 31.9 22.3 21.7 69.7 78.2

± ± ± ± ± ± ± ± ± ± ± ± ± ±

1.4 1.6 1.4 1.2 1.3 1.2 1.3 1.1 1.4 1.1 1.3 1.1 1.1 1.3

3.7 3.1 64.6 60.7 60.2 56.4 60.5 59.7 59.5 57.6 58.9 57.8 17.7 9.05

± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.1 0.6 1.3 1.4 1.4 0.91 1.2 1.6 1.5 1.4 1.1 1.4 0.9 0.05

1.8 0.80 3.05 1.17 0.48 0.58 0.34 0.24 4.7 4.89 0.11 0.19

0.4 0.01 0.06 0.06 0.02 0.01 0.06 0.04 0.3 0.08 0.01 0.01

% Total

R (%)

± ± ± ± ± ± ± ± ± ± ± ± ± ±

84.7 81.9 84.2 81.2 84.9 82.5 85.3 79.8 86.2 84.1 85.2 80.1 84.8 85.2

99.9 98.7 99.9 98.8 99.4 98.4 99.7 94.2 99.7 98.1 99.2 96.6 99.4 99.1

1.4 1.7 1.9 1.8 1.9 1.5 1.8 1.9 2.1 1.8 1.7 1.8 1.7 1.3

Note: *Biodiesel from waste cooking oil.

this kind of analysis. Very good results were obtained when the method was applied to determine FAMEs in biodiesel from commercial and waste cooking oil. Therefore, it can be concluded that this is a green, simple, fast, reliable and convenient analysis method to carry out the separation and determination of FAMEs in biodiesel samples, and it could be employed for the quality control of biodiesel and for the characterization of FAMEs. Therefore, the proposed method is of great interest for the analysis of biodiesel samples from different sources. Acknowledgements

[4] [5]

[6] [7]

C. Molina Mayo thanks ‘Consejería de Educación, Cultura y Deporte’ of Canary Islands Government for a Ph.D. grant. [8]

Disclosure statement No potential conflict of interest was reported by the authors.

Funding

[9] [10]

The authors would like to thank ‘Ministerio de Educación y Ciencia’ of Spanish Government (CTQ2005-02626) for financial support.

[11]

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