Determination of methylmercury in marine biota samples with advanced mercury analyzer: Method validation

Food Chemistry 176 (2015) 367–375

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Analytical Methods

Determination of methylmercury in marine biota samples with advanced mercury analyzer: Method validation Sabine Azemard, Emilia Vassileva ⇑ International Atomic Energy Agency, Department of Nuclear Sciences and Applications, Environment Laboratories, 4 Quai Antoine 1er, MC 98000, Monaco

a r t i c l e

i n f o

Article history: Received 8 August 2014 Received in revised form 17 December 2014 Accepted 20 December 2014 Available online 29 December 2014 Keywords: Methyl mercury Advanced mercury analyzer Marine biota Sample preparation Method validation Traceability Uncertainty

a b s t r a c t In this paper, we present a simple, fast and cost-effective method for determination of methyl mercury (MeHg) in marine samples. All important parameters influencing the sample preparation process were investigated and optimized. Full validation of the method was performed in accordance to the ISO17025 (ISO/IEC, 2005) and Eurachem guidelines. Blanks, selectivity, working range (0.09–3.0 ng), recovery (92–108%), intermediate precision (1.7–4.5%), traceability, limit of detection (0.009 ng), limit of quantification (0.045 ng) and expanded uncertainty (15%, k = 2) were assessed. Estimation of the uncertainty contribution of each parameter and the demonstration of traceability of measurement results was provided as well. Furthermore, the selectivity of the method was studied by analyzing the same sample extracts by advanced mercury analyzer (AMA) and gas chromatography–atomic fluorescence spectrometry (GC–AFS). Additional validation of the proposed procedure was effectuated by participation in the IAEA-461 worldwide inter-laboratory comparison exercises. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction Mercury (Hg) is a persistent global pollutant, particularly in the form of methylmercury (MeHg), a potent neurotoxin produced in the aquatic environment from inorganic mercury by sulfate and iron-reducing bacteria, as well as methanogens (Siciliano, O’Driscoll, & Lean, 2002). Indeed, MeHg is recognized as a major environmental pollution issue and health hazard for humans (Qiu, 2013). Owing to its capability to permeate through biological membranes, once MeHg enters the food chain, it is efficiently accumulated and transferred to organisms at higher trophic levels (Mason & Benoit, 2003). As a result, the fraction of MeHg from the total Hg (THg) in muscle tissue of top predator fish can be up to almost 100% (Senn et al., 2010). The majority of population is exposed to Hg through consumption of marine and freshwater biota, mainly fish and seafood products (Sunderland, 2007). Specifically, large predatory fish which are at the top of the foodchain, such as swordfish and tuna, contain high levels of MeHg and are significant sources of human exposure to that contaminant. Public health warnings and guidelines on consumption of fish containing high levels of MeHg have been published by the U.S. Food and Drug Administration (USFDA, 2004) and the European Union (European ⇑ Corresponding author. E-mail address: [email protected] (E. Vassileva). http://dx.doi.org/10.1016/j.foodchem.2014.12.085 0308-8146/Ó 2014 Elsevier Ltd. All rights reserved.

Union, 2008). However, to this date, official legislation establishing the maximum level of MeHg threshold authorized in seafood for human consumption has not been issued. Typically, the determination of MeHg in biota samples involves the following analytical steps: (i) extraction, (ii) separation and (iii) detection. The most widely used procedures for extraction are based on alkaline (Carrasco & Vassileva, 2014) and acidic leaching (Hintelmann & Nguyen, 2005), both assisted by microwave (Nevado, Martin-Doimeadios, Bernardo, & Moreno, 2005) and conventional heating (Carrasco & Vassileva, 2014; Clémens, Monperrus, Donard, Amouroux, & Guérin, 2011; Hintelmann & Nguyen, 2005). More recently, enzymatic digestion (Lopez, Cuello, Camara, & Madrid, 2010; Reyes, Rahman, Fahrenholz, & Kingston, 2008), has also been described to isolate MeHg from biota matrices. As the extraction process must preserve the integrity of the original chemical forms, special attention should be paid in order to prevent transformation of species (Reyes et al., 2008). Final steps, i.e. separation and detection, are commonly tackled using hyphenated techniques, which couple the high resolution power of a separation method, namely gas chromatography (GC) (Carrasco, Diez, & Bayona, 2009), high-performance liquid chromatography (HPLC) (Jagtap, Krikowa, Maher, Foster, & Ellwood, 2011), and capillary zone electrophoresis (CZE) (Silva da Rocha, Soldado, Blancoa, & Sanz-Medel, 2001), to a Hg-selective and sensitive detector. The major drawback of the most commonly used

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separation technique, GC, is the requirement for derivatization of the ionic MeHg into volatile species, and subsequent solid phase micro extraction (SPME) or purge and trap collection (Carrasco & Vassileva, 2014; Yang, Truong, Chen, & Belzile, 2009). The most widely used detectors are atomic fluorescence spectrometry (AFS) (Carrasco & Vassileva, 2014; Nevado et al., 2005) and inductively coupled plasma mass spectrometry (ICP-MS) (Hight & Cheng, 2006; Hintelmann & Nguyen, 2005; Vassileva, Wysocka, & Betti, 2014). Consequently in interlaboratory comparison and proficiency test a common result is that less than 25% of participants reporting THg can provide MeHg results (IAEA, 2012). Considering that more restrictive regulations on MeHg levels in marine samples are expected, the current analytical challenge faced is the development and validation of ready-to-use analytical methods, covering the broadest possible range of sample matrices. Those methods will be ultimately implemented in laboratories devoted to routine analysis of MeHg. Direct and automated mercury analyzers, such as advanced mercury analyzer (AMA-254) and direct mercury analyzer (DMA80), have proven to be a valuable tool for the direct analysis of THg in a variety of biota matrices (Carrasco, Benejam, Benito, Bayona, & Diez, 2011; Gerstenberger, 2004; Gerstenberger & Pearson, 2002) and are widely found in laboratories performing THg measurement as a routine. In marine biota, organic mercury can be considered as MeHg, with a negligible error. Therefore, by selecting a proper organic mercury extraction, the direct mercury analyzer can be potentially applied for mercury speciation. Such application has already been reported (Carbonell, Bravo, Fernandez, & Tarazona, 2009; Maggi, Berducci, Bianchi, Giani, & Campanella, 2009; Scerbo & Barghigiani, 1998; Valega et al., 2006) and the European Commission has recently published a standard operating procedure based on AMA-254 or DMA-80 determination (Calderón, Gonçalves, Cordeiro, & de la Calle, 2013; Cordeiro et al., 2013). The aim of this study was to develop and validate a ready-touse analytical method, consisting of extraction of MeHg, and direct mercury analyzer (AMA) determination, for routine analysis of MeHg in marine biota samples, focusing on the reduction of waste and extraction time. For evaluating the method over a broad spectrum of MeHg levels (0.022–3.67 mg kg1), as well as MeHg/THg ratios (14–88%), the following certified reference materials (CRMs) were used as common samples: IAEA-452 (scallop soft tissue), IAEA-436 (tuna fish muscle tissue), DOLT-2 (dogfish liver) and TORT-2 (lobster hepatopancreas). The full validation of the method was performed in accordance to the ISO-17025 guideline (ISO/IEC, 2005) assessing the following parameters: linearity, working range of the calibration curve, limits of detection and quantification, repeatability, intermediate precision, recovery and trueness. Estimations of the individual uncertainty contributions of each parameter and the final expanded uncertainties have also been performed. Demonstration of traceability of measurement results is provided as well. The proposed method is very appropriate for application in environmental monitoring studies, based on determination of MeHg in marine biota samples and in food safety control, when large number of samples needs to be analyzed.

liquid) is dried at 220 °C and then thermally decomposed at 725 °C. The gaseous decomposition products are carried in an oxygen stream through the catalytic section of the furnace, where Mn3O4/CaO based catalyst allows complete oxidation, while halogens and nitrogen/sulfur oxides are trapped. Subsequently, the different mercury species are converted into elemental mercury (Hg0) vapor and selectively trapped on a gold-based amalgamator. After flushing the system with oxygen the amalgamator is rapidly heated, releasing the mercury vapor. The oxygen flow carries the mercury vapor to the absorbance cell in the light path of a single wavelength atomic absorption spectrophotometer. A low pressure mercury vapor lamp is used at the working wavelength of 253.7 nm. The detector is connected to a computer for data acquisition and analysis. Temperatures of both, drying and decomposition stages, were set by default at 220 °C and 725 °C, respectively. Drying time (s) was programed as 0.7 times the volume (lL) of the sample injected. Decomposition and waiting time were 150 s and 45 s, respectively.

2.1.2. Hg speciation analysis by gas chromatography and pyrolysis and AFS Mercury speciation analysis was accomplished with a dual trap desorption module TDM II interfaced to an Atomic Fluorescent Spectrometer (AFS) model III detector via a Hg speciation GC and pyrolysis module (Py). All the three modules were supplied by Brooks Rand Labs (Seattle, WA, USA). Full details about the instrumentation can be found in Carrasco, & Vassileva, (Carrasco & Vassileva, 2014).

2.2. Chemicals and reagents Deionized water used for the preparation of all solutions in this study was from Milli-Q Element system (Millipore, Bedford, MA, USA). Certified reference materials (CRMs) applied as a test samples in method validation process were as follows: IAEA-452 (scallop soft tissue) and IAEA-436 (tuna fish muscle tissue) produced in Environment Laboratories-IAEA, Monaco, DOLT-2 (dogfish liver) and TORT-2 (lobster hepatopancreas) purchased from the National Research Council of Canada (NRCC, Ottawa, Ontario, Canada). Hydrochloric acid (HCl) (30%, Suprapur) or hydrobromic acid (HBr) (47%, pro analysis), both from Merck, Darmstadt, Germany were used for hydrolysis of investigated samples. 0.002 M sodium thiosulfate solution (Suprapur, Merck) or a 1% (w/v) L-cysteine (Sigma Aldrich, Steinheim, Germany) prepared in 12% (w/v) anhydrous sodium sulfate and 0.8% (w/v) sodium acetate (Suprapur, Merck) were used for back-extraction. Standard solution of inorganic mercury 1000 mg kg1 in 12% (v/ v) nitric acid was from TraceCert, Fluka, Steinheim, Germany. Working solutions were prepared by dilution of the standard solutions in 1% (v/v) nitric acid (40%, Suprapur Merck), 0.1% (v/v) HCl (Suprapur, Merck) and 0.2% potassium dichromate (analytical grade, 10% (w/v), Merck). Calibration solutions in the range of 0.5–15 lg L1 were prepared daily by further dilution of working solution in 0.002 M thiosulfate solution. Detail about chemical used for GC–Py–AFS can be found in Carrasco, & Vassileva, (Carrasco & Vassileva, 2014).

2. Experimental part

2.3. Sample preparation

2.1. Instrumentation

Two sample preparation procedures for extraction of MeHg followed by AMA determination (herein denoted 1–2) were investigated. Three subsamples of the forth different CRMs were used in each extraction procedure. Three procedural blanks were prepared in parallel with each sample batch.

2.1.1. Advance mercury analyzer – AMA-254 The analyses were carried out using an advance mercury analyzer (AMA-254, Altech Czech Republic). The sample (solid or

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2.3.1. Procedure 1 A 0.1–0.8 g portion of sample (or CRM) was weighted in a 50 mL polypropylene centrifuge tube; 5 mL of 25% (v/v) HCl solution were added and the mixture was vigorously shaken for 30 s. Then, 10 mL of toluene were added in the tube and a vortex shaking method was subsequently employed for 3 min to ensure the homogenization of the phases. The mixture was centrifuged at 5000 rpm for 5–20 min. A known volume (4–8 mL) of the upper organic phase was removed and transferred to a second 50 mL polypropylene centrifuge tube containing 5–10 mL of 0.002 M sodium thiosulfate solution. This second tube was vigorously shaken (vortex, 3 min) and centrifuged at 5000 rpm for 5–15 min. Two milliliters of the lower aqueous phase, which contains the extracted organic mercury, was transferred to a 15 mL polypropylene container or glass vial, using a Pasteur glass pipette. Then, an aliquot (50–400 lL) of the extract was directly analyzed with AMA. The thiosulfate extract was found to be stable for 2 days at temperature of 4 °C. 2.3.2. Procedure 2 0.1–0.5 g of sample was placed into a 50 mL polypropylene centrifuge tube and hydrolyzed with 10 mL of HBr. Twenty milliliter of toluene was added and the mixture was homogenized for 2 min and centrifuged for 10 min at 3000 rpm. The organic phase was transferred to a tube containing 6.0 mL of 1% L-cysteine solution. A second organic extraction was subsequently performed. A 0.5 mL aliquot of L-cysteine extract was immediately analyzed with the AMA. This procedure was proposed by the European Commission as a standard operation procedure (SOP) for determination of MeHg by direct mercury analyzer in sea food to all European Reference Laboratories for trace elements in food and feed (Calderón et al., 2013). 2.4. Determination of moisture content Correction for dry-mass was obtained from 3 sub samples of biota sample of minimum mass of 1.0 g. The material was dried for 24 h in a ventilated oven at a temperature of 85 ± 2 °C. Then weighing and repeated drying was performed until constant mass was attained (0.0002 g difference between two successive weighs). The loss of mass corresponds to the ‘‘dry mass correction factor’’, which was applied for the estimation of the combined uncertainty. 2.5. Experimental set up for method validation Several parameters were evaluated for the validation of the proposed procedure, namely: selectivity; trueness by recovery, repeatability and within-laboratory reproducibility, instrumental/ method detection limits (LoDs) and quantification limits (LoQs), range of linearity, measurement uncertainty, traceability of measurement results. Recovery, repeatability and intermediate precision were evaluated at 4 levels of concentrations. Furthermore, stability studies of the solution were carried out. The validation experiments were performed on six different days. Independent samples were prepared on each single day. Some of the experiments were used in the estimation of different parameters. During the validation study, an internal quality control (IQC) procedure was adopted – the blank level and the drift of the instrument readings were systematically checked analyzing one standard solution after every 10 samples. Procedural blank was prepared together with unknown samples in order to account for cross contaminations during the validation study. It underwent the same analytical procedure as for biota samples without adding biota matrix. The calibration curve was prepared with several different mass quantities, covering a range of mercury from 0.1 to 3 ng, in a fix

369

volume (200 lL) of calibration standard prepared in thiosulfate solution. In order to achieve such low mass levels, calibration standard were prepared from a working standard solution of 0.1 mg L1, obtained by sequential dilution of the stock standard solution of 1 g L1. Calibration standards were measured at the beginning of the sequence, followed by the procedural blanks, and then the samples. Instrumental blank was obtained from the measurement of the same volume of 0.002 M thiosulfate solution. Calibration was performed at the beginning of the sequence, followed by the procedural blanks, and then unknown samples. To monitor for instrumental drift the standard with the lowest Hg content was randomly re-measured during the measurement sequence. In parallel, second calibration strategy based on bracketing technique was also applied and obtained results compared. First, a preliminary estimate of the analyte concentration in the test sample is obtained. Second, two calibration standards at levels that bracket the sample concentration as closely as possible are then used, i.e. the two calibrant mass fraction value differs from the sample mass fraction value in a factor no greater than 20%. The absolute limit of detection (LoD) of the method was calculated as the mean of the blank plus three times the standard deviation of the blank in twelve replicates. The absolute limit of quantification (LoQ) was calculated as the mean of blank plus ten times the standard deviation of the blank in twelve replicates. For method LoDs and LoQs, final dilution and weight were taken into account to calculate the final values. Repeatability (Sr) and intermediate precision (SR) were calculated by the application of one way of variance as prescribe in ISO 5725 (ISO/IEC, 1994; Thompson, Ellison, & Wood, 2002). For repeatability and intermediate precision, the experimental plan was applied on four concentration levels (IAEA 452; IAEA 436, TORT-2 and DOLT-2), three repetitions per days and per levels for a period of 6 days. The same set of CRM samples were used for the trueness (recovery) studies at 4 different concentration levels. 2.6. Evaluation of the measurement uncertainty All possible sources of uncertainty were carefully identified. Afterwards, the uncertainty components were quantified and the combined uncertainty is calculated. Combined standard uncertainties were obtained by propagating together individual uncertainty components according to the ISO/GUM guide (JCGM, 2008). The calculations were performed using Kragten spreadsheet approach (Kragten, 1994). All uncertainties indicated in the final results are expanded uncertainties U = kuc where uc is the combined standard uncertainty and k is a coverage factor equal to 2. 3. Results and discussion 3.1. Extraction procedure optimization The effect of HCl concentration on the extraction recovery of MeHg was investigated. Tuna fish CRM IAEA-436 was used in this test. The use of 25% (v/v) HCl in the extraction step leaded to recovery rate of 99.9%. Recovery decrease was observed with further increase of HCl concentration, probably due to the degradation of the MeHg. Similar pattern was observed by Hintelmann and Nguyen (2005) for nitric and sulfuric acid. Consequently, no higher concentrations were further evaluated. Additionally, the effects of solvent and back extraction duration were also investigated. Maximum recoveries (i.e. 98%) were obtained for 3 and 5 min of solvent and back extraction duration respectively. Since no significant differences were found between

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3 and 5 min extraction time, the shortest time was selected. Overall, the extraction conditions were fixed at 25% (v/v) HCl and 3 min of shaking time for solvent and back extraction steps. Ultraviolet (UV) and visible (Vis) radiations lead to degradation of MeHg (Li et al., 2010). In this respect, parallel extractions, under and without UV exposition, were conducted. No significant differences in the recovery of MeHg from marine biota samples were observed. Although some published protocols (Calderón et al., 2013; Maggi et al., 2009; Scerbo & Barghigiani, 1998; Valega et al., 2006) recommend double solvent extraction, the quantitative recoveries obtained for IAEA-436 using proposed methodology demonstrates that single extraction is sufficient. In order to avoid long centrifugation time, sample size and volume of back extracted toluene were kept as small as possible, but sufficient to obtain a measurable signal in the measurement step. In the case of formation of undesirable emulsion at the liquid– liquid interface, the final volume of thiosulfate solution was increased. The latter had to be optimized as a function of the volume of measured sample aliquot, because measurement time with AMA strongly depends from the volume of the sample used in the measurement step. Measurement time was from 4 to almost 8 min for aliquot volumes from 50 to 400 lL, respectively. 3.2. Stability study The variation of analyte level in the thiosulfate extract may give significant biases of measurement result. The stability was first checked by repeated measurements of one sample extract kept at room temperature during 5 h, 2 days after their preparation (extracts are stored at 4 °C in between). No statistical differences were observed in the different determination and it was concluded that extracted solutions are stable at room temperature for at least 5 h. Five hours is the usual duration of the measurement sequence. Additionally solutions can be kept at 4 °C up to 2 days before the measurement. 3.3. Comparison of both extraction procedures The extraction procedure proposed in this study was then compared with the extraction procedure described in procedure 2, where MeHg was extracted following the standard operation procedure distributed for the collaborative study in EU (Calderón et al., 2013). For this comparison three CRMs namely IAEA-436, IAEA-452 and TORT-2 covering a wide range of MeHg concentration, (i.e. 0.02–3.67 mg kg1) and MeHg/THg ratio (from 14% to 88%) in different biota matrices were analyzed by applying both extraction procedures. Obtained results are presented in Table 1. MeHg mass fraction yielded by the methodology developed in this study is in very good agreement with those obtained with procedure 2. One of the advantages of the proposed extraction protocol is the significant reduction of the generated waste volume of organic solvent. In addition damages of sample boat and auto sampler

holder were observed when applying procedure 2, mainly due to the spread of cysteine solution. Conversely, after 200 injections performed with the proposed extraction procedure, no visible damages or depositions on the samples boats were observed. As a result of the reduction of the number of extraction steps, the extraction time was shortened and the production of waste significantly reduced. 3.4. Validation According to the ISO-17025 guidelines, validation is ‘‘the confirmation by examination and the provision of objective evidence that the particular requirements for a specific intended use are fulfilled’’ (ISO/IEC, 2005). The factors influencing the final results were systematically assessed, as follows: 3.4.1. Selectivity The selectivity can be defined as the ability of a method to determine accurately and specifically the analyte of interest in the presence of other components in the sample matrix (Vessman et al., 2001). In order to evaluate the selectivity of the proposed analytical procedure (i.e. the absence of inorganic mercury in the final extract), samples of IAEA-436, IAEA-452 and DOLT-2 were treated following the procedure 1 and the speciation of mercury in the organic extracts determined after aqueous-phase ethylation, purge-trap, gas chromatography separation, followed by pyrolysis and atomic fluorescence spectrometry detection (GC–Py–AFS) as described in Carrasco and Vassileva (2014). Typical chromatograms for the IAEA 452 biota sample obtained with GC–Py–AFS methodology are shown on Fig. 1; the two peaks (Tr: 2.3 and 4.9 min) correspond to MeHg and inorganic Hg. The absence of inorganic mercury in the extract from IAEA 452 biota sample (a) (same peak than in the procedural blank sample) shows the capacity of the proposed procedure to extract selectively the organic mercury from biota samples. As comparison the chromatogram (c) of the same sample (IAEA 452) solubilized in KOH/MeOH exhibit a high inorganic mercury peak, representing 86% from the total mercury content. The MeHg content in above mentioned CRM was measured in parallel with GC–Py–AFS and AMA techniques and obtained results are presented in Table 1. The agreement of obtained results within their combined uncertainties confirms the selectivity of the proposed sample preparation procedure and the absence of inorganic mercury in the final extract. 3.4.2. Calibration curve, linearity and working range For any quantitative method, it is necessary to determine the range of analyte concentrations or property values over which the method may be applied. This refers to the range of concentrations in the solutions actually measured rather than in the original samples. In the present study this test was performed with 10 different concentrations. At the lower end of the concentration range,

Table 1 Comparison of results obtained for MeHga content (X ± U, mg kg1)b in marine biota CRM with the extraction procedure developed in this study and different detection methods with the results obtained with EC recommended method.

IAEA 436 DOLT-2 TORT-2 IAEA 452 a

Certified values

Proposed procedure

GC–Py–AFSc Procedure

EC recommended procedure

3.67 ± 0.42 0.693 ± 0.053 0.152 ± 0.013 0.022 ± 0.004

3.39 ± 0.51 0.743 ± 0.111 0.149 ± 0.022 0.021 ± 0.003

3.80 ± 0.45 0.737 ± 0.088 – 0.017 ± 0.002

3.75 ± 0.45 – 0.147 ± 0.022 0.019 ± 0.005

Reported as mercury. Uncertainties are reported as expanded uncertainties U = kuc (k = 2). Expanded uncertainties of the method proposed by EC were taken from the report of the collaborative study. c As described in Carrasco and Vassileva (2014). b

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Fig. 1. Typical chromatograms (a) for the separation of mercury and MeHg from CRM IAEA-452 subjected to the optimized extraction procedure, (b) for the instrumental blank and (c) for mercury and MeHg extracted by traditional alkaline digestion with 25% (w/v) KOH in methanol from CRM IAEA-452.

the limiting factors are the values of the limits of quantitation. At the upper end of the concentration range, limitations are imposed by various effects depending on the instrument response system. The linear range of the calibration curve was from 0.09 to 3 ng as absolute mass of mercury. The linear correlation coefficient (R2) was found to be 0.9993. The linearity was confirmed by visual inspection and checking of the distribution of residuals. Residuals over the studied range were all below 2% and were distributed randomly around zero. Depending on the variation in the procedural conditions, i.e. sample weight, thiosulfate and injection volumes, this linear range allowed the determination of methyl mercury for sample with concentrations in the range of 0.002–20 mg kg1. An alternative calibration approach, which has been tested, is bracketing calibration. The results obtained with both calibration strategies did not differ by more than 0.1%. 3.4.3. Estimation of limit of detection and limit of quantification The absolute LoD and LoQ of the proposed methodology for determination of MeHg in marine biota were found 0.045 and 0.09 ng, respectively. Procedural detection and quantification lim-

its depend on the mass of initial sample, injected volumes, volumes of thiosulfate and toluene collected for back-extraction. Accordingly, under experimental conditions of 0.8 g of sample, injection volume of 400 lL, 5 mL of thiosulfate and 8 mL of toluene collected for back-extraction, detection and quantification limits were found to be 0.0009 mg kg1 and 0.0017 mg kg1, expressed as Hg. 3.4.4. Repeatability and within-laboratory reproducibility The repeatability and intermediate precision of the measurement procedure were evaluated following the steps described in the Section 2.5. Repeatability varied from 1.3% to 3.9% and intermediate precision from 1.7% to 4.5% over the 4 CRMs used. 3.4.5. Recovery (trueness) study The trueness of the method was assessed by using recovery tests. For the 4 different matrices CRM, recoveries of MeHg with proposed procedure were in the range of 92–108%. Considering the estimated uncertainty of the analytical recovery, no statistical significant difference could be identified between measured and certified values in the tested matrices.

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3.4.6. Accuracy profile Another strategy recently used in validation practice is the construction of accuracy profile, called also total error approach (Clémens et al., 2011). The accuracy profile is a decision-making graphical tool aiming to help the analyst to decide whether an analytical procedure is fit for purpose. The building of such profile helps to determine the experimental tolerance intervals or limits, which have to be compared with acceptable limits fixed by the analyst as a function of the analytical problem (Mermet & Granier, 2012; Feinberg, 2007). The accuracy profile was applied in the present study to demonstrate the ability of the proposed methodology to quantify MeHg in biota samples using data obtained during repeatability and intermediate precision studies. The probability b and acceptance limits were set to 90% and 20%, respectively; bracketing strategy was used for calibration. Obtained profile presented in Fig. 2, shows that all b-expectation tolerance intervals were comprised within the acceptable limits. 3.4.7. Uncertainty The estimation of combined uncertainty of measurement results was done by applying two different approaches: the modeling approach recommended by ISO GUM (JCGM, 2008) and single laboratory validation approach (Nordtest, 2012). 3.4.7.1. Modeling approach The equations described in Table 2, represent our mathematical model, used to calculate MeHg mass fractions in biota sample. The value for each parameter in the described equations, obtained either by an analytical measurement or a mathematical calculation, was with an associated standard uncertainty. The uncertainties of all input quantities are found and thereafter combined into the combined standard uncertainty. Bracketing calibration strategies was used in the modeling approach. This type of calibration is in theory more advantageous in term of uncertainty propagation as (i) the measurement cycle is fast and the instrumental drift is minimized, (ii) the effect of instrumental non-linearity between two calibration points is insignificant. Therefore, the uncertainty coming from the calibration step of the measurement procedure was estimated according to the Eq. (2), Table 2, which describes the application of bracketing approach. Beside the correction for recovery, the measured mass fractions were also corrected for procedural blank and moisture content. Typically, the relative expanded uncertainty on the MeHg content in biota sample was found to be 15% (k = 2). In this way, the combined uncertainty statements that arise go far beyond the

simple repeatability calculations and reflect our understanding of the measurement process. The contributions of the individual parameters are expressed in terms of their relative contribution to the expanded uncertainty and are as follows: the main uncertainty component (72%) was originated from the uncertainty coming from recovery, followed by the repeatability of the measurements (17.5%), the extraction and injection volumes (5.9%). Finally, uncertainties coming from preparation of standard solutions and other factors are found to be 3.9% and 0.4%, respectively. 3.4.7.2. Single laboratory validation approach The single-lab validation approach, contrary to the ISO GUM modeling approach, does not go deeply into the measurement procedure and does not attempt to quantify all uncertainty sources individually. Instead the uncertainty sources are quantified in large ‘‘batches’’ via components that take a number of uncertainty sources into account. Most of the data that are used come from validation of the analytical procedure. This is the reason for the word ‘‘validation’’ in the name of the approach. This type of approach is sometimes called the ‘‘top-down’’ approach and is also known as a Nordtest approach (Nordtest, 2012). The equations for the singlelab validation approach are presented in Table 3. The Eq. (1) includes the two main components of uncertainty budget: u (Rw) which stands for the within laboratory reproducibility component of uncertainty and u (bias) accounting the uncertainty component taking into account possible bias. The within laboratory reproducibility (intermediate precision) component takes into account all uncertainty sources that are random in the long term. The bias component takes into account the systematic effects that cause long-term bias (but not those that just cause bias within a given day). The long-term bias can be regarded as sum of procedure bias (bias inherent in the nature of the procedure) and laboratory bias (bias caused by the way how the procedure is implemented in the laboratory). The relative expanded uncertainty calculated with validation data was found to be 20% (k = 2), which is consistent with the one calculated by the modeling approach. 3.4.8. Traceability A principal requirement exists in ISO 17025 (ISO/IEC, 2005) for laboratories to produce measurements that are traceable to a common system of measurement, SI in this case, to ensure comparability of measurement results. A typical chemical measurement involves a number of steps as illustrated in Table 2. The way to demonstrate traceability is to use an uncertainty budget, where all the parameters influencing the final result are systematically

130% 120%

Recovery

110% 100% 90% 80% 70% 0.0

0.5

1.0

1.5

2.0

2.5

W(MeHg) in mg kg-1 as Hg Fig. 2. Accuracy profile.

3.0

3.5

4.0

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S. Azemard, E. Vassileva / Food Chemistry 176 (2015) 367–375 Table 2 Modeling approach for the calculation of combined uncertainty of MeHg mass fraction in biota sample. Preparation of calibration standards

CD i ¼ CM 

mði1Þ mM m1       ðmM þ md 1 Þ1 ðm1 þ md 2 Þ2 mði1Þ þ md i i

ð1Þ

Table 3 Single laboratory validation approach for the calculation of combined uncertainty of MeHg mass fraction in biota sample. Combined standard uncertainty (as relative)

uc ¼

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi u2Rw þ u2bias

ð1Þ

Sample bracketing calibration and other corrections

C meas ¼

CD

ðiþ1Þ

   ðAS  Aicorr  ABlk Þ þ C D i  Aðiþ1Þcorr  AS þ ABlk   Aðiþ1Þcorr  Aicorr

Random effect (as relative)

ð2Þ uRw ¼ SRw

ð2Þ

Absorbance correction

Acorr ¼ Astd  AI

ð3Þ

Blk

Recovery calculation

ubias ¼

n 1 X ½C CRM n R¼  C CRM cert n 1

ð4Þ

Final calculation with corrections for recovery and moisture content p 1 X C meas  V t1  V thio 1 CS ¼   f p 1W ms  V t2  R 1

Parameter

m

ð3Þ

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Pn 2 i¼1 ðbiasi Þ ¼ n

ð4Þ

clab i  cref i cref i sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi Pp 2 i¼1 ðuc ref i Þ ¼ n

ð5Þ

uc

ð6Þ

ð5Þ ref

Index

Mass fraction (mg kg1)

D

Working calibration standard

Parameter

Index

Mass fraction average (mg MeHg kg1 as Hg) Mass (kg)

M

Stock solution

i

u S RMS C

lab n Rw ref

A

Absorbance

S

Dilution step after dilution 1 (i P 2) Sample

R

Recovery

CRM

Certified Reference Material

V W

Volume (mL) Moisture content of biota sample (%) Dilution factor

Std meas

Calibration standard Measured

cert n, p Blk I_Blk Corr

Certified Number of repeats Procedural blank Instrumental background Correction for instrumental background Added toluene Collected toluene Volume of sodium thiosulfate Measured aliquot thiosulfate

f

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi RMS2bias þ u2ref

biasi ¼

t1 t2 thio aliquot

assessed. Key steps in the attainment of traceability were as follows: 1. The analytical method used was properly selected and validated, both in terms of matrix composition and analyte concentration 2. The unbroken chain linking the MeHg mass fraction to SI unit was described with the mathematical model. Table 2 presents the mathematical model of the analytical procedure, which is completely understood. This model, together with sub-calculations or references to certified values, relates each of the input quantity to SI units of the mol or the kilogram 3. The use of CRM for calibration and bias (recovery) estimation is the way to link MeHg mass fraction to the common system of reference SI. CRM with similar matrix was used also in the validation of sample preparation step

Standard uncertainty Standard deviation Root mean Square Mass fraction (mg kg1)

8

A: candidate CRM IAEA 470 (Oysters)

6 5 4 3 2 ILC

90

ID-ICP-MS

GC-Pyr-AFS

Org Hg AMA

B: IAEA 461 (Clams)

80 70 60 50 40 30 ILC

3.4.9. Comparison with IAEA worldwide inter-laboratory comparison assigned values and independent techniques Alternative approach for the method validation indicated in the ISO 17025 (ISO/IEC, 2005), is the participation in inter-laboratory

Laboratory Number of CRM used Within laboratory reproducibility Certified reference material

7 W(MeHg) mg kg-1 as Hg

C

RMSbias

W(MeHg) mg kg-1 as Hg

C

Possible bias (as relative)

ID-ICP-MS

GC-Pyr-AFS

Org Hg AMA

Fig. 3. Comparison of the MeHg mass fractions in candidate CRM IAEA 470 (A) and IAEA 461 (B) obtained from: the IAEA world-wide inter-laboratory comparison (ILC), isotope-dilution inductively coupled plasma mass spectrometry (ID-ICP-MS); gas chromatography coupled to atomic fluorescence spectrometry (GC–Py–AFS) and the method proposed in the present study (Org Hg AMA).

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comparisons and comparison of obtained results with results from independent method. Accordingly, results obtained with developed in this study measurement procedure were compared with the assigned reference value from the IAEA 461 worldwide inter-laboratory comparison (ILC) on the determination of trace elements and methyl mercury in biota sample (Clam) and IAEA 470 (candidate CRM) reference value. In addition they were compared with results from two independent methods namely; species specific isotope dilution ICP-MS (Vassileva et al., 2014) and GC–Py–AFS (Carrasco & Vassileva, 2014). As can be seen from Fig. 3, an excellent agreement within stated uncertainties was obtained. This agreement contributes for further validation of the described analytical procedure for determination of MeHg in marine biota samples. 4. Conclusion A method for the routine determination of MeHg in marine biota samples, based on solvent extraction of organic mercury species, back-extraction into aqueous phase and direct mercury analyzer determination has been validated. Important parameters influencing the extraction procedure efficiency, such as acid concentration, solvent and back-extraction time were optimized. The validation of the methodology was performed according to the ISO-17025 guideline, using four different certified reference materials. Selectivity was evaluated by the analysis of the same extracts by GC–AFS hyphenated method. An uncertainty budget was built for the analytical procedure, allowing for the quantification of the relative uncertainty contributions for each parameter in the measurement procedure and the determination of their relative contributions to the final expanded uncertainty. Contributions arising from recovery and repeatability of the measurements dominated the uncertainty budget. Overall, the proposed method is simple, cost-effective and allows the analysis of 20 samples per working day. As a consequence from the single solvent extraction step the volume of generated waste is considerably decreased. In light of the results presented in this study, the methodology proposed could ultimately be a ready-to-use analytical method for the determination of MeHg in marine biota samples. Acknowledgements The Agency is grateful for the support provided to its Environment Laboratories by the Government of the Principality of Monaco. The IAEA-NAEL in Monaco operates under an agreement between the IAEA and the Government of the Principality of Monaco. Dr. Luis Carrasco is acknowledged for the helpful comments and remarks during this study. References Calderón, J., Gonçalves, S., Cordeiro, F., & de la Calle, B. 2013. Determination of methylmercury in seafood by direct mercury analysis: standard operating procedure. JRC technical reports. Joint Research Centre, Institute for Reference Materials and Measurements, Belgium. Carbonell, G., Bravo, J. C., Fernandez, C., & Tarazona, J. V. (2009). A new method for total mercury and methyl mercury analysis in muscle of seawater fish. Bulletin of Environmental Contamination and Toxicology, 83, 210–213. Carrasco, L., Benejam, L., Benito, J., Bayona, J. M., & Diez, S. (2011). Methylmercury levels and bioaccumulation in the aquatic food web of a highly mercurycontaminated reservoir. Environment International, 37, 1213–1218. Carrasco, L., Diez, S., & Bayona, J. M. (2009). Methylmercury determination in biota by solid-phase microextraction: Matrix effect evaluation. Journal of Chromatography A, 1216, 8828–8834. Carrasco, L., & Vassileva, E. (2014). Determination of methylmercury in marine biota samples: Method validation. Talanta, 122, 106–114. Clémens, S., Monperrus, M., Donard, O. F. X., Amouroux, D., & Guérin, T. (2011). Mercury speciation analysis in seafood by species-specific isotope dilution:

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