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A novel application of an isotope binary mixing model for determination of precise mercury isotopic composition in samples with low mercury concentration Shuyuan Huang, Qingyong Song, Yuanbiao Zhang, Dongxing Yuan, Lumin Sun, Yaojin Chen, Ronggen Jiang, and Hui Lin Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b05940 • Publication Date (Web): 25 Apr 2019 Downloaded from http://pubs.acs.org on April 25, 2019

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Analytical Chemistry

A novel application of an isotope binary mixing model for determination of precise mercury isotopic composition in samples with low mercury concentration Shuyuan Huanga, Qingyong Songb, Yuanbiao Zhanga,*, Dongxing Yuanb, Lumin Sunc, Yaojin Chenb, Ronggen Jianga, Hui Lina a

Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, 361005,

China b State

Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen,

361102, China c

Tan KahKee College, Xiamen University, Zhangzhou, 363105, China

Abstract: An isotope binary mixing model was applied for high precision measurement of mercury isotope ratios in samples with low mercury concentrations by multicollector inductively coupled plasma mass spectrometry (MC-ICP-MS). Standard addition was used to evaluate the precision and accuracy of the isotope composition calculations resulting from the isotope binary mixing model. A high, steady

202Hg

signal of approximately 2.13 V was achieved, with the mercury concentration reaching 3 ng/mL. The isotopic composition of three standards (NIST SRM 1646a; NIST SRM 1575a; BCR 482) and natural samples were precisely determined. The standards and natural samples were diluted to low mercury concentrations (low to 0.90 ng/mL) and mixed with standard solutions (NIST SRM 3133) with high mercury concentrations (50 ng/mL), the isotopic compositions of low mercury concentration samples were calculated using an isotope binary mixing model after the isotopic compositions of the mixing solutions were measured. The results showed that the uncertainty of the

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calculated mercury isotopic compositions was in an acceptable range and the calculation isotope data were in good agreement with direct measurements. Our method allows the precise determination of mercury isotope composition in mercury solutions of concentrations (0.90 ng/mL) below the detection limit of the current system (3.00 ng/mL).

1. Introduction High precision determination of mercury isotope ratios by multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) was developed,1 and it offers a highly efficient, highly precise method of determining the mercury isotope ratio determination, outperforming such other techniques as neutron activation analysis (NAA),2,3 singlecollector ICP-MS,4 and ICP-time-of-flight-MS (ICP-TOF-MS).5 In 2006, the accuracy and precision of the MC-ICP-MS isotope ratio methods were improved with the inclusion of an on-line mercury reduction technique.6 Although other sample introduction systems have been developed for high-precision mercury isotope ratio determination,5,7-9 the on-line mercury reduction technique has seen the widest use in environmental samples.10-12 In 2007, all laboratories adopted a common means of data correction, standardization, and nomenclature in order to easily evaluate and compare data from different laboratories.13 Mercury isotope signatures in geochemistry and environmental studies are now recognized as powerful means of better understanding mercury geochemical processes and tracing mercury sources and sinks in the environment. Mercury has seven natural, stable isotopes (196Hg, 198Hg, 199Hg, 200Hg, 201Hg, 202Hg, and 204Hg) and both mass dependent fractionation


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(MDF) and mass independent fractionation (MIF) of mercury isotopes are common during various physical, chemical, and biological processes.13,14 The isotopic compositions of natural materials show large variations.14 For example, continental sediment samples show negative δ202Hg and Δ199Hg values,11,

15

oceanic sediments show negative δ202Hg and

positive Δ199Hg values,16, 17 and snow samples show positive δ202Hg and negative Δ199Hg values.18, 19 The use of binary mixing models was first proposed by Faure20 and successfully used for tracing lead sources in a river in Northern Germany.21 Since then, binary mixing models have been developed to trace and quantify mercury sources in various environmental systems (e.g. soils, lichens, and seawater) by numerous studies.15, 16, 2225 For

example, mercury isotopic anomalies in lichens were due to mixing between the

atmospheric reservoir and direct anthropogenic sources;15 the fractions of mercury sources from desulfurization seawater and local background seawater was evaluated;23 the spatial distribution of mercury isotope compositions in mineral soils across North American forests assuming atmospheric Hg (II), atmospheric Hg (0) and geogenic mercury as major sources.25 With the development and coupling of sample introduction systems to MC-ICPMS analysis, the volume and mercury concentration required for analysis by MC-ICPMS was reduced to 5–10 mL and 0.5–3.0 ng/mL, respectively.26-29 However, environmental mercury concentrations are on the order of 1–100 pg/m3 and 0.3 ng/L in reactive gaseous mercury (RGM)30 and marine seawater31, respectively, and required large sample volumes for successful isotopic measurement. In order to reduce the large



sample volume requirements, it was necessary to either directly improve the δ202Hg instrument signal or indirectly measure the mercury isotopic composition in these low mercury samples. Recently, Geng et al.32 achieved direct high precision isotopic composition determination in low mercury samples using a modified cone arrangement (X skimmer cone + jet cone) with Neptune Plus MC-ICP-MS. In the current study, a steady and high δ202Hg signal of approximately 2.13 V was achieved when mercury sample concentrations reached 3 ng/mL. Under these conditions, an indirect method for isotope measurement of low mercury samples was developed. The standard (NIST SRM 3133) has two functions here: one is as bracket standards to ensure precision and accuracy as previously reported; the other one is to proportionately dilute the isotope ratios of the mixing solution with regard to its nearly zero isotopic composition. The results were evaluated by standard addition method and unaffected by matrix interference and initial mercury. We then demonstrated that isotopic compositions of low mercury samples indirectly calculated by binary mixing model were consistent with directly measurements using MC-ICP-MS.

2. Experimental methods 2.1 Instrumental settings and mercury isotope determination Mercury isotope measurements were conducted on a Nu Plasma MC-ICP-MS housed at the State Key Laboratory of Marine Environmental Science at Xiamen University. Following previously published methods,27 the sample introduction system included a modified cold-vapor generator (CVG) and an Aridus III desolvating


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nebulizer system (CETAC Technologies, USA) for mercury and thallium introduction, respectively. Briefly, stannous chloride (SnCl2) was continually pumped along with the Hg (II) solutions and allowed to mix in a tee junction prior to being introduced into a gas–liquid separator (GLS), producing gaseous elemental Hg (0). The Hg (0) was then removed with a counter-flow “mix gas” (Ar) from the bottom of the GLS and moisture was removed with a 0.45-µm PTFE filter. The Hg (0) was then mixed with a dry thallium aerosol generated by the Aridus III nebulizer and introduced into the plasma. Eight Faraday cups (L6, L5, L4, L3, L2, L1, Ax and H1) of the MC-ICP-MS were used to monitor

198Hg, 199Hg, 200Hg, 201Hg, 202Hg, 203Tl, 204Hg

and 205Tl, respectively. The

operation parameters were tuned for a maximum ion intensity of Hg and Tl in standard solutions (Table 1). Data were acquired using 1 block of 100 cycles, with 6.0 seconds per cycle. Between samples, the CVG was rinsed with 3% (v/v) HNO3 solution for 7 min until the signal intensity returned to the background level, typically below 20 mV. Standards of mercury (NIST 3133, 3 ppb) and thallium (NIST 997, 20 ppb) were chosen as the bracketing and internal standard samples, respectively, to correct for the instrumental mass bias.13,33 The isotopic composition of mercury was reported as δ (‰) and Δ (‰) notation, which represents MDF and MIF of the isotopes, respectively:13 δxxxHg(‰) = [(xxxHg/198Hg)sample/(xxxHg/198Hg)standard − 1]×1000

(1)

ΔxxxHg = δxxxHg − (δ202Hg×β)

(2)

where xxx values are 199, 200, 201 and 202 amu, the fractionation factor β is 0.2520, 0.5024 and 0.7520 for 199Hg, 200Hg and 201Hg, respectively.



2.2 Reagents Reagents and solutions were prepared in ultrapure water (18.2 MΩ·cm) from a water purification system (Millipore, USA). All acid used for vessel cleaning and solution preparation in this study were of GR grade (Merck, Germany). All standard solutions of mercury (NIST SRM 3133, NIST RM 8610) and thallium (NIST SRM 997) were purchased from the National Institute of Standards and Technology (NIST, U.S. Department of Commerce). SnCl2 (30%, w/v) was prepared in 10% HCl. The KMnO4 (Alfa Aesar, UK) solutions, 2.00 mmol/L in concentration, were prepared in 0.50 mol/L H2SO4.27

2.3 Digestion of the standard and natural samples The standard (NIST SRM 1646a, Estuary Sediment; NIST SRM 1575a, Pine Needles; BCR 482, Lichen) and natural samples were digested at 95 °C for 3 h in 5 mL aqua regia (HNO3:HCl = 1:3, v/v), following previously reported methods.34-37 Digestion solutions were diluted to 25 mL with ultrapure water and amended with BrCl (1%) prior to storage in brown borosilicate glass sample bottles at 4 °C. Low mercury samples were prepared using the standard and natural samples, respectively. For each batch of digested samples, reagent blanks and duplicate samples were prepared. The reagent blanks for mercury were below 0.03 ng/mL and the relative standard deviation of sample duplicates was within 8.0% of the measure values. Three sediment samples were collected from mangrove ecosystems in Xiamen


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(SED-1) and Guangxi (SED-2 and SED-3). Four surface seawater samples were collected for isotopic analysis. Three were collected from Dandou Sea, Guangxi (SW1, SW-2 and SW-3) and the fourth was collected from Eastern India Ocean in 2017 (SW-4). The samples were selected for their sufficient sample mass (volume). Sampling and sample preparation were performed following the US EPA method.37 A minimum volume of 20 L seawater samples were collected and stabilized in 0.5% (v/v) BrCl prior to preconcentration. Sample preconcentration procedures followed those developed by Lin et al.27 Briefly, SnCl2 was added to the seawater samples to reduce mercury, followed by immediate purging with mercury-free argon onto gold traps after excess NH2OH·HCl was added to the sample. The mercury in the gold traps was then thermally desorbed by mercury-free argon and trapped in a KMnO4 solution. The preconcentrated mercury solutions were stored in brown borosilicate glass sample bottles at 4 °C until analysis.

2.4 Measurements of mixing solutions The standard addition method is commonly used to quantify the accuracy and precision of isotope data for samples having complex matrices, which are often different from the matrix of the standard materials.38 In the current study, standard addition was also used to validate the isotope data of the mixing solutions. The standard and natural samples were thus doped with increasing masses of a standard solution (NIST SRM 3133) of known isotope ratio. In order to obtain precise results, all solutions were prepared with identical



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mercury concentrations (3.0 ng/mL) and similar acid matrices prior to isotopic determination. At least 10 mL of solution was necessary, similar to previous studies.27,39 Ten samples (including three standard samples and seven natural samples) were processed to evaluate the precise measurement of low mercury samples. For the mixing solutions, standard mercury solutions (NIST SRM 3133) of 50 ng/mL were prepared. As shown in Figure 1, the mercury concentration in the standard solution was held constant, while concentrations of low mercury samples ranged from 0.90 to 1.80 ng/mL in known proportions.

2.5 Isotope binary mixing model An isotope binary mixing model was used to discriminate mercury sources in different solutions. The mixing solutions were interpreted as the result of a binary mixing of two sources, namely the standard solution and the low mercury samples. An isotope binary mixing model was conducted to determine the mercury isotopic compositions of low mercury samples using the following equations: δxxxHgSam = (δxxxHgMix − δxxxHgStd×XStd)/XSam

(3)

ΔxxxHgSam = (ΔxxxHgMix − ΔxxxHgStd×XStd)/XSam

(4)

XStd + XSam = 1

(5)

where xxx values are 199, 200, 201 and 202 amu, Sam, Std and Mix denote the low mercury sample, standard solution, and mixing solution, respectively, and XStd and XSam are the mercury mass fractions of the standard solution and low mercury sample in the mixing solution, respectively. Because NIST SRM 3133 was adopted as the mercury


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isotope reference standard, the reported isotopic compositions of NIST SRM 3133 were displayed with near-zero values of δ202Hg, Δ199Hg, Δ200Hg and Δ201Hg. That is, NIST SRM 3133 could be considered the isotope blank sample, as far as mercury isotope data were concerned. Thus, equations (3) and (4) could be simplified to: δxxxHgSam = δxxxHgMix/XSam

(6)

ΔxxxHgSam = ΔxxxHgMix/XSam

(7)

2.6 Reporting uncertainties For the standard solutions (NIST SRM 3133 and NIST RM 8610), uncertainties were reported as twice the standard deviation (2SD) of repeated measurements of the same solution. For the standard (NIST 1646a, NIST SRM 1575a, BCR 482) and natural samples, uncertainties were reported as the maximum 2SD values between the duplicate sample digests and NIST RM 8610.

3. Results and discussion 3.1 Mercury isotopic determination of standard solutions and standard samples The NIST SRM 3133 and NIST RM 8610 standards were repeatedly determined to evaluate the uncertainties and accuracy of the instrument. The δ202Hg and Δ199Hg were 0.00 ± 0.06 (2SD, n = 52) and 0.00±0.01 (2SD, n = 52) for NIST SRM 3133, respectively and were −0.55 ± 0.09 (2SD, n = 8) and 0.06 ± 0.05 (2SD, n = 8) for NIST RM 8610, respectively (Table 2). These results were in agreement with previous studies.23,34,40-42 Three standard samples (NIST SRM 1646a, NIST SRM 1575a and



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BCR 482) were digested for mercury isotope analysis. The standard samples were analyzed repeatedly over two separate measuring sessions on different days, with constant mercury concentration in the solutions of 3.0 ng/mL. As shown in Table 2, the mercury isotopic compositions of the standard samples were comparable to previous results.24,25,43-45

3.2 Theoretical uncertainty of calibrating data from a binary mixing model The uncertainties for calibrating data from the binary mixing model relied on both of the variables and uncertainties associated with equations (6) and (7). The uncertainties associated with low mercury sample data calibration were thus estimated by error propagation, using the following equation (for details see Text S1): 𝜎𝑆𝑎𝑚 =

1 𝑋2𝑆𝑎𝑚

𝑑2𝑀𝑖𝑥

× 𝜎28610 + 𝑋4 × 𝜎2𝑋 𝑆𝑎𝑚

(8)

where σ8610 and σX represent the 2SD values of NIST RM 8610 and mass fractions, respectively, and dMix represents both the MDF and MIF values (including δ202Hg, Δ199Hg, Δ200Hg and Δ201Hg) of the mixing solutions. We suggest that the uncertainties of the mixing solutions were substituted by that of NIST RM 8610 because the NIST RM 8610 uncertainty was fixed and it was actually impossible to make duplicate measurements for the available natural sample quantity. The mercury isotopic compositions of the standard samples and natural samples were all measured at a mercury concentration of 3.0 ng/mL, with the XStd and XSam values calculated according to the equations in Section 2.5. The σX was subsequently reported using the 2SD value of the results of XSam. In our study, the σX was generally lower than 0.03 and regarded


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here as a constant (σX = 0.03) in Equation 8 for convenience of calculation. However, in the practical calculation, the σX was a variable calculated from the experimental results. The σ8610 was obtained by repeatedly measuring the in-house standard (NIST RM 8610) and these values are listed in Table 2. The variation of σSam was narrower for Δ199Hg and relied on dMix and XSam. Note that XSam was a known value as soon as the mixing solution was measured. Thus, for δ202Hg, Equation 8 could be expressed as: 𝑄(𝑑) = 𝜎2𝑆𝑎𝑚 =

(0.03)2 𝑋4𝑆𝑎𝑚

× 𝑑2𝑀𝑖𝑥 +

(0.09‰)2 𝑋2𝑆𝑎𝑚

(9)

where Q (d) correlated linearly with 𝑑2𝑀𝑖𝑥 once XSam was fixed. However, |𝑑𝑀𝑖𝑥| was not an infinite value in previous experiments. Blum et al.14 summarized data in each publication under strict quality control and found that the observed mercury isotopic compositions of more than 90% of a compilation of natural materials was within ±3.5‰ for both δ202Hg and Δ199Hg. We used this reported variability to set the maximum

|𝑑𝑀𝑖𝑥| to 3.5‰ in this study. Through the above analysis, the limits of σSam could be estimated from the XSam and the results are listed in Table 4. In order to increase confidence in the data quality, we adopted data selection criteria from a review article on mercury isotopes.14 Published results included in this review study had external standards with lower than 0.30‰ uncertainty (2SD) and the natural materials had XSam values higher than 0.60. For instruments more sensitive than ours, an XSam lower than 0.40 was included. Atmospheric samples were recommended to have a σd = 2.0 since most of the atmospheric samples (including precipitation and snow samples) were displayed within the range of ±2.00‰ for both MDF and MIF.43,46,47 Because both δ202Hg and Δ199Hg for six out of the seven samples in the



current study were lower than 2.0‰ (Table 3), XSam≥50% was utilized.

3.3 Evaluation by the standard addition method The standard addition method has previously been used to identify interference of the quartz fiber membrane matrix on isotope analysis.48 Although the effect of different matrices on isotope analysis have been conducted,27,47 most studies, including ours, have preferred to use the same matrix solution to dilute standards and samples in order to avoid matrix interference.29,32 In this study, the standard addition method was employed to evaluate both the influence of initial mercury on the isotopic compositions of the mixing solutions and the isotope data of the binary mixing model. Previous results have shown that initial mercury was elemental mercury generated through mixing between high concentration and low concentration mercury solutions.49,50 Therefore, a standard solution (NIST SRM 3133) of high concentration was mixed with an in-house standard (NIST RM 8610) of low concentration in incremental proportions. A total of eight samples were prepared in duplicate by spiking the in-house standards with NIST SRM 3133 at four different mixture proportions. The results are shown in Figure 2. A strong linear correlation was found between the isotope data for NIST SRM 3133 and the mixing solutions, the r2 values were 0.97, 0.80, 0.82, and 0.31 for δ202Hg, Δ199Hg, Δ201Hg, and Δ200Hg, respectively. The y intercepts of the linear correlations represent the mercury isotope values of the in-house standard and were −0.57‰, 0.08‰, 0.07‰, and −0.01‰ for δ202Hg, Δ199Hg, Δ201Hg, and Δ200Hg, respectively. These data were correlative with mercury isotope data from the in-house standard (squares in


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Figure 2), as well as with that of the in-house standard listed in Table 2, confirming our determination without interference from initial mercury. It is possible that the initial mercury was too little to shift the isotopic composition of the mixing solutions, though it may also be a result of the initial mercury re-dissolving into the mixing solutions. Due to the extremely low concentration of mercury in natural samples that are challenging to collect, such as seawater and aerosol samples, it was not possible to make duplicate measurements of mercury isotopic compositions using pre-concentration methods. Therefore, the binary mixing model was validated using the standard addition method, and the calculated isotope ratios were determined by extrapolating the linear relationships to the y intercept for the dashed lines (Figure 2a). The intercepts of the solid line and dash lines were within ±0.06‰ (1SD) of each other except for one dash line. The dash line passed through the point which represented for XStd=90%. The similar drifts were illustrated in Figure 2b, c and d and in agreement with the theoretically estimated results that as the mercury mass fractions of the sample decreased in the mixing solutions, the uncertainties of the isotope data obtained from the binary mixing model increased. These results further suggest that more than 50% of the mercury mass fraction in the mixing solutions determined by this method should come from the mercury in the original sample.

3.4 Statistical comparison of the direct measurements and binary mixing model The direct measurements of mercury isotopic compositions for natural samples are listed in Table 3. The δ202Hg and Δ199Hg of the natural samples ranged from −2.37‰ to −0.30‰ and −0.25‰ to 0.14‰, respectively. No MIF of even mass isotopes was



observed. Significantly different δ202Hg and Δ199Hg values were observed for the different types of samples. Sediment samples collected from Guangxi exhibited negative Δ199Hg, while samples from Xiamen exhibited positive Δ199Hg. Seawater samples exhibited slightly negative δ202Hg and near-zero Δ199Hg and the sediment samples did not. As discussed above, the mixing solutions were prepared by combining NIST SRM 3133 and low mercury sample digests. The details, as well as mercury isotopic compositions of mixing solutions, are shown in Figure 3 and Table S1. The standard sample NIST SRM 482 were mixed with 60% mass fraction of NIST SRM 3133, whereas the natural sample SED-3 were mixed with 70% mass fraction of NIST SRM 3133. According to the results, mercury isotopic compositions of standard and natural samples were calculated by equations (6) and (7). The uncertainties of all the calculation results were determined to be within 0.30‰, confirming the isotope data were reliable. The recovery of the mixing solutions ranged from 94.9% to 108%, confirming that the influence of the potential errors from Hg concentration, such as the differing extent of reduction and volatilization of Hg from samples and Hg from the standard—which were not equilibrated in the mixture—on the binary mixing model could be disregarded. A comparison was conducted between the direct and indirect measurements of isotope data in all of the samples. As shown in Figure 3, the indirect calculation results of the binary mixing model are here compared to the direct determination results of MC-ICP-MS. Briefly, only SED-2 was calculated with a slightly higher δ202Hg (−1.54‰, n=1) than direct


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determination results (−1.69‰, n=1); the other samples were calculated with moderate δ202Hg values within the direct determination results. The standard deviation of δ202Hg between the calculation and determination results ranged from 0.00‰ to 0.10‰. For Δ199Hg, the standard deviations between the two results were from 0.00‰ to 0.11‰. The NIST SRM 1646 was calculated with lower Δ199Hg (−0.04‰ and −0.06‰, n=1) than the direct determination results (0.09‰±0.08‰, n=3, 2SD), but the calculated Δ199Hg values were also within ±0.10‰, indicating no MIF. The SW-1calA was calculated with much higher Δ199Hg (0.17‰, n=1) than the direct determination results (0.05‰, n=1). Instead, the duplicate measurements (SW-1calB: Δ199Hg = 0.08‰, n=1) were comparable to the direct determination results. The SW-1mixA and SW-1mixB were duplicate samples, and Δ199Hg values were all within ±0.10‰, indicating no MIF. However, the Δ199Hg value of SW-1mixA was twice that of SW-1mixB. That is, the higher Δ199Hg of SW-1calA was the result of error amplification. The lower Δ199Hg (−0.35‰, n=1) calculated in SED-3 compared to the direct determination results (−0.25‰, n=1) was due to the lower mass fraction of SED-3 (Xsam = 0.29) in the mixing solution. In this regard, our method enabled the measurement of low mercury samples (0.90–1.8 ng/mL). As a result, this method demonstrated that valid isotope determination can be determined on samples with a much lower (0.90 ng/mL) minimum mercury sample concentration requirement relative to that required for samples measured directly by MC-ICP-MS (3.0 ng/mL).

Considering the optimum detection limit of MC-ICP-MS was at 0.10 ng/mL in the



available publications,32 the minimum mercury concentration would be 0.03 ng/mL in the samples prior to determination according to our method. Future work should be conducted to increase the accuracy of determination and reduce the uncertainties of the calculation results from the binary mixing model. This method is extremely useful for the measurement of precious samples with both low sample volume and low mercury concentration.

4. Conclusions Through optimization of instrument conditions, including those of a modified CVG, an Aridus III desolvating nebulizer system and a Nu Plasma MC-ICP-MS, high precision mercury isotope determinations were achieved for 10 mL solutions with 3.0 ng/mL mercury. Mercury isotopic compositions of low mercury samples (0.90 ng/mL) were calculated using an isotope binary mixing model that was validated by standard addition. The results with acceptable uncertainties were in good agreement with direct measurements. The NIST SRM 3133 was used as standard blank sample with regard to isotope data. Our method relied on the accuracy of the instrument, but was independent of the detection limit of MC-ICP-MS. This method enables the precise determination of lower mercury solutions (0.03 ng/mL) using an instrument with the best detection limit (0.10 ng/mL) and can be widely used with under different conditions, as long as high instrument accuracy is achieved.

Acknowledgements


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This research was financed by the Scientific Research Foundation of Third Institute of Oceanography, Ministry of Natural Resource (No. 2016045; No. 2016014). We also thank State Key Laboratory of Marine Environmental Science, Xiamen University, for isotopic analysis assistance. We would like to thank LetPub (www.letpub.com) for providing linguistic assistance during the preparation of this manuscript.

Supporting information. One SI file including Test S1 and Table S1 was supplied. Test S1 was the details for Equation 8 of calculating the combined uncertainty. Table S1 was the detail results of mixing solutions and binary mixing model.



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Figure legends Figure 1 Schematic of the experimental setup. Figure 2 Standard addition method for evaluation of the isotope data using a binary mixing model. Measurements of mercury in mixing solutions define linear arrays for isotope ratios δ202Hg (a), Δ199Hg (b), Δ201Hg (c), and Δ200Hg (d) as a function of the mass fraction of NIST SRM 3133 (XStd). The solid lines are the linear fits obtained by the least squares method, excluding the square points (in-house standard NIST RM 8610). The regression equations are for the solid lines. Each of four dash lines pass through two points: circle point (NIST SRM 3133) and one triangle point (mixing solution with different mass fractions of NIST SRM 3133). Figure 3 A comparison of the direct and indirect measurements of mercury isotopic compositions in all samples.



Page 26 of 33

Table 1 Operating parameters employed during mercury isotope analysis MC-ICP-MS Cool gas (L/min)

13.8

Auxiliary gas (L/min)

0.78

Mix gas (L/min)

0.20

Mix gas 2 (L/min)

1.15

RF power (W)

1300

Acquisition time (s)

600

Cycles/blocks

100/1

Aridus III Spray chamber temperature (°C)

110

Membrane temperature (°C)

140

Nebulizer gas flow (L/min)

1.13

Tl solution uptake rate (mL/min)

0.15

GLS system Solution uptake rate (mL/min)

0.80


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Table 2 Mercury isotopic compositions of standard reference materials Standard

n

NIST SRM 3133 NIST RM 8610

δ202Hg (‰)

2SD

Δ199Hg (‰)

2SD

Δ200Hg (‰)

2SD

Δ201Hg (‰)

2SD

References

52

0.00

0.06

0.00

0.01

0.00

0.01

0.00

0.02

this study

8

−0.55

0.09

0.06

0.05

0.02

0.02

0.03

0.06

this study

3 NIST SRM 1646a

NIST SRM 1575a

−1.13

0.13

0.09

0.08

0.02

0.02

0.03

0.07

this study

2

−0.92

0.09

0.09

0.01

0.02

0.01

0.02

0.02

Zheng et al., 2015

3

−0.98

0.08

0.08

0.04

0.03

0.03

0.03

0.05

Zheng et al., 2016

−1.17

0.25

−0.26

0.06

0.06

0.03

−0.30

0.06

this study

−1.13

0.08

−0.34

0.04

0.02

0.03

−0.42

0.05

Zheng et al., 2016

−1.61

0.16

−0.57

0.07

0.06

0.01

−0.59

0.08

this study

7

−1.67

0.16

−0.57

0.10

0.06

0.08

−0.58

0.09

Yu et al., 2016

11

−1.58

0.12

−0.64

0.06

-

-

−0.65

0.08

Liu et al., 2017

6

−1.62

0.12

−0.65

0.07

0.08

0.07

−0.65

0.06

Enrico et al., 2016

4

0.041

0.039

3 7

BCR 482

Hg (ng/mg)

0.46



Page 28 of 33

Table 3 Mercury isotopic compositions of natural samples Sample

n

Hg

δ202Hg (‰)

Δ199Hg (‰)

Δ200Hg (‰)

Δ201Hg (‰)

SED-1

2

0.39*

−2.37±0.04

0.14±0.01

0.04±0.00

0.09±0.01

SED-2

1

0.014

−1.69

−0.25

−0.02

−0.38

SED-3

1

0.011

−0.99

−0.25

0.01

−0.37

SW-1

2

2.27

−0.30±0.05

0.05±0.02

0.01±0.03

0.01±0.01

SW-2

1

8.91

−1.06

0.00

0.01

0.02

SW-3

1

11.21

−0.94

0.00

0.03

−0.01

SW-4

1

5.39

−1.23

−0.08

0.03

−0.16

* *

* * *

*

* ng/mg for sediment samples and ng/L for seawater samples.


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Table 4 The estimated uncertainties of calibrating data from binary mixing model XSam

Expression

Limit values of σSam (‰)

σd = 2.0(‰)

σd = 1.0(‰)

0.40

Q (d) = 0.0352d2 + 0.0506*10−6

0.69

0.44

0.29

0.50

Q (d) = 0.0144d + 0.0324*10

0.45

0.30

0.22

0.60

Q (d) = 0.0069d + 0.0225*10

0.33

0.22

0.17

0.70

Q (d) = 0.0037d + 0.0165*10

0.25

0.18

0.14

2 2

−6

2

−6 −6

σd = 2.0 and σd = 1.0 are the limit values of σSam when |𝑑𝑀𝑖𝑥| is 2.0‰ and 1.0‰, respectively.



Figure 1


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Figure 2



Figure 3


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