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Institute for Reference Materials and Measurements (IRMM), Joint Research Centre (JRC), European Commission (EC), Retieseweg 111, 2440 Geel, Belgium...
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Toward the Development of Certified Reference Materials for Effective Biodiesel Testing. Part 1: Processing, Homogeneity, and Stability  Manuela Ulberth-Buchgraber,* Monica Potalivo, Hakan Emteborg, and Andrea Held

Institute for Reference Materials and Measurements (IRMM), Joint Research Centre (JRC), European Commission (EC), Retieseweg 111, 2440 Geel, Belgium ABSTRACT: To address the current lack of certified reference materials (CRMs) for biodiesel analysis, the Institute for Reference Materials and Measurements (IRMM), Joint Research Centre (JRC), European Commission (EC), launched a comprehensive feasibility study on the production of biodiesel CRMs for relevant specification parameters as provided in EN 14214,1 the basis for defining product specifications and measurement methods for biodiesel in the European Union (EU). Laboratories need to be able to check the performance of their methods. This is also true for standardized methods, the use of which does not per se guarantee reliable results. Without underestimating the role and importance of other quality control tools, this paper is focused on aspects for the development of appropriate CRMs to be used for quality control in biodiesel analysis. Homogeneity and stability of a biodiesel material were investigated with dedicated studies. Of the 22 parameters considered overall, it could be shown that it would be feasible to produce a sufficiently homogeneous and stable material for 12 of them in a straightforward manner.

1. INTRODUCTION Technical standards defining the quality requirements for biofuels are of vital importance for biofuel producers, suppliers, and consumers for quality assurance and allowing for the free movement of these goods. The determination of fuel quality is an issue of great importance to the successful commercialization of biofuels. The international trade of biofuels is anticipated to grow steadily, and a need for further harmonization of biofuel standards was identified in the recent White Paper2 authored by a tripartite task force from Brazil, the European Union (EU), and the U.S.A. Differing standards for biofuels are a potential handicap to the free circulation of biofuels among the three regions. Reliable and comparable measurements of biofuels are also required in the frame of EU legislation3 concerning biofuels for transport. The term biofuels refers to liquid or gaseous fuels for the transport sector that are predominantly produced from biomass. A variety of fuels can be produced from biomass resources, including liquid fuels, such as ethanol, methanol, biodiesel, and FischerTropsch diesel, and gaseous fuels, such as hydrogen and methane.4 In Europe, the most important biofuel is biodiesel, which is defined as the monoalkyl esters of fatty acids derived from vegetable oils or animal fats. Current standards established to govern the quality of biodiesel on the market are based on a variety of parameters, which vary from region to region, including characteristics of the existing diesel fuel standards, the predominance of the types of diesel engines most common in the region, and the emission regulations governing those engines. The European standard for biodiesel to be used as automotive fuel was set in 2003 by the European Committee for Standardization [Comite Europeen de Normalisation (CEN)] and is known under the standard EN 14214.1 This documentary standard is the basis for defining product specifications and measurement methods for biodiesel. The confidence in any assessment of biodiesel will depend upon the quality of measurement data. Consequently, laboratories need r 2011 American Chemical Society

to be able to check the performance of their methods and staff. This is also true for standardized methods, the use of which does not per se guarantee reliable results. Therefore, it is widely accepted that laboratories need to demonstrate their proficiency in the applicability of standard methods. Internal quality control measures include typically the analysis of reference materials (RMs), the analysis of blanks and blind samples, replicate analysis, and the establishment of control charts. External quality control is commonly performed by proficiency testing of the laboratory performance. The level of quality control adopted must be demonstrably sufficient to ensure the validity of the results. Moreover, third-party assessment, namely, in form of accreditation, is increasingly recognized as a structured way of demonstrating competence. Without underestimating the role and importance of the other quality control tools, this paper is focused on aspects for the development of appropriate RMs for quality control in biodiesel analysis. Using ISO/IEC 17025 “General Requirements for the Competence of Testing and Calibration Laboratories” as the standard for good analytical practice, the important role of RMs in chemical metrology becomes apparent.5 Section 5.6 on traceability devotes a complete subsection to RMs. ISO Guide 306 gives a comprehensive overview on definitions, terminology, and application areas of RMs and certified reference materials (CRMs). Basically, two different types of RMs can be distinguished: non-certified and certified. Non-certified RMs are materials sufficiently homogeneous and stable with respect to one or more specified properties, which have been established to be fit for its intended use in a measurement process. CRMs are characterized by a metrologically valid procedure for one or more specified properties, accompanied by a certificate that provides the value of the specified property, its associated uncertainty, and Received: June 20, 2011 Revised: September 12, 2011 Published: September 15, 2011 4622

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Figure 1. General procedure for CRM production, according to Institute for Reference Materials and Measurements (IRMM).

a statement of metrological traceability. CRMs are primarily used for method validation; they are the best means to establish the trueness of a measurement value. Guidelines for the production and certification of RMs are provided in ISO Guide 347 and ISO Guide 35,8 and many credible producers of CRMs have adopted them or have even sought accreditation on the basis of those guidelines. Generally, a crucial issue for the preparation and certification of a CRM are the time and resources required. The production of CRMs, as shown in Figure 1, is certainly a very complex process. Usually at least 23 years are needed, covering planning, processing, homogeneity and stability studies, the characterization exercise, data evaluation, reporting, and final measures to make the material available. This time largely depends upon in-depth knowledge from previous or similar exercises, experience in processing RMs, the quality and availability of appropriate analytical methods and expert laboratories, and of course, the long-term stability studies. While there are several CRMs available for diesel, there is still a deficiency of CRMs for the analysis of biodiesel. Currently, there are two materials available at the National Institute for Standard and Technology (NIST), which are based on soybean oil and animal fat. To address this deficiency, the IRMM launched a comprehensive feasibility study on the production of a biodiesel RM for relevant specification parameters as provided in EN 14214.1 The study was planned and performed, where possible, in the same manner as for other RM production projects, as outlined in Figure 1, following ISO Guide 347 and ISO Guide 35.8 Only three steps of the complete process were left out, i.e., the final assessment by experts, the CRM distribution and sales, and the post-certification stability monitoring, because the intention of this study was to gain valuable knowledge to be used for the production of a real candidate CRM. The purpose of the study was to verify whether biodiesel, which is known for not being very stable because of susceptibility to oxidative degradation from contact with oxygen in ambient air,9 can under certain conditions be homogeneous and stable enough to be considered as RM. The findings of this feasibility study related to the processing, homogeneity, and stability study results are summarized in this paper, whereas the outcome from the final characterization to assign values together with their expanded uncertainties is reported in “Toward the Development of Certified Reference

Materials for Effective Biodiesel Testing. Part 2: Characterization and Value Assignment” (10.1021/ef200896c).10

2. MATERIALS AND METHODS 2.1. Material. EN 142141 defines biodiesel as fatty acid methyl esters in general. The present standard was developed on the basis of rapeseed-based biodiesel, which was and still is the predominant source of biodiesel in Europe. Most information and data available are dealing with the practical experience gained in the use of rapeseed oil fatty acid methyl esters (RMEs). Hence, a RME material was selected for the feasibility study as candidate material. Silo Rothensee GmbH and Co. KG, c/o ADM Hamburg (Hamburg, Germany), provided 50 L of commercial RME, including a certificate of analysis indicating the suitability of the material. 2.1.1. Processing of Materials. A crucial step of RM production is the processing of a candidate material. At first, every processing step has to be defined in a detailed plan. Therefore, the type of material, number of units, and quantity per unit have to be defined. To assess the impact of the addition of an antioxidant on the stability of the material, it was decided to produce two materials: one pure RME without antioxidant [test material A (TM A)] and the same RME with the addition of an antioxidant [test material B (TM B)]. The addition of synthetic antioxidants was identified as a viable means of improving oxidation stability by several working groups.1114 tert-Butylhydroquinone (TBHQ, from Merck, Darmstadt, Germany) was chosen for this feasibility study because (i) it had been used effectively to improve the oxidation stability of biodiesel13 and (ii) it had already been used successfully for the production of other vegetable-oilbased CRMs at IRMM. Homogeneity and stability are two crucial characteristics of any CRM. Utmost care must be taken during preparation to create materials as homogeneous and stable as possible. A proper processing exercise must begin with careful cleaning of the final containers, in this case, 25 mL amber glass ampules (Nederlandse Ampullen Fabriek, NAF, Nijmegen, The Netherlands). Because this brand of ampules is delivered in a closed state, all of the ampules were first opened in an ampouling machine (ROTA automatic ampouling machine, model R910/PA, Wehr, Baden, Germany) by making a little hole on the top. Next, the opened ampules were washed in sequence by rinsing them with 2% nitric acid (m/m) and type 1 water from a Millipore system using a dispenser. After the last rinse, the ampules were dried overnight in a drying cabinet. Prior to filling, the material was flushed continuously with argon for 4 h by releasing the argon at the bottom of a double-wall glass container (QVF Glasstechnik GmbH, Wiesbaden-Schierstein, Germany) to ensure good homogenization. 4623

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Table 1. Estimated Uncertainty Contributions from the Homogeneity Study parameter ester linolenic acid

method EN 14103 EN 14103

swba

sbbb

u*bbc

ubb

(%)

(%)

(%)

(%)

0.32 0.25

0.26 ncd

0.15 0.12

0.26 0.12

methyl ester monoacylglycerol

EN 14105

3.42

2.76

1.62

2.76

diacylglycerol

EN 14105

5.53

nc

2.62

2.62

triacylglycerol

EN 14105

14.47

nc

6.84

6.84

total glycerol

EN 14105

3.76

2.66

1.78

2.66

methanol

EN 14110

1.63

13.67e

0.77

13.67

sulfur water

EN ISO 20846 EN ISO 12937

8.03 6.26

8.70 18.41e

3.80 2.96

8.70 18.41

iodine value

EN 14111

0.39

0.84f

0.18

0.84

flashpoint

EN ISO 3679

0.93

4.37f

0.44

4.37

oxidation stability

EN 14112

1.36

2.29

0.64

2.29

acid value

EN 14104

0.69

nc

0.22

0.22

viscosity

EN ISO 3104

0.01

0.36

0.25

0.36

density

EN ISO 12185

ng

n

n

n

a

swb = standard deviation of within ampoule variation (repeatability). b sbb = standard deviation of between ampoule variation. c u*bb = maximum heterogeneity that can be hidden by method repeatability. d nc = cannot be calculated, because mean squares among groups are smaller than the mean squares within groups. e Rectangular approach used for estimation of between unit heterogeneity (eq 2). f Rectangular approach used for estimation of between unit heterogeneity (eq 1). g n = negligible. Ampouling was performed on the ROTA ampouling machine used initially to open all ampules. This type of ampouling machine is equipped with a very precise ceramic piston pump used to fill 21 mL per ampule. To remove most of the oxygen from the amber glass ampules, they were (i) flushed with argon, (ii) filled with biodiesel, (iii) flushed with argon over the headspace, and (iv) flame-sealed. After the filling of TM A, a 250 ppm TBHQ solution was prepared with the material remaining in the QVF vessel. Homogenization was achieved by bubbling argon for approximately 20 h. Ampouling of TM B was performed the day after ampouling TM A, with exactly the same experimental settings as used for TM A. The first 100 units filled with TM B were discarded. The two materials were subjected to the same stability studies to check the influence of the antioxidant on the stability of the final material. The homogeneity and characterization studies were only performed on TM B. 2.2. Selected Parameters. Of the many parameters listed in EN 14214,1 a few had to be excluded for practical reasons, i.e., cold filter plugging point, total contamination, copper band corrosion, carbon residue remnant, cetane number, and sulfated ash content. The sample intake required by the standard test methods exceeded by far the volume that was filled per ampule (21 mL) for the test material. From the 28 parameters listed in EN 14214,1 22 were finally considered in the feasibility study. All measurements in this study were carried out as described in the official standard methods as provided in EN 14214.1 2.3. Homogeneity Study. The homogeneity study aimed to quantify any between ampule heterogeneity of the individual parameters of interest. On physical grounds, there was no reason to expect differences in the composition of the material in the ampules. The main purpose of the homogeneity assessment was to detect unexpected problems, for example, because of contamination during processing. Only TM B, containing the antioxidant TBHQ, was selected for the study. For each parameter, a total of 10 ampules were selected using

random stratified sampling of the whole batch. For practical reasons, some of the analytes were grouped. From each ampule, two independent measurements per analyte were performed whenever possible under repeatability conditions by using the standard test methods as provided in EN 14214,1 as given in Table 1. Care was taken to ensure that the order of measurements did not correspond to the filling sequence of the ampules, which enabled differentiation between a potential trend in the filling sequence and analytical drift. 2.3.1. Homogeneity Data Evaluation. The data sets were screened for outliers using the Grubbs procedure, and regression analyses were performed to check for potential trends in the filling sequence. The distribution of results was checked using normal probability plots and histograms. Finally, an analysis of variance (ANOVA) was performed to quantify the standard deviations of within ampule variation (swb; repeatability) and between ampule variation (sbb). Method repeatability sets a limit to the heterogeneity that can be detected by a particular method with a given study setup (number of repetitions per sample; number of samples). The maximum heterogeneity that could be hidden by method repeatability (u*bb) was calculated as described by Linsinger et al.15 In the case of the presence of trends in the filling sequence and outlier averages, the evaluation by ANOVA is not the most appropriate. In those cases, an alternative approach for the estimation of heterogeneity was followed; i.e., the between-unit heterogeneity was modeled as a rectangular distribution limited by the outlying average. The standard uncertainty using this outlier (urect) was estimated as urect ¼

jlargest outlier  yj ̅ pffiffiffi 3

ð1Þ

where y is the average of all results. In case a trend in the filling sequence was detected, the between unit heterogeneity was modeled using the half-width of a rectangular distribution between the highest and lowest ampule average. urect ¼

jhighest result  lowest resultj pffiffiffi 2 3

ð2Þ

In case a significant trend in the analytical sequence was detected, the results were corrected for their trend as follows: xi, corr ¼ xi  ib

ð3Þ

where i denotes the index of the measurement in the sequence, xi denotes the measurement result, and b denotes the slope of the line from fitting x to i. 2.4. Stability Studies. Stability studies are conducted to establish both dispatch conditions (short-term stability) and storage conditions (long-term stability). Fatty acid methyl esters can undergo degradation over time, mainly influenced by temperature and oxygen. Principal means of stabilization of the biodiesel for a long-term perspective were the creation of an inert atmosphere by flushing argon into the ampule just before and after filling, removing the oxygen present, and the usage of flame-sealed amber glass ampules and storage in darkness, excluding degradation by light. The setup of the studies followed an isochronous scheme.16 In such designs, samples are moved to a reference temperature after having been kept for some time at a certain temperature. At the end of the study, all samples from the complete study can be analyzed in one analytical run, allowing for the reduction of analytical data variation and the increase of significance of the result by measuring the samples where possible under repeatability conditions. The reference temperature was set at 8 °C, assuming that the stability of the material is sufficient at this temperature. A lower temperature was ruled out because of the risk of solidification. The results were grouped and evaluated for each time point and temperature. Results were screened for single and double outliers by applying the Grubbs test at confidence levels of 95 and 99%, respectively. Data were plotted as a function of time, and the 4624

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regression lines were calculated to check for significant trends possibly indicating degradation of the material. The observed slopes were tested for significance using a t test, with tα,df being the critical t value (twotailed) for a significance level α = 0.05 (95% confidence interval). 2.4.1. Study Design of Short-Term Stability. The overall aim of this study was to simulate degradation conditions and decide on proper transport conditions. Experience has shown that conditions during transport often differ considerably from those during storage; temperatures above 30 °C can be expected during road transport, especially in the summer months. A stability study should therefore be conducted at a relevant temperature to investigate possible degradation. For this purpose,

Figure 2. Estimated uncertainties from homogeneity compared to performance characteristics of official standard methods.

storage under extreme conditions at 60 °C was compared to storage at lower temperatures, i.e., 4 and 18 °C, during relatively short periods of time (1, 2, and 4 weeks). A total of 100 ampules were selected for TM A, and a total of 100 ampules were selected for TM B, by random stratified sampling from the entire batches produced. Because of practical reasons, the target analytes were grouped into 5 lots and, for each lot, 20 ampules were chosen from the whole batches. From each ampule, two independent measurements per analyte were performed using the standard methods as provided in EN 14214.1 For economic reasons, the following parameters were excluded from the short-term stability study: acid value, viscosity, and density. 2.4.2. Study Design of Long-Term Stability. A long-term stability study will allow for the definition of the shelf life of the target analytes and the estimation of their uncertainty contributions. For practical reasons, the target analytes were grouped into 9 lots. The setup was as follows: two ampules were kept at 4 and 18 °C for 4, 8, and 12 months and, after this time, put back (until analyzed) to 8 °C, where the “reference” ampules were stored since the beginning. For practical reasons, the target analytes were grouped into 11 lots and, for each lot, 14 ampules were chosen from all batches. In total, 154 ampules were selected for TM A and 154 ampules were selected for TM B by random stratified sampling from all batches produced. From each ampule, two independent measurements per analyte were performed using the standard methods of EN 14214.1 The measurements were performed whenever possible under repeatability conditions and according to an imposed random sequence. 2.4.3. Short- and Long-Term Stability Data Evaluation. The results were grouped and evaluated for each time point and temperature. Results were screened for single and double outliers by applying the Grubbs test at confidence levels of 95 and 99%, respectively. The most important conclusion that can be drawn from the results is the presence/absence of a

Table 2. Linear Regression and Statistical Parameters Associated with Short-Term Stability analyte

unit

slope

SE slope significant slope TM A at 4 °C

study temperature

SE slope significant slope

slope

TM A at 18 °C

[% (m/m)]

0.0286

0.0452

no

linolenic acid methyl ester [% (m/m)]

0.0064

0.004

no

ester

slope

0.0471

SE slope significant slope TM A at 60 °C

0.0639

no

0.0264

all values are equal

0.0443

no

all values are equal

monoacylglycerol

[% (m/m)]

0.0056

0.0042

no

0.0005

0.0039

no

0.0043

0.004

no

diacylglycerol triacylglycerol

[% (m/m)] [% (m/m)]

0.0034 0.0002

0.0017 0.0008

no no

0.0021 0.0016

0.0015 0.0010

no no

0.0007 0.0001

0.0017 0.0009

no no

total glycerol

[% (m/m)]

0.0014

0.0011

no

0.0005

0.0012

no

0.0006

0.0012

no

methanol

[% (m/m)]

0.0006

0.0008

no

0.0005

0.0007

no

0.0009

0.0007

no

sulfur

(mg/kg)

0.0229

0.0252

no

0.0157

0.0243

no

0.0021

0.0216

no

water

(mg/kg)

0.1643

2.4551

no

1.6143

1.4822

no

1.1429

1.9755

no

iodine value

(g of iodine/100 g)

0.1500

0.2375

no

0.0857

0.1675

no

0.1143

0.1945

no

flashpoint

(°C)

0.6643

0.4177

no

1.5071

0.4272

yes

0.6571

0.3316

no

oxidation stability

(h)

0.0393

0.0228

no

0.0479

0.0251

no

0.1536

0.0319

yes

0.0540

0.0580

no

0.0590

no

0.1290

0.0880

no

0.0190

0.0070

yes

TM B at 4 °C

study temperature ester

[% (m/m)]

linolenic acid methyl ester [% (m/m)]

TM B at 18 °C

all values are equal

TM B at 60 °C

0.0330 all values are equal

monoacylglycerol

[% (m/m)]

0.0070

0.0050

no

0.0060

0.0050

no

0.0090

0.0050

no

diacylglycerol

[% (m/m)]