Numerical simulations of radon as an in situ ... - Semantic Scholar
Journal of Contaminant Hydrology 78 (2005) 87 – 103 www.elsevier.com/locate/jconhyd
Numerical simulations of radon as an in situ partitioning tracer for quantifying NAPL contamination using push–pull tests B.M. Davisa,*, J.D. Istokb,1, L. Semprinib,1 a
ChevronTexaco Energy Technology Co., PO Box 1627, 100 Chevron Way, Richmond, CA 94802, USA b Department of Civil, Construction and Environmental Engineering, Oregon State University, Corvallis, OR 97331, USA Received 6 October 2003; received in revised form 24 March 2005; accepted 31 March 2005
Abstract Presented here is a reanalysis of results previously presented by Davis et al. (2002) [Davis, B.M., Istok, J.D., Semprini, L., 2002. Push–pull partitioning tracer tests using radon-222 to quantify nonaqueous phase liquid contamination. J. Contam. Hydrol. 58, 129–146] of push–pull tests using radon as a naturally occurring partitioning tracer for evaluating NAPL contamination. In a push–pull test where radon-free water and bromide are injected, the presence of NAPL is manifested in greater dispersion of the radon breakthrough curve (BTC) relative to the bromide BTC during the extraction phase as a result of radon partitioning into the NAPL. Laboratory push–pull tests in a dense or DNAPL-contaminated physical aquifer model (PAM) indicated that the previously used modeling approach resulted in an overestimation of the DNAPL (trichloroethene) saturation (S n). The numerical simulations presented here investigated the influence of (1) initial radon concentrations, which vary as a function of S n, and (2) heterogeneity in S n distribution within the radius of influence of the push–pull test. The simulations showed that these factors influence radon BTCs and resulting estimates of S n. A revised method of interpreting radon BTCs is presented here, which takes into account initial radon concentrations and uses non-normalized radon BTCs. This revised method produces greater radon BTC sensitivity at small values of S n and was used to re-analyze the results from the PAM push–pull tests reported by Davis et al. The re-analysis resulted in a more accurate * Corresponding author. Fax: +1 510 242 1380. E-mail addresses: [email protected] (B.M. Davis), [email protected] (J.D. Istok), [email protected] (L. Semprini). 1 Fax: +1 541 737 3099. 0169-7722/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jconhyd.2005.03.003
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estimate of S n (1.8%) compared with the previously estimated value (7.4%). The revised method was then applied to results from a push–pull test conducted in a light or LNAPL-contaminated aquifer at a field site, resulting in a more accurate estimate of S n (4.1%) compared with a previously estimated value (13.6%). The revised method improves upon the efficacy of the radon push–pull test to estimate NAPL saturations. A limitation of the revised method is that dbackgroundT radon concentrations from a non-contaminated well in the NAPL-contaminated aquifer are needed to accurately estimate NAPL saturation. The method has potential as a means of monitoring the progress of NAPL remediation. D 2005 Elsevier B.V. All rights reserved. Keywords: NAPL; Tracers; Partitioning; Single-well tests; Radon
1. Introduction Partitioning interwell tracer tests have been used to quantify nonaqueous phase liquid (NAPL) saturations in laboratory and field settings of saturated groundwater flow (Jin et al., 1995; Nelson and Brusseau, 1996; Annable et al., 1998; Nelson et al., 1999; Young et al., 1999). Recently, single-well dpush–pullT partitioning tracer tests have been used to quantify NAPL saturations (Davis et al., 2002, 2003; Istok et al., 2002). In a push–pull test, an injection solution containing partitioning and conservative tracers is injected (dpushedT) into an aquifer through a well. The solution/groundwater mixture is then extracted (dpulledT) from the same well. These tests have involved the use of both dex situT (i.e., injected) and din situT (i.e., naturally occurring radon) partitioning tracers. For the ex situ tracer method, partitioning and conservative (e.g., bromide) tracers are injected into the aquifer, while for the in situ tracer method, a radon-free injection solution (containing a conservative bromide tracer) is injected into the aquifer. In both cases, the presence of NAPL is indicated by a greater dispersion of the extraction phase breakthrough curve (BTC) for the partitioning tracer relative to a conservative tracer (Schroth et al., 2000). In situ radon that is generated by aquifer solids (t 1/2 = 3.83 days) has been used as a partitioning tracer for locating and quantifying dense or DNAPL saturation (Semprini et al., 1993, 1998, 2000; Davis et al., 2002, 2003) and light or LNAPL saturation (Hunkeler et al., 1997; Davis et al., 2002). The steady-state or dbackgroundT radon concentration in groundwater (C w,bkg) is a function of the radium content (C Ra, mass/mass) and radon emanation power (E p, unitless) of the aquifer solids and the bulk density (q b) and porosity (n) of the aquifer as described by (Semprini et al., 2000): Cw;bkg ¼
CRa Ep qb n
ð1Þ
Model equations for the equilibrium partitioning of radon and the secular equilibrium that is achieved between radon emanation and decay are provided by Semprini et al. (2000) and Davis et al. (2002). The models are based on linear partitioning, with the partition coefficient (K) for radon defined as: K¼
Cn Cw;n
ð2Þ
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where C n is the concentration of radon in the NAPL, and C w,n is the concentration of radon in the aqueous phase in the presence of NAPL. Partition coefficients may be determined using the methodology of Cantaloub (2001) and range from 37 (o-xylene) to 50 (trichloroethene, or TCE) to 61 (cyclohexane). As groundwater flows through a NAPLcontaminated zone of an aquifer, radon in NAPL will obtain a concentration in equilibrium with radon in groundwater. Because radon is continually being generated by aquifer solids and is continually decaying, and because groundwater flow is typically slow, a closedsystem equilibrium equation (Eq. (3)) describes radon concentrations in water and NAPL. Model simulations by Semprini et al. (2000) show that if transport through the NAPLcontaminated zone is long enough for equilibrium to be achieved, radon concentrations can be described by Eq. (3): Cn Sn þ Cw;n Sw ¼ Cw;bkg
ð3Þ
Based on linear radon partitioning between NAPL and water (Eq. (2)), radon concentration in the water phase is given by a rearranged Eq. (3): Cw;n ¼
Cw;bkg 1 þ S n ð K 1Þ
ð4Þ
where C w,n is a non-linear function of S n and K. This non-linear relationship is shown in Fig. 1, using a K = 50. Eq. (4) can be further rearranged to solve for the NAPL saturation in an aquifer as a function of C w,bkg, C w,n, and K: Cw;bkg 1 Sn ¼ 1 ð5Þ ð K 1Þ Cw;n Note that Eq. (5) does not require estimation of radon retardation (R) via a push–pull test in order to calculate S n. However, radon retardation during transport can be used to 200
Cw,n (pCi/L)
150
100
50
0 0
5
10
15
20
Sn (%) Fig. 1. Aqueous phase radon concentrations (C w,n) as a function of NAPL saturation, plotted using Eq. (3) with a background radon concentration (C w,bkg) = 200 pCi/l and K = 50.
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determine NAPL saturation. The retardation factor for a partitioning tracer is given by (Dwarakanath et al., 1999): R¼1þ
KSn Sw
ð6Þ
If K is known and R is estimated using a push–pull test, S n can be determined using: Sn ¼
R1 RþK1
ð7Þ
Push–pull tests using radon as a partitioning tracer were performed in laboratory physical aquifer models (PAMs) containing TCE (Davis et al., 2002). Experimental conservative (bromide) tracer and radon extraction phase BTCs were fitted to an approximate analytical solution to estimate R, which was then used to calculate S n. This approach resulted in an overestimation of S n compared to the NAPL saturation emplaced in the PAM. Furthermore, the numerical modeling in Davis et al. (2002) assumed that radon behaved similarly to an injected tracer. Although these simulations accounted for radon partitioning between the NAPL and aqueous phases during the push–pull test, they did not account for steady-state radon partitioning into NAPL prior to the test. The pre-test radon concentrations are in fact reduced in the presence of NAPL, with the steady-state radon concentration being a non-linear function of S n (Eq. (4)). Also, the model construct did not agree with the actual conditions in the PAM. For example, the model assumed that NAPL was distributed throughout the PAM sediment, while in the laboratory push–pull tests, the NAPLcontaminated zone existed in only part of the PAM’s sediment. The heterogeneous NAPL distribution will affect initial radon concentrations and partitioning behavior during the push–pull test. As will be shown, this heterogeneous distribution can affect estimations of R and S n. The goal of this study was to examine two factors that can influence the interpretation of push–pull tests for estimating S n: (1) the influence of NAPL on initial (i.e., preinjection) phase radon concentrations, and (2) heterogeneous NAPL saturation distributions. A revised method of interpreting radon BTCs is presented, which results in more accurate estimates of S n and in an increase in sensitivity of the estimation method at small values of S n. This method was then used to re-estimate values of S n in previously conducted laboratory and field push–pull tests.
2. Methods Simulations were performed with the STOMP code (White and Oostrom, 2000), a fully implicit volume-integrated finite difference simulator for modeling one-, two-, and threedimensional groundwater flow and transport. The simulator models the advective/ dispersive equation, with linear equilibrium partitioning. STOMP has been extensively tested and validated against analytical solutions and other numerical codes (Nichols et al., 1997). Simulations were based on a hypothetical push–pull test conducted in a 5 cm
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diameter well over a 91.4 cm long screened interval of an aquifer. The model aquifer is based on an aquifer composed of sediment from the Hanford Formation, an alluvial deposit of sands and gravels of mixed basaltic and granitic origin (Lindsey and Jaeger, 1993) previously used in laboratory push–pull tests. Solid density (q s) = 2.9 g/cm3, porosity (n) = 0.35, calculated bulk density (q b) = 1.89 g/cm3, and longitudinal dispersivity (a L) = 4.0 cm were used in all the simulations. Simulations incorporated an injection volume of 250 l and an extraction volume ranging from 500 to 2000 l. Injection and extraction pumping rates were constant at 1 l/min with no rest period between the injection and extraction phases. The computational domain consisted of a line of 500 nodes with a uniform radial node spacing of Dr = 1.0 cm. The model geometry and injection volumes resulted in the injection solution traveling 48 cm from the well, as measured by the travel distance to half the solution injection concentration of the conservative tracer (C/C 0 = 0.5). Simulations were performed using time-varying third-type flux boundary conditions to represent pumping at the well, with a constant hydraulic head. Constant head and zero solute flux boundary conditions were used to represent aquifer conditions at r = 500 cm. Specified NAPL saturations were modeled using TCE with a value of K = 50 for radon (Davis et al., 2003). To simplify the modeling procedure, NAPL saturations (S n) were incorporated into the model using solid:aqueous phase partition coefficients, which enabled the model to mimic radon partitioning into NAPL as radon partitioning into aquifer solids. These two partitioning processes are similar for radon. First, Eq. (6) was used to determine a retardation factor (R) for a given ratio of S n to water saturation (S w). Second, this calculated R value, the sediment porosity, and the bulk density were used to determine a solid:aqueous phase partition coefficient (K d): n Kd ¼ ð R 1Þ ð8Þ qb Simulations were performed with specified S n values from 0% to 15.25%, which corresponds to retardation factors (R) ranging from 1 to 10, respectively. The effects of initial radon concentrations and S n heterogeneity on simulation results were investigated with three sets of simulations, with NAPL extending homogeneously from (1) r = 500 cm, (2) r = 48 cm (corresponding to the maximum travel radius of a conservatively transported tracer, as defined by C/C 0 = 0.5), and (3) r = 24 cm (corresponding to half the maximum travel radius of a conservatively transported tracer), where r is the radial distance from the injection/extraction well. An initial radon concentration of 200 pCi/ l (corresponding to S n = 0%) was emplaced at r N 48 cm for the second set of simulations and at r N 24 cm for the third set of simulations. Each simulation utilized (1) an injection radon concentration of 0 pCi/l, which corresponds to the true radon injection concentration in laboratory and field push–pull tests, and (2) an initial radon concentration in the model that varied in space as a function of S n. The simulations involving the PAM and field tests are described below. All simulations and PAM and field push–pull tests were performed over time periods such that the effects of radon emanation and decay on radon concentrations could be neglected (i.e., Ve/Vi = 2 was obtained in V 12.5 h, where Vi is the volume of solution injected and Ve is the volume of solution extracted at a given time).
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3. Results and discussion 3.1. Injection phase results Fig. 2 shows radon concentration spatial profiles at the end of the injection phase of a simulated push–pull test (corresponding to Ve /Vi = 0) for S n values of 0–4% and for different distributions of NAPL. When S n = 0%, the radon-free injection solution is transported to r = 48 cm, as measured by half the initial radon concentration (C/C 0 = 0.5) at the injection well (i.e., one manner in which to measure transport distance). In contrast, when S n p 0% over a specified portion of the model domain, radon is retarded. When S n = 4% for r V 500 cm (i.e., a homogeneous NAPL distribution) and the initial radon concentration in the model is 68 pCi/l (Eq. (4)), the radon-free injection solution is transported only to r = 26 cm, as measured by half the initial radon concentration at the injection well, due to retardation resulting from radon partitioning into the NAPL during transport. When S n = 4% for r V 48 cm and S n = 0% for r N 48 cm (i.e., a heterogeneous NAPL distribution), the injection solution is again transported only to r = 26 cm. A twostep radon concentration profile results from this heterogeneous NAPL distribution. When S n = 4% for r V 24 cm and S n = 0% for r N 24 cm, the radon-free injection solution is retarded as indicated by the profile, but the concentration increases rapidly as the radial distance increases. Thus, when the portion of the model domain containing NAPL decreases, the profiles tend towards the zero saturation case. Radon concentration profiles are influenced by both radon partitioning between the aqueous phase and NAPL prior to the push–pull test, and radon partitioning between the injection solution and NAPL during the test. Heterogeneity in NAPL distribution affects radon concentration profiles due to the partitioning processes and mixing of water with different initial radon concentrations during the test.
200 Sn=4% to 500cm Sn=4% to 48cm Sn=4% to 24cm
Cw,n (pCi/L)
150
Sn=0% to 500cm
100
50
0 0
20
40
60
80
100
radial distance (cm) Fig. 2. Simulated radon concentration profiles (C w,n) at the end of the injection phase of push–pull tests with no NAPL (S n = 0% to 500 cm); heterogeneous NAPL saturation (S n = 4% to 48 cm) and (S n = 4% to 24 cm); and homogeneous NAPL saturation (S n = 4% to 500 cm).
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3.2. Extraction results—concentration profiles 3.2.1. Radon concentration profiles for different degrees of fluid extraction Simulated radon concentration profiles as a function of the volume of groundwater extracted are presented in Fig. 3. Note that the volume of injection solution/groundwater extracted (Ve) is divided by the total volume of injection solution injected (at the end of the injection phase, Vi) to calculate dimensionless time (Ve/Vi) during the extraction phase. For the case of S n = 4% for r V 500 cm (i.e., a homogeneous NAPL distribution), radon concentrations increase with time as the injection solution/groundwater mixture is extracted from the well (Fig. 3a). The initial radon equilibrium concentration was 68 pCi/l for r V 500 cm (Eq. (4)). The radon concentration at the well (r = 0 cm) is 63% of the initial radon concentration at Ve/Vi = 1, 89% at Ve/Vi = 2, and 96% at Ve/Vi = 3. Thus, as extraction proceeds, radon concentrations approach but do not exceed the initial radon concentration. Profiles for a heterogeneous NAPL distribution when S n = 4% for r V 48 cm and S n = 0% for r N 48 cm are shown in Fig. 3b. The initial equilibrium radon concentration was 68 pCi/l for r V 48 cm and 200 pCi/l for r N 48 cm (shown with a step-function concentration change for simplicity). The radon concentration measured at the well (r = 0 cm) is 63% of the initial radon concentration at Ve /Vi = 1, 103% at 2, and 153% at 3, and increases to 291% at 8. As the extraction proceeds, radon concentrations at the well exceed the initial radon concentration due to the influx of water with a radon concentration of 200 pCi/l. Such a response in push–pull tests might be utilized in identifying heterogeneous NAPL distributions. Fig. 3c shows the profiles that result from the heterogeneous distribution when S n = 4% for r V 24 cm and S n = 0% for r N 24 cm. Radon concentrations increase more quickly with time as the injection solution/groundwater mixture is extracted from the well compared to the previous simulation. Radon concentrations at the well exceed the initial radon concentration at the well after just Ve/Vi = 1 due to the influx of water with a radon concentration of 200 pCi/l. Thus, as NAPL is concentrated closer to the well, radon concentrations more rapidly exceed initial values at the well as the extraction phase proceeds. Conversely, if NAPL saturations are distributed farther from the well, radon concentrations would possibly not approach initial values at the well. 3.3. Extraction phase results—breakthrough curves Usually the only radon concentration data available at field sites are obtained from the well in which the push–pull test is conducted. To investigate radon BTC behavior, a set of six simulations was performed for each of the homogeneous and heterogeneous NAPL distributions. Simulations performed for the homogeneous NAPL distribution are presented in Fig. 4a, while those for the heterogeneous NAPL distributions are presented in Fig. 4b and c. Each simulation represented a different value of S n. For homogeneous NAPL distributions (Fig. 4a), as the extraction phase approaches Ve /Vi = 2, radon concentrations approach but do not exceed their initial value at the well. Radon concentrations approach initial values at the well more slowly as S n increases due to the
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(a)
200 initial conditions Ve/Vi = 0 Ve/Vi = 1
Cw,n (pCi/L)
150
Ve/Vi = 2 Ve/Vi = 4
100
50
0 0
20
40
60
80
100
radial distance (cm)
(b)
200
Cw,n (pCi/L)
150
100
initial Ve/Vi = 0
Ve/Vi = 1 Ve/Vi = 2
50
Ve/Vi = 4 Ve/Vi = 6 Ve/Vi = 8
0 0
20
40
60
80
100
radial distance (cm)
(c)
200
Cw,n (pCi/L)
150 initial Ve/Vi = 0
100
Ve/Vi = 1 Ve/Vi = 2
50
Ve/Vi = 4 Ve/Vi = 6 Ve/Vi = 8
0 0
20
40
60
80
100
radial distance (cm) Fig. 3. Simulated radon concentration profiles (C w,n) during the extraction phase of a push–pull test. (a) S n = 4% for r V 500 cm; (b) S n = 4% for r V 48 cm; S n = 0% for r N 48 cm; (c) S n = 4% for r V 24 cm; S n = 0% for r N 24 cm.
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(a) 200 Sn=0%,R=1
Sn=1.96%,R=2
Cw,n (pCi/L)
150
Sn=5.66%,R=4 Sn=9.09%,R=6 Sn=12.28%,R=8 Sn=15.25%,R=10
100
50
0 0.0
0.5
1.0
1.5
2.0
1.5
2.0
1.5
2.0
Ve/Vi
(b) 200 Sn=0%,R=1
Sn=1.96%,R=2
Cw,n (pCi/L)
150
Sn=5.66%,R=4 Sn=9.09%,R=6 Sn=12.28%,R=8 Sn=15.25%,R=10
100
50
0 0.0
0.5
1.0
Ve/Vi
(c)
200 Sn=0%,R=1
Sn=1.96%,R=2
Cw,n (pCi/L)
150
Sn=5.66%,R=4 Sn=9.09%,R=6 Sn=12.28%,R=8 Sn=15.25%,R=10
100
50
0 0.0
0.5
1.0
Ve/Vi Fig. 4. Simulated radon breakthrough curves during the extraction phases of six push–pull tests. (a) S n = 0– 15.25% for r V 500 cm; (b) S n = 0–15.25% for r V 48 cm; S n = 0% for r N 48 cm; (c) S n = 0–15.25% for r V 24 cm; S n = 0% for r N 24 cm.
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increase in dispersion of the radon BTC (Schroth et al., 2000). Radon BTCs show the greatest sensitivity at small values of S n, which is due to the non-linear relationship between S n and the initial radon concentration. The simulations performed for a heterogeneous NAPL distribution (S n for r V 48 cm and S n = 0% for r N 48 cm) are presented in Fig. 4b. As the extraction phase approaches Ve / Vi = 2, radon concentrations approach their initial value at the well. Radon concentrations would increase beyond the initial radon concentration for S n N 0% if Ve /Vi progressed beyond 2. However, the shapes of the radon BTCs are similar at early times for the two sets of simulations (Fig. 4a and b), since conditions close to the well dominate the response. The third set of six simulations performed with the heterogeneous NAPL distribution (S n for r V 24 cm and S n = 0% for r N 24 cm) are presented in Fig. 4c. As the extraction phase reaches Ve /Vi = 2, radon concentrations approach and exceed their initial value at the well to a greater degree than when NAPL extended to 48 cm. These percentages vary as a function of S n, reaching 165% of the initial value at the well for S n = 1.96%, 239% for S n = 5.66%, and 189% for S n = 15.25%. The presence of S n = 0% for r N 24 cm produces greater radon concentrations for each simulation as compared to the prior simulations. Radon concentrations would continue to increase beyond the initial radon concentration for S n N 0% if Ve/Vi progressed beyond 2. The S n = 0% at r N 24 cm results in greater slopes for radon BTCs compared to the previous simulations (Fig. 4a and b). The shape of the radon BTCs, especially at late time, can be potentially used to investigate heterogeneity in NAPL distribution. 3.4. Extraction phase results—normalized breakthrough curves Fig. 5 presents the extraction phase normalized BTCs for the results presented in Fig. 4. Radon concentrations are normalized to the initial concentrations at the well prior to the injection phase. For the homogenous NAPL distribution, the normalized concentration does not exceed 1 at Ve/Vi = 2 (Fig. 5a). The effect of increasing dispersion as S n increases is apparent (Schroth et al., 2000). A drawback to normalizing to the initial radon concentration is the decrease in sensitivity of the radon BTCs to small values of S n compared to the non-normalized method (Fig. 4a). This drawback is a concern when fitting experimental radon BTCs to simulated BTCs in order to determine a best-fit value of R in order to estimate S n. The normalized BTC for the heterogeneous NAPL distribution where S n = 0% for r N 48 cm deviates from the homogenous cases as the extraction volume increases (Fig. 5b). The deviation becomes even more pronounced when normalized radon BTCs deviate from those for the heterogeneous NAPL distribution S n = 0% for r N 24 cm (Fig. 5c). Thus, the interpretation of normalized radon BTCs becomes more difficult as heterogeneity in S n increases. Fig. 5. Simulated radon breakthrough curves during the extraction phases of six push–pull tests. Radon concentrations are normalized to the initial radon concentrations at the well for each value of S n. (a) S n = 0 –15.25% for r V 500 cm; (b) S n = 0 –15.25% for r V 48 cm; S n = 0% for r N 48 cm); (c) S n = 0 –15.25% for r V 24 cm; S n = 0% for r N 24 cm.
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Normalized Cw,n
(a)
1.0 0.8 0.6 Sn=0%,R=1
0.4
Sn=1.96%,R=2 Sn=5.66%,R=4 Sn=9.09%,R=6
0.2
Sn=12.28%,R=8 Sn=15.25%,R=10
0.0 0.0
0.5
1.0
1.5
2.0
Ve/Vi
Normalized Cw,n
(b)
1.0 0.8 0.6 Sn=0%,R=1
0.4
Sn=1.96%,R=2 Sn=5.66%,R=4 Sn=9.09%,R=6
0.2
Sn=12.28%,R=8 Sn=15.25%,R=10
0.0 0.0
0.5
1.0
1.5
2.0
Ve/Vi
(c)
1.0
Normalized Cw,n
0.8 0.6 Sn=0%,R=1
0.4
Sn=1.96%,R=2 Sn=5.66%,R=4 Sn=9.09%,R=6
0.2
Sn=12.28%,R=8 Sn=15.25%,R=10
0.0 0.0
0.5
1.0
Ve/Vi
1.5
2.0
97
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3.5. Revised method for radon BTC interpretation The use of non-normalized radon BTCs to estimate S n provides two advantages over normalized radon BTCs in that (1) the sensitivity of non-normalized radon BTCs to small values of S n can be utilized, and (2) the effect of heterogeneity in S n on the shape of radon BTCs can be lessened. The revised method for estimating S n utilizing non-normalized radon BTCs requires obtaining a dbackgroundT radon concentration (C w,bkg) from a noncontaminated portion of the contaminated aquifer. Using this sample as a dbackgroundT concentration assumes homogeneity in porosity and radon emanation between the noncontaminated location chosen for the dbackgroundT radon sample and the location with suspected NAPL contamination where the push–pull test is conducted. To use this revised method extraction phase, radon and bromide results are plotted in concentration units (pCi/ l for Rn and mg/l for Br) as a function of Ve /Vi. The y-axis of the plot shows radon concentrations ranging from 0 at the origin to a maximum value equal to the dbackgroundT concentration. Bromide concentrations are plotted on a secondary y-axis with concentrations ranging from the injection solution concentration to 0 mg/l, the injection solution concentration at the origin, and 0 mg/l at the maximum or dbackgroundT radon concentration. This inverts the bromide concentrations and causes the radon and bromide BTCs to overlap. Numerical simulations are then performed to best-fit (using a least squares procedure) the experimental bromide BTC to a non-retarded simulated BTC (i.e., with R = 1) by varying the sediment dispersivity (a L). The best-fit a L value is then used in subsequent simulations to best-fit (using a least squares procedure) the experimental radon BTC to a simulated BTC corresponding to a particular value of R. For each simulated BTC, Eq. (4) is used to input the initial radon concentration in the model as a function of S n and K. The initial radon concentration can be inputted into the model as a homogeneous or heterogeneous distribution. Eq. (7) is then used to calculate the value of S n that corresponds to the best-fit R value. 3.6. PAM push–pull tests re-analysis The revised method was applied to existing radon and bromide extraction phase data from push–pull tests performed in wedge-shaped physical aquifer models (PAMs) by Davis et al. (2002). These push–pull tests were performed in clean sediment (Test 1) and TCE-contaminated sediment (Test 2), with the contaminated zone (S n ~ 2%) of Test 2 extending 74 cm from the narrow end of the PAM, beyond which S n = 0%. The tests were originally modeled by Davis et al. (2002) using normalized BTCs without the incorporation of initial radon concentrations in the model domain and the lack of NAPL saturation after 74 cm. This resulted in overestimates of R and the likely S n in the PAM (Table 1). Test 1 was modeled using the revised method, with an average initial radon concentration of 198 pCi/l (measured in four sampling ports in this PAM before the test). The bromide data are well fitted by a simulated R = 1 BTC, with a best-fit a L = 1.9 cm, and the radon data were fitted by a simulated R = 1.3 BTC (Fig. 6). Both the bromide and the radon simulations underestimate results during the early stages of extraction. This likely results from mixing processes not accounted for in the model. The radon retardation
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Table 1 Radon retardation factors (R), adjusted retardation factors for the effect of trapped gas (in italics), best-fit dispersivities (a L), and calculated TCE saturations (S n) from push–pull tests From Davis et al. (2002) (a L best-fit using approximate solution) Test 1, no TCE Test 2, with TCE
Using revised method (a L best-fit using STOMP)
R
a L (cm)
S n (%)
R
a L (cm)
S n (%)
1.1 5.1/5.0
3.2 4.0
– 7.4
1.3 2.2/1.9
1.9 3.7
– 1.8
Results from Davis et al. (2002) are shown on the left, while results using the revised method are shown on the right. A value of K = 50 was used to calculate S n in the presence of TCE.
in Test 1 is attributed to partitioning of radon between the trapped gas and aqueous phases, in analogy to what has been described for O2 by Fry et al. (1995): Hcc Sg R¼1þ ð9Þ Sw where H cc is radon’s dimensionless Henry’s coefficient and S g is the trapped gas saturation. Radon would show a BTC with R = 1, if (H cc(S g/S w)) = 0. Using Eq. (9), H cc = 3.9 (Clever, 1979), and R = 1.3, the estimated S g = 7.1%. These values are similar to those from Davis et al. (2002) (Table 1), who reported a best-fit a L = 3.2 cm, R = 1.1, and estimated S g ranging up to 9.3%. The best-fit R = 1.3 also compares favorably to the retardation factors measured in sampling ports 1 and 2 (located 15 and 30 cm from the narrow end of the PAM) during the injection phase of Test 1, which ranged from 1.0 to 1.4 (Davis et al., 2002). Similar values of trapped gas saturation were reported by Fry et al. (1995) for the same sediment material. Test 2 was also modeled using the revised method, with an average initial radon concentration of 262 pCi/l (measured in four sampling ports in this PAM prior to TCE contamination). A simulation was performed in which TCE contamination extended to 74 cm, with uncontaminated sediment at N74 cm. TCE was emplaced in the PAM (as 200
0 20
100
60 80
BrR=1 Rn R=1.3
100
0.0
0.5
1.0
1.5
Rn (pCi/L)
Br- (mg/L)
150 40
50
0 2.0
Ve/Vi Fig. 6. Radon (pCi/l) and bromide (mg/l) experimental and simulated (R = 1 and R = 1.3) breakthrough curves during the extraction phase of a push–pull test performed in a non-contaminated physical aquifer model (Test 1).
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described in Davis et al., 2002); then, Test 2 was performed after a 3-week static period allowed radon concentrations to reach N 95% of their secular equilibrium value as a result of concurrent radon emanation from sediment and decay. The bromide data are well fitted by a simulated R = 1 BTC and a L = 3.7 cm, and the radon data are fitted by a simulated R = 2.2 BTC (Fig. 7). The radon retardation in Test 2 is attributed to partitioning of radon between (1) the trapped gas and aqueous phases, and (2) the NAPL and aqueous phases. The portion of radon retardation due to TCE partitioning was determined by adjusting R to account for trapped gas partitioning using (Davis et al., 2002): Radj ¼ RTest 2 ðRTest 1 1:0Þ
ð10Þ
where R adj is the adjusted retardation factor, RTest 2 is the retardation factor from Test 2, and RTest 1 is the retardation factor from Test 1. Using Eq. (10), an adjusted R value of 1.9 is calculated, which results in an estimated S n = 1.8% (Table 1). The fitted a L = 3.7 cm compares favorably with the value of a L = 4.0 cm from Davis et al. (2002). Moreover, the estimated S n = 1.8% compares more favorably with the actual TCE saturation emplaced in the sediment pack (~2%) than the estimated S n = 7.4% from Davis et al. (2002) (using K = 50). The adjusted R = 1.9 compares favorably with the adjusted retardation factors measured in sampling ports 1 and 2 during the injection phase of Test 2, which ranged from 1.1 to 1.5 (Davis et al., 2002). Thus, the revised method results in better agreement of extraction and injection phase estimated R values and subsequent estimations of S n. The new estimate of S n = 1.8% is also in agreement with S n values ranging from 0.7% to 1.6% from partitioning alcohol push–pull tests performed in this PAM (Istok et al., 2002). 3.7. Field push–pull test application The revised method was also applied to radon and bromide BTCs from a field test performed at a former petroleum refinery in the Ohio River valley. As described in Davis 200
0 20
100
60 80
BrR=1 Rn R=2.2
100
0.0
0.5
1.0
1.5
Rn (pCi/L)
Br- (mg/L)
150 40
50
0 2.0
Ve/Vi Fig. 7. Radon (pCi/l) and bromide (mg/l) experimental and simulated (R = 1 and R = 2.2) breakthrough curves during the extraction phase of a push–pull test performed in a TCE-contaminated physical aquifer model (Test 2).
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101
et al. (2002) and Istok et al. (2002), the site consists of glacial outwash deposits that are contaminated with a mixture of petroleum light or LNAPLs including gasoline, heating oil, and jet and aviation fuel. Radon samples from a non-contaminated well showed a maximum concentration of 790 pCi/l. This value was used as the dbackgroundT concentration for radon. A push–pull test was performed in a contaminated well in which LNAPL has been detected. Radon concentrations increased and bromide concentrations decreased smoothly as the test solution/groundwater mixture was extracted from the aquifer, with the radon BTC being retarded relative to the bromide BTC (Fig. 8). Numerical simulations were performed for this test, with LNAPL assuming to extend far beyond the radius of influence of the test. The simulation results fit the bromide BTC to a simulated R = 1 BTC using a best-fit a L = 11 cm. This value is less than the value of a L = 20.3 cm from the approximate analytical solution used to fit the normalized bromide BTC by Davis et al. (2002), where the BTC was adjusted to intersect a normalized concentration of 0.5 at Ve /Vi = 1. Using the revised method and a L = 11 cm, the radon BTC was fit using a simulated R = 2.7 BTC. Using the R = 2.7, a value of S n = 4.1% was calculated using Eq. (7) and a value of K = 40 for radon in the presence of diesel fuel, as reported by Hunkeler et al. (1997). Davis et al. (2002) determined an R = 7.3 using the approximate analytical solution to the normalized radon BTC. That R value results in S n = 13.6%, which is likely an overestimation of LNAPL saturation. Istok et al. (2002) reported S n values of V 4.0% in this aquifer using partitioning alcohol tracers. The relatively poor fits of the simulated BTCs to the experimental BTCs likely are a result of heterogeneities in hydraulic conductivity and porosity in the aquifer and potential impacts of groundwater flow. In addition, the use of a K value for radon in the presence of diesel fuel adds uncertainty to the value of S n = 4.1%, since the actual LNAPL composition at the site is a mixture of LNAPLs. However, the method does provide a more accurate method to estimate the LNAPL saturation in the vicinity of the well compared to the results of Davis et al. (2002). Furthermore, a series of similar push–pull tests could be conducted in this well over time to track the efficacy of remediation and source zone removal. 800
Br- (mg/L)
20 BrR=1 Rn R=2.7
40
600
400
60 200
80 100 0.0
Rn (pCi/L)
0
0.5
1.0
1.5
0 2.0
Ve/Vi Fig. 8. Radon (pCi/l) and bromide (mg/l) experimental and simulated (R = 1 and R = 2.7) breakthrough curves during the extraction phase of a push–pull test performed in a LNAPL-contaminated aquifer.
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4. Conclusions The revised method enhances the ability of the radon push–pull test to provide estimates for S n at NAPL-contaminated sites. The effect of heterogeneity in S n on radon BTCs is lessened, and a greater sensitivity to smaller values of S n is realized. Also, the revised method more accurately represents the true condition of in situ radon partitioning both prior to and during the push–pull test. The method shows promise in providing estimates for S n and showing changes in S n over time as, for example, source zone remediation is effected. However, the revised method is potentially constrained by the need to obtain a dbackgroundT radon sample from a non-contaminated well in the contaminated aquifer. Geologic properties with respect to radon emanation and porosity must be similar between the contaminated and non-contaminated wells. This may or may not be the case at a field site. The collection of radon samples from additional noncontaminated wells emplaced in the NAPL-contaminated aquifer could provide a range of dbackgroundT values, which could be used in conjunction with the revised method to provide a range of estimated values of S n. The simulations presented represent conditions where radon emanation and decay are not important. Future modeling efforts should consider including these terms for conditions where they may be important. Also, it should be noted that estimated values of S n represent a volume-averaged value, and may or may not be representative of the true value of S n at a given location within the radius of influence of the push–pull test. These uncertainties highlight our view that push–pull test results provide an estimate of NAPL saturation in the immediate vicinity of the well in which the test was conducted. Acknowledgements This work was funded by the U.S. Department of Defense Environmental Security Technology Certification Program (project no. 199916) and the U.S. Department of Energy Environmental Management Science Program (project no. 60158). We also thank Jennifer Field, Ralph Reed, Jason Lee, Mike Cantaloub, and Melora Park for help with laboratory methods and activities; Mark Lyverse and Jesse Jones for help with field activities; Martin Schroth and Mark White for help with STOMP; and Dr. Eduard Hoehn, Dr. E.O. Frind, and an anonymous reviewer for their helpful comments and suggestions. References Annable, M.D., Rao, P.S.C., Hatfield, K., Graham, W.D., Wood, A.L., Enfield, C.G., 1998. Partitioning tracers for measuring residual NAPL: field-scale test results. J. Environ. Eng. 124, 498 – 503. Cantaloub, M., 2001. Aqueous–organic partition coefficients for radon-222 and their application to radon analysis by liquid scintillation methods. Master’s thesis, Oregon State University. Clever, H.L., 1979. Solubility Data Series, vol. 2. Pergamon Press, New York. Davis, B.M., Istok, J.D., Semprini, L., 2002. Push–pull partitioning tracer tests using radon-222 to quantify nonaqueous phase liquid contamination. J. Contam. Hydrol. 58, 129 – 146. Davis, B.M., Istok, J.D., Semprini, L., 2003. Static and push–pull methods using radon-222 to characterize dense nonaqueous phase liquid saturations. Ground Water 41, 470 – 481.
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Dwarakanath, V., Deeds, N., Pope, G.A., 1999. Analysis of partitioning interwell tracer tests. Environ. Sci. Technol. 33, 3829 – 3836. Fry, V.A., Istok, J.D., Semprini, L., O’Reilly, K.T., Buscheck, T.E., 1995. Retardation of dissolved oxygen due to a trapped gas in porous media. Ground Water 33, 391 – 398. Hunkeler, D., Hoehn, E., Ho¨hener, P., Zeyer, J., 1997. 222-Rn as a partitioning tracer to detect diesel fuel contamination in aquifers: laboratory study and field observations. Environ. Sci. Technol. 31, 3180 – 3187. Istok, J.D., Field, J.A., Schroth, M.H., Davis, B.M., Dwarakanath, V., 2002. Single-well bpush–pullQ tracer test for NAPL detection in the subsurface. Environ. Sci. Technol. 36, 2708 – 2716. Jin, M., Delshad, M., Dwarakanath, V., McKinney, D.C., Pope, G.A., Sepehrnoori, K., Tilburg, C.E., Jackson, R.E., 1995. Partitioning tracer test for detection, estimation, and remediation performance assessment of subsurface nonaqueous phase liquids. Water Resour. Res. 31, 1201 – 1211. Lindsey, K.A., Jaeger, G.K., 1993. Geologic setting of the 100-HR-3 operable unit, Hanford site, south-central Washington. WHC-SD-EN-TI-132, Rev. 0, Westinghouse Hanford Company, Richland, WA. Nelson, N.T., Brusseau, M.L., 1996. Field study of the partitioning tracer method for detection of dense nonaqueous phase liquid in a trichloroethene-contaminated aquifer. Environ. Sci. Technol. 30, 2859 – 2863. Nelson, N.T., Oostrom, M., Wietsma, T.W., Brusseau, M.L., 1999. Partitioning tracer method for the in situ measurement of DNAPL saturation: influence of heterogeneity and sampling method. Environ. Sci. Technol. 33, 4046 – 4053. Nichols, W.E., Aimo, N.J., Oostrom, M., White, M.D., 1997. STOMP: Subsurface Transport Over Multiple Phases, Application Guide. PNNL-11216, Richland, WA. Schroth, M.H., Istok, J.D., Haggerty, R., 2000. In situ evaluation of solute retardation using single-well push–pull tests. Adv. Water Resour. 24, 105 – 117. Semprini, L., Broholm, K., McDonald, M., 1993. Radon-222 deficit for locating and quantifying NAPL contamination in the subsurface. Abstr., EOS Trans. Am. Geophys. Union 76, F276. Semprini, L., Cantaloub, M., Gottipati, S., Hopkins, O., Istok, J., 1998. Radon-222 as a tracer for quantifying and monitoring NAPL remediation. In: Wickramanayake, G.B., Hinchee, R.E. (Eds.), Nonaqueous-Phase Liquids. Battelle Press, Columbus, OH, pp. 137 – 142. Semprini, L., Hopkins, O.S., Tasker, B.R., 2000. Laboratory, field and modeling studies of radon-222 as a natural tracer for monitoring NAPL contamination. Transp. Porous Media 38, 223 – 240. White, M.D., Oostrom, M., 2000. STOMP: Subsurface Transport Over Multiple Phases, Version 2.0, User’s Guide. PNNL-12034, Richland, WA. Young, C.M., Jackson, R.E., Jin, M., Londergan, J.T., Mariner, P.E., Pope, G.A., Anderson, F.J., Houk, T., 1999. Characterization of a TCE NAPL zone in alluvium by partitioning tracers. Ground Water Monit. Remediat. 19, 84 – 94.
Numerical simulations of radon as an in situ partitioning tracer for quantifying NAPL contamination using push–pull tests B.M. Davisa,*, J.D. Istokb,1, L. Semprinib,1 a
ChevronTexaco Energy Technology Co., PO Box 1627, 100 Chevron Way, Richmond, CA 94802, USA b Department of Civil, Construction and Environmental Engineering, Oregon State University, Corvallis, OR 97331, USA Received 6 October 2003; received in revised form 24 March 2005; accepted 31 March 2005
Abstract Presented here is a reanalysis of results previously presented by Davis et al. (2002) [Davis, B.M., Istok, J.D., Semprini, L., 2002. Push–pull partitioning tracer tests using radon-222 to quantify nonaqueous phase liquid contamination. J. Contam. Hydrol. 58, 129–146] of push–pull tests using radon as a naturally occurring partitioning tracer for evaluating NAPL contamination. In a push–pull test where radon-free water and bromide are injected, the presence of NAPL is manifested in greater dispersion of the radon breakthrough curve (BTC) relative to the bromide BTC during the extraction phase as a result of radon partitioning into the NAPL. Laboratory push–pull tests in a dense or DNAPL-contaminated physical aquifer model (PAM) indicated that the previously used modeling approach resulted in an overestimation of the DNAPL (trichloroethene) saturation (S n). The numerical simulations presented here investigated the influence of (1) initial radon concentrations, which vary as a function of S n, and (2) heterogeneity in S n distribution within the radius of influence of the push–pull test. The simulations showed that these factors influence radon BTCs and resulting estimates of S n. A revised method of interpreting radon BTCs is presented here, which takes into account initial radon concentrations and uses non-normalized radon BTCs. This revised method produces greater radon BTC sensitivity at small values of S n and was used to re-analyze the results from the PAM push–pull tests reported by Davis et al. The re-analysis resulted in a more accurate * Corresponding author. Fax: +1 510 242 1380. E-mail addresses: [email protected] (B.M. Davis), [email protected] (J.D. Istok), [email protected] (L. Semprini). 1 Fax: +1 541 737 3099. 0169-7722/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jconhyd.2005.03.003
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estimate of S n (1.8%) compared with the previously estimated value (7.4%). The revised method was then applied to results from a push–pull test conducted in a light or LNAPL-contaminated aquifer at a field site, resulting in a more accurate estimate of S n (4.1%) compared with a previously estimated value (13.6%). The revised method improves upon the efficacy of the radon push–pull test to estimate NAPL saturations. A limitation of the revised method is that dbackgroundT radon concentrations from a non-contaminated well in the NAPL-contaminated aquifer are needed to accurately estimate NAPL saturation. The method has potential as a means of monitoring the progress of NAPL remediation. D 2005 Elsevier B.V. All rights reserved. Keywords: NAPL; Tracers; Partitioning; Single-well tests; Radon
1. Introduction Partitioning interwell tracer tests have been used to quantify nonaqueous phase liquid (NAPL) saturations in laboratory and field settings of saturated groundwater flow (Jin et al., 1995; Nelson and Brusseau, 1996; Annable et al., 1998; Nelson et al., 1999; Young et al., 1999). Recently, single-well dpush–pullT partitioning tracer tests have been used to quantify NAPL saturations (Davis et al., 2002, 2003; Istok et al., 2002). In a push–pull test, an injection solution containing partitioning and conservative tracers is injected (dpushedT) into an aquifer through a well. The solution/groundwater mixture is then extracted (dpulledT) from the same well. These tests have involved the use of both dex situT (i.e., injected) and din situT (i.e., naturally occurring radon) partitioning tracers. For the ex situ tracer method, partitioning and conservative (e.g., bromide) tracers are injected into the aquifer, while for the in situ tracer method, a radon-free injection solution (containing a conservative bromide tracer) is injected into the aquifer. In both cases, the presence of NAPL is indicated by a greater dispersion of the extraction phase breakthrough curve (BTC) for the partitioning tracer relative to a conservative tracer (Schroth et al., 2000). In situ radon that is generated by aquifer solids (t 1/2 = 3.83 days) has been used as a partitioning tracer for locating and quantifying dense or DNAPL saturation (Semprini et al., 1993, 1998, 2000; Davis et al., 2002, 2003) and light or LNAPL saturation (Hunkeler et al., 1997; Davis et al., 2002). The steady-state or dbackgroundT radon concentration in groundwater (C w,bkg) is a function of the radium content (C Ra, mass/mass) and radon emanation power (E p, unitless) of the aquifer solids and the bulk density (q b) and porosity (n) of the aquifer as described by (Semprini et al., 2000): Cw;bkg ¼
CRa Ep qb n
ð1Þ
Model equations for the equilibrium partitioning of radon and the secular equilibrium that is achieved between radon emanation and decay are provided by Semprini et al. (2000) and Davis et al. (2002). The models are based on linear partitioning, with the partition coefficient (K) for radon defined as: K¼
Cn Cw;n
ð2Þ
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where C n is the concentration of radon in the NAPL, and C w,n is the concentration of radon in the aqueous phase in the presence of NAPL. Partition coefficients may be determined using the methodology of Cantaloub (2001) and range from 37 (o-xylene) to 50 (trichloroethene, or TCE) to 61 (cyclohexane). As groundwater flows through a NAPLcontaminated zone of an aquifer, radon in NAPL will obtain a concentration in equilibrium with radon in groundwater. Because radon is continually being generated by aquifer solids and is continually decaying, and because groundwater flow is typically slow, a closedsystem equilibrium equation (Eq. (3)) describes radon concentrations in water and NAPL. Model simulations by Semprini et al. (2000) show that if transport through the NAPLcontaminated zone is long enough for equilibrium to be achieved, radon concentrations can be described by Eq. (3): Cn Sn þ Cw;n Sw ¼ Cw;bkg
ð3Þ
Based on linear radon partitioning between NAPL and water (Eq. (2)), radon concentration in the water phase is given by a rearranged Eq. (3): Cw;n ¼
Cw;bkg 1 þ S n ð K 1Þ
ð4Þ
where C w,n is a non-linear function of S n and K. This non-linear relationship is shown in Fig. 1, using a K = 50. Eq. (4) can be further rearranged to solve for the NAPL saturation in an aquifer as a function of C w,bkg, C w,n, and K: Cw;bkg 1 Sn ¼ 1 ð5Þ ð K 1Þ Cw;n Note that Eq. (5) does not require estimation of radon retardation (R) via a push–pull test in order to calculate S n. However, radon retardation during transport can be used to 200
Cw,n (pCi/L)
150
100
50
0 0
5
10
15
20
Sn (%) Fig. 1. Aqueous phase radon concentrations (C w,n) as a function of NAPL saturation, plotted using Eq. (3) with a background radon concentration (C w,bkg) = 200 pCi/l and K = 50.
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determine NAPL saturation. The retardation factor for a partitioning tracer is given by (Dwarakanath et al., 1999): R¼1þ
KSn Sw
ð6Þ
If K is known and R is estimated using a push–pull test, S n can be determined using: Sn ¼
R1 RþK1
ð7Þ
Push–pull tests using radon as a partitioning tracer were performed in laboratory physical aquifer models (PAMs) containing TCE (Davis et al., 2002). Experimental conservative (bromide) tracer and radon extraction phase BTCs were fitted to an approximate analytical solution to estimate R, which was then used to calculate S n. This approach resulted in an overestimation of S n compared to the NAPL saturation emplaced in the PAM. Furthermore, the numerical modeling in Davis et al. (2002) assumed that radon behaved similarly to an injected tracer. Although these simulations accounted for radon partitioning between the NAPL and aqueous phases during the push–pull test, they did not account for steady-state radon partitioning into NAPL prior to the test. The pre-test radon concentrations are in fact reduced in the presence of NAPL, with the steady-state radon concentration being a non-linear function of S n (Eq. (4)). Also, the model construct did not agree with the actual conditions in the PAM. For example, the model assumed that NAPL was distributed throughout the PAM sediment, while in the laboratory push–pull tests, the NAPLcontaminated zone existed in only part of the PAM’s sediment. The heterogeneous NAPL distribution will affect initial radon concentrations and partitioning behavior during the push–pull test. As will be shown, this heterogeneous distribution can affect estimations of R and S n. The goal of this study was to examine two factors that can influence the interpretation of push–pull tests for estimating S n: (1) the influence of NAPL on initial (i.e., preinjection) phase radon concentrations, and (2) heterogeneous NAPL saturation distributions. A revised method of interpreting radon BTCs is presented, which results in more accurate estimates of S n and in an increase in sensitivity of the estimation method at small values of S n. This method was then used to re-estimate values of S n in previously conducted laboratory and field push–pull tests.
2. Methods Simulations were performed with the STOMP code (White and Oostrom, 2000), a fully implicit volume-integrated finite difference simulator for modeling one-, two-, and threedimensional groundwater flow and transport. The simulator models the advective/ dispersive equation, with linear equilibrium partitioning. STOMP has been extensively tested and validated against analytical solutions and other numerical codes (Nichols et al., 1997). Simulations were based on a hypothetical push–pull test conducted in a 5 cm
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diameter well over a 91.4 cm long screened interval of an aquifer. The model aquifer is based on an aquifer composed of sediment from the Hanford Formation, an alluvial deposit of sands and gravels of mixed basaltic and granitic origin (Lindsey and Jaeger, 1993) previously used in laboratory push–pull tests. Solid density (q s) = 2.9 g/cm3, porosity (n) = 0.35, calculated bulk density (q b) = 1.89 g/cm3, and longitudinal dispersivity (a L) = 4.0 cm were used in all the simulations. Simulations incorporated an injection volume of 250 l and an extraction volume ranging from 500 to 2000 l. Injection and extraction pumping rates were constant at 1 l/min with no rest period between the injection and extraction phases. The computational domain consisted of a line of 500 nodes with a uniform radial node spacing of Dr = 1.0 cm. The model geometry and injection volumes resulted in the injection solution traveling 48 cm from the well, as measured by the travel distance to half the solution injection concentration of the conservative tracer (C/C 0 = 0.5). Simulations were performed using time-varying third-type flux boundary conditions to represent pumping at the well, with a constant hydraulic head. Constant head and zero solute flux boundary conditions were used to represent aquifer conditions at r = 500 cm. Specified NAPL saturations were modeled using TCE with a value of K = 50 for radon (Davis et al., 2003). To simplify the modeling procedure, NAPL saturations (S n) were incorporated into the model using solid:aqueous phase partition coefficients, which enabled the model to mimic radon partitioning into NAPL as radon partitioning into aquifer solids. These two partitioning processes are similar for radon. First, Eq. (6) was used to determine a retardation factor (R) for a given ratio of S n to water saturation (S w). Second, this calculated R value, the sediment porosity, and the bulk density were used to determine a solid:aqueous phase partition coefficient (K d): n Kd ¼ ð R 1Þ ð8Þ qb Simulations were performed with specified S n values from 0% to 15.25%, which corresponds to retardation factors (R) ranging from 1 to 10, respectively. The effects of initial radon concentrations and S n heterogeneity on simulation results were investigated with three sets of simulations, with NAPL extending homogeneously from (1) r = 500 cm, (2) r = 48 cm (corresponding to the maximum travel radius of a conservatively transported tracer, as defined by C/C 0 = 0.5), and (3) r = 24 cm (corresponding to half the maximum travel radius of a conservatively transported tracer), where r is the radial distance from the injection/extraction well. An initial radon concentration of 200 pCi/ l (corresponding to S n = 0%) was emplaced at r N 48 cm for the second set of simulations and at r N 24 cm for the third set of simulations. Each simulation utilized (1) an injection radon concentration of 0 pCi/l, which corresponds to the true radon injection concentration in laboratory and field push–pull tests, and (2) an initial radon concentration in the model that varied in space as a function of S n. The simulations involving the PAM and field tests are described below. All simulations and PAM and field push–pull tests were performed over time periods such that the effects of radon emanation and decay on radon concentrations could be neglected (i.e., Ve/Vi = 2 was obtained in V 12.5 h, where Vi is the volume of solution injected and Ve is the volume of solution extracted at a given time).
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3. Results and discussion 3.1. Injection phase results Fig. 2 shows radon concentration spatial profiles at the end of the injection phase of a simulated push–pull test (corresponding to Ve /Vi = 0) for S n values of 0–4% and for different distributions of NAPL. When S n = 0%, the radon-free injection solution is transported to r = 48 cm, as measured by half the initial radon concentration (C/C 0 = 0.5) at the injection well (i.e., one manner in which to measure transport distance). In contrast, when S n p 0% over a specified portion of the model domain, radon is retarded. When S n = 4% for r V 500 cm (i.e., a homogeneous NAPL distribution) and the initial radon concentration in the model is 68 pCi/l (Eq. (4)), the radon-free injection solution is transported only to r = 26 cm, as measured by half the initial radon concentration at the injection well, due to retardation resulting from radon partitioning into the NAPL during transport. When S n = 4% for r V 48 cm and S n = 0% for r N 48 cm (i.e., a heterogeneous NAPL distribution), the injection solution is again transported only to r = 26 cm. A twostep radon concentration profile results from this heterogeneous NAPL distribution. When S n = 4% for r V 24 cm and S n = 0% for r N 24 cm, the radon-free injection solution is retarded as indicated by the profile, but the concentration increases rapidly as the radial distance increases. Thus, when the portion of the model domain containing NAPL decreases, the profiles tend towards the zero saturation case. Radon concentration profiles are influenced by both radon partitioning between the aqueous phase and NAPL prior to the push–pull test, and radon partitioning between the injection solution and NAPL during the test. Heterogeneity in NAPL distribution affects radon concentration profiles due to the partitioning processes and mixing of water with different initial radon concentrations during the test.
200 Sn=4% to 500cm Sn=4% to 48cm Sn=4% to 24cm
Cw,n (pCi/L)
150
Sn=0% to 500cm
100
50
0 0
20
40
60
80
100
radial distance (cm) Fig. 2. Simulated radon concentration profiles (C w,n) at the end of the injection phase of push–pull tests with no NAPL (S n = 0% to 500 cm); heterogeneous NAPL saturation (S n = 4% to 48 cm) and (S n = 4% to 24 cm); and homogeneous NAPL saturation (S n = 4% to 500 cm).
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3.2. Extraction results—concentration profiles 3.2.1. Radon concentration profiles for different degrees of fluid extraction Simulated radon concentration profiles as a function of the volume of groundwater extracted are presented in Fig. 3. Note that the volume of injection solution/groundwater extracted (Ve) is divided by the total volume of injection solution injected (at the end of the injection phase, Vi) to calculate dimensionless time (Ve/Vi) during the extraction phase. For the case of S n = 4% for r V 500 cm (i.e., a homogeneous NAPL distribution), radon concentrations increase with time as the injection solution/groundwater mixture is extracted from the well (Fig. 3a). The initial radon equilibrium concentration was 68 pCi/l for r V 500 cm (Eq. (4)). The radon concentration at the well (r = 0 cm) is 63% of the initial radon concentration at Ve/Vi = 1, 89% at Ve/Vi = 2, and 96% at Ve/Vi = 3. Thus, as extraction proceeds, radon concentrations approach but do not exceed the initial radon concentration. Profiles for a heterogeneous NAPL distribution when S n = 4% for r V 48 cm and S n = 0% for r N 48 cm are shown in Fig. 3b. The initial equilibrium radon concentration was 68 pCi/l for r V 48 cm and 200 pCi/l for r N 48 cm (shown with a step-function concentration change for simplicity). The radon concentration measured at the well (r = 0 cm) is 63% of the initial radon concentration at Ve /Vi = 1, 103% at 2, and 153% at 3, and increases to 291% at 8. As the extraction proceeds, radon concentrations at the well exceed the initial radon concentration due to the influx of water with a radon concentration of 200 pCi/l. Such a response in push–pull tests might be utilized in identifying heterogeneous NAPL distributions. Fig. 3c shows the profiles that result from the heterogeneous distribution when S n = 4% for r V 24 cm and S n = 0% for r N 24 cm. Radon concentrations increase more quickly with time as the injection solution/groundwater mixture is extracted from the well compared to the previous simulation. Radon concentrations at the well exceed the initial radon concentration at the well after just Ve/Vi = 1 due to the influx of water with a radon concentration of 200 pCi/l. Thus, as NAPL is concentrated closer to the well, radon concentrations more rapidly exceed initial values at the well as the extraction phase proceeds. Conversely, if NAPL saturations are distributed farther from the well, radon concentrations would possibly not approach initial values at the well. 3.3. Extraction phase results—breakthrough curves Usually the only radon concentration data available at field sites are obtained from the well in which the push–pull test is conducted. To investigate radon BTC behavior, a set of six simulations was performed for each of the homogeneous and heterogeneous NAPL distributions. Simulations performed for the homogeneous NAPL distribution are presented in Fig. 4a, while those for the heterogeneous NAPL distributions are presented in Fig. 4b and c. Each simulation represented a different value of S n. For homogeneous NAPL distributions (Fig. 4a), as the extraction phase approaches Ve /Vi = 2, radon concentrations approach but do not exceed their initial value at the well. Radon concentrations approach initial values at the well more slowly as S n increases due to the
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(a)
200 initial conditions Ve/Vi = 0 Ve/Vi = 1
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Ve/Vi = 2 Ve/Vi = 4
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radial distance (cm)
(b)
200
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initial Ve/Vi = 0
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Ve/Vi = 4 Ve/Vi = 6 Ve/Vi = 8
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radial distance (cm)
(c)
200
Cw,n (pCi/L)
150 initial Ve/Vi = 0
100
Ve/Vi = 1 Ve/Vi = 2
50
Ve/Vi = 4 Ve/Vi = 6 Ve/Vi = 8
0 0
20
40
60
80
100
radial distance (cm) Fig. 3. Simulated radon concentration profiles (C w,n) during the extraction phase of a push–pull test. (a) S n = 4% for r V 500 cm; (b) S n = 4% for r V 48 cm; S n = 0% for r N 48 cm; (c) S n = 4% for r V 24 cm; S n = 0% for r N 24 cm.
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(a) 200 Sn=0%,R=1
Sn=1.96%,R=2
Cw,n (pCi/L)
150
Sn=5.66%,R=4 Sn=9.09%,R=6 Sn=12.28%,R=8 Sn=15.25%,R=10
100
50
0 0.0
0.5
1.0
1.5
2.0
1.5
2.0
1.5
2.0
Ve/Vi
(b) 200 Sn=0%,R=1
Sn=1.96%,R=2
Cw,n (pCi/L)
150
Sn=5.66%,R=4 Sn=9.09%,R=6 Sn=12.28%,R=8 Sn=15.25%,R=10
100
50
0 0.0
0.5
1.0
Ve/Vi
(c)
200 Sn=0%,R=1
Sn=1.96%,R=2
Cw,n (pCi/L)
150
Sn=5.66%,R=4 Sn=9.09%,R=6 Sn=12.28%,R=8 Sn=15.25%,R=10
100
50
0 0.0
0.5
1.0
Ve/Vi Fig. 4. Simulated radon breakthrough curves during the extraction phases of six push–pull tests. (a) S n = 0– 15.25% for r V 500 cm; (b) S n = 0–15.25% for r V 48 cm; S n = 0% for r N 48 cm; (c) S n = 0–15.25% for r V 24 cm; S n = 0% for r N 24 cm.
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increase in dispersion of the radon BTC (Schroth et al., 2000). Radon BTCs show the greatest sensitivity at small values of S n, which is due to the non-linear relationship between S n and the initial radon concentration. The simulations performed for a heterogeneous NAPL distribution (S n for r V 48 cm and S n = 0% for r N 48 cm) are presented in Fig. 4b. As the extraction phase approaches Ve / Vi = 2, radon concentrations approach their initial value at the well. Radon concentrations would increase beyond the initial radon concentration for S n N 0% if Ve /Vi progressed beyond 2. However, the shapes of the radon BTCs are similar at early times for the two sets of simulations (Fig. 4a and b), since conditions close to the well dominate the response. The third set of six simulations performed with the heterogeneous NAPL distribution (S n for r V 24 cm and S n = 0% for r N 24 cm) are presented in Fig. 4c. As the extraction phase reaches Ve /Vi = 2, radon concentrations approach and exceed their initial value at the well to a greater degree than when NAPL extended to 48 cm. These percentages vary as a function of S n, reaching 165% of the initial value at the well for S n = 1.96%, 239% for S n = 5.66%, and 189% for S n = 15.25%. The presence of S n = 0% for r N 24 cm produces greater radon concentrations for each simulation as compared to the prior simulations. Radon concentrations would continue to increase beyond the initial radon concentration for S n N 0% if Ve/Vi progressed beyond 2. The S n = 0% at r N 24 cm results in greater slopes for radon BTCs compared to the previous simulations (Fig. 4a and b). The shape of the radon BTCs, especially at late time, can be potentially used to investigate heterogeneity in NAPL distribution. 3.4. Extraction phase results—normalized breakthrough curves Fig. 5 presents the extraction phase normalized BTCs for the results presented in Fig. 4. Radon concentrations are normalized to the initial concentrations at the well prior to the injection phase. For the homogenous NAPL distribution, the normalized concentration does not exceed 1 at Ve/Vi = 2 (Fig. 5a). The effect of increasing dispersion as S n increases is apparent (Schroth et al., 2000). A drawback to normalizing to the initial radon concentration is the decrease in sensitivity of the radon BTCs to small values of S n compared to the non-normalized method (Fig. 4a). This drawback is a concern when fitting experimental radon BTCs to simulated BTCs in order to determine a best-fit value of R in order to estimate S n. The normalized BTC for the heterogeneous NAPL distribution where S n = 0% for r N 48 cm deviates from the homogenous cases as the extraction volume increases (Fig. 5b). The deviation becomes even more pronounced when normalized radon BTCs deviate from those for the heterogeneous NAPL distribution S n = 0% for r N 24 cm (Fig. 5c). Thus, the interpretation of normalized radon BTCs becomes more difficult as heterogeneity in S n increases. Fig. 5. Simulated radon breakthrough curves during the extraction phases of six push–pull tests. Radon concentrations are normalized to the initial radon concentrations at the well for each value of S n. (a) S n = 0 –15.25% for r V 500 cm; (b) S n = 0 –15.25% for r V 48 cm; S n = 0% for r N 48 cm); (c) S n = 0 –15.25% for r V 24 cm; S n = 0% for r N 24 cm.
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Normalized Cw,n
(a)
1.0 0.8 0.6 Sn=0%,R=1
0.4
Sn=1.96%,R=2 Sn=5.66%,R=4 Sn=9.09%,R=6
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3.5. Revised method for radon BTC interpretation The use of non-normalized radon BTCs to estimate S n provides two advantages over normalized radon BTCs in that (1) the sensitivity of non-normalized radon BTCs to small values of S n can be utilized, and (2) the effect of heterogeneity in S n on the shape of radon BTCs can be lessened. The revised method for estimating S n utilizing non-normalized radon BTCs requires obtaining a dbackgroundT radon concentration (C w,bkg) from a noncontaminated portion of the contaminated aquifer. Using this sample as a dbackgroundT concentration assumes homogeneity in porosity and radon emanation between the noncontaminated location chosen for the dbackgroundT radon sample and the location with suspected NAPL contamination where the push–pull test is conducted. To use this revised method extraction phase, radon and bromide results are plotted in concentration units (pCi/ l for Rn and mg/l for Br) as a function of Ve /Vi. The y-axis of the plot shows radon concentrations ranging from 0 at the origin to a maximum value equal to the dbackgroundT concentration. Bromide concentrations are plotted on a secondary y-axis with concentrations ranging from the injection solution concentration to 0 mg/l, the injection solution concentration at the origin, and 0 mg/l at the maximum or dbackgroundT radon concentration. This inverts the bromide concentrations and causes the radon and bromide BTCs to overlap. Numerical simulations are then performed to best-fit (using a least squares procedure) the experimental bromide BTC to a non-retarded simulated BTC (i.e., with R = 1) by varying the sediment dispersivity (a L). The best-fit a L value is then used in subsequent simulations to best-fit (using a least squares procedure) the experimental radon BTC to a simulated BTC corresponding to a particular value of R. For each simulated BTC, Eq. (4) is used to input the initial radon concentration in the model as a function of S n and K. The initial radon concentration can be inputted into the model as a homogeneous or heterogeneous distribution. Eq. (7) is then used to calculate the value of S n that corresponds to the best-fit R value. 3.6. PAM push–pull tests re-analysis The revised method was applied to existing radon and bromide extraction phase data from push–pull tests performed in wedge-shaped physical aquifer models (PAMs) by Davis et al. (2002). These push–pull tests were performed in clean sediment (Test 1) and TCE-contaminated sediment (Test 2), with the contaminated zone (S n ~ 2%) of Test 2 extending 74 cm from the narrow end of the PAM, beyond which S n = 0%. The tests were originally modeled by Davis et al. (2002) using normalized BTCs without the incorporation of initial radon concentrations in the model domain and the lack of NAPL saturation after 74 cm. This resulted in overestimates of R and the likely S n in the PAM (Table 1). Test 1 was modeled using the revised method, with an average initial radon concentration of 198 pCi/l (measured in four sampling ports in this PAM before the test). The bromide data are well fitted by a simulated R = 1 BTC, with a best-fit a L = 1.9 cm, and the radon data were fitted by a simulated R = 1.3 BTC (Fig. 6). Both the bromide and the radon simulations underestimate results during the early stages of extraction. This likely results from mixing processes not accounted for in the model. The radon retardation
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Table 1 Radon retardation factors (R), adjusted retardation factors for the effect of trapped gas (in italics), best-fit dispersivities (a L), and calculated TCE saturations (S n) from push–pull tests From Davis et al. (2002) (a L best-fit using approximate solution) Test 1, no TCE Test 2, with TCE
Using revised method (a L best-fit using STOMP)
R
a L (cm)
S n (%)
R
a L (cm)
S n (%)
1.1 5.1/5.0
3.2 4.0
– 7.4
1.3 2.2/1.9
1.9 3.7
– 1.8
Results from Davis et al. (2002) are shown on the left, while results using the revised method are shown on the right. A value of K = 50 was used to calculate S n in the presence of TCE.
in Test 1 is attributed to partitioning of radon between the trapped gas and aqueous phases, in analogy to what has been described for O2 by Fry et al. (1995): Hcc Sg R¼1þ ð9Þ Sw where H cc is radon’s dimensionless Henry’s coefficient and S g is the trapped gas saturation. Radon would show a BTC with R = 1, if (H cc(S g/S w)) = 0. Using Eq. (9), H cc = 3.9 (Clever, 1979), and R = 1.3, the estimated S g = 7.1%. These values are similar to those from Davis et al. (2002) (Table 1), who reported a best-fit a L = 3.2 cm, R = 1.1, and estimated S g ranging up to 9.3%. The best-fit R = 1.3 also compares favorably to the retardation factors measured in sampling ports 1 and 2 (located 15 and 30 cm from the narrow end of the PAM) during the injection phase of Test 1, which ranged from 1.0 to 1.4 (Davis et al., 2002). Similar values of trapped gas saturation were reported by Fry et al. (1995) for the same sediment material. Test 2 was also modeled using the revised method, with an average initial radon concentration of 262 pCi/l (measured in four sampling ports in this PAM prior to TCE contamination). A simulation was performed in which TCE contamination extended to 74 cm, with uncontaminated sediment at N74 cm. TCE was emplaced in the PAM (as 200
0 20
100
60 80
BrR=1 Rn R=1.3
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0.0
0.5
1.0
1.5
Rn (pCi/L)
Br- (mg/L)
150 40
50
0 2.0
Ve/Vi Fig. 6. Radon (pCi/l) and bromide (mg/l) experimental and simulated (R = 1 and R = 1.3) breakthrough curves during the extraction phase of a push–pull test performed in a non-contaminated physical aquifer model (Test 1).
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described in Davis et al., 2002); then, Test 2 was performed after a 3-week static period allowed radon concentrations to reach N 95% of their secular equilibrium value as a result of concurrent radon emanation from sediment and decay. The bromide data are well fitted by a simulated R = 1 BTC and a L = 3.7 cm, and the radon data are fitted by a simulated R = 2.2 BTC (Fig. 7). The radon retardation in Test 2 is attributed to partitioning of radon between (1) the trapped gas and aqueous phases, and (2) the NAPL and aqueous phases. The portion of radon retardation due to TCE partitioning was determined by adjusting R to account for trapped gas partitioning using (Davis et al., 2002): Radj ¼ RTest 2 ðRTest 1 1:0Þ
ð10Þ
where R adj is the adjusted retardation factor, RTest 2 is the retardation factor from Test 2, and RTest 1 is the retardation factor from Test 1. Using Eq. (10), an adjusted R value of 1.9 is calculated, which results in an estimated S n = 1.8% (Table 1). The fitted a L = 3.7 cm compares favorably with the value of a L = 4.0 cm from Davis et al. (2002). Moreover, the estimated S n = 1.8% compares more favorably with the actual TCE saturation emplaced in the sediment pack (~2%) than the estimated S n = 7.4% from Davis et al. (2002) (using K = 50). The adjusted R = 1.9 compares favorably with the adjusted retardation factors measured in sampling ports 1 and 2 during the injection phase of Test 2, which ranged from 1.1 to 1.5 (Davis et al., 2002). Thus, the revised method results in better agreement of extraction and injection phase estimated R values and subsequent estimations of S n. The new estimate of S n = 1.8% is also in agreement with S n values ranging from 0.7% to 1.6% from partitioning alcohol push–pull tests performed in this PAM (Istok et al., 2002). 3.7. Field push–pull test application The revised method was also applied to radon and bromide BTCs from a field test performed at a former petroleum refinery in the Ohio River valley. As described in Davis 200
0 20
100
60 80
BrR=1 Rn R=2.2
100
0.0
0.5
1.0
1.5
Rn (pCi/L)
Br- (mg/L)
150 40
50
0 2.0
Ve/Vi Fig. 7. Radon (pCi/l) and bromide (mg/l) experimental and simulated (R = 1 and R = 2.2) breakthrough curves during the extraction phase of a push–pull test performed in a TCE-contaminated physical aquifer model (Test 2).
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et al. (2002) and Istok et al. (2002), the site consists of glacial outwash deposits that are contaminated with a mixture of petroleum light or LNAPLs including gasoline, heating oil, and jet and aviation fuel. Radon samples from a non-contaminated well showed a maximum concentration of 790 pCi/l. This value was used as the dbackgroundT concentration for radon. A push–pull test was performed in a contaminated well in which LNAPL has been detected. Radon concentrations increased and bromide concentrations decreased smoothly as the test solution/groundwater mixture was extracted from the aquifer, with the radon BTC being retarded relative to the bromide BTC (Fig. 8). Numerical simulations were performed for this test, with LNAPL assuming to extend far beyond the radius of influence of the test. The simulation results fit the bromide BTC to a simulated R = 1 BTC using a best-fit a L = 11 cm. This value is less than the value of a L = 20.3 cm from the approximate analytical solution used to fit the normalized bromide BTC by Davis et al. (2002), where the BTC was adjusted to intersect a normalized concentration of 0.5 at Ve /Vi = 1. Using the revised method and a L = 11 cm, the radon BTC was fit using a simulated R = 2.7 BTC. Using the R = 2.7, a value of S n = 4.1% was calculated using Eq. (7) and a value of K = 40 for radon in the presence of diesel fuel, as reported by Hunkeler et al. (1997). Davis et al. (2002) determined an R = 7.3 using the approximate analytical solution to the normalized radon BTC. That R value results in S n = 13.6%, which is likely an overestimation of LNAPL saturation. Istok et al. (2002) reported S n values of V 4.0% in this aquifer using partitioning alcohol tracers. The relatively poor fits of the simulated BTCs to the experimental BTCs likely are a result of heterogeneities in hydraulic conductivity and porosity in the aquifer and potential impacts of groundwater flow. In addition, the use of a K value for radon in the presence of diesel fuel adds uncertainty to the value of S n = 4.1%, since the actual LNAPL composition at the site is a mixture of LNAPLs. However, the method does provide a more accurate method to estimate the LNAPL saturation in the vicinity of the well compared to the results of Davis et al. (2002). Furthermore, a series of similar push–pull tests could be conducted in this well over time to track the efficacy of remediation and source zone removal. 800
Br- (mg/L)
20 BrR=1 Rn R=2.7
40
600
400
60 200
80 100 0.0
Rn (pCi/L)
0
0.5
1.0
1.5
0 2.0
Ve/Vi Fig. 8. Radon (pCi/l) and bromide (mg/l) experimental and simulated (R = 1 and R = 2.7) breakthrough curves during the extraction phase of a push–pull test performed in a LNAPL-contaminated aquifer.
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4. Conclusions The revised method enhances the ability of the radon push–pull test to provide estimates for S n at NAPL-contaminated sites. The effect of heterogeneity in S n on radon BTCs is lessened, and a greater sensitivity to smaller values of S n is realized. Also, the revised method more accurately represents the true condition of in situ radon partitioning both prior to and during the push–pull test. The method shows promise in providing estimates for S n and showing changes in S n over time as, for example, source zone remediation is effected. However, the revised method is potentially constrained by the need to obtain a dbackgroundT radon sample from a non-contaminated well in the contaminated aquifer. Geologic properties with respect to radon emanation and porosity must be similar between the contaminated and non-contaminated wells. This may or may not be the case at a field site. The collection of radon samples from additional noncontaminated wells emplaced in the NAPL-contaminated aquifer could provide a range of dbackgroundT values, which could be used in conjunction with the revised method to provide a range of estimated values of S n. The simulations presented represent conditions where radon emanation and decay are not important. Future modeling efforts should consider including these terms for conditions where they may be important. Also, it should be noted that estimated values of S n represent a volume-averaged value, and may or may not be representative of the true value of S n at a given location within the radius of influence of the push–pull test. These uncertainties highlight our view that push–pull test results provide an estimate of NAPL saturation in the immediate vicinity of the well in which the test was conducted. Acknowledgements This work was funded by the U.S. Department of Defense Environmental Security Technology Certification Program (project no. 199916) and the U.S. Department of Energy Environmental Management Science Program (project no. 60158). We also thank Jennifer Field, Ralph Reed, Jason Lee, Mike Cantaloub, and Melora Park for help with laboratory methods and activities; Mark Lyverse and Jesse Jones for help with field activities; Martin Schroth and Mark White for help with STOMP; and Dr. Eduard Hoehn, Dr. E.O. Frind, and an anonymous reviewer for their helpful comments and suggestions. References Annable, M.D., Rao, P.S.C., Hatfield, K., Graham, W.D., Wood, A.L., Enfield, C.G., 1998. Partitioning tracers for measuring residual NAPL: field-scale test results. J. Environ. Eng. 124, 498 – 503. Cantaloub, M., 2001. Aqueous–organic partition coefficients for radon-222 and their application to radon analysis by liquid scintillation methods. Master’s thesis, Oregon State University. Clever, H.L., 1979. Solubility Data Series, vol. 2. Pergamon Press, New York. Davis, B.M., Istok, J.D., Semprini, L., 2002. Push–pull partitioning tracer tests using radon-222 to quantify nonaqueous phase liquid contamination. J. Contam. Hydrol. 58, 129 – 146. Davis, B.M., Istok, J.D., Semprini, L., 2003. Static and push–pull methods using radon-222 to characterize dense nonaqueous phase liquid saturations. Ground Water 41, 470 – 481.
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Dwarakanath, V., Deeds, N., Pope, G.A., 1999. Analysis of partitioning interwell tracer tests. Environ. Sci. Technol. 33, 3829 – 3836. Fry, V.A., Istok, J.D., Semprini, L., O’Reilly, K.T., Buscheck, T.E., 1995. Retardation of dissolved oxygen due to a trapped gas in porous media. Ground Water 33, 391 – 398. Hunkeler, D., Hoehn, E., Ho¨hener, P., Zeyer, J., 1997. 222-Rn as a partitioning tracer to detect diesel fuel contamination in aquifers: laboratory study and field observations. Environ. Sci. Technol. 31, 3180 – 3187. Istok, J.D., Field, J.A., Schroth, M.H., Davis, B.M., Dwarakanath, V., 2002. Single-well bpush–pullQ tracer test for NAPL detection in the subsurface. Environ. Sci. Technol. 36, 2708 – 2716. Jin, M., Delshad, M., Dwarakanath, V., McKinney, D.C., Pope, G.A., Sepehrnoori, K., Tilburg, C.E., Jackson, R.E., 1995. Partitioning tracer test for detection, estimation, and remediation performance assessment of subsurface nonaqueous phase liquids. Water Resour. Res. 31, 1201 – 1211. Lindsey, K.A., Jaeger, G.K., 1993. Geologic setting of the 100-HR-3 operable unit, Hanford site, south-central Washington. WHC-SD-EN-TI-132, Rev. 0, Westinghouse Hanford Company, Richland, WA. Nelson, N.T., Brusseau, M.L., 1996. Field study of the partitioning tracer method for detection of dense nonaqueous phase liquid in a trichloroethene-contaminated aquifer. Environ. Sci. Technol. 30, 2859 – 2863. Nelson, N.T., Oostrom, M., Wietsma, T.W., Brusseau, M.L., 1999. Partitioning tracer method for the in situ measurement of DNAPL saturation: influence of heterogeneity and sampling method. Environ. Sci. Technol. 33, 4046 – 4053. Nichols, W.E., Aimo, N.J., Oostrom, M., White, M.D., 1997. STOMP: Subsurface Transport Over Multiple Phases, Application Guide. PNNL-11216, Richland, WA. Schroth, M.H., Istok, J.D., Haggerty, R., 2000. In situ evaluation of solute retardation using single-well push–pull tests. Adv. Water Resour. 24, 105 – 117. Semprini, L., Broholm, K., McDonald, M., 1993. Radon-222 deficit for locating and quantifying NAPL contamination in the subsurface. Abstr., EOS Trans. Am. Geophys. Union 76, F276. Semprini, L., Cantaloub, M., Gottipati, S., Hopkins, O., Istok, J., 1998. Radon-222 as a tracer for quantifying and monitoring NAPL remediation. In: Wickramanayake, G.B., Hinchee, R.E. (Eds.), Nonaqueous-Phase Liquids. Battelle Press, Columbus, OH, pp. 137 – 142. Semprini, L., Hopkins, O.S., Tasker, B.R., 2000. Laboratory, field and modeling studies of radon-222 as a natural tracer for monitoring NAPL contamination. Transp. Porous Media 38, 223 – 240. White, M.D., Oostrom, M., 2000. STOMP: Subsurface Transport Over Multiple Phases, Version 2.0, User’s Guide. PNNL-12034, Richland, WA. Young, C.M., Jackson, R.E., Jin, M., Londergan, J.T., Mariner, P.E., Pope, G.A., Anderson, F.J., Houk, T., 1999. Characterization of a TCE NAPL zone in alluvium by partitioning tracers. Ground Water Monit. Remediat. 19, 84 – 94.
