Published online July 5, 2005

Sorption, Mobility, and Transformation of Estrogenic Hormones in Natural Soil
Francis X. M. Casey,* Jiřı́ Šimůnek, Jaehoon Lee, Gerald L. Larsen, and Heldur Hakk

Reproduced from Journal of Environmental Quality. Published by ASA, CSSA, and SSSA. All copyrights reserved.

ABSTRACTwhen exposed for durations of 28 d (Irwin et al., 2001).
Also, vitellogen production, which is only normal for
females, has been induced in male fathead minnows(Pimephales promelas) exposed to 17␤-estradiol for 21 dat concentrations as low as 30 ng L⫺1 (Panter et al., 2000).
Recent batch (Lee et al., 2003) and column studies(Das et al., 2004; Casey et al., 2003, 2004) have foundthat hormones have short half-lives and a high affinity
for sorption in natural soils. However, definitive mechanisms of hormone sorption and transformation in soil
are still not fully understood. A better understandingof these mechanisms and their interaction is necessaryfor explaining why these hormones are consistently detected in natural aquatic systems (e.g., Kolpin et al., 2002;
Gentili et al., 2002; Kuch and Ballschmitter, 2001), albeit
in small concentrations. The objective of this research
was to improve the understanding of the processes ofsorption, mobility, and transformation for estrogens innatural soils, and their interaction, using improved batchand continuous flow column experiments.

Potent estrogenic hormones are consistently detected in the environment at low concentration, yet these chemicals are strongly sorbed
to soil and are labile. The objective of this research was to improvethe understanding of the processes of sorption, mobility, and transformation for estrogens in natural soils, and their interaction. Equilibriumand kinetic batch sorption experiments, and a long-term column study
were used to study the fate and transport of 17␤-estradiol and its
primary metabolite, estrone, in natural soil. Kinetic and equilibrium
batch experiments were done using radiolabeled 17␤-estradiol andestrone. At the concentrations used, it appeared that equilibrium
sorption for both estrogens was achieved between 5 and 24 h, andthat the equilibrium sorption isotherms were linear. The log Koc values
for 17␤-estradiol (2.94) and estrone (2.99) were consistent with previously reported values. Additionally, it was found that there was
rate-limited sorption for both 17␤-estradiol (0.178 h⫺1) and estrone(0.210 h⫺1). An approximately 42 h long, steady-flow, saturated column experiment was used to study the transport of radiolabeled 17␤estradiol, which was applied in a 5.00 mg L⫺1 solution pulse for 44 porevolumes. 17␤-estradiol and estrone were the predominant compounds
detected in the effluent. The effluent breakthrough curves were asymmetric and the transport modeling indicated that sorption was ratelimited. Sorption rates and distributions of the estrogens were inagreement between column and batch experiments. This research canprovide a better link between the laboratory results and observationsin the natural environment.

MATERIALS AND METHODS
Experimental procedures were similar to those describedby Casey et al. (2003, 2004). Radiolabeled (14C) 17␤-estradiol(American Radiolabeled Chemicals, St. Louis, MO) was used
as an input for both the batch and column experiments, while
radiolabeled estrone was only used as an input for the batch
experiments. Any 14C estrone detected in the column experiment was a result of 14C 17␤-estradiol transformation. The
radiolabeled C located at the C-4 position of the A-ring ismaintained in the steroidal structure when the 17␤-estradiol
is transformed to estrone. The soil that was used in bothcolumn and batch experiments was a LaDelle silt loam (finesilty, mixed, superactive, frigid Cumulic Hapludolls), which
was sampled from a cultivated area near Northwood, ND, by
Ag-Vise Company (Northwood, ND). The LaDelle has anorganic matter content of 9.2% (Nelson and Sommers, 1982),
a pH of 7.9, a specific surface area of 1.51 ⫻ 105 m2 kg⫺1
(Cihacek and Bremner, 1979), and a particle size distributionof 10% sand, 64% silt, and 26% clay (Gee and Bauder, 1986).
All the physical soil properties, except specific surface, were
determined at the Soil and Water Environmental Laboratory
at North Dakota State University. The soil was prepared forthe column and batch experiments by air drying and sieving
with a 2-mm sieve.

A

nimal manures are typically managed for their nutrient content and applied to field soil accordingly.
Manures can contain hormones, which have the potential to contaminate soils as well as surface and subsurface
waters. With their extensive reconnaissance of U.S. surface freshwaters, Kolpin et al. (2002) showed a potential
connection between animal feedlot operations and thepresence of pharmaceuticals and hormones in surface
waters. Soto et al. (2004) have shown that runoff fromconcentrated feedlot operations can enter surface waters and result in hormone concentrations that could
adversely affect aquatic health. The potency and potential for widespread contamination are the major concerns regarding hormones in the environment. Somestudies have shown that 17␤-estradiol concentrations of⬍1 to 7 ng L⫺1 can significantly increase vitellogenin
production in female painted turtles (Chrysemys picta)
F.X.M. Casey, Dep. of Soil Science, North Dakota State Univ., Fargo,
ND 58105; J. Šimůnek, Dep. of Environ. Sciences, Univ. of California,
Riverside, CA 92521; J. Lee, Dep. of Biosystems Eng. and Environ.
Sciences, Univ. of Tennessee, Knoxville, TN 37996–4531; and G.L.
Larsen and H. Hakk, Animal Metabolism: Agricultural Chemicals
Research, Biosciences Research Lab., USDA-ARS, Fargo, ND 581055674. Received 26 July 2004. *Corresponding author (francis.casey@
ndsu.edu).

Chemical Preparation and Analysis
Ethanol was used to initially dissolve the stock 14C labeled
17␤-estradiol and the estrone in a 0.001M CaCl2 solution. The
percentages of the ethanol in each batch solutions were 0.163
and 0.125% for 17␤-estradiol and estrone, respectively. The
percentage of ethanol in the initial concentration of the column experiment was 0.17%. All these ethanol concentrations
were ⬍0.5%, which has been shown not to affect the sorption

Published in J. Environ. Qual. 34:1372–1379 (2005).
Technical Reports: Vadose Zone Processes and Chemical Transport
doi:10.2134/jeq2004.0290© ASA, CSSA, SSSA
677 S. Segoe Rd., Madison, WI 53711 USA

Abbreviations: ASE, accelerated solvent extractor; CI, confidence
interval; LCMS, liquid chromatography/mass spectrometer; SSQ,
sum-of-squares error; TLC, thin-layer chromatography.

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1373

Reproduced from Journal of Environmental Quality. Published by ASA, CSSA, and SSSA. All copyrights reserved.

CASEY ET AL.: ESTROGENIC HORMONES IN NATURAL SOILof an organic pollutant to soil (Wauchope and Koskinen, 1983).
The initial radioactivity of the 14C 17␤-estradiol (specificactivity ⫽ 4.21 ⫻ 1014 dpm kg⫺1) in the batch experiments
ranged from 14 230 dpm to 761 869 dpm, and the minimal
radioactivity detected was 560 dpm, which was equivalent to
1.7 ⫻10⫺4 mg L⫺1. The initial radioactivity for the 14C estrone(specific activity ⫽ 4.18 ⫻ 1014 dpm kg⫺1) in batch experiments
ranged between 5536 dpm to 509 407 dpm, and the minimal
radioactivity detected was 213 dpm, which was equivalent to
6.4 ⫻10⫺5 mg L⫺1. For the column experiment, 124.3 ␮g 14C
17␤-estradiol was mixed with 8518 ␮g of 12C 17␤-estradiol in
1.73 L to create the application concentration of 5.0 mg L⫺1.
The total 14C labeled 17␤-estradiol (specific activity ⫽ 5.96 ⫻1012 dpm kg⫺1) applied in the column experiment was 5.2 ⫻107
dpm and the minimal dpm detected in the effluent was 42
dpm, which was equivalent to 4.1 ⫻ 10⫺6 mg L⫺1.
Several analytical procedures were used to determine theconcentrations of 17␤-estradiol and its metabolites in the experiments. Liquid scintillation counting was used to analyze
for total 14C, and thin-layer chromatography (TLC) was used
to analyze for metabolites of 14C 17␤-estradiol. Liquid chromatography/mass spectrometer (LCMS) was also used to analyze
selected samples from the column transport experiments. Liquid scintillation counting was done using a 1900 CA Scintillation Counter (Packard, Downers Grove, IL), and TLC analysis
was done using a System 2000 Imaging Scanner (Bioscan,
Washington, DC). Thin-layer chromatography was conductedusing silica gel plates (250 mm; Whatman Lab. Div., Clinton,
NJ) and a 25:25:50 tetrahydrofuran/ethyl acetate/hexane mobile phase. A combustion analysis assay (Packard Model 307
Oxidizer; Downers Grove, IL) was also used to determine total
14
C sorbed to the soil.
The liquid chromatograph system of the LCMS was an Alliance 2695 Separation Model (Waters, Beverly, MA) equippedwith a Symmetry C18 column (3.5 ␮m, 2.1 by 100 mm), a C18
guard column (2.1 by 10 mm), and a quadrupole-time of flightmass spectrometer (Waters Q-TOF Ultima API-US; Waters,
Beverly, MA). A linear binary gradient pump was used, which
consisted of 95/5 aqueous 7.4 mM NH4OH/acetonitrile (A)and 100% acetonitrile containing 7.4 mM NH4OH (B). The
linear gradient that was used began with 40% B at time 0 min
and increased to 100% B at 10 min. The flow rate of the mobile
phase was 0.2 mL min⫺1. The mass spectrometer analysis was
performed in negative ion mode (ES⫺) with capillary and cone
voltages of 2.33 and 55, respectively; source and desolvation
temperatures of 120 and 400⬚C, respectively; and desolvation
gas flows of 0 and 500 L h⫺1, respectively. The LCMS sample
injection volumes were always 10 ␮L, and 25 pg mass oncolumn could be reliably detected using selected ion monitoring.

Batch Experiments
In 10-mL vials, 1.6 g of soil and 8 mL of 0.0l M CaCl2 wereadded. The 14C solution was then added to the vials to create
solution concentrations of 0.0015, 0.015, 0.0825, and 0.150 mg
L⫺1 for 17␤-estradiol and 0.0014, 0.014, 0.076, and 0.138 mg
L⫺1 for estrone. These concentrations were chosen because
they span the range of concentrations reported for manuresthat are applied to fields (Shore et al., 1993, 1995; FinlayMoore et al., 2000). Each batch experiment was replicatedthree times. The soil–water slurries were agitated by rotationof the vials top to bottom (360⬚/5 s). After 0.5, 1, 5, 24, and48 h, the bottles were centrifuged at 1000 ⫻ g (1700 rpm),
100 ␮L aliquots were removed, and the solution was analyzed
using the liquid scintillation and TLC methods describedearlier.

Batch Sorption Model
The aqueous concentrations (C; mg L⫺1) of steroidal estrogens will decrease at the same time the sorbed phase concentrations (S; mg kg⫺1) increase. The mass balance of the solutepartitioning through time can be expressed with the following
ordinary differential equation when sorbed phase degradation(␮s ; h⫺1) is considered as follows:

V

冢

dC
dS
⫽ ⫺M
⫹ ␮sS
dt
dt

冣

[1]

In Eq. [1] there are two dependent variables, C and S, andone independent variable, t.
The following first-order expression was used as the driving
force of sorption through time, as follows:dS⫽ ␣(KdC ⫺ S) ⫺ ␮sS
dt[2]

where ␣ is the sorption rate coefficient (h⫺1) and Kd (L mg⫺1)is the linear distribution coefficient between the sorbed andaqueous phases. At equilibrium S ⫽ Kd ⫻ C.
Equation [1] was solved in a spreadsheet using an Euler
numeric method with a time step of 0.001 h. This solution
was done by coupling Eq. [2] with the following ordinary
differential equation as follows:MdC⫽ ⫺ ␣(KdC ⫺ S)
dt
V

[3]

A nonlinear, least-square fitting algorithm was used to fit thesolution of Eq. [1] to the measured batch data. The KdC termof Eq. [2] and [3] was fit to the 24-h equilibrium sorption data,
while the time series data was simultaneously fit with thenumerically calculated C values. The time series batch data
were a set of measured C(ti) values at specific time increments,
ti (i ⫽ 1,2,…N ). These C(ti) values are the input data forthe numerical inversion problem. The numerically calculatedaqueous concentrations are represented by C (ti, b), whichcorresponds to a trial vector of parameter values b, where b isthe vector of optimized parameters ␣, Kd, and ␮s. An optimum
combination of parameters bo is then sought to minimize thefollowing objective function:
NE(b) ⫽ 兺 {wi[C(ti) ⫺ C(ti,b)]}2

[4]

i⫽1

where wi is a weighting function. The Solver tool in Microsoft
Excel that uses a Newton method of minimization was used
to determine bo.
For all our calculations, S was determined by mass-balancedifference (i.e., whatever mass of 14C not present in solution
was considered to be sorbed). No metabolites were detectedin the aqueous phases so it was assumed that transformations
took place in the sorbed phase. It was also possible that transformations took place in the aqueous phase and then quickly
reabsorbed to the solid, but this was assumed not to happen.
The ␮s value that we obtained from the column experiment
was considered in the numerical solution of Eq. [1] to determine the affect of sorbed phase transformation on the batch
Kd estimates.

Column Transport Experiments
A glass column with diameter of 0.03 m was packed with
0.047 kg of dry soil to a length of ≈0.074 m. The column was
saturated from the bottom up over 24 h using a solution of
0.01 M CaCl2. After the column was saturated, steady state flow
was established through the column using the same 0.01 M

Reproduced from Journal of Environmental Quality. Published by ASA, CSSA, and SSSA. All copyrights reserved.

1374

J. ENVIRON. QUAL., VOL. 34, JULY–AUGUST 2005

CaCl2 solution. The steady state pore-water velocity was 0.145 m
h⫺1. Once steady state velocity was achieved a CaCl2 breakthrough curve was run to characterize the transport of a nonreactive solute (i.e., Cl⫺) through the column. This was done
by applying a 5.16 pore volume pulse of 0.05 M CaCl2 solution
to the column, followed by the application of the 0.01 M CaCl2
solution. The column effluent was collected in approximately
0.13 pore volume increments and analyzed using an ion-specific electrode. The 0.01 M CaCl2 solution was applied forseveral pore volumes, after which a 1.721-L (44 pore volume)
pulse of 5.00 mg L⫺1 17␤-estradiol in 0.01 M CaCl2 was applied
to the column, followed by 0.01 M CaCl2 without 17␤-estradiol
for approximately 66 pore volumes. The effluent was collected
in 0.1 pore volume increments and analyzed for total 14C andmetabolites using scintillation counting and TLC, respectively,
with LCMS analysis on selected samples. The total duration
for the 17␤-estradiol breakthrough curve experiment was approximately 42 h and the total mass of 14C 17␤-estradiol applied
to the column during this time was 8.605 mg.
When the column experiment was complete, the soil was
extruded from the glass column in approximately 1-cm increments. This was done to identify the redistribution of the 14C
with soil depth. The soil was then analyzed for total 14C using
combustion analysis. Sequential solution extraction was doneby eluting with toluene, ethyl acetate, and finally methanol
in the cell of an accelerated solvent extractor (ASE, model
200; Dionex, Sunnyvale, CA). Liquid scintillation was doneon all ASE extractions to quantify total 14C. Also, TLC wasused to detect any metabolites in these extractions.

Column Transport Model
The CaCl2 and 17␤-estradiol miscible-displacement experiments were inversely modeled using the program HYDRUS-1D
version 2.0 (Šimůnek et al., 1998). This inverse model routine
uses a least-squares method that minimizes an objective function, which provides a best-fit model solution to the measured
transport data. The best-fit model solution to the transport
data is obtained by finding the optimum combination of reaction and transport parameters. The code of HYDRUS-1D
was modified to inversely model two solutes involved in atransformation chain reaction.
Two model variations, one with instantaneous sorption andthe other with time dependent sorption, were used to describe
the transport data. In both model variations it was assumed
that the solute was transported in the aqueous phase by convection and dispersion, and that there was a first-order transformation reaction of 17␤-estradiol into estrone. The following
differential equations represent the convective–dispersive transport of a solute undergoing transformation (van Genuchten,1985), and instantaneous or time-dependent sorption (Selim
et al., 1977; van Genuchten and Wagenet, 1989) as follows:

␪

⳵2C1
⳵S
⳵C
⳵C1
⫹ ␳b 1 ⫽ ␪v␭
⫺ ␪v 1 ⫺ ␮⬘s,1 ␳b S1 [5]
2
⳵t
⳵t
⳵x
⳵x
⳵C
⳵S
⳵2C2
⳵C2
⫺ ␪v 2 ⫹⫹ ␳b 2 ⫽ ␪v␭
⳵t
⳵t
⳵x2
⳵x
␮⬘s,1 ␳b S1 ⫺ ␮⬘s,2 ␳b S2
␪[6]

where the subscripts 1 and 2 represent the parent solute, 17␤estradiol, and the daughter product, estrone, respectively; ␳bis soil bulk density (kg m⫺3), ␪ is the volumetric water content(m3 m⫺3), ␭ (m) is the dispersivity, v is steady state porevelocity (m h⫺1), x is depth (m), and ␮s⬘ is a first-order transformation rate constant in the solid phase (h⫺1) that provides
connection between parent and daughter compounds. In Eq.

[5] and [6], when sorption is considered to be only instantaneous thenS ⫽ KdC[7]

When sorption is partially dependent on time, then the conceptof two-site sorption is implemented, where sorption can occur
instantaneously on equilibrium exchange sites (S e) or kinetically on the remaining exchange sites (S k) (Selim et al., 1977;
van Genuchten and Wagenet, 1989). The following provides
the mass balance for this two-site sorption concept:

S ⫽ S e ⫹ Sk
Se ⫽ fKdC

[8]
[9]

⳵Sk
⫽ ␣[(1 ⫺ f)KdC ⫺ Sk] ⫺ ␮⬘s Sk
⳵t

[10]

where f is the fraction of sorption sites that are consideredequilibrium, and ␣ is a first-order sorption rate coefficient(h⫺1). To model the CaCl2 breakthrough, Eq. [5] was usedwith no transformations or sorption (i.e., ␮⬘s1 ⫽ S1 ⫽ 0), and␭ was estimated.

RESULTS AND DISCUSSION
Batch Results
The sorbed concentrations of 17␤-estradiol and estrone were determined by mass-balance difference forthe batch experiments and were not measured directly.
Other studies have indicated that degradation of estrogens occurs rapidly. Colucci et al. (2001) reported highdegradation values for 17␤-estradiol (0.060–0.134 h⫺1)
in soil; therefore, it is possible that transformation occurs even over a short period of time. Our TLC analysis,
however, indicated that no metabolites were present (orwere below our detection limits) in the aqueous phasefor either the 17␤-estradiol or estrone batch experiments.
This could have indicated that transformation occurredin the aqueous phase and the metabolite quickly reabsorbed, or that degradation occurred in the solid phase,or that there was no degradation. In a similar study,
Holthaus et al. (2002) used anaerobic conditions to decrease biodegradation of 14C 17␤-estradiol; however,transformation of 17␤-estradiol into estrone still occurred. They reported that their 17␤-estradiol distribution coefficients probably reflected a combination ofboth estrogen species. Holthaus et al. (2002) also notedthat both 17␤-estradiol and estrone had very similarsolubilites, which would make their sorption parametersvery similar. When 14C 17␤-estradiol is converted into
estrone the steroid ring system remains intact and theradiolabel is not lost. Thus, the 17␤-estradiol Kd valuesof this study may reflect a mixture of 17␤-estradiol andits metabolite estrone. Estrone, on the other hand, ismore resistant to degradation (Colucci et al., 2001) and
its Kd values likely represent the parent molecule.
Sorption Kinetics and Degradation
The slopes of the sorption isotherms of 17␤-estradiol
and estrone (Fig. 1a and 1b) increased through time, andaqueous concentration decreased through time (Fig. 2aand 2b). These results indicated that there was a kinetic
process occurring, which may be explained by sorptionReproduced from Journal of Environmental Quality. Published by ASA, CSSA, and SSSA. All copyrights reserved.

CASEY ET AL.: ESTROGENIC HORMONES IN NATURAL SOIL

1375

Fig. 2. Kinetic sorption batch data showing the aqueous concentrationof (a) 17␤-estradiol and (b) estrone vs. time. The batch data shown
are from the different initial aqueous concentrations, which are fit
with a first-order kinetic sorption model, Eq. [1].

Fig. 1. Batch sorption data of sorbed vs. aqueous concentrations for(a) 17␤-estradiol and (b) estrone. Five different batch sample times
are presented with their corresponding linear sorption isotherms.

kinetics, degradation, or a combination of these processes. In this section we look at the effect of sorbed
phase degradation and sorption kinetics on the interpretation of the 17␤-estradiol batch experiments. We assumed that if degradation occurred, then it was in thesorbed phase, because no metabolites were detected in
the aqueous phase. Equation [1] was fit to the timeseries of C values (e.g., Fig. 2a) using a fixed ␮⬘s value
obtained from the column experiment (␮s ⫽ 0.09 h⫺1,presented later) and optimizing ␣ and Kd. The optimized
␣ and Kd values were 0.44 h⫺1 and 41.00 L kg⫺1, respectively, and the model fit was excellent for the measured
points ⱕ5 h (r 2 ⫽ 0.99). However, at times ⱖ24 h, the ␮sof 0.09 h⫺1 provided an over-prediction of 17␤-estradiol
dissipation. This model solution predicted a continual
decrease in concentrations instead of approaching amore steady value, as our data indicated (Fig. 2a and2b). This result suggests that within the first 24 to 48 h
sorption kinetics was more significant than degradation,
because the aqueous concentrations converged to an
apparent constant rather than continually decreasing asa result of degradation (Fig. 2).
Sorbed-Phase Distributions
For the range of concentrations used in this study, it
was found that both 17␤-estradiol and estrone sorption
isotherms were linear for each time step of 0.5, 1, 5, 24,
and 48 h (Fig. 1a and 1b), and that sorption equilibrium
was achieved between 5 and 24 h. This equilibration
period (苲5–24 h) for hormone sorption has been observed in other studies (Lai et al., 2000; Holthaus et al.,
2002; Yu et al., 2004). Our 24 to 48 h log Koc (log Koc ⫽log10[Kd/(OC/100)] values for 17␤-estradiol (≈3.2) andestrone (≈3.3) were comparable to values reported byother studies for soil. Yu et al. (2004) reports log Koc
values for 17␤-estradiol that range from 3.14 to 5.38 andestrone values that range from 3.3 to 5.25. Lee et al.
(2003) also report values for 17␤-estradiol that range
from 3.21 to 3.46 and estrone values that range from
3.19 to 3.22.
Lee et al. (2003) indicate that the primary sorption

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J. ENVIRON. QUAL., VOL. 34, JULY–AUGUST 2005

Table 1. The linear partitioning coefficient (Kd), the log10 of theorganic C normalized partitioning coefficients (log Koc), the log10octanol–water portioning coefficient (log Kow), and the coefficient of determination (r2) of the linear isotherm fit of thebatch sorption data for 17␤-estradiol and estrone through time.

Reproduced from Journal of Environmental Quality. Published by ASA, CSSA, and SSSA. All copyrights reserved.

Time

Kd

h

L kg⫺1

0.5
1
5
24
48

17.98
27.74
64.27
89.47
84.41

0.5
1
5
24
48

30.36
46.53
84.91
95.19
93.37

Log Koc

r2

2.27
2.46
2.83
2.97
2.94

0.98
1.00
1.00
1.00
0.99

2.50
2.69
2.95
3.00
2.99

0.98
0.98
0.98
0.98
0.98

17␤-estradiol

Estronedomain for the estrogen hormones is organic C, and thatpartitioning is consistent with hydrophobic partitioning
process; that is, there is a direct linear correlation between the log10 octanol–water portioning coefficient (log
Kow) and log Koc. Our 24-h log Koc values (Table 1) wereused to calculate the log Kow values using the Means etal. (1980) linear relation, where log Koc ⫽ log Kow ⫺0.317. The calculated log Kow values for 17␤-estradiol
and estrone were 3.25 and 3.28, respectively, and fellwithin the range of values reported in the literature,
which was 3.10 (Hansch et al., 1995) to 4.01 (Suzuki etal., 2001) for 17␤-estradiol, and 2.45 (Suzuki et al., 2001)
to 3.43 (cited by Lai et al., 2000) for estrone. This result
suggests that the log Koc information is useful in predicting partitioning of these estrogens.

(Rogers, 1965). Pignatello and Xing (1996) indicate that
this type of Fickian behavior is consistent with sorptionof dilute contaminants (penetrant concentrations in thisstudy ≈1 ⫻ 10⫺7 to 1 ⫻ 10⫺5 kg kg⫺1) into soft organic C
or the amorphous organic matter domain. Others (e.g.,
Brusseau et al., 1991; Luthy et al., 1997; Xing et al.,1996) have also observed this type of rate-limited diffusion process.
The 17␤-estradiol batch data from the Casey et al.
(2003) study were revisited to see whether the data wereconsistent with our current study. The sorption model(Eq. [1]) described the Casey et al. (2003) batch datawell for the various soils (see r 2 values presented inTable 2). The resulting log Koc values (Table 2) wereconsistent with the values of the current study (Table 1).
These log Koc values increased with time, which was
also similar to the current study. There was a negative
correlation between log Koc values and OC (correlation
coefficient ⫽ ⫺0.872), which indicated that other nonhydrophobic processes contributed to sorption. The predominant sorption process remains hydrophobic as Lee
et al. (2003) demonstrates; however, the contributionof other nonhydrophobic processes increases as OC decreases, and the apparent Koc values increase. One explanation for nonhydrophobic sorption is provided by
Yu et al. (2004), who suggests that the phenolic groupof 17␤-estradiol and estrone can interact with humic
acids or mineral surfaces via hydrogen and covalentbonding. They propose that the polar groups at the C-17
position of both molecules can react with humic acids
and mineral surfaces causing sorption to follow somespecific interactions in addition to hydrophobic interactions.

Rate-Limited Sorption
An explanation for the time-dependent sorption is
rate-limited sorption caused by soil organic matter. Figures 2a and 2b show the first-order kinetic sorption
model (Eq. [1]) fit with the measured aqueous concentrations through time. The same ␣ and Kd values were used
to model the data for each initial concentration of both17␤-estradiol (␣ ⫽ 0.178 h⫺1, Kd ⫽ 86.00 L kg⫺1) andestrone (␣ ⫽ 0.210 h⫺1, Kd ⫽ 94.00 L kg⫺1). This model
provided excellent descriptions of the sorption data for17␤-estradiol (r2 ranged from 0.94 to 0.98 with mean of0.98) and estrone (r2 ranged from 0.94 to 1.00 with mean
0.98). This sorption data obeyed Fick’s law, where sorption was found to be linear and proportional to thesquare root of time, and ␣ was the same for each C0

Column Results
The total mass of 14C 17␤-estradiol applied to the crosssectional area of the soil column was 8.605 mg over anapproximate time of 19 h. This amount of 17␤-estradiol
appears to be large. However, pregnant dairy cattle (Bostaurus) and sows (Sus scrofa) have been shown to eliminate quantities of 163 000 ⫾ 20 000 ␮g d⫺1 and 108 000 ⫾103 000 ␮g d⫺1, respectively, based on 1000 kg of live
animal mass (Raeside, 1963). A number of pregnant stock
animals in a confined area can eliminate large amountsof hormones possibly posing a risk to surface and subsurface water quality. In the soil column effluent, 26%of the total 14C 17␤-estradiol applied was recovered asparent compound, and 36.7% was recovered as estrone.

Table 2. The organic carbon (OC) content of the soils from the Casey et al. (2003) study. Also, the calculated log10 of the organic C
normalized partitioning coefficients (log Koc) and first-order kinetic sorption coefficients (␣) from the Casey et al. (2003) batch experiments.
Log KOC
Soil series/texture
Bearden silty clay loam
Gardena clay loam
Glyndon sandy clay loam
LaDelle silt loam
Sioux loam

OC
%
7.5
5.3
3.3
9.2
7.5

0.5 h†

1h

5h

24 h

48 h

␣

r2

h⫺1
2.65
2.46
3.94
2.29
2.58

2.76
2.64
4.03
2.48
2.75

3.02
3.06
4.18
2.84
2.94

† The log Koc values are segregated by the time at which the isotherms were determined.

3.17
3.17
4.13
2.99
2.75

3.20
3.18
4.14
2.96
2.73

0.200
0.178
instantaneous
0.184
0.543

0.99
0.99
1.00
0.99
0.99

Reproduced from Journal of Environmental Quality. Published by ASA, CSSA, and SSSA. All copyrights reserved.

CASEY ET AL.: ESTROGENIC HORMONES IN NATURAL SOIL

1377

Fig. 3. Concentrations of 17␤-estradiol and its transformation products through the depth of the soil column. Also included is theprediction using the “two-site/2” parameter estimates obtained
from the effluent breakthrough curves in Table 3.

An additional 22.4% was recovered from the soil inside
the column through combustion analysis. Thus, the total
14
C recovery was approximately 84%. Analysis of thesoil extractions indicated that 16.9% 17␤-estradiol, 5.08%
estrone, 0.18% estriol, and 0.08% of an unidentified
metabolite of higher polarity were recovered based on
the total 14C applied. The estriol and the unidentified
metabolite were not eluted until the final solvent extraction, and 17␤-estradiol and estrone were eluted fromthe three solvent extractions in approximately equalamounts. Figure 3 shows the distribution of each of
the 14C compounds recovered from the soil extractions
relative to the total amount applied. In general, 17␤estradiol increased with depth and estrone was distributed equally with depth, except in the bottom layer
where it was not detected. The other metabolites (estriol
and unidentified) were only found in the upper 3 cm ofsoil. The incomplete 14C mass balance (84%) may be a
result of incomplete combustion, or could have also
resulted from mineralization of the 14C 17␤-estradiol toform 14CO2.
Modeling Approach
The CaCl2 breakthrough curve was symmetric andwas fit with an advective–dispersive model using a retardation coefficient of 1 (data not shown) and an optimized ␭ value of 0.024 m. The model fit to the Cl⫺
breakthrough curve was good (r2 ⫽ 0.98) and indicatedthat transport was a physical equilibrium process. The
breakthrough curves of 17␤-estradiol, estrone, and total
14
C were all asymmetric (Fig. 4). The asymmetric breakthrough curves indicated chemical nonequilibrium transport of the estrogens and not physical nonequilibrium,

Fig. 4. The soil column, relative, effluent concentrations of total 14C,
17␤-estradiol, and estrone through time. The 17␤-estradiol andestrone data were fit with (a) an instantaneous sorption model
option (Table 3, Instantaneous) and (b) a two-site sorption model
option (Table 3, Two-site/2).

because the CaCl2 was transported as a physical equilibrium process. Instantaneous and two-site sorption scenarios were considered in modeling the estrogen breakthrough curves. For two-site sorption, sorption takes
place on both instantaneous and kinetic sites, and there
is a fixed ratio (f) between these two sorption sites (vanGenuchten and Wagenet, 1989). The batch sorption parameters (Tables 1) and the ␭ value from the CaCl2
column experiment were fixed in our initial model runs,
whereas ␮s⬘ and f values were estimated. Then, various
model parameters were optimized to obtain a bettermodel description of the data. Also, the 17␤-estradiol andestrone breakthrough curves were optimized simultaneously, which improves the uniqueness of parameter estimates (Casey and Šimůnek, 2001).
Fitting Results
Table 3 summarizes the inverse modeling results,
where estimated parameters are presented with their
95% confidence intervals (CI). Also, Fig. 4a and 4bshow the model fits to the estrogen breakthrough curves
using instantaneous and kinetic sorption models, respec-

1378

J. ENVIRON. QUAL., VOL. 34, JULY–AUGUST 2005

Table 3. The model parameter estimates of the instantaneous and two-site sorption miscible-displacement models. The goodness of themodel fit was indicated by the sum-of-squares error (SSQ) between the measured and calculated effluent concentrations. The model
parameters were linear partitioning coefficient (Kd), sorbed phase transformation (␮sⴕ), first-order kinetic sorption (␣), and fractionof equilibrium sorption sites (f ). Subscripts 1 and 2 indicate 17␤-estradiol and estrone, respectively.

Reproduced from Journal of Environmental Quality. Published by ASA, CSSA, and SSSA. All copyrights reserved.

Sorption type/run
InstantaneousTwo-site/1
Two-site/2

SSQ

Kd1

0.165
0.629
0.028

L kg⫺1
27.74
86.00
55.87 (49.20–62.53)

␮ⴕs1

␣1

Kd2

␮ⴕs2

␣2

f

NA†
0.18
0.18

L kg⫺12.65 (⫺0.87–6.18)‡
94.00
30.36 (19.00–41.73)

h ⫺1
1.02 (⫺0.30–2.34)
0.019 (⫺0.00–0.04)
0.14 (0.05–0.23)

NA
0.21
0.21

NA
0.0004 (⫺0.006–0.006)
0.145 (0.092–0.177)

h⫺1
0.15
0.14 (⫺0.02–0.30)
0.09 (0.07–0.11)† NA indicates that this parameter is not applicable to this particular model.
‡ The values inside parentheses represent the 95% confidence interval, and indicate that this parameter was estimated.

tively. The instantaneous sorption model option (Fig. 4a)
could only provide a realistic description of the solute
breakthrough curves when the 1-h batch Kd value for17␤-estradiol was fixed, and when estrone Kd and ␮⬘swere fitted. The 17␤-estradiol Kd value made sense,
because the contact time within the soil column wasapproximately 0.5 h and corresponded to the batch Kd
value determined at approximately the same time. The
optimized values for estrone had large 95% CIs, whichindicates more uncertainty in these parameter estimates.
The Kd value for estrone was lower than expected (log
Koc ⫽ 1.44), which may be attributed to the shorter
contact times in the soil column. The 17␤-estradiol ␮⬘s(0.15 h⫺1) was similar to values reported by Colucci
et al. (2001), which ranged from 0.13 to 0.06 h⫺1. The
estrone ␮⬘s (1.02 h⫺1) estimate was large and fell out of
the range of values reported in the literature for soil,
0.006 (Das et al., 2004) to 0.05 h⫺1 (Colucci et al., 2001).
Although the instantaneous sorption model provided
a reasonable fit of the observed breakthrough curves(Fig. 4a), the estrone parameter estimates were not satisfactory and the tail of the breakthrough curves werepoorly described (Fig. 4a).
Das et al. (2004) used a two-site sorption model (vanGenuchten and Wagenet, 1989) to describe estrogen
breakthrough curves from a 1.0-cm long soil column.
The two-site sorption concept was also appropriate fordescribing our breakthrough curves, because there appeared to be a rate-limiting sorption process, whichcaused the breakthrough curve tail and was observedin our batch experiments. In the first two-site sorption
model simulation (Table 3, two-site/1), Kd and ␣ were
fixed to values obtained from the batch study (Kd1 ⫽86.00 L kg⫺1, Kd ⫽ 94.00 L kg⫺1, ␣1 ⫽ 0.18 h⫺1, ␣2 ⫽0.21 h⫺1) and ␮⬘s1, ␮⬘s2, and f were optimized. The SSQ
value for this simulation was reasonable. However, thepeak concentrations of 17␤-estradiol were underestimated, and the tail of the estrone was over-predicted(fit not shown). Still, the two-site sorption model option
was able to capture the shape of the breakthrough curve
better than the instantaneous sorption option using thebatch determined parameters.
The two-site sorption model was fit to the breakthrough data again using fixed values of ␭, ␣1, and ␣2,
while optimizing for ␮⬘s1, ␮⬘s2, Kd1, Kd2, and f (Table 3;
two-site/2). The Kd values were estimated because it was
not clear from the batch experiments how degradation/transformation affected this parameter. The number ofparameters that were estimated was five, which appears
to be large. However, there were two breakthroughcurves or 2.5 parameters estimated per curve, which is
not unreasonable. The model fit was excellent (Fig. 4b;
SSQ ⫽ 0.028) and the confidence intervals of the parameter estimates were narrow (Table 3), which indicatesa more unique solution. The Kd estimates for 17␤-estradiol and estrone fell within the range of values calculated
from the batch studies. Also, the 17␤-estradiol ␮⬘s estimate was similar to values reported by Colucci et al.
(2001), but the estrone ␮⬘s value was higher than the17␤-estradiol value. Das et al. (2004) found that estrone
degraded faster than 17␤-estradiol for their flow-interruption soil column experiment. The ␣ values from thebatch experiments provided a good prediction of the
breakthrough curve tail. Also, the f value indicated thatabout one-sixth of the sorption sites were instantaneousor readily available to sorption.
To further evaluate the confidence in these column
parameter estimates, the 17␤-estradiol Kd1, ␣1, and ␮⬘s1
values (Table 3, two-site/2) were used to solve the kinetic sorption model, Eq. [2]. This solution was thencompared with the 17␤-estradiol batch aqueous concentrations through time. This model provided a good description of the batch data through 5 h (r 2 ⫽ 0.95, SSQ ⫽0.001), but at times ⱖ24 h this solution over-predicted
the dissipation of 17␤-estradiol. This result may suggestthat degradation slows as aqueous concentrations decrease, and may not, as Das et al. (2004) suggests, follow
a first-order process. This may also explain why theaqueous 17␤-estradiol concentrations in the batch experiments did not go to zero but approached an apparent constant. Lastly, the two-site sorption option andparameter estimates (Table 3, two-site/2) were used to
predict profile distribution of 17␤-estradiol and estrone,and compared well to the measured distribution of these
hormones (Fig. 3). This further confirmed the confidence in this model and these parameter estimates.

CONCLUSIONSThis research can provide a better link between laboratory results and observations in the natural environment. The batch and column experiments of this study
resulted in close agreement. A first-order, rate-limited
sorption process was evident in both the batch and column experiments and was found to be rapid. The column
experiments indicated that degradation was rapid and wasadequately modeled with a first-order process. There wasalso evidence that degradation rates decreased throughtime or with lower concentrations. Although the estrogen
hormone escaped the 7-cm organic rich topsoil, these ex-Reproduced from Journal of Environmental Quality. Published by ASA, CSSA, and SSSA. All copyrights reserved.

CASEY ET AL.: ESTROGENIC HORMONES IN NATURAL SOIL

perimental conditions (i.e., continuous application of
hormone, and flowing, saturated conditions) are likely
not to be found under natural conditions. Under natural
conditions, the sorption and degradation rates of these
estrogens would likely result in little mobility and little
persistence. Nonetheless, hormones are consistently detected in the environment at low concentrations. Thereis a need to better understand the degradation processof these hormones under natural conditions and theirnatural background levels and sources.
ACKNOWLEDGMENTS
This research was based on work supported by the National
Science Foundation under Grant no. 0244169. Any opinions,findings, and conclusions or recommendations expressed inthis material are those of the authors and do not necessarilyreflect the views of the National Science Foundation. Also, aspecial thanks is given to Barbara K. Magelky and Colleen
M. Pfaff for their analytical and technical work. Also theauthors thank Grant Harrington for his LC-MS-MS analysis.

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