Air–Water Partitioning of 222Rn and its Dependence on

Article pubs.acs.org/est

Air−Water Partitioning of Temperature and Salinity

222

Rn and its Dependence on Water

Michael Schubert,†,* Albrecht Paschke,† Eric Lieberman,‡ and William C. Burnett‡ †

UFZHelmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig, Germany Department of Earth, Ocean and Atmospheric Sciences, Florida State University, Tallahassee, Florida 32306-4320, United States

‡

ABSTRACT: Radon is useful as a tracer of certain geophysical processes in marine and aquatic environments. Recent applications include detection of groundwater discharges into surface waters and assessment of air/sea gas piston velocities. Much of the research performed in the past decade has relied on continuous measurements made in the field using a radon stripping unit connected to a radon-in-air detection system. This approach assumes that chemical equilibrium is attained between the water and gas phases and that the resulting air activity can be multiplied by a partition coefficient to obtain the corresponding radon-in-water activity. We report here the results of a series of laboratory experiments that describes the dependence of the partition coefficient upon both water temperature and salinity. Our results show that the temperature dependence for freshwater closely matches results that were previously available. The salinity effect, however, has largely been ignored and our results show that this can result in an overestimation of radon concentrations, especially in cooler, more saline waters. Related overestimates in typical situations range between 10 (warmer less saline waters) and 20% (cooler, more saline waters).

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INTRODUCTION Radon activities in water samples can be detected in the laboratory either by means of liquid scintillation counting (e.g., ref 1) or by sparging of the water sample with helium and collecting the quantitatively extracted radon from the helium stream in a cold trap for transferring it into a Lucas cell for counting (e.g., ref 2). However, if radon-in-water detection is required immediately on site, detection can alternatively (and in many cases preferably) be performed by radon extraction from the water into a closed recirculating air loop with continuous measurement of the radon activity in that air loop by means of a portable radon-in-air monitor. Several practical approaches for the on-site radon extraction step have been described in the literature, all based on either stripping by air sparging,3 or membrane extraction,4,5 or the application of a spray chamber.6−8 No matter which of these approaches is applied, on-site radon-in-water detection relies upon a radon concentration equilibrium between water and recirculating air. For converting the detected radon equilibrium concentration in air (Cair) into the corresponding radon-inwater concentration (Cw) the water/air partition coefficient of radon (Kw/air) needs to be known. Kw/air depends on salinity as well as temperature with possible values in natural waters covering a range of one magnitude between about 0.5 (cold fresh water) and 0.05 (hot saline water9). While the temperature effect on Kw/air is generally applied, the salinity dependence of Kw/air has not been as comprehensively studied and reported in the literature and not accounted for at all in many cases. © 2012 American Chemical Society

The solubility of a gas (radon) in a solvent (water) is always decreased if the solvent is not pure, an effect which can be referred to as “salting-out”. The salinity dependence of Kw/air does theoretically apply for all natural waters. Still, in freshwater systems, i.e., in waters with negligibly low salinities (lakes, rivers, most groundwater bodies) the resulting impact on the radon solubility is insignificant. However, in salt-water environments, i.e., in brines, seawater, or some groundwaters, the salinity dependence of Kw/air may have a significant impact on the radon partitioning between water and air. This, in turn, would affect the quantification of radon results when based on an air−water equilibrium approach. A prominent example for the practical relevance of these considerations is the use of radon as a naturally occurring tracer for submarine groundwater discharge “SGD” (e.g., refs 6, 11, and 12). If the radon concentration of the coastal sea (high in salinity, low in radon) is mapped for localizing and quantifying groundwater discharge (low in salinity, high in radon) by means of a mobile radon-in-air monitor that relies on air−water equilibrium, then ignoring the salting-out effect might lead to overestimates of the radon activities. However, this potential source of error can easily be accounted for since both influential parameters, temperature and salinity (typically measured continuously by electrical conductivity), can easily be recorded during a field campaign. Thus, Kw/air can just as straightforReceived: Revised: Accepted: Published: 3905

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wardly and continuously be adapted to the actual field conditions if their influence is known. This work presents results of experimental investigation related to the “salting out” of radon from water that are based on prior but limited experimental data and on our own extended data sets that cover a wide range of salinities and temperatures. With a focus on practical implications, e.g., using radon as natural tracer of SGD, we introduce a theoretical framework and an easily applicable model equation that allows uncomplicated evaluation of the dependence of Kw/air on both temperature and salinity.

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RADON SOLUBILITY IN WATER The temperature dependence of radon solubility in water (Kw/air = f (T)) is well reported in the literature. Clever9 assembled a comprehensive set of experimental data including results originally reported by Kofler in 1913 (p 233, hereafter referred to as “the Kofler data set”). Weigel10 introduced an empirical equation for quantifying the temperature influence on radon partitioning between pure water and air (eq 1). The “Weigel equation” is based on a data set published by Meyer and Schweidler in 191626 who assembled all related data available at the time. The results of the Weigel equation are in good agreement with the Kofler data set.

Figure 1. (A) Dependence of Kw/air for radon as a function of both temperature [°C] and salinity based on a data set assembled by Kofler in 1913 (dots are Kofler data points); dashed lines were fitted by interpolation from the neighboring salinity curves representing 0 and 109; the plot valid for 362 was extrapolated from the data representative for less saline waters; (B) Salinity dependence of Kw/air at 18 °C based on the Kofler data set.

C K w/air = w = f (T ) = 0.105 + 0.405e−0.0502T[°C] Cair (1)

Although there is a wealth of information available on the temperature dependence of Kw/air, ly few data are reported regarding its salinity dependence. Wanninkhof13 published results for other noble gases (He, Ne, Ar, Kr) suggesting an empirical equation for quantification of the dependence of the respective Kw/air values on both temperature and salinity. However, information on radon (and Xe) is missing from that data set. A limited set of experimental data for the radon solubility in saline water (NaCl) was reported by Kofler in 1913 as part of the Kofler data set and republished by Clever9 after evaluation. Figure 1A displays Kw/air vs T plots that illustrate the related findings for salinities ranging from pure water to values close to seawater (∼32 ‰ NaCl; = parts per thousand) and all the way to saturated brine (362 ‰ NaCl). Due to the limited number of original data points in the Kofler data set some of the curves shown in Figure 1A (salinities 13, 32, 59, and 362 ‰) are based on only a single data point (valid for 18 °C). In Figure 1B, the salinity dependence of Kw/air is plotted for a temperature typical for natural waters (18 °C). We selected this temperature because: (1) it roughly reflects the medium temperature that is expected for the coastal sea (a typical environment for methodical radon applications), and (2) because the Kofler data set presents the most data points (n = 7) for that temperature (five of which are also displayed in Figure 1A). As illustrated in Figure 1B, an assumed salinity of 35 ‰ at 18 °C yields (based on the Kofler data set) a partition coefficient of about 0.196. If salinity is not taken into consideration, then a partition coefficient of 0.280 would apply for that temperature,9,10 finally resulting in an overestimation of the radon-in-water concentration (cf. eq 1). Although the quality of the data assembled for pure water by Kofler in 1913 has been reviewed by many authors,9 the quality and reliability of the Kofler data for saline waters has not been verified to our knowledge. Hence, we have carried out a large

number of laboratory experiments in order to re-evaluate the relation Kw/air = f (S). In order to ensure high reliability of the experimental results and to minimize any systematic experimental errors, two independent experimental setups (“Setup 1” and “Setup 2”) were applied that are based on different approaches, as well as different laboratories, allowing the production of two autonomous data sets.

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MODEL APPROACH

The solubility of gases in aqueous electrolyte solutions at a given temperature may be quantitatively described by the Setschenow equation.14,15 This equation (eq 2) relates the logarithmic ratio of the solubility of a gas in a pure solvent (e.g., water; C0) to that in an electrolyte solution (C>0) to the electrolyte concentration in the solution (Cel). The empirical Setschenow constant (k) is the proportionality factor and depends upon solvent, gas, electrolyte, and temperature. ln(C0/C> 0) = kCel

(2)

Several empirical model approaches exist for estimating the Setchenow constant. Schumpe16 published a model for a temperature of 25 °C in which ion- and gas-specific parameters are derived from available experimental solubility data. In its extended version, the model also contains the required parameter for radon, but systematically underestimates the salinity dependence of the radon solubility.17 A more general approach for the simultaneous evaluation of the dependence of gas solubility on both temperature and salinity is expressed with an equation derived by Weiss18 (eq 3) that is applicable to 3906

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experiments, each unit was filled with water of a known salinity without any headspace. Air bubbling through the water filled units without water entering the tubing connected to the air outlet was made possible by attaching a removable glass bulb as a trap. All four units were put in parallel, as illustrated in Figure 2A. During each experimental run, one of the units was filled with pure water (for comparison between the individual experimental runs); the other three units contained water with a defined salinity (NaCl) up to saturation (358 g/L at 20 °C). In order to ensure an equal flow rate through the stripping units, the airflow was adjusted individually by means of valves (a measure that was necessary due to the different density of the aqueous solutions). We used the portable radon monitor RAD7 (Durridge, U.S.) for radon-in-air determination. The radon rich air was recirculated through the system for at least 2 h to ensure chemical equilibrium. During that time, the radon concentration in air was recorded continuously with a 5 min counting cycle. That way we were able to evaluate when the chemical equilibrium between the two phases was established. Three series of individual experimental runs were carried out using the described setup, one at 5 °C (four experimental runs with the complete setup placed in a laboratory refrigerator), one at constant room temperature of 21 °C (ten runs) and one at 50 °C (four runs with the setup placed in a hot-air cabinet) yielding a total of 71 data points for Kw/air = f (T, S). In order to measure the radon equilibrium concentration of the aqueous solutions in the stripping units directly (e.g., without any stripping, transfer, or extraction step involved) the individual water filled units were analyzed by γ-spectroscopy. We used an ORTEC-Gamma-X HPGE coaxial low-energy ntype detector with an active volume of 39 cm3 and a 0.5 mm beryllium window. Before each measurement, the volume traps were removed from the stripping units and the units were immediately closed with gastight glass stoppers. The stripping units were thus completely filled with water with no air-filled headspace. Each sample was measured for 24 h. Detector and measuring geometry were calibrated using a certified aqueous radium solution applying exactly the same type of glass stripping unit as used for the experiments. Setup 2. Two series of individual experimental runs were carried out with Setup 2, one at 1.4 °C (nine experimental runs with the setup placed in an ice bath) and one at 26.7 °C (seven runs using a submersible heater) yielding a total of 15 data points for Kw/air = f (0 ≤ S ≤ 45, T = 1.4, 26.7 °C). The experiments with Setup 2, all performed at Florida State University and illustrated in Figure 2B, utilized a manganese dioxide impregnated acrylic fiber charged with 226Ra in a flowthrough cartridge as a radon source.22 After reaching chemical equilibrium with the water radon activities in the air ranged between 70 and 132 kBq/m3. The closed air loop was led through a 6-L bottle that contained approximately 5 L of radium-free water of known salinity. The bottle used was made of radon-tight high-density polyethylene with a modified threeport cap.23 All experiments were carried out with the sample bottle submerged in a water bath to control the temperature during the radon stripping. The salinities in the experiments ranged from 0 to 45 and were obtained by dissolving commercial sea salt (“Instant Ocean”)24 into a sample bottle and cross-checking with a conductivity probe (YSI Model 63). The experiments were initiated by directing the air through the radon source, the closed sample bottle via a bubble stone at its bottom, and finally the radon-in gas monitor (RAD7). The

several trace gases, including He, Ne, Ar, and Kr (refs 19 and 20; see also refs 13 and 21 for the compiled parameters). ⎛ T ⎞ ⎛ 100 ⎞ ⎟ + a ln⎜ ⎟ ln β = a1 + a2⎜ 3 ⎝ ⎝ T ⎠ 100 ⎠ ⎧ ⎛ T ⎞ ⎛ T ⎞2 ⎫ ⎟ + b ⎜ ⎟ ⎬ + S ⎨b1 + b2⎜ 3⎝ ⎝ 100 ⎠ 100 ⎠ ⎭ ⎩ ⎪

⎪

⎪

⎪

withK w/air = β • T /273.15

(3)

In eq 3 β is the Bunsen coefficient, S the salinity, T the temperature [K], and a1 to b3 refer to six adjustable parameters. Since the six parameters a1 to b3 were not yet available for radon, we designed a series of experiments to parametrize these coefficients applying the two different experimental setups “Setup 1” and “Setup 2”.

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EXPERIMENTAL SECTION Setup 1. The first experimental setup applied is illustrated schematically in Figure 2A. The setup included (i) a radon

Figure 2. Schematic sketch of the complete experimental Setup 1 (A) and Setup 2 (B); in part B “T” symbolizes a heater/cooler; radon source was bypassed after 10 min of bubbling.

source, (ii) a cluster of stripping units, and (iii) a radon-in-air monitor. The individual parts were connected with radon impermeable Tygon tubing. The Setup 1 experiments were conducted at the UFZ−Helmholtz Centre for Environmental Research, Leipzig, Germany. Each experimental run included four stripping units and was carried out by recirculating radon-rich air in a closed loop through the system as indicated by the arrows. The radon source consisted of a flow-through radon calibration standard (Pylon, Canada). The source was included into the system for the first 10 min of each experimental run and yielded radon concentrations in the closed air loop of about 250 kBq/m3. The radon stripping units (150 mL) were all made of glass and designed identically and allowed air injection at their bottom via a bubble stone and air release at their top. For the 3907

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Figure 3. (A) Experimental results achieved in five series of individual experiments with Setup 1 (S1) at 5, 21, and 50 °C and Setup 2 (S2) at 1.4, and 26.7 °C; (B) data for salinities of up to 45 depicted in more detail; for the displayed data points an uncertainty of 7.8% was estimated based on the law of error propagation; lines show sample scatter plots with potential regression line and related fitting statistics (no coefficient of determination is given for 50 °C since only two data points exist in the temperature range.

If the “S1: 21°C” data set produced in this study is compared to the Kofler data set valid for a temperature of 18 °C, then it is revealed that the Kofler data seems to slightly overestimate the salting out effect (Kw/air values are somewhat lower than our results, even though they were achieved at a slightly lower temperature). Since the Kofler data were determined about 100 years ago, we suspect that the limited analytical capability and precision available at that time might be the reason for the difference. On the basis of the theoretical considerations discussed above, we used the complete set of 71 analytical results displayed in Figure 3A for quantifying the six parameters a1 to b3 in order to adjust eq 3 for the water/air partitioning of radon. The resulting six model parameters a1 to b3 are listed in Table 1. The six parameters were estimated using the regression routine of Microsoft Excel. The standard error of estimate for the resulting model amounts to 0.012 (i.e., 6.9%). The resultant relationship (in the following referred to as eq 3a, cf. Table 1) allows quantifying the radon partition coefficient Kw/air as a function of both temperature and salinity. The obtained model is valid at atmospheric pressure, a temperature range 273 < T[K] < 323, and a salinity range 0 < S < 360. Figure 4A illustrates how well the experimental results are predicted by the model equation. Our empirical set of parameters was also tested against the equation presented by Weigel10 for freshwater (eq 1). The results of the two independent theoretical (empirical) approaches are in excellent agreement, which confirms the applicability of our empirical set of parameters for freshwater (Figure 4B). In order to find out if there is a significant difference between the model quantified with all 71 experimental data presented in this work and a model that only involves the more common range salinity range 0 < S < 54, the limited set of data points displayed in Figure 3B was used for estimating the model parameters a1 to b3 using the same regression approach (in the following referred to as eq 3b, cf. Table 1). The resulting parameters are also summarized in Table 1. For this partial data set with only 30 values we obtained 0.015 as standard error of estimate (5.2%), i.e., a value that is somewhat lower than the value achieved with the model employing the entire data set. We compared the results of the two model approaches (i.e., eqs

radon activity in the gas phase was continuously monitored using a 5 min counting cycle. In this manner, it was easy to determine when radon partitioning equilibrium had been established. The radon-in-air equilibrium concentration was recorded based on an average of the last 7 readings, i.e., 35 min. Subsequently, the connections to the sample container were replaced with a connection to a high-purity helium tank in order to pressurize the bottle and direct water samples to three 250-mL glass bottles. The radon-in-water activity was then determined applying a Durridge RAD-H2O accessory that sparges the water in the glass bottles, directing the air to a radon-in gas monitor (RAD7). By measuring the radon-inwater concentrations in triplicate, a precision ranging between 5 and 7% was obtained. By using the same RAD7 as used for the radon-in-air determinations, we were able to eliminate any source of error from differences in calibrations between instruments.

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RESULTS AND DISCUSSION

Figure 3A illustrates all the experimental results achieved in this study. The 18 experimental runs carried out with Setup 1 yielded 71 data points. The 18 results achieved for pure water (4 at 5 °C, 10 at 21 °C, 4 at 50 °C) are displayed as respective mean values. Hence, of the total number of 71 data points achieved with the setup 56 are displayed in Figure 3A (S1). The 15 data points achieved with Setup 2 are also displayed in Figure 3A (S2). Since salinities of up to about 45 are most common for natural environments, the results covering that range are represented in more detail in Figure 3B. The data shows the apparent dependence of Kw/air on both water temperature and water salinity. For each data point in Figure 3, we detected the analytical uncertainty associated with the applied instruments and the methodical approaches (2σ) for each radon measurement in air (range 1.2−2.7%, average 1.7%), each radon measurement in water (range 5.3−10.0%, average 7.6%) and each radon measurement applying γ spectrometry (range 3.0−6.0%, average 5.0%). On the basis of standard deviations achieved by running replicates as described in this work, the uncertainties were propagated to finally get a 7.8% uncertainty of the K coefficients displayed in Figure 3. 3908

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273−323 273−300 273−323

this study (all data) this study (selected data) this study +Kofler9

0−360 0−54 0−360

S range 71 30 110

n −76.14 (21.43) −77.91 (31.40) −95.90 (22.90)

a1 (sa1)

a3 (sa3) 31.26 (10.29) 32.13 (15.10) 40.81 (11.00)

a2 (sa2) 120.36 (30.34) 122.82 (44.39) 148.12 (32.42)

b2 (sb2) 0.1673 (0.0230) 0.3049 (0.1659) 0.1373 (0.0225)

b1 (sb1) −0.2631 (0.0345) −0.4656 (0.2458) −0.2178 (0.0335)

−0.0270 (0.0038) −0.0504 (0.0279) −0.0220 (0.0038)

b3 (sb3) 0.9882 0.9848 0.9792

R2 1085 311 981

F 6.9 5.2 8.6

se [%]a

eq. (3a) (3b) (3c)

a

se [%] = 100((Σi(Ki(exp.) − Ki(calc.))2)/(n-6−1))1/2/((Σi(Ki(exp.))/(n)) bThe bold-printed parameters are significant on the 95% confidence level; the standard deviations of the parameters are given in parentheses (sa1, ..., sb1); R2 is the multiple coefficient of determination, F the value of the test statistics on the significance of R2 and se is the standard error of estimate for Kw/air; for practical applications the set of parameters “this study (all data)” (eq 3a) is the most recommendable.

T [K] range

data source

Table 1. Parameters a1 to b3 of Eq 3 Obtained from Different Data Sets (Resp. Ranges of Temperature and Salinity) Using Multiple Linear Regression (from MS Excel Analysis Functions)b

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Figure 4. A Comparison between Kw/a values calculated according to the parametrized eq 3a (cf. Table 1) and the values determined experimentally in this study. The lines above and below the 1:1 line, respectively, illustrate the ±10% range. The inserted part A shows low K values. Part B Comparison between Kw/air values after Weigel (1978) and values calculated applying eq 4 for S = 0.

3a and 3b) as displayed in Figure 5. We used temperatures

typical for groundwater as well as the coastal ocean (5, 10, 20,

and 30 °C) and a salinity range of 0 < S < 35 for the

comparison. The results show that both models yield analogous

results, especially for salinities typical for the coastal sea.

Figure 5. Results of eq 3a valid for typical surface temperatures between 5 and 30 °C and salinities between 0 and 35 .

3909

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As a final step of evaluation, the complete set of available data points, i.e., our experimental data (Figure 3A) and the Kofler data (Figure 1A), was used for estimating the model parameters a1 to b3 (in the following referred to as eq 3c, cf. Table 1). The resulting data are also given in Table 1. The related standard error of estimate is 0.016 (8.6%). The obtained model parameters as well as the model performance differ only slightly from the model based on our own data only even though the Kofler data set seems to overestimate the salting out effect. Although parameters b1, b2, and b3 are obtained as insignificant for the data set restricted to the salinity range of seawater (therefore not printed in bold in Table 1), a further parameter reduction in eq 3b, i.e., regression with the parameters a1, a2 and a3 only, does not yield better results (in terms of R2 and se). For that reason, the authors recommend the use of the full parameter set when applying eq 3 (i.e., eq 3a). For better illustration, the dependence of the air/water partition coefficient of radon on both water temperature and salinity is shown in a 3-dimensional diagram in Figure 6 (based

Table 2. Theoretical Results (cf. Equations 4 and 5) of Three Different Experimental Setups Adjusted to the Effect of Salinity Each Applying Either the Salinity Corrected (Salinity: 35; Kw/air = 0.244) or the Uncorrected (Freshwater; Kw/air = 0.293) Value for Kw/air at 15 °C Vair [l]

Cair [Bq/l]

Kw/air

Cw [Bq/l]

Δ [%]

0.26

1.4

10

2.9

10

∞

n.a.

10

56.78 56.29 7.76 7.27 2.93 2.44

0.9

6.00

0.293 0.244 0.293 0.244 0.293 0.244

6.7 20.1

volume (Vw) in relation to the circulating air volume (Vair), the less radon that remains in the water phase when equilibrium is obtained, thereby significantly decreasing the impact of Kw/air on the resulting radon-in-water concentration (a principle that the mentioned RAD-H2O system relies on). The equation applicable for discrete water samples is given in eq 5.3,2 ⎞ ⎛V C w = Cair⎜ air + K w/air⎟ ⎠ ⎝ Vw

(5)

Table 2 summarizes results for typical experimental setups for radon-in-water detection by means of a radon-in-air monitor. As an example the use of the RAD7 as a radon-in-air monitor is assumed with an air volume (detection chamber plus desiccant cartridge and associated tubing) of about 1.4 L. Setups are given for a small sample flask containing a water volume of only 0.26 L and barely any headspace,3 for a larger canister containing a water sample of 6.0 L and about 1.5 L of headspace4 and finally for a constantly running water stream as discussed above (with Vw = ∞ and Vair not applicable). We assumed that the water had a salinity of 35 and a temperature of 15 °C. The results related to both the salinity corrected and the uncorrected freshwater value for Kw/air (Kw/air = 0.244 and Kw/air = 0.293, respectively), are given. We also show the resulting overestimation of the radon-in-water concentration due to the use of the uncorrected, i.e., wrong salinity coefficient. Even though the salting out effect has been ignored in studies in the coastal ocean carried out so far, cases have been reported where both continuously running pump streams as well as discrete water samples were analyzed with overlapping results.6,8,25 That was likely the result of the sampling being performed in relatively warm subtropical waters where the salting out effect is less serious. For example, intercomparison measurements that were made in Florida were obtained in coastal waters with temperatures at about 30 °C and a salinity of about 25. Although an overestimation of the radon-in-water concentration by about 20% is expected at 15 °C water temperature and a salinity of 35, that overestimation is reduced to about 10% at the conditions encountered in Florida. However, even though the error that results from ignoring the salting out effect might in cases be below or around typical measurement uncertainties of 10% (in warm and less saline waters), the effect should still be considered for two reasons: (1) it adds a systematic error to the detection results; and (2) since temperature and salinity can easily be recorded continuously without much effort during a field campaign (and are recorded in most cases anyway), Kw/air can be relatively easily considered for obtaining the most precise results. For quantification of Kw/air = f (T, S) we recommend

Figure 6. Dependence of the water/air partitioning behavior of radon on both water temperature and salinity based on eq 3.

on our own experimental data). The diagram gives a good impression of the impact of the salting out effect and how it relates to temperature. Highlighted in bold for a temperature of 15 °C are water salinities for fresh water, typical seawater, and a saturated salt solution (e.g., Dead Sea water). It is clear from Figure 6 that radon-in-water concentrations (Cw) determined by radon stripping from a constant water pump stream (Cair) would systematically be overestimated if salinity is not accounted for. For example (cf. eq 3a, Table 1) if Cw of water with a salinity of 35 and temperature of 15 °C is calculated from Cair applying the Kw/air for freshwater, the radon concentration would be overestimated by 19% (applying eq 4, cf. Table 2). C w = CairK w/air

Vw [l]

(4)

If instead of a constantly running water pump stream (i.e., an unlimited volume of water), the analytical scheme is using a discrete water sample with a defined limited volume, the salinity related overestimation of the radon-in-water concentration is less pronounced (Table 2). The smaller the analyzed water 3910

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(14) Young, C. L.; et al. the Solubility of Gases in Liquids. In Solubility Data Series: Krypton, Xenon and RadonGas Solubilities; Clever, H. L., Ed.; Pergamon Press: Oxford/UK, 1979, Vol. 2. (15) Fogg, P. Solubility of gases in strong electrolyte solutions. In: Chemicals in the Atmosphere- Solubility, Sources and Reactivity; Fogg, P. G. T., Sangster, J. M., Eds.; IUPAC & Wiley: Chichester/UK, 2003; Chap. 7. (16) Schumpe, A. The estimation of gas solubilities in salt solutions. Chem. Eng. Sci. 1993, 48, 153−158. (17) Hermann, C.; Dewes, I.; Schumpe, A. The estimation of gas solubilities in salt solutions. Chem. Eng. Sci. 1995, 50, 1673−1675. (18) Weiss, R. F. The solubility of nitrogen, oxygen and argon in water and seawater. Deep Sea Res. 1970, 17, 721−735. (19) Weiss, R. F. Solubility of helium and neon in water and seawater. J. Chem. Eng. Data 1971, 16, 235−241. (20) Weiss, R. F.; Kyser, T. K. Solubility of krypton in water and seawater. J. Chem. Eng. Data 1978, 23, 69−72. (21) Sangster, J. Herny’s Law Constants for Dissolution in Seawater. In Chemicals in the AtmosphereSolubility, Sources and Reactivity; Fogg, P. G. T., Sangster, J. M., Eds.; IUPAC & Wiley: Chichester/UK, 2003; Chap. 12 (22) Peterson, R. N.; Burnett, W. C.; Dimova, N.; Santos, I.R. A comparison of measurement methods for radium-226 on manganesefiber. Limnol. Oceanogr. Methods 2009, 7, 196−205. (23) Stringer, C.; Burnett, W. C. Sample bottle design improvements for radon emanation analysis of natural waters. Health Phys. 2004, 87, 642−646. (24) Atkinson, M. J.; Bingman, C. Elemental composition of commercial seasalts. J. Aquaricult. Aquat. Sci. 1997, 8 (2), 39−43. (25) Stieglitz, T. C.; Cook, P. G.; Burnett, W. C. Inferring coastal processes from regional-scale mapping of 222Radon and salinity Examples from the Great Barrier Reef, Australia. J. Environ. Radioactiv. 2010, 101 (7), 544−552. (26) Meyer, S.; Schweidler, E. V. Radioaktivität; Teubner: Leipzig, Germany (in German), 1916, p 326.

applying the six model parameters based on our own experimental data set “this study (all data)” (eq 3a). In the presented work, we did not address the fact that the pH of an aqueous solution influences the solubility of gases as well. The main reason for excluding the pH as an influential parameter was that we do not expect a major influence in the pH range that is of practical interest for groundwater and SGD studies. Moreover, a significant influence of the pH is not likely due to the nonpolar nature of radon. However, we do acknowledge the subject as a still open question, encouraging further research activities in that field. Also care should be taken if water of a composition very different from seawater, such as MgCl2-rich brines of the Dead Sea, is under investigation, since our results are based on NaCldominated solutions.

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AUTHOR INFORMATION

Corresponding Author

*Phone: 0049 341 235 1410; fax: 0049 341 235 1443; e-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS W.C.B. acknowledges financial support from the National Science Foundation (OCE-0961970). The authors also thank Derek Lane-Smith (Durridge) for helpful advice.

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dx.doi.org/10.1021/es204680n | Environ. Sci. Technol. 2012, 46, 3905−3911