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DIVISION S-1 - SOIL PHYSICS

Diffusion of Sorbing Organic Chemicals in the Liquid and Gaseous Phases of Repacked Soil

^a Dept. of Environmental Engineering, Aalborg Univ., Sohngaardsholmsvej 57, DK-9000 Aalborg, Denmark
^b Dep. of Social and Environmental Engineering, Graduate School of Engineering, Hiroshima Univ., 1-4-1 Kagamiyama, Higashi-Hiroshima, 739, Japan
^c Soils and Biogeochemistry, Dep. of Land, Air and Water Resources, Univ. of California, Davis, CA 95616

* Corresponding Author (i5pm{at}civil.auc.dk)

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS THEORY CONCLUSIONS REFERENCES

 
Transport models for sorbing organic chemicals in soil require accurate predictions of the diffusion and sorption processes in both the liquid and gaseous phases. In this study, the ability of recently-presented diffusivity models in combination with equilibrium sorption models to predict the effective (i.e., including sorption effects) diffusion coefficient, D_eff, as a function of soil-water content, , is tested for different sorbing organic chemicals in different soils. The water-induced linear reduction (WLR) gas diffusivity model, combined with a two-component (hydrophobic and vapor) equilibrium sorption model, well described short-term (<24 h) D_eff() of two volatile organic compounds, toluene and trichloroethylene (TCE), in Yolo loam (fine-silty, thermic Typic Xerorthent). Further extended with the constant slope impedance factor (CSIF) solute diffusivity model, the resulting two-phase diffusion and two-component equilibrium sorption (DATES) model accurately predicted short-term (48 h) D_eff() of a semivolatile pesticide, lindane (C₆H₆Cl₆), in Gila silt loam (coarse-loamy, thermic Typic Torrifluvents). To test the DATES model for longer-term data, D_eff() of naphthalene (C₁₀H₈) in Lerbjerg sandy clay (L5) was measured at different soil-water contents and incubation times in air-tight diffusion cells. Because of sorption kinetics, both the apparent hydrophobic sorption coefficient, K_D, derived from the column diffusion experiments and K_D derived from batch desorption experiments increased with naphthalene-soil contact time for t > 700 h. Consequently, an increasing K_D value with time was required in the DATES model to obtain successful D_eff() predictions. Since chemical-soil contact time and adsorption-desorption history typically vary in each compartment of a soil profile, transport models, including sorption kinetics, will become very complex and DATES with a time-dependent K_D relation may represent a useful model alternative.

Abbreviations: CSIF, Constant slope impedance factor • D_eff, effective diffusion coefficient • DATES, Diffusion and two-component equilibrium sorption • L5, Lerbjerg sandy clay • TCE, Trichloroethylene • WLR, Water-induced linear reduction

	INTRODUCTION

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DIFFUSION of sorbing organic chemicals in the soil liquid and gaseous phases affects and potentially controls the spreading and fate of organic pollutants in the soil. Recently, Moldrup et al. (2000a) and Olesen et al. (2001) suggested improved models to predict the diffusion coefficients of nonsorbing tracers in the gaseous and liquid phases, respectively, of repacked soil. For sorbing organic chemicals, however, the effective diffusion rate is determined partly by the diffusion properties and partly by the sorption of the organic chemicals in the soil gaseous and liquid phases.

Hydrophobic sorption onto soil organic matter is described for many chemicals and soil types (e.g., Karickhoff et al., 1979; Abdul and Gibson, 1986; Weber et al., 1992; Pignatello and Xing, 1996), while studies of vapor sorption onto dry soil mineral surfaces are limited to very few different chemicals and in most cases only TCE (e.g., Petersen et al., 1994, 1995, 1996a; Ong and Lion, 1991a,b; Shimuzu et al., 1992, 1994). Consequently, several predictive expressions to estimate hydrophobic adsorption coefficients from soil and chemical characteristics are available (e.g., Briggs, 1973; Karickhoff, 1981; Abdul et al., 1987), while it remains to be verified that recent predictive expressions for vapor sorption of TCE (e.g., Petersen et al., 1995; Poulsen et al., 1998, 2000; Yamaguchi et al., 1999; Chen et al., 2000) can be applied for other chemicals.

A correct description of diffusion and sorption processes in both the soil liquid and gaseous phases is required to accurately predict the effective diffusion of a sorbing organic chemical (Ryan and Cohen, 1990). In this study, a combined diffusion and sorption theory is derived, yielding a two-phase diffusion and two-component equilibrium sorption (DATES) model. The diffusion in the gaseous and liquid phase is predicted using recently presented gas and solute diffusivity models by Moldrup et al. (2000a) and Olesen et al. (2001). Sorption from the liquid (hydrophobic) and gaseous (vapor) phase need to be experimentally determined or estimated from empirical expressions. The DATES model is tested against short term (48 h) data from the literature for volatile (TCE and toluene) and semivolatile (lindane) organic chemicals. Finally, the DATES model is used to describe longer-term data for naphthalene (semivolatile), measured in this study, to evaluate possible effects of sorption kinetics.

	MATERIALS AND METHODS

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Radiolabeled ¹⁴C naphthalene (Sigma Chemical Co., St. Louis, MO) with a specific activity of 1.16 x 10⁹ Bq mmol^-1 (31.3 mCi mmol^-1) was used. A stock solution containing ¹⁴C naphthalene with a specific activity of 1.17 x 10⁹ Bq L^-1 (31.5 mCi L^-1) was prepared in methanol (128 mg L^-1) and a stock solution containing 10 µg cm^-3 unlabeled naphthalene in 0.01 M CaCl₂ was prepared for the adsorption or desorption, and diffusion experiments. Sieved (<2 mm) L5 was used for all experiments. Soil physical properties for L5 and chemical properties for naphthalene are shown in Tables 1 and 2, respectively. To avoid microbial degradation, the soil and the water used for naphthalene solutions were autoclaved for 2 h prior to each experiment. The autoclaving procedure did not affect the sorption results (not shown).

Naphthalene Desorption
The samples with the initial naphthalene concentration of 5.0 µg cm^-3 from the adsorption experiment were continued for 12 (2-d) desorption steps. Prior to each desorption step, the samples were centrifuged at 2665 x g for 10 min, and 20 mL of the supernatant plus two 1-mL samples for liquid-scintillation counting was replaced by 22 mL of 0.01 M CaCl₂. The amount of naphthalene adsorbed to the soil after each desorption step was calculated as the initial amount of naphthalene minus the amount removed during previous desorption steps and minus the amount present in the liquid phase. At the end of the desorption experiments, the soil was extracted with hexane to determine the mass balance. The samples were gently rotated (50 rpm) for 24h, and two 1-mL samples were removed for liquid-scintillation counting. This extraction procedure was carried out for up to 5 successive extraction steps. The average recovery was 98.2%.

Naphthalene Effective Diffusion
The effective diffusion of naphthalene was measured in L5 at a bulk density of 1.35 g cm^-3 at eight different soil-water contents, ranging from 0.05 to 0.34 cm³ cm^-3 (from air-dry soil to soil at a soil-water potential of -100 cm H₂O). Air-dry soil was mixed with water to obtain the desired water content. Subsequently, ¹⁴C labeled (466 Bq per g dry soil; 0.0126 µCi per g dry soil) and unlabeled naphthalene were added in hexane to obtain a concentration of 5 µg cm^-3 soil-water which was 50 µg g^-1 dry soil. The hexane was allowed to volatilize off before the soil was packed in air-tight (tested over the range of -0.09 to 1.3 MPa [-0.9–13 bar]) 8-cm aluminum half-cells, 2 cm at a time. Between the packing of each 2-cm layer, the surface was disturbed to obtain good contact between the layers. The half-cells were sealed with aluminum lids, and allowed to equilibrate for 10 to 14 d depending on the soil-water content. For the three highest soil-water contents, the half cells were packed with air-dry soil, and the required amount of water was added with a pipette after packing each 1-cm layer. These half-cells were allowed 2 to 3 wk of equilibration before incubation. After the equilibration period, the source and recipient half-cells (cells without addition of naphthalene) were connected and incubated horizontally at 10°C. The incubation time varied between 5 d and 6 wk depending on the water content, to obtain sufficient spreading of the concentration versus distance profile.

The cells were subsequently sliced in 0.5-cm slices (within 0–4 cm on each side of the interface) and 1.0-cm slices (within 4–8 cm distance from the interface). Between one and three replicate 1-g soil samples were transferred to glass scintillation vials, and 15 mL of Packard Ultima XR Gold scintillation counting liquid (Packard Bioscience, Groningen, The Netherlands) was added. The vials were shaken and then allowed to settle for 24 h, and the samples were then counted with 24-h intervals until maximum counts were obtained. The water content was measured in three samples from each half-cell. At the highest water content (0.34 cm³ cm^-3) 3-cm half-cells were used. The cells were packed in 1-cm layers, and sectioned in 0.3- and 0.5-cm slices after incubation.

	THEORY

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The gas and solute diffusion coefficients are governed by the length, geometry, and connectivity of the diffusive pathways in the gaseous and liquid phases, and are often predicted from empirical equations for nonsorbing chemicals (e.g., freon-12 and Cl). For predicting diffusion in the soil gaseous phase, a model for gas diffusivity in sieved, repacked soils was proposed by Moldrup et al. (2000a), the so-called water-induced linear reduction (WLR) model,

[1]

where D_P,g is the gas diffusion coefficient in soil (cm³ soil air cm^-1 soil s^-1), D_0,g is the gas diffusion coefficient in free air (cm² air s^-1), is the soil total porosity (cm³ pores cm^-3 soil), and is the air-filled porosity (cm³ soil air cm^-3 soil). Equation [1] is used in this study where all data are for repacked soil columns. A macroporosity dependent model for gas diffusivity in undisturbed soil was developed by Moldrup et al. (2000b) and should be used instead of Eq. [1] in the case of undisturbed soil systems. The second term (/) in Eq. [1] takes into account the increased tortuosity (reduced diffusivity) in a wet soil compared with a dry soil at the same air-filled porosity. The WLR model, Eq. [1], accurately predicted gas diffusivity as a function of soil air contents in 12 repacked soils with different soil textures and total porosities (Moldrup et al., 2000a).

For predicting diffusion in the soil-liquid phase, a soil-type dependent solute diffusivity model, the so-called CSIF model, was proposed by Olesen et al. (2001),

[2a]

[2b]

where D_P,l is the solute diffusion coefficient in soil (cm³ soil water cm^-1 soil s^-1), D_0,l is the solute diffusion coefficient in water (cm² water s^-1), is the soil-water content (cm³ soil water cm^-3 soil), and b is the Campbell (1974) pore-size distribution parameter. The term 0.02b in Eq. [2] describes the threshold soil-water content, _th, where the diffusion ceases because of disconnection of the diffusive pathway, and the constant (1.1) is a factor describing the meandering of the diffusive pathway. Olesen et al. (2001) suggested that the term 0.02b can be replaced by an empirical soil texture and bulk density dependent expression if the soil-water characteristic curve is not known. Equation [2] is assumed valid for both sieved, repacked, and for undisturbed soil since no significant difference in measured diffusivities for repacked and for undisturbed soil was observed by Olesen et al. (2000) and Barraclough and Tinker (1982). Equation [2] well predicted solute diffusivities for 22 repacked soils with different soil textures (Olesen et al., 2001).

The combined diffusion of a sorbing chemical in the soil gaseous and liquid phases, assuming constant and , can be described by,

[3]

[4]

where F is the chemical flux (µg cm^-2 soil s^-1); C_total is the total chemical concentration (µg cm^-3 soil); t is time (s); z is soil depth (cm soil); D_eff is the effective diffusion coefficient (cm² soil s^-1), and R_g and R_l are the retardation factors (due to sorption) for the gas and liquid phases, respectively.

Assuming immediate equilibrium among the soil phases, where Henry's constant, K_H (cm³ soil water cm^-3 soil air), describes the distribution between the liquid and gas phase, and K_d (cm³ soil water g^-1 soil) is the liquid/solid partition coefficient (assuming linear sorption/desorption behavior), the retardation factors are,

[5a]

[5b]

where _b is the soil bulk density (g soil cm^-3 soil).

At low soil-water contents, i.e., typically below a water content corresponding to three to five molecular layers of water coverage, the adsorption capacity of soils increase drastically because of chemical adsorption from the gas phase onto dry mineral surfaces (Ong and Lion, 1991a,b; Petersen et al., 1994, 1995), and Henry's law and Eq. [5] are not applicable (this is referred to as the non-Henry range in the following). Instead the adsorption can be described by the combined vapor sorption (soil mineral surface–gas phase partitioning) and hydrophobic sorption (soil organic matter–aqueous phase partitioning) coefficient, K^'_D (cm³ soil air g^-1 soil), describing the partitioning of the chemical between the gas phase and the rest of the soil system,

[6]

where C_g is the concentration in the gaseous phase (µg cm^-3 soil air), C_l is the concentration in the liquid phase (µg cm^-3 soil water), and C_S is the sorbed concentration (µg g^-1 soil). Including vapor sorption, the retardation factors can be expressed as,

[7a]

[7b]

The partitioning coefficient K^'_D can be expressed as a function of the water content by,

[8]

where K_sg is the solid/vapor phase partitioning coefficient (cm³ soil air g^-1 soil), w is the gravimetric water content (g H₂O g^-1 dry soil), is the aqueous activity coefficient [equal to 1], and is the water density (equal to 1 g cm^-3). It should be noted that Eq. [8] is valid only at low chemical vapor pressures, where chemical vapor sorption is linearly related to the vapor pressure (Amali et al., 1994). At high soil-water contents where chemical vapor sorption is negligible (K_sg = 0), Eq. [8] inserted in Eq. [7] yields Eq. [5]. Thus, Eq. [7] is generally valid in both the dry (nonHenry) and wetter (Henry) soil-water content regions.

The retardation factors given by Eq. [7] combined with Eq. [8] can be used to predict K^'_D if K_sg(w) is known. By rewriting Eq. [8], Petersen et al. (1995) proposed a semi-empirical model that can be used to describe K_sg(w) and K^'_D,

[9]

where K^'_D is the value of K^'_D at zero moisture content, describes the decrease in K^'_D with increasing w in the low water content range, and the last term of the equation describes the hydrophobic sorption in the high water content (Henry) range. In the first (vapor sorption) term, K^'_D and can be obtained either from laboratory experiments (e.g., Petersen et al., 1995, 1996a) or predicted from soil texture and surface area by empirical expressions (e.g., Poulsen et al., 1998, 2000; Yamaguchi et al., 1999).

Equation [4] together with Eq. [1], [2], [7], and [9] represent a two-phase diffusion and two-component equilibrium sorption (DATES) model, that can be used to predict the effective diffusion coefficient, D_eff, of a sorbing (hydrophobic and vapor) chemical in sieved, repacked soil.

Assuming constant and , the flux equation, Eq. [3], combined with the continuity equation yields the governing differential equation for one-dimensional diffusion of a sorbing chemical,

[10]

where the soil chemical concentration C_total = C_g + C_l + C_Sb, and D_eff is given by Eq. [4].

Predicting Short-term (48 h) Diffusion of Volatile and Semivolatile Chemicals
The WLR gas diffusivity prediction model, Eq. [1], in combination with the two- component (hydrophobic and vapor) equilibrium sorption model, Eq. [4], [7] and [9], is first tested against data from Petersen et al. (1994) for TCE and toluene effective diffusion coefficients in Yolo loam soil (Fig. 1) . For these two volatile chemicals, the contribution from liquid phase diffusion on D_eff() is negligible. The effective TCE and toluene diffusion coefficients were measured using a two-chamber diffusion apparatus consisting of two air-filled chambers separated by a packed soil column (7.57-cm diameter and 10- or 20-cm length). The incubation time was <24 h. Soil physical properties for Yolo loam and chemical properties for TCE and toluene are shown in Tables 1 and 2, respectively. From independent batch sorption experiments, Petersen et al. (1994)(1995) found K_D = 0.58 cm³ g^-1, K^'_D = 3401 cm³ g^-1, and = 37.5 for TCE and K_D = 0.87 cm³ g^-1, K^'_D = 21678 cm³ g^-1, and = 34.3 for toluene. Figure 1 shows that the effective diffusion coefficients of D_eff() for TCE and toluene are well described by the combined gas diffusion (WLR) and two-component (hydrophobic and vapor) sorption model, when the independently measured sorption characteristics [K_D, K^'_D, and ] are used. The average relative prediction error is 15% for both TCE and toluene, excluding the measurement at the lowest water content. At the lowest water content (air-dry soil) there is a relatively large deviation between measured and predicted values. Some of this deviation is because of uncertainty in determining the exact water content for air-dry soil. To illustrate that the WLR part, Eq. [1], of the DATES model is accurate, Fig. 1 shows that the WLR model well predicts the effective diffusion coefficients for freon 12 (nonsorbing).

View larger version (24K): [in this window] [in a new window]   Fig. 1. Measured freon-12, TCE, and toluene effective diffusion coefficients in Yolo loam, compared with predictions by the WLR model, Eq. [1], in combination with retardation factors calculated from Eq. [7]. For freon-12 Rg = Rl = 1. Data from Petersen et al. (1994).

View larger version (28K): [in this window] [in a new window]   Fig. 2. Comparison of measured lindane effective diffusion in Gila silt loam and predictions by the two-phase diffusion and two-component equilibrium sorption (DATES) model. The influence of the separate diffusion and sorption processes on Deff is illustrated. Data from Ehlers et al. (1969). (a) 20°C; (b) 30°C.

View larger version (23K): [in this window] [in a new window]   Fig. 3. Measured and predicted diffusivities for nonsorbing tracers (O2 and Cl) in Lerbjerg sandy clay (L5).

View larger version (26K): [in this window] [in a new window]   Fig. 4. Examples of measured concentration versus distance profiles for naphthalene diffusion at different soil-water contents () and incubation times (t). The solid lines are model fit to measured data to obtain the Deff value, while the dotted lines represent model predictions using measured gas and solute diffusivities (Fig. 3) and adsorption KD (equal to 9.5 cm3 g-1).

View larger version (24K): [in this window] [in a new window]   Fig. 5. Twenty-one day naphthalene adsorption isotherm for Lerbjerg sandy clay (L5) and subsequent 2 d desorption steps. The adsorption is approximated by a linear isotherm . A linear isotherm is plotted for the first and the last desorption step corresponding to an apparent KD value between 13 cm3 g-1 and 93 cm3 g-1 for contact times (adsorption plus desorption time) between 552 and 1080 h.

For comparison, apparent K_D values can be found from each column diffusion experiment as the K_D value in Eq. [5] that combined with the measured diffusivities of nonsorbing tracers (Fig. 3) yields the best model fit of the measured concentration versus distance profile (assuming instantaneous linear sorption equilibrium). In Fig. 6 , the apparent K_D values are shown as a function of the contact time (equal to equilibration plus incubation time) for the experiments performed in the Henry range ( > 0.17 cm³ cm^-3). It is obvious that the apparent K_D is fairly constant for short-term experiments (contact time <700 h), while an increase is seen for long-term experiments. Similarly White et al. (1999) showed that increased aging slowed the initial desorption rate of phenanthrene (C₁₄H₁₀) and also increased the resistant fraction (this would correspond to an increase in the apparent K_D if diffusion experiments were carried out). Alexander (1995) suggested that changes in extractability with residence time in soil is because of sequestration in inaccessible microsites within the soil matrix.

View larger version (24K): [in this window] [in a new window]   Fig. 6. Apparent KD value as a function of contact time (equilibration plus incubation time) for the column diffusion experiments. Only experiments in the Henry range are included ( > 0.17 cm3 cm-3). For comparison, apparent KD values from the desorption batch experiments (contact time equals adsorption plus desorption time) are shown.

In Fig. 7 , the measured effective diffusion coefficients are compared with predictions by the DATES model. The apparent K_D value derived from the short-term column experiments (17 cm³ g^-1, Fig. 5) was used. The K^'_D was expressed by Eq. [9], where the value of = 30 was estimated from the clay content using an empirical expression (based on vapor sorption of TCE) suggested by Yamaguchi et al. (1999). The value of K^'_D was fitted to 3.5 x 10⁵ to provide a good description of D_eff() in the nonHenry range. In accordance with Fig. 5, Fig. 7 shows that the effective diffusion coefficients are largely overestimated for long-term experiments. Using apparent K_D values between 35 and 70 cm³ g^-1 gave a fair description of D_eff for the long-term experiments.

View larger version (34K): [in this window] [in a new window]   Fig. 7. Effects of apparent KD on DATES predicted effective diffusion coefficients for naphthalene in Lerbjerg sandy clay(L5). The influence of each diffusion and sorption process on Deff is illustrated.

The importance of each of the diffusion and sorption processes are compared in Fig. 7, showing that diffusion in the liquid phase is unimportant as compared with diffusion in the gaseous phase except at water contents very close to water-saturation. This is in contrast to lindane diffusion in Gila silt loam, Fig. 2, where diffusion in the liquid phase was shown to be very important at > 0.25 cm³ cm^-3. Hydrophobic sorption decreases the effective diffusion by two to three orders of magnitude as compared with diffusion of a nonsorbing compound, which is similar to what was seen for lindane (Fig. 2). Vapor sorption further decreases D_eff up to around two orders of magnitude. Vapor sorption is important in a wider soil-water content range for L5 as compared with Gila silt loam, because of the difference in soil mineral surface area. This is also evident from the different values of 30 and 89 for L5 and Gila soil, respectively.

	CONCLUSIONS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS THEORY CONCLUSIONS REFERENCES

 
Recently presented gas and solute diffusivity models were combined with hydrophobic and vapor sorption models yielding a two-phase diffusion and two-component equilibrium sorption (DATES) model. The DATES model successfully described short-term (48h) effective diffusion data from the literature for volatile (TCE and toluene) and semivolatile (lindane) organic chemicals.

For longer-term experiments with naphthalene diffusion in a sandy clay, the effective diffusion could not be accurately predicted using a constant value of the hydrophobic sorption coefficient K_D in DATES. Because of sorption kinetics, both the apparent hydrophobic sorption coefficient, K_D, derived from the column diffusion experiments and K_D obtained from batch desorption experiments increased with naphthalene-soil contact time. Since sorption history is typically different in each compartment of a soil-profile, results for K_D(t) from batch and diffusion column experiments were different. Thus, a both time-dependent (kinetics) and space-dependent (sorption history) based modeling seems required to get a fully accurate description of the effective diffusive transport.

The DATES model is suggested as a model platform for further development of a two-phase, diffusive-reactive chemical transport model, and is useful to evaluate the relative importance of each of the diffusion (gaseous and liquid phase) and sorption (hydrophobic and vapor) processes for different combinations of chemicals and soil types. Using a time-dependent K_D term in DATES may provide a good preliminary evaluation of the possible effects of sorption kinetics on chemical mobility.

	ACKNOWLEDGMENTS

 
This study was funded by the Danish Technical Research Council, Research Talent Project entitled: ‘New methods for measuring and predicting liquid and gaseous phase transport properties in undisturbed soils’, grant 5P42ESO4699 from the National Institute of Environmental Health Sciences, NIH, and the U.S. EPA (R819658) Center for Ecological Health Research at University of California–Davis. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official view of the NIEHS, NIH, or EPA. The authors gratefully acknowledge a research grant from the Japanese Ministry of Education, Science, Sports, and Culture (Monbushu International Scientific Research Program: Joint Research No. 12555156).

Received for publication October 16, 2000.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS THEORY CONCLUSIONS REFERENCES

 

• Abdul, A.S., and T.L. Gibson. 1986. Equilibrium batch experiments with six polycyclic aromatic hydrocarbons and two aquifer materials. Hazard. Waste Hazard. Mater. 3:125–137.
• Abdul, A.S., T.L. Gibson, and D.N. Rai. 1987. Statistical correlations for predicting the partition coefficient for nonpolar organic contaminants between aquifer organic carbon and water. Hazard. Waste Hazard. Mater. 4:211–222.
• Alexander, M. 1995. How toxic are toxic chemicals in soil? Environ. Sci. Technol. 29:2713–2717.
• Amali, S., L.W. Petersen, D.E. Rolston, and P. Moldrup. 1994. Modeling multicomponent volatile organic and water vapor adsorption on soils. J. Hazard. Mater. 36:89–108.
• Barraclough, P.B., and P.B. Tinker. 1982. The determination of ionic diffusion coefficients in field soils. II. Diffusion of bromide ions in undisturbed soil cores. J. Soil Sci. 33:13–24.
• Briggs, G.G. 1973. A simple relationship between soil sorption of organic chemicals and their octanol/water partition coefficients. Proc. 7th Br. Insectici. Fungici. Conf. 11:475–478.
• Burgos, W.D., J.T. Novak, and D.F. Berry. 1996. Reversible sorption and irreversible binding of naphthalene and naphtol to soil: Elucidation of processes. Environ. Sci. Technol. 30:1205–1211.
• Campbell, G.S. 1974. A simple method for determining unsaturated conductivity from moisture retention data. Soil Sci. 117:311–314.
• Chen, D., D.E. Rolston, and T. Yamaguchi. 2000. Calculating partition coefficients of organic vapors in unsaturated soil and clays. Soil Sci. 165:217–225.
• Ehlers, W., W.J. Farmer, W.F. Spencer, and J. Letey. 1969. Lindane diffusion in soils: II. Water content, bulk density, and temperature effects. Soil Sci. Soc. Am. Proc. 33:505–508.
• Fuller, E.N., P.D. Schettler, and J.C. Giddings. 1966. A new method for prediction of binary gas-phase diffusion coefficients. Ind. Eng. Chem. 58:19–27.
• Hayduk, W., and H. Laudie. 1974. Prediction of diffusion coefficients for nonelectrolytes in dilute aqueous solutions. AIChE J. 20:661–615.
• Jury, W.A, D. Russo, G. Streile, and H.E. Abd. 1990. Evaluation of volatilization by organic chemicals residing below the soil surface. Water Resour. Res. 26:13–20.
• Karickhoff, S.W., D.S. Brown, and T.A. Scott. 1979. Sorption of hydrophobic pollutants on natural sediments. Water Res. 13:241–248.[ISI]
• Karickhoff, S.W. 1981. Semi-empirical estimation of sorption of hydrophobic pollutants on natural sediments and soil. Chemosphere 10:833–846.[ISI]
• Lide, D.R. (Editor in Chief). 1997. CRC Handbook of chemistry and physics. 78th edition. CRC Press, Boca Raton, FL.
• Mills, A.C., and J.W. Biggar. 1969. Solubility-temperature effect on the adsorption of gamma- and beta-BHC from aqueous and hexane solutions by soil materials. Soil Sci. Soc. Am. Proc. 33:210–216.
• Moldrup, P., C.W. Kruse, T. Yamaguchi, and D.E. Rolston. 1996. Modeling diffusion and reaction in soils: I. A diffusion and reaction corrected finite difference calculation scheme. Soil Sci. 161:347–354.
• Moldrup, P., T. Olesen, J. Gamst, P. Schjønning, T. Yamaguchi, and D.E. Rolston. 2000a. Predicting gas diffusion coefficient in repacked soil: Water-induced linear reduction model. Soil Sci. Soc. Am. J. 64:1588–1594.[Abstract/Free Full Text]
• Moldrup, P., T. Olesen, P. Schjønning, T. Yamaguchi, and D.E. Rolston. 2000b. Predicting the gas diffusion coefficient in undisturbed soil from soil water characteristics. Soil Sci. Soc. Am. J. 64:94–100.[Abstract/Free Full Text]
• Olesen, T., P. Moldrup, and J. Gamst. 1999. Solute diffusion and adsorption in six soils along a soil texture gradient. Soil Sci. Soc. Am. J. 63:519–524.[Abstract/Free Full Text]
• Olesen, T., P. Moldrup, T. Yamaguchi, H.H. Nissen, and D.E. Rolston. 2000. Modified half-cell method for measureing the solute diffusion coefficient in undisturbed, unsaturated soil. Soil Sci. 165:835–840.
• Olesen, T., P. Moldrup, T. Yamaguchi, and D.E. Rolston. 2001. Constant slope impedance factor model for predicting the solute diffusion coefficient in unsaturated soil. Soil Sci. 166:89–96.
• Ong, S.K., and L.W. Lion. 1991a. Mechanisms for trichloroethylene vapor sorption onto soil minerals. J. Environ. Qual. 20:180–188.[Abstract/Free Full Text]
• Ong, S.K., and L.W. Lion. 1991b. Effects of soil properties and moisture on the sorption of trichloroethylene vapor. Water Res. 25:29–36.
• Petersen, L.W., D.E. Rolston, P. Moldrup, and T. Yamaguchi. 1994. Volatile organic vapor diffusion and adsorption in soils. J. Environ. Qual. 23:799–805.[Abstract/Free Full Text]
• Petersen, L.W., P. Moldrup, Y.H. El-Farhan, O.H. Jacobsen, T. Yamaguchi, and D.E. Rolston. 1995. The effect of moisture and soil texture on the adsorption of organic vapors. J. Environ. Qual. 24: 752–759.[Abstract/Free Full Text]
• Petersen, L.W., Y.H. El-Farhan, P. Moldrup, D.E. Rolston, and T. Yamaguchi. 1996a. Transient diffusion, adsorption, and emission of volatile organic vapors in soils with fluctuating low water contents. J. Environ. Qual. 25:1054–1063.[Abstract/Free Full Text]
• Petersen, L.W., P. Moldrup, O.H. Jacobsen, and D.E. Rolston. 1996b. Relations between specific surface area and soil physical and chemical properties. Soil Sci. 161:9–21.
• Pignatello, J.J., and B. Xing. 1996. Mechanisms of slow sorption of organic chemicals to natural particles. Environ. Sci. Technol. 30:1–11.
• Podoll, T., K.C. Irwin, and H.J. Parish. 1989. Dynamic studies of naphthalene sorption on soil from aqeous solution. Chemosphere 18:2399–2412.
• Poulsen, T.G., P. Moldrup, T. Yamaguchi, J.W. Massmann, and J. Aa. Hansen. 1998. VOC vapor sorption in soil: Soil type dependent model and implications for vapor extraction. J. Environ. Eng. 124: 146–155.
• Poulsen, T.G., T. Yamaguchi, P. Moldrup, L.W. de Jonge, and D.E. Rolston. 2000. Predicting volatile organic vapor sorption from soil specific surface area and texture. J. Environ. Qual. 29:1642–1649.[Abstract/Free Full Text]
• Rao, P.S.C., and J.M. Davidson. 1980. Estimation of pesticide retention and transformation parameters required in non-point source pollution models. In M.R. Overcash and J.M. Davidson (ed.) Environmental impact of nonpoint source pollution. Ann Arbor Sci. Publ., Ann Arbor, MI.
• Ryan, P.A., and Y. Cohen. 1990. Diffusion of sorbed solutes in gas and liquid phases of low-moisture soils. Soil Sci. Soc. Am. J. 54:341–346.[Abstract/Free Full Text]
• Schjønning, P., I.K. Thomsen, J.P. Møberg, H. de Jonge, K. Kristensen, and B.T. Christensen. 1999. Turnover of organic matter in differently textured soils: I. Physical characteristics of structurally disturbed and intact soils. Geoderma 89:177–198.
• Shimuzu, Y., N. Takei, and Y. Tereshima. 1992. Sorption of organic pollutants from vapor phase: The effects of natural solid characteristics and moisture content. Water Sci. Technol. 26:79–87.
• Shimuzu, Y., N. Takei, and Y. Tereshima. 1994. Roles of solid components on the sorption of trichloroethylene (TCE) onto solids from the vapor phase. Water Sci. Tech. 30:1–11.
• Snell, F.D., and L.S. Ettre. 1972. Encyclopedia of industrial chemical analysis, Vol. 16. Wiley-InterScience Publishers, New York.
• Spencer, W.F., and M.M. Cliath. 1983. Desorption of lindane from soil as related to vapor density. Soil Sci. Soc. Am. Proc. 34:574–578.
• Weber, W.J., P.M. McGinley, and L.E. Katz. 1992. A distributed reactivity model for sorption by soils and sediments. 1. Conceptual basis and equilibrium assessments. Environ. Sci. Technol. 26:1955–1962.
• White, J.C., M. Hunter, N. Kyoungphile, J.J. Pignatello, and M. Alexander. 1999. Correlation between biological and physical availabilities of phenanthrene in soils and soil humin in aging experiments. Environ. Toxicol. Chem. 18:1720–1727.
• Yamaguchi, T., T. Poulsen, P. Moldrup, and T. Fukushima. 1999. Predictive model for adsorption of volatile organic chemicals in soils. Environ. Eng. Research 36:477–482.

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