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Simultaneous determination of methyl- and ethyl-mercury by solid-phase microextraction followed by gas chromatography atomic fluorescence detection
Journal of Chromatography A, 1216 (2009) 8828–8834
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Journal of Chromatography A journal homepage: www.elsevier.com/locate/chroma
Simultaneous determination of methyl- and ethyl-mercury by solid-phase microextraction followed by gas chromatography atomic fluorescence detection Luis Carrasco, Sergi Díez ∗ , Josep M. Bayona Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research, IDÆA-CSIC, Jordi Girona, 18-26, E-08034 Barcelona, Spain
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Article history: Received 3 September 2009 Accepted 13 October 2009 Available online 20 October 2009 Keywords: Methylmercury Ethylmercury Py-AFS Detection parameters Multivariate optimization Biota matrixes
a b s t r a c t A method for trace level determination of organomercury species in different biota matrixes by using aqueous-phase propylation followed by headspace solid-phase microextraction (HS-SPME) and gas chromatography (GC) coupled to pyrolysis-atomic fluorescence spectrometry (Py-AFS) detection has been optimized. To maximize peak area and symmetry factors of methylmercury (MeHg) and ethylmercury (EtHg) analyzed as propyl derivatives, carrier and make-up flow rates were optimized by a user-defined experimental design. A multiple response simultaneous optimization was applied using the desirability function to achieve global optimal operating conditions. They were attained at 2 and 6 mL min−1 as carrier and make-up gas flow rates, respectively. In addition, pyrolyser temperature was also optimized, yielding the best value at 750 ◦ C. Limits of detection and quantification at the optimum conditions were 0.04 ng g−1 and 0.13 ng g−1 for both, MeHg and EtHg. The developed analytical procedure was validated with a certified reference material (DORM-2) and applied to the determination of organomercury incurred in waterfowl egg and fish samples. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Alkylmercury compounds are the most toxic mercury species found in the environment, because of their capability to permeate through biological membranes and to bioaccumulate and to biomagnificate through the trophic chain [1]. Methylmercury (MeHg), the most widespread alkylmercury compound, can cause severe neurological damage to humans and wildlife [2,3] and it is by far the most studied organomercury compound. However, the exposure to other organomercury species, mainly ethylmercury (EtHg), which is believed to have toxicity similar to MeHg [4], is often neglected. EtHg in the form of thimerosal has been found in a wide range of applications in medicine as a disinfectant agent or preservative in vaccines [5]. The toxicity of EtHg after its exposure and death at high doses has already been reported [6]. In addition, the occurrence of EtHg in abiotic matrixes, namely soils and sediments from Florida Everglades, mercury contaminated industrial sites in Germany, the mining areas in Slovenia, Canadian wetlands and sediments from St. Clair River [7–10] has also been reported. Reliable and sensitive methods are essential to carry out the speciation of organomercury compounds in biological and environmental matrixes. Although methods for MeHg determination are well developed, few analytical techniques are available for EtHg. Thus, the development of analytical techniques able to the simul-
∗ Corresponding author. Tel.: +34 93 4006100; fax: +34 93 2045904. E-mail address: [email protected] (S. Díez). 0021-9673/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.chroma.2009.10.043
taneous and accurate determination of MeHg and EtHg is a valuable tool for understanding the mercury biogeochemistry and ecotoxicology. The most widely used separation techniques for organomercury speciation are gas chromatography (GC), high-performance liquid chromatography (HPLC), supercritical-fluid chromatography (SFC), and, recently, capillary zone electrophoresis (CZE) [11]. Although GC separation ensures a powerful resolution and sensitivity of alkylmercury species [12], the lack of volatility of MeHg and EtHg requires a derivatization step prior to their determination. The major drawback of the most commonly used derivatization reagent, sodium tetraethylborate (NaBEt4 ), is the inability to distinguish between EtHg and the inorganic mercury ion (Hg2+ ) because the ethylation of both species leads to the formation of the same product, diethylmercury. To overcome this limitation, sodium tetrapropylborate (NaBPr4 ) and sodium tetraphenylborate (NaBPh4 ) have been proposed [13,14]. Both species are commercially available and able to distinguish between ethyl- and inorganic mercury derivatives. NaBPr4 presents three major advantages over NaBPh4 , e.g. higher volatility of the propylated species, higher derivatization yields and shorter equilibration time in SPME [15]. Therefore, NaBPr4 has already been used for the optimization of headspace solid-phase microextraction (HS–SPME) of MeHg [16,17]. Detection systems used for speciation should exhibit elemental selectivity and sensitivity to the target analytes. For organomercury speciation, the most common detectors used are cold-vapor atomic absorption spectrometry (CVAAS) [18], cold-vapor (CV) atomic flu-
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orescence spectrometry (AFS) [19], microwave-induced plasma atomic emission spectrometry (MIP–AES) [20], inductively coupled plasma mass spectrometry (ICP–MS) [21,22] and furnace atomization plasma emission spectrometry (FAPES) [15,23]. The AFS is a concentration-sensitive detector, which provides an output that is directly proportional to the concentration of a sample component in the mobile phase [24]. In this regard, when high make-up gas flow rates are used, a decrease in the analytical signal is noted, attributable to an excess dilution. Therefore, the study of the optimum make-up gas flow rate is essential to achieve suitable peak and symmetry area. On the other hand, the quenching factor of hydrogen gas (H2 ), one of the most widely used carrier gas, is about 700 times higher than that of Argon (Ar). As a consequence, strong fluorescence signal quenching is observed when using H2 as carrier gas [25]. To overcome this drawback introduced by the H2 gas, the use of Ar as carrier gas would be expected to provide a much better fluorescence signal. The goal of this study was to develop a method for the simultaneous determination of MeHg and EtHg in which the parameters affecting the pyrolysis and the detection were optimized. Analyte extraction has been carried out by aqueous-phase propylation followed by HS-SPME preconcentration and GC-Py-AFS determination. Accordingly, aiming to obtain suitable MeHg and EtHg peak symmetry and area, carrier and make-up gas flow rates have been optimized by a user-defined experimental design. The effect of the pyrolyser temperature has been evaluated as well. 2. Experimental 2.1. Reagents, standards and materials Mercury dichloride (HgCl2 , 99.9995%) and methylmercury chloride (CH3 HgCl, 99%) were obtained from Strem (Newburgport, MA, USA). Ethylmercury chloride (CH3 CH2 HgCl) was purchased from Alfa Aesar (Karlsruhe, Germany). Sodium tetrapropylborate (NaBPr4 , 98%) was obtained form Galab (Geesthacht, Germany). ACS reagent sodium citrate tribasic dihydrate (99.0%) and citric acid monohydrate (99.0–102%) were obtained from Sigma–Aldrich (Steinheim, Germany). Stock standard solutions were prepared at 1000 mg L−1 (as Hg) in acetone and stored at −20 ◦ C. Working solutions were prepared weekly by diluting the stock solutions with acetone to a range of 0.02–500 g L−1 as Hg. A fresh NaBPr4 solution of 1% (w/v) was daily prepared in deionized water and stored at 4 ◦ C. Citric buffer (pH 4.5) was prepared by mixing in Milli-Q water citric acid monohydrate (0.1 M) and sodium citrate dihydrate (0.1 M). A certified reference material, DORM-2 (dogfish muscle), was purchased from National Research Council of Canada (NRCC, Ottawa, Ontario, Canada). Diisobutylmercury (iBu2 Hg) was used as the internal standard. It was synthesized in our laboratory from mercury dichloride and the Grignard reagent isobutyl magnesium bromide 2.0 M in diethyl ether, which was obtained from Sigma–Aldrich. A 25 L volume of HgCl2 (4000 g g−1 ) and 1 mL of isobutyl magnesium bromide (2 M) were added to 2 mL of acetonitrile. After 20 min, the reaction was stopped by adding 10 mL of Milli-Q water and the solution was cooled down by using an ice bath. Finally, iBu2 Hg was extracted with 4 mL of hexane and percolated through a funnel containing sodium sulphate. The purity of the synthesized standard was examined by using the GC-Py-AFS. 2.2. Apparatus 2.2.1. SPME device The SPME fiber holder for manual use and the silica fiber coated with 100 m thickness of poly(dimethylsiloxane) (PDMS) were
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obtained from Supelco (Bellefonte, PA, USA). A 6 mL glass vial with PTFE-coated silicone rubber septa was used for headspace SPME. Experiments were performed at constant temperature (30 ◦ C) using an ETS-D4 fuzzy thermometer and a digital RCT hot plate stirrer working at 1200 rpm, both purchased from Ika Labortechnik (Staufen, Germany). A 12 mm × 2 mm PTFE-coated magnetic stirring bar was used. 2.2.2. GC-Py-AFS The GC analysis was accomplished with a non-commercial system formed by a Thermo trace GC ultra (Rodano, Milan, Italy) gas chromatograph interfaced to an AFS Tekran Model 2500 (Toronto, Canada) detector via a 18 cm × 23 cm × 18 cm pyrolyzer (Hg-800, Rektorik R&D Chromatography, Meyrin, Switzerland). The main body of the pyrolyzer consists of a low volume quartz tube heated up to 800 ◦ C. The heated length to maximum temperature is 140 mm. The pyrolysed compounds are fed to the mercury detector through a fused silica tubing of 300 mm. This one is heated to above 160 ◦ C. The AFS system is an extremely sensitive detector where the elemental mercury (Hg0 ) atoms, in an inert carrier gas stream, are excited by a source of UV radiation. A split/splitless injector equipped with a Merlin valve was used in the splitless mode (3 min). To overcome MeHg decomposition [26], the injector temperature was maintained at 150 ◦ C. A 15 m × 0.32 mm I.D. fused-silica column coated with a 0.25 m film thickness of BP1 (SGE, Ringwood, Victoria, Australia) was used as analytical column. The initial column temperature was held at 40 ◦ C for 3 min, programmed at 15 ◦ C min−1 to 180 ◦ C, and this latter temperature was held for 2 min. After the different Hg forms had been separated in the GC column, they were converted into Hg0 by thermal decomposition at 750 ◦ C in the pyrolyzer and finally detected by AFS. Ar 5.0 grade gas was used as the carrier gas (i.e. 2 mL min−1 ) and also as make-up gas (i.e. 6 mL min−1 ) for the AFS detector connected to the system before it was connected to the pyrolyzer. All the tubing was made of PTFE. Finally, data were acquired and processed by Chrom-Card software (Rodano, Milan, Italy). 2.3. Procedure 2.3.1. Sample collection Fish samples were collected from several locations in the Ebro River (NE Spain). Fishes (common carp, Cyprinus carpio) were captured using electrofishing boat equipped with a 5.0-GPP SmithRoot Inc. engine (Vancouver, WA, USA), providing up to 1000 V and 16 A. Captured fish were preserved on ice and transported to the laboratory. Once in the lab, samples of their dorsal muscle were dissected, immediately frozen, and stored at −20 ◦ C for Hg determination. Sample preparation and digestion were carried out following a methodology described elsewhere [16]. Briefly, a 200 mg (wet weight, ww) fish sample was placed in a 40 mL glass bottle. Then, 10 mL of 25% (w/v) aqueous KOH solution was added. Vortex shaking was subsequently employed for 1 min to ensure the homogenization of both phases, followed by heating in a water bath at 60 ◦ C for 180 min. The digested sample was vortexed and stored at 4 ◦ C before analysis. All the digested samples were analyzed within one week. Ardea Purpurea egg samples were collected in the Flix reservoir (NE Spain). Eggs belonging to several clutches were collected, under license, in a small breeding subcolony. Fresh eggs were frozen until analyzed in the laboratory. Egg content was separated from the egg shell and freeze-dried. In a 40 mL glass vial, 200 mg of the freeze-dried egg content was placed. Subsequently, 2 mL of aqueous KOH solution (25%, w/v) were added. After 1 min of vortex shaking, the mixture was heated in a water bath at 50 ◦ C for 60 min.
6.851 −0.022 0.117 −1.760 −0.012 0.850 C, M, CM, C2 , M2 −0.136 −0.217 0.022 −0.070 5.4exp−003 0.869 CM, M2 0.055 −0.134 0.015 −0.078 3.2exp−003 0.870 CM, C2 , M2
The matrix digest was vortexed and stored at 4 ◦ C before analysis. All the digested samples were analyzed within one week. 2.3.2. SPME sampling MeHgCl and EtHgCl standards were used for method development and optimization. A 50 L volume of both standards (100 g L−1 ) in acetone were placed in a 6 mL glass vial with 3 mL of citric–citrate buffer solution (0.1 M, pH 4.5) containing a magnetic stirring bar. Then, 50 L of 100 g L−1 iBu2 Hg (internal standard) in acetone solution was added and the vial was closed. Subsequently, 50 L of 1% aqueous NaBPr4 solution was injected through the septum. After 5 min of reaction time, at 30 ◦ C and 1200 rpm, the fiber was drawn into the needle of the holder, and the needle was used to pierce the septum of the vial. The fiber was then lowered into the headspace by depressing the plunger. After 12 min of sampling time at 30 ◦ C and 1200 rpm, the fiber was retracted into the needle and immediately injected into the GC-Py-AFS system. 2.3.3. Statistics and experimental design A one-way analysis of variance was performed on the experimental data obtained. All statistical analyses were conducted with SPSS, version 15.0 for Windows (SPSS Inc., Chicago, IL, USA). Statistical significance was defined as p ≤ 0.05. An experimental design was performed with MeHg and EtHg standards in order to optimize important detection parameters such as carrier and make-up gas flow rates. Therefore, an experimental design was built by using the user-defined application of the program Design-Expert 7.1.6 (Stat-Ease Inc., Minneapolis, MN, USA). Response was statistically tested with a polynomial regression model, which was also used to generate surface plots. To overcome differing responses of individual analytes, a multiple response optimization approach was performed. Desirability, D is an objective function that ranges from zero for a completely undesirable response to one for a fully desired response [27]. The numerical optimization finds a point that maximizes the desirability function; then, the function D was used to simultaneously optimize all the responses for MeHg and EtHg as well. 3. Results and discussion 3.1. Detection parameters optimization
C: carrier gas flow rate; M: make-up gas flow rate.
1.625 0.061 0.094 −0.484 −0.011 0.841 C, M, CM, C2 , M2 −0.221 −0.076 0.015 −6.6exp−003 9.0exp−004 0.593 M, CM ˇ1 ˇ2 ˇ3 ˇ4 ˇ5 R2 Significant terms in the model (p < 0.05)
201.3 −21.55 7.389 −60.84 −0.173 0.949 C, M CM, C2
−0.522 −0.126 0.026 0.019 1.4exp−003 0.577 M, CM
377.0 −56.66 12.70 −122.4 0.306 0.974 C, M, CM, C2 , M2
Height/width at half height ratio Asymmetry ratio Area Height/width at half height ratio Asymmetry ratio Tailing factor Area
MeHg Table 1 Model characteristics of analytes.
Tailing factor
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EtHg
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3.1.1. Response surface design The peak area and symmetry factors are strongly dependent on the make-up Ar gas flow rate, added coaxially after the GC column effluent, as well as on the carrier Ar gas flow rate employed to transport the analytes through the analytical column. Considering the MeHg and EtHg peak area, tailing factor, asymmetry ratio and height/width at half height ratio as response variables, the experimental design described in Section 2.3.3, was applied to obtain further information on the effect of factors, namely carrier and make-up gas flow rates on the response variables. Factor ranges were from 6 to 27 mL min−1 and 1 to 3 mL min−1 for make-up and carrier gas flow rates, respectively. Data were modeled using a multiple linear regression, including the first order interaction and the quadratic terms. The general equation for the polynomial regression was as follows: Rx = ˇ0 + ˇ1 C + ˇ2 M + ˇ3 CM + ˇ4 C 2 + ˇ5 M 2
(1)
where Rx is the response variable, namely peak area, tailing factor, asymmetry ratio and height/width at half height ratio obtained for the target analyte x, C and M were the carrier and make-up gas flow rates, respectively and ˇn the different coefficients obtained. The regression coefficient (R2 ) for all the response variables of each analyte, their corresponding ˇn values, and significance terms in the model are shown in Table 1.
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Fig. 1. Response surface plots for (a) EtHg area, (b) MeHg tailing factor, (c) EtHg asymmetry ratio, and (d) MeHg height/width at half height ratio.
Fig. 2. Contour plot for the EtHg desirability function.
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Table 2 Comparison between theoretical data provided by the desirability function and experimental results under the optimized conditions. Analyte
Theoretical area
Experimental area
Theoretical–experimental comparison (%)
Theoretical height/width at half height ratio
Experimental height/width at half height ratio
Theoreticalexperimental comparison (%)
MeHg EtHg
175.05 362.60
178.99 379.33
2.3 4.6
1.51 3.43
1.26 3.76
16.6 9.6
Fig. 3. Effect of the pyrolyser temperature on the peak area and symmetry factors for MeHg and EtHg.
Fig. 1a shows the surface response and contour plots for EtHg area according to the carrier and/or make-up gas flow rates. A minimum is observed at lower carrier and higher make-up, whereas the highest peak area is reached in the zone of mean carrier (2 mL min−1 ) and lowest make-up (6 mL min−1 ). All the coefficient terms were significant (p < 0.05) in the model, indicating that the EtHg area behavior is clearly influenced by both the gas flow rates. Similar behavior is exhibited for MeHg (figure not shown). Fig. 1b shows the surface response for MeHg tailing factor. As can be seen, the make-up gas flow rate exerts more influence on the tail factor than the carrier gas flow rate. In this sense, as the make-up gas flow rate increases, the response decreases, yielding the best results using values of flow rate close to 27 mL min−1 . A similar response plot was obtained for MeHg asymmetry ratio. On the other hand, the tailing factor and asymmetry ratio (Fig. 1c) for EtHg are described by two maxima and two minima in the response surface. One maximum is located in the zone of maximum value for the two gases, while the other one is at the minimum for the two gases. Moreover, there is one minimum at the mean make-up and the lowest carrier, and another one at the mean make-up, but at the highest carrier gas flow rate. Fig. 1d shows the response plot for MeHg height/width at half height ratio. Following the peak area pattern for both, MeHg and EtHg, Fig. 1d shows a minimum in the lowest carrier and the highest make-up gas flow rates values. Nevertheless, the best results are obtained in the zone of maximum carrier and when the make-up gas flow rate reaches about 13 mL min−1 . In summary, all the coefficient terms are significant, indicating that both, carrier and make-up gas flow rates, have a high influence in the MeHg height/width at half height ratio behavior. Finally, the EtHg height/width at half height ratio surface response (figure not shown) follows the same trend as MeHg, which can be explained by the significance of carrier and make-up gas flow rates in the model. However for EtHg, the best results were obtained for medium values of carrier gas flow rate.
3.1.2. Multi-response optimization using desirability function To overcome the problem of conflicting responses of individual analyte, a multi-response optimization was used. In multi-response optimization, a desired weight is given to each response. In the present study, when building this function, higher desirable values were given to both MeHg and EtHg peak area and height/width at half height ratio. Then, two D functions (one for each analyte) were numerically maximized. Fig. 2 shows the contour plot for result of overall desirability function for EtHg when the carrier and make-up gas flow rates were modified. The overall desirability value is lowest in the region of high to medium make-up gas and low carrier gas. The maximum value, e.g. 0.848, is reached in the zone of the lowest make-up and the mean carrier gas flow rates. It is important to note that the goal of optimization is to find the best set of conditions in which all responses are maximized not to get a desirability value of 1. The overall desirability function for MeHg (figure not shown) exhibited a similar trend. According to these results, the optimum carrier and make-up gas flow rates were fixed at 2 and 6 mL min−1 , respectively. Theoretical area and height/width at half height ratio values provided by the desirability function are shown in Table 2. As can be seen, theoretical results match very well with experimental results. 3.2. Pyrolyser temperature optimization Prior to detection by AFS, the different mercury species, which elute from the analytical column must be converted to Hg0 by thermal treatment in a pyrolytic reactor. Since the temperature of the pyrolytic reactor influences the peak area [28], different temperatures (e.g. 700, 750 and 800 ◦ C) have been tested, and their effect on the peak symmetry and area were evaluated under the detector optimized conditions. There were statistically significant differences among 700 ◦ C and the other two temperatures, 750 and 800 ◦ C for MeHg area and height/width at half height ratio (Fig. 3). Following manufacturer recommendations, no higher temperatures than 800 ◦ C were evaluated. No significant differences
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and 11% (EtHg) for the repeatability study and 10% (MeHg) and 16% (EtHg) for the reproducibility study, thus showing the robustness of the analytical procedure. Quantification and recovery calculation were performed based on the internal standard procedure, for which iBu2 Hg was used as the internal standard. The external calibration linearity ranged from 0.007 to 1 ng as introduced mass in the detector (R2 > 0.99), which is equivalent to 0.01–3 g g−1 as Hg in the samples for MeHg and EtHg. Procedural blanks of below 0.01 g g−1 as Hg were obtained for every batch of samples. The limit of detection (LOD) of the method, defined as the mean background noise in a procedural blank triplicate plus three times the standard deviation of the background, was 0.04 ng g−1 , ww, for both MeHg and EtHg; the limit of quantitation (LOQ), defined as the mean background noise in a blank triplicate plus ten times the standard deviation of the background, was 0.13 ng g−1 , ww, for both compounds. Such detection limits make it possible to simultaneously determine MeHg and EtHg levels in biota samples without preconcentration using this method.
3.4. Application to real samples The efficiency of the developed method was evaluated by analyzing different biota matrixes, namely fish and waterfowl eggs, collected in a highly polluted area close to a chlor-alkali plant. Fig. 4a–c shows typical chromatograms of MeHg and EtHg standards, a waterfowl egg sample and a fish sample, respectively. In these samples, MeHg but not EtHg were identified.
4. Conclusions
Fig. 4. GC-Py-AFS chromatograms obtained for (a) MeHg and EtHg standards, (b) egg sample, and (c) fish sample. (1) Hg0 , (2) MeHgPr, (3) EtHgPr, (4) HgPr2 , (5) PriBuHg, and (6) iBu2 Hg. MeHg and EtHg standards and fish sample chromatograms were obtained with Chrom-Card software, whereas egg sample chromatogram was obtained with Atlas software.
were observed for MeHg asymmetry ratio and tailing factor. In the case of EtHg, statistically significant differences were not found for either the peak area or any of the peak symmetry factors studied. For both, MeHg and EtHg, the best repeatability results were achieved at 750 ◦ C, which was the final selected temperature. 3.3. Method validation, linearity and figures of merit The MeHg concentration in the CRM DORM-2 was determined and compared to the certified value. Since DORM-2 did not contain measurable EtHg levels, recoveries of this analyte were evaluated spiking the CRM DORM-2 with a known amount of EtHgCl. The MeHg concentration found in the DORM-2 was 4.15 ± 0.19 g g−1 (n = 5), which was in good agreement to the certified value (4.47 ± 0.31). The EtHg recovery from the spiked DORM-2 was also high (over 80%) indicating that MeHg and EtHg in samples could be simultaneously analyzed using this aqueous phase propylation, subsequent headspace SPME sampling and finally, GCPy-AFS determination. In support of this, the repeatability was tested by analyzing six replicates of MeHgCl (5.396 ng) and EtHgCl (3.269 ng) standards in the same day, whereas the reproducibility was evaluated by analyzing such standards on six different days. The relative standard deviations (RSDs) were found to be 9% (MeHg)
A method for the simultaneous determination of MeHg and EtHg in biota samples has been developed, which is based on aqueous propylation derivatization, HS-SPME preconcentration, GC separation and Py-AFS detection. Carrier and make-up gas flow rates were optimized using response surface methodology with peak symmetry and area of both analytes as response variables. The use of the desirability function allowed for the simultaneous optimization of all response variables in spite of their conflicting responses to yield global optimal conditions. Theoretical data provided by this function were validated by running these conditions with both standards; the results obtained were in accordance with the theoretical prediction. Indeed, the pyrolyser temperature, another factor affecting the analyte peak symmetry and area, has been optimized. The accuracy of the methodology presented has been validated by characterizing a reference material and it proved to be fast, simple and sensitive. Moreover, the aqueous propylationHS-SPME-GC-Py-AFS method has been successfully applied to the analysis of real samples, providing a powerful tool to assess the relationship between the specific mercury species and its wildlife toxicity.
Acknowledgements Financial support was obtained from the Spanish Ministry of Environment, the Catalan Agency of Water (ACA, Generalitat de Catalunya) and the Fundación BBVA (BIOCON06/113; Project EMECO, IV Convocatoria de Ayudas a la Investigación en Ecología y Biología de la Conservación). L. Carrasco would like to express his gratitude to Consejo Superior de Investigaciones Científicas for an I3P fellowship. D. Calderón-Preciado is thanked for helping in the statistical analysis of data.
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Journal of Chromatography A journal homepage: www.elsevier.com/locate/chroma
Simultaneous determination of methyl- and ethyl-mercury by solid-phase microextraction followed by gas chromatography atomic fluorescence detection Luis Carrasco, Sergi Díez ∗ , Josep M. Bayona Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research, IDÆA-CSIC, Jordi Girona, 18-26, E-08034 Barcelona, Spain
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Article history: Received 3 September 2009 Accepted 13 October 2009 Available online 20 October 2009 Keywords: Methylmercury Ethylmercury Py-AFS Detection parameters Multivariate optimization Biota matrixes
a b s t r a c t A method for trace level determination of organomercury species in different biota matrixes by using aqueous-phase propylation followed by headspace solid-phase microextraction (HS-SPME) and gas chromatography (GC) coupled to pyrolysis-atomic fluorescence spectrometry (Py-AFS) detection has been optimized. To maximize peak area and symmetry factors of methylmercury (MeHg) and ethylmercury (EtHg) analyzed as propyl derivatives, carrier and make-up flow rates were optimized by a user-defined experimental design. A multiple response simultaneous optimization was applied using the desirability function to achieve global optimal operating conditions. They were attained at 2 and 6 mL min−1 as carrier and make-up gas flow rates, respectively. In addition, pyrolyser temperature was also optimized, yielding the best value at 750 ◦ C. Limits of detection and quantification at the optimum conditions were 0.04 ng g−1 and 0.13 ng g−1 for both, MeHg and EtHg. The developed analytical procedure was validated with a certified reference material (DORM-2) and applied to the determination of organomercury incurred in waterfowl egg and fish samples. © 2009 Elsevier B.V. All rights reserved.
1. Introduction Alkylmercury compounds are the most toxic mercury species found in the environment, because of their capability to permeate through biological membranes and to bioaccumulate and to biomagnificate through the trophic chain [1]. Methylmercury (MeHg), the most widespread alkylmercury compound, can cause severe neurological damage to humans and wildlife [2,3] and it is by far the most studied organomercury compound. However, the exposure to other organomercury species, mainly ethylmercury (EtHg), which is believed to have toxicity similar to MeHg [4], is often neglected. EtHg in the form of thimerosal has been found in a wide range of applications in medicine as a disinfectant agent or preservative in vaccines [5]. The toxicity of EtHg after its exposure and death at high doses has already been reported [6]. In addition, the occurrence of EtHg in abiotic matrixes, namely soils and sediments from Florida Everglades, mercury contaminated industrial sites in Germany, the mining areas in Slovenia, Canadian wetlands and sediments from St. Clair River [7–10] has also been reported. Reliable and sensitive methods are essential to carry out the speciation of organomercury compounds in biological and environmental matrixes. Although methods for MeHg determination are well developed, few analytical techniques are available for EtHg. Thus, the development of analytical techniques able to the simul-
∗ Corresponding author. Tel.: +34 93 4006100; fax: +34 93 2045904. E-mail address: [email protected] (S. Díez). 0021-9673/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.chroma.2009.10.043
taneous and accurate determination of MeHg and EtHg is a valuable tool for understanding the mercury biogeochemistry and ecotoxicology. The most widely used separation techniques for organomercury speciation are gas chromatography (GC), high-performance liquid chromatography (HPLC), supercritical-fluid chromatography (SFC), and, recently, capillary zone electrophoresis (CZE) [11]. Although GC separation ensures a powerful resolution and sensitivity of alkylmercury species [12], the lack of volatility of MeHg and EtHg requires a derivatization step prior to their determination. The major drawback of the most commonly used derivatization reagent, sodium tetraethylborate (NaBEt4 ), is the inability to distinguish between EtHg and the inorganic mercury ion (Hg2+ ) because the ethylation of both species leads to the formation of the same product, diethylmercury. To overcome this limitation, sodium tetrapropylborate (NaBPr4 ) and sodium tetraphenylborate (NaBPh4 ) have been proposed [13,14]. Both species are commercially available and able to distinguish between ethyl- and inorganic mercury derivatives. NaBPr4 presents three major advantages over NaBPh4 , e.g. higher volatility of the propylated species, higher derivatization yields and shorter equilibration time in SPME [15]. Therefore, NaBPr4 has already been used for the optimization of headspace solid-phase microextraction (HS–SPME) of MeHg [16,17]. Detection systems used for speciation should exhibit elemental selectivity and sensitivity to the target analytes. For organomercury speciation, the most common detectors used are cold-vapor atomic absorption spectrometry (CVAAS) [18], cold-vapor (CV) atomic flu-
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orescence spectrometry (AFS) [19], microwave-induced plasma atomic emission spectrometry (MIP–AES) [20], inductively coupled plasma mass spectrometry (ICP–MS) [21,22] and furnace atomization plasma emission spectrometry (FAPES) [15,23]. The AFS is a concentration-sensitive detector, which provides an output that is directly proportional to the concentration of a sample component in the mobile phase [24]. In this regard, when high make-up gas flow rates are used, a decrease in the analytical signal is noted, attributable to an excess dilution. Therefore, the study of the optimum make-up gas flow rate is essential to achieve suitable peak and symmetry area. On the other hand, the quenching factor of hydrogen gas (H2 ), one of the most widely used carrier gas, is about 700 times higher than that of Argon (Ar). As a consequence, strong fluorescence signal quenching is observed when using H2 as carrier gas [25]. To overcome this drawback introduced by the H2 gas, the use of Ar as carrier gas would be expected to provide a much better fluorescence signal. The goal of this study was to develop a method for the simultaneous determination of MeHg and EtHg in which the parameters affecting the pyrolysis and the detection were optimized. Analyte extraction has been carried out by aqueous-phase propylation followed by HS-SPME preconcentration and GC-Py-AFS determination. Accordingly, aiming to obtain suitable MeHg and EtHg peak symmetry and area, carrier and make-up gas flow rates have been optimized by a user-defined experimental design. The effect of the pyrolyser temperature has been evaluated as well. 2. Experimental 2.1. Reagents, standards and materials Mercury dichloride (HgCl2 , 99.9995%) and methylmercury chloride (CH3 HgCl, 99%) were obtained from Strem (Newburgport, MA, USA). Ethylmercury chloride (CH3 CH2 HgCl) was purchased from Alfa Aesar (Karlsruhe, Germany). Sodium tetrapropylborate (NaBPr4 , 98%) was obtained form Galab (Geesthacht, Germany). ACS reagent sodium citrate tribasic dihydrate (99.0%) and citric acid monohydrate (99.0–102%) were obtained from Sigma–Aldrich (Steinheim, Germany). Stock standard solutions were prepared at 1000 mg L−1 (as Hg) in acetone and stored at −20 ◦ C. Working solutions were prepared weekly by diluting the stock solutions with acetone to a range of 0.02–500 g L−1 as Hg. A fresh NaBPr4 solution of 1% (w/v) was daily prepared in deionized water and stored at 4 ◦ C. Citric buffer (pH 4.5) was prepared by mixing in Milli-Q water citric acid monohydrate (0.1 M) and sodium citrate dihydrate (0.1 M). A certified reference material, DORM-2 (dogfish muscle), was purchased from National Research Council of Canada (NRCC, Ottawa, Ontario, Canada). Diisobutylmercury (iBu2 Hg) was used as the internal standard. It was synthesized in our laboratory from mercury dichloride and the Grignard reagent isobutyl magnesium bromide 2.0 M in diethyl ether, which was obtained from Sigma–Aldrich. A 25 L volume of HgCl2 (4000 g g−1 ) and 1 mL of isobutyl magnesium bromide (2 M) were added to 2 mL of acetonitrile. After 20 min, the reaction was stopped by adding 10 mL of Milli-Q water and the solution was cooled down by using an ice bath. Finally, iBu2 Hg was extracted with 4 mL of hexane and percolated through a funnel containing sodium sulphate. The purity of the synthesized standard was examined by using the GC-Py-AFS. 2.2. Apparatus 2.2.1. SPME device The SPME fiber holder for manual use and the silica fiber coated with 100 m thickness of poly(dimethylsiloxane) (PDMS) were
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obtained from Supelco (Bellefonte, PA, USA). A 6 mL glass vial with PTFE-coated silicone rubber septa was used for headspace SPME. Experiments were performed at constant temperature (30 ◦ C) using an ETS-D4 fuzzy thermometer and a digital RCT hot plate stirrer working at 1200 rpm, both purchased from Ika Labortechnik (Staufen, Germany). A 12 mm × 2 mm PTFE-coated magnetic stirring bar was used. 2.2.2. GC-Py-AFS The GC analysis was accomplished with a non-commercial system formed by a Thermo trace GC ultra (Rodano, Milan, Italy) gas chromatograph interfaced to an AFS Tekran Model 2500 (Toronto, Canada) detector via a 18 cm × 23 cm × 18 cm pyrolyzer (Hg-800, Rektorik R&D Chromatography, Meyrin, Switzerland). The main body of the pyrolyzer consists of a low volume quartz tube heated up to 800 ◦ C. The heated length to maximum temperature is 140 mm. The pyrolysed compounds are fed to the mercury detector through a fused silica tubing of 300 mm. This one is heated to above 160 ◦ C. The AFS system is an extremely sensitive detector where the elemental mercury (Hg0 ) atoms, in an inert carrier gas stream, are excited by a source of UV radiation. A split/splitless injector equipped with a Merlin valve was used in the splitless mode (3 min). To overcome MeHg decomposition [26], the injector temperature was maintained at 150 ◦ C. A 15 m × 0.32 mm I.D. fused-silica column coated with a 0.25 m film thickness of BP1 (SGE, Ringwood, Victoria, Australia) was used as analytical column. The initial column temperature was held at 40 ◦ C for 3 min, programmed at 15 ◦ C min−1 to 180 ◦ C, and this latter temperature was held for 2 min. After the different Hg forms had been separated in the GC column, they were converted into Hg0 by thermal decomposition at 750 ◦ C in the pyrolyzer and finally detected by AFS. Ar 5.0 grade gas was used as the carrier gas (i.e. 2 mL min−1 ) and also as make-up gas (i.e. 6 mL min−1 ) for the AFS detector connected to the system before it was connected to the pyrolyzer. All the tubing was made of PTFE. Finally, data were acquired and processed by Chrom-Card software (Rodano, Milan, Italy). 2.3. Procedure 2.3.1. Sample collection Fish samples were collected from several locations in the Ebro River (NE Spain). Fishes (common carp, Cyprinus carpio) were captured using electrofishing boat equipped with a 5.0-GPP SmithRoot Inc. engine (Vancouver, WA, USA), providing up to 1000 V and 16 A. Captured fish were preserved on ice and transported to the laboratory. Once in the lab, samples of their dorsal muscle were dissected, immediately frozen, and stored at −20 ◦ C for Hg determination. Sample preparation and digestion were carried out following a methodology described elsewhere [16]. Briefly, a 200 mg (wet weight, ww) fish sample was placed in a 40 mL glass bottle. Then, 10 mL of 25% (w/v) aqueous KOH solution was added. Vortex shaking was subsequently employed for 1 min to ensure the homogenization of both phases, followed by heating in a water bath at 60 ◦ C for 180 min. The digested sample was vortexed and stored at 4 ◦ C before analysis. All the digested samples were analyzed within one week. Ardea Purpurea egg samples were collected in the Flix reservoir (NE Spain). Eggs belonging to several clutches were collected, under license, in a small breeding subcolony. Fresh eggs were frozen until analyzed in the laboratory. Egg content was separated from the egg shell and freeze-dried. In a 40 mL glass vial, 200 mg of the freeze-dried egg content was placed. Subsequently, 2 mL of aqueous KOH solution (25%, w/v) were added. After 1 min of vortex shaking, the mixture was heated in a water bath at 50 ◦ C for 60 min.
6.851 −0.022 0.117 −1.760 −0.012 0.850 C, M, CM, C2 , M2 −0.136 −0.217 0.022 −0.070 5.4exp−003 0.869 CM, M2 0.055 −0.134 0.015 −0.078 3.2exp−003 0.870 CM, C2 , M2
The matrix digest was vortexed and stored at 4 ◦ C before analysis. All the digested samples were analyzed within one week. 2.3.2. SPME sampling MeHgCl and EtHgCl standards were used for method development and optimization. A 50 L volume of both standards (100 g L−1 ) in acetone were placed in a 6 mL glass vial with 3 mL of citric–citrate buffer solution (0.1 M, pH 4.5) containing a magnetic stirring bar. Then, 50 L of 100 g L−1 iBu2 Hg (internal standard) in acetone solution was added and the vial was closed. Subsequently, 50 L of 1% aqueous NaBPr4 solution was injected through the septum. After 5 min of reaction time, at 30 ◦ C and 1200 rpm, the fiber was drawn into the needle of the holder, and the needle was used to pierce the septum of the vial. The fiber was then lowered into the headspace by depressing the plunger. After 12 min of sampling time at 30 ◦ C and 1200 rpm, the fiber was retracted into the needle and immediately injected into the GC-Py-AFS system. 2.3.3. Statistics and experimental design A one-way analysis of variance was performed on the experimental data obtained. All statistical analyses were conducted with SPSS, version 15.0 for Windows (SPSS Inc., Chicago, IL, USA). Statistical significance was defined as p ≤ 0.05. An experimental design was performed with MeHg and EtHg standards in order to optimize important detection parameters such as carrier and make-up gas flow rates. Therefore, an experimental design was built by using the user-defined application of the program Design-Expert 7.1.6 (Stat-Ease Inc., Minneapolis, MN, USA). Response was statistically tested with a polynomial regression model, which was also used to generate surface plots. To overcome differing responses of individual analytes, a multiple response optimization approach was performed. Desirability, D is an objective function that ranges from zero for a completely undesirable response to one for a fully desired response [27]. The numerical optimization finds a point that maximizes the desirability function; then, the function D was used to simultaneously optimize all the responses for MeHg and EtHg as well. 3. Results and discussion 3.1. Detection parameters optimization
C: carrier gas flow rate; M: make-up gas flow rate.
1.625 0.061 0.094 −0.484 −0.011 0.841 C, M, CM, C2 , M2 −0.221 −0.076 0.015 −6.6exp−003 9.0exp−004 0.593 M, CM ˇ1 ˇ2 ˇ3 ˇ4 ˇ5 R2 Significant terms in the model (p < 0.05)
201.3 −21.55 7.389 −60.84 −0.173 0.949 C, M CM, C2
−0.522 −0.126 0.026 0.019 1.4exp−003 0.577 M, CM
377.0 −56.66 12.70 −122.4 0.306 0.974 C, M, CM, C2 , M2
Height/width at half height ratio Asymmetry ratio Area Height/width at half height ratio Asymmetry ratio Tailing factor Area
MeHg Table 1 Model characteristics of analytes.
Tailing factor
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EtHg
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3.1.1. Response surface design The peak area and symmetry factors are strongly dependent on the make-up Ar gas flow rate, added coaxially after the GC column effluent, as well as on the carrier Ar gas flow rate employed to transport the analytes through the analytical column. Considering the MeHg and EtHg peak area, tailing factor, asymmetry ratio and height/width at half height ratio as response variables, the experimental design described in Section 2.3.3, was applied to obtain further information on the effect of factors, namely carrier and make-up gas flow rates on the response variables. Factor ranges were from 6 to 27 mL min−1 and 1 to 3 mL min−1 for make-up and carrier gas flow rates, respectively. Data were modeled using a multiple linear regression, including the first order interaction and the quadratic terms. The general equation for the polynomial regression was as follows: Rx = ˇ0 + ˇ1 C + ˇ2 M + ˇ3 CM + ˇ4 C 2 + ˇ5 M 2
(1)
where Rx is the response variable, namely peak area, tailing factor, asymmetry ratio and height/width at half height ratio obtained for the target analyte x, C and M were the carrier and make-up gas flow rates, respectively and ˇn the different coefficients obtained. The regression coefficient (R2 ) for all the response variables of each analyte, their corresponding ˇn values, and significance terms in the model are shown in Table 1.
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Fig. 1. Response surface plots for (a) EtHg area, (b) MeHg tailing factor, (c) EtHg asymmetry ratio, and (d) MeHg height/width at half height ratio.
Fig. 2. Contour plot for the EtHg desirability function.
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Table 2 Comparison between theoretical data provided by the desirability function and experimental results under the optimized conditions. Analyte
Theoretical area
Experimental area
Theoretical–experimental comparison (%)
Theoretical height/width at half height ratio
Experimental height/width at half height ratio
Theoreticalexperimental comparison (%)
MeHg EtHg
175.05 362.60
178.99 379.33
2.3 4.6
1.51 3.43
1.26 3.76
16.6 9.6
Fig. 3. Effect of the pyrolyser temperature on the peak area and symmetry factors for MeHg and EtHg.
Fig. 1a shows the surface response and contour plots for EtHg area according to the carrier and/or make-up gas flow rates. A minimum is observed at lower carrier and higher make-up, whereas the highest peak area is reached in the zone of mean carrier (2 mL min−1 ) and lowest make-up (6 mL min−1 ). All the coefficient terms were significant (p < 0.05) in the model, indicating that the EtHg area behavior is clearly influenced by both the gas flow rates. Similar behavior is exhibited for MeHg (figure not shown). Fig. 1b shows the surface response for MeHg tailing factor. As can be seen, the make-up gas flow rate exerts more influence on the tail factor than the carrier gas flow rate. In this sense, as the make-up gas flow rate increases, the response decreases, yielding the best results using values of flow rate close to 27 mL min−1 . A similar response plot was obtained for MeHg asymmetry ratio. On the other hand, the tailing factor and asymmetry ratio (Fig. 1c) for EtHg are described by two maxima and two minima in the response surface. One maximum is located in the zone of maximum value for the two gases, while the other one is at the minimum for the two gases. Moreover, there is one minimum at the mean make-up and the lowest carrier, and another one at the mean make-up, but at the highest carrier gas flow rate. Fig. 1d shows the response plot for MeHg height/width at half height ratio. Following the peak area pattern for both, MeHg and EtHg, Fig. 1d shows a minimum in the lowest carrier and the highest make-up gas flow rates values. Nevertheless, the best results are obtained in the zone of maximum carrier and when the make-up gas flow rate reaches about 13 mL min−1 . In summary, all the coefficient terms are significant, indicating that both, carrier and make-up gas flow rates, have a high influence in the MeHg height/width at half height ratio behavior. Finally, the EtHg height/width at half height ratio surface response (figure not shown) follows the same trend as MeHg, which can be explained by the significance of carrier and make-up gas flow rates in the model. However for EtHg, the best results were obtained for medium values of carrier gas flow rate.
3.1.2. Multi-response optimization using desirability function To overcome the problem of conflicting responses of individual analyte, a multi-response optimization was used. In multi-response optimization, a desired weight is given to each response. In the present study, when building this function, higher desirable values were given to both MeHg and EtHg peak area and height/width at half height ratio. Then, two D functions (one for each analyte) were numerically maximized. Fig. 2 shows the contour plot for result of overall desirability function for EtHg when the carrier and make-up gas flow rates were modified. The overall desirability value is lowest in the region of high to medium make-up gas and low carrier gas. The maximum value, e.g. 0.848, is reached in the zone of the lowest make-up and the mean carrier gas flow rates. It is important to note that the goal of optimization is to find the best set of conditions in which all responses are maximized not to get a desirability value of 1. The overall desirability function for MeHg (figure not shown) exhibited a similar trend. According to these results, the optimum carrier and make-up gas flow rates were fixed at 2 and 6 mL min−1 , respectively. Theoretical area and height/width at half height ratio values provided by the desirability function are shown in Table 2. As can be seen, theoretical results match very well with experimental results. 3.2. Pyrolyser temperature optimization Prior to detection by AFS, the different mercury species, which elute from the analytical column must be converted to Hg0 by thermal treatment in a pyrolytic reactor. Since the temperature of the pyrolytic reactor influences the peak area [28], different temperatures (e.g. 700, 750 and 800 ◦ C) have been tested, and their effect on the peak symmetry and area were evaluated under the detector optimized conditions. There were statistically significant differences among 700 ◦ C and the other two temperatures, 750 and 800 ◦ C for MeHg area and height/width at half height ratio (Fig. 3). Following manufacturer recommendations, no higher temperatures than 800 ◦ C were evaluated. No significant differences
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and 11% (EtHg) for the repeatability study and 10% (MeHg) and 16% (EtHg) for the reproducibility study, thus showing the robustness of the analytical procedure. Quantification and recovery calculation were performed based on the internal standard procedure, for which iBu2 Hg was used as the internal standard. The external calibration linearity ranged from 0.007 to 1 ng as introduced mass in the detector (R2 > 0.99), which is equivalent to 0.01–3 g g−1 as Hg in the samples for MeHg and EtHg. Procedural blanks of below 0.01 g g−1 as Hg were obtained for every batch of samples. The limit of detection (LOD) of the method, defined as the mean background noise in a procedural blank triplicate plus three times the standard deviation of the background, was 0.04 ng g−1 , ww, for both MeHg and EtHg; the limit of quantitation (LOQ), defined as the mean background noise in a blank triplicate plus ten times the standard deviation of the background, was 0.13 ng g−1 , ww, for both compounds. Such detection limits make it possible to simultaneously determine MeHg and EtHg levels in biota samples without preconcentration using this method.
3.4. Application to real samples The efficiency of the developed method was evaluated by analyzing different biota matrixes, namely fish and waterfowl eggs, collected in a highly polluted area close to a chlor-alkali plant. Fig. 4a–c shows typical chromatograms of MeHg and EtHg standards, a waterfowl egg sample and a fish sample, respectively. In these samples, MeHg but not EtHg were identified.
4. Conclusions
Fig. 4. GC-Py-AFS chromatograms obtained for (a) MeHg and EtHg standards, (b) egg sample, and (c) fish sample. (1) Hg0 , (2) MeHgPr, (3) EtHgPr, (4) HgPr2 , (5) PriBuHg, and (6) iBu2 Hg. MeHg and EtHg standards and fish sample chromatograms were obtained with Chrom-Card software, whereas egg sample chromatogram was obtained with Atlas software.
were observed for MeHg asymmetry ratio and tailing factor. In the case of EtHg, statistically significant differences were not found for either the peak area or any of the peak symmetry factors studied. For both, MeHg and EtHg, the best repeatability results were achieved at 750 ◦ C, which was the final selected temperature. 3.3. Method validation, linearity and figures of merit The MeHg concentration in the CRM DORM-2 was determined and compared to the certified value. Since DORM-2 did not contain measurable EtHg levels, recoveries of this analyte were evaluated spiking the CRM DORM-2 with a known amount of EtHgCl. The MeHg concentration found in the DORM-2 was 4.15 ± 0.19 g g−1 (n = 5), which was in good agreement to the certified value (4.47 ± 0.31). The EtHg recovery from the spiked DORM-2 was also high (over 80%) indicating that MeHg and EtHg in samples could be simultaneously analyzed using this aqueous phase propylation, subsequent headspace SPME sampling and finally, GCPy-AFS determination. In support of this, the repeatability was tested by analyzing six replicates of MeHgCl (5.396 ng) and EtHgCl (3.269 ng) standards in the same day, whereas the reproducibility was evaluated by analyzing such standards on six different days. The relative standard deviations (RSDs) were found to be 9% (MeHg)
A method for the simultaneous determination of MeHg and EtHg in biota samples has been developed, which is based on aqueous propylation derivatization, HS-SPME preconcentration, GC separation and Py-AFS detection. Carrier and make-up gas flow rates were optimized using response surface methodology with peak symmetry and area of both analytes as response variables. The use of the desirability function allowed for the simultaneous optimization of all response variables in spite of their conflicting responses to yield global optimal conditions. Theoretical data provided by this function were validated by running these conditions with both standards; the results obtained were in accordance with the theoretical prediction. Indeed, the pyrolyser temperature, another factor affecting the analyte peak symmetry and area, has been optimized. The accuracy of the methodology presented has been validated by characterizing a reference material and it proved to be fast, simple and sensitive. Moreover, the aqueous propylationHS-SPME-GC-Py-AFS method has been successfully applied to the analysis of real samples, providing a powerful tool to assess the relationship between the specific mercury species and its wildlife toxicity.
Acknowledgements Financial support was obtained from the Spanish Ministry of Environment, the Catalan Agency of Water (ACA, Generalitat de Catalunya) and the Fundación BBVA (BIOCON06/113; Project EMECO, IV Convocatoria de Ayudas a la Investigación en Ecología y Biología de la Conservación). L. Carrasco would like to express his gratitude to Consejo Superior de Investigaciones Científicas for an I3P fellowship. D. Calderón-Preciado is thanked for helping in the statistical analysis of data.
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