Journal of Environmental Quality 31:1716-1721 (2002)
© 2002 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
TECHNICAL REPORTS
Vadose Zone Processes and Chemical Transport
Sorption and Transport Behavior of Naphthalene in an Aggregated Soil
Jaehoon Lee*,a,
Lakhwinder S. Hundalb,
Robert Hortonc and
Michael L. Thompsonc
a Biosystems Engineering and Environmental Science Dep., The University of Tennessee, Knoxville, TN 37996
b Dep. of Civil Engineering and Geological Sciences, University of Notre Dame, Notre Dame, IN 46556
c Dep. of Agronomy, Iowa State University, Ames, IA 50011
* Corresponding author (jhlee{at}utk.edu)
Received for publication November 20, 2001.
 |
ABSTRACT
|
|---|
Soil solution chemistry influences the sorption and transport behavior of hydrophobic organic compounds (HOCs) in soil. We used both batch and column studies to investigate the influence of ionic strengths (0.03 and 1.5 M) and flow velocities (12 and 24 cm h-1) on sorption and transport of naphthalene (NAP) in aggregated soil. Sorption parameters such as the Freundlich coefficient (Kf) and exponent (n) calculated from batch studies and column experiments were also compared. Retardation of NAP transport was greater at higher solution ionic strength, which may be attributed to greater sorption affinity due to enhanced aggregation of the sorbent. The effect of ionic strength on sorption of NAP observed in the batch study was consistent with the results from the column study. The Kf and n values obtained from the batch study for the two ionic strengths ranged from 7.8 to 13.7 and 0.68 to 0.80, respectively, whereas the Kf and n values obtained from the column study ranged from 7.9 to 9.9 and 0.73 to 0.85, respectively. The effluent breakthrough curve (BTC) of NAP at a flow rate of 24 cm h-1 showed significant chemical and physical nonequilibrium behavior, implying that a considerable amount of sorption in aggregated soil was time dependent when flow was relatively fast. The BTCs calculated with the parameters determined from batch studies compared poorly with the measured BTCs. The potential for nonequilibrium transport should be incorporated in models used for predicting the fate and transport of HOCs. Furthermore, caution is required when extrapolating the results from batch studies, especially for aggregated soils.
Abbreviations: BTC, effluent breakthrough curve • HOC, hydrophobic organic compound • NAP, naphthalene
|
INTRODUCTION
|
|---|
SOIL AND GROUND WATER contamination by HOCs has become a national problem (National Research Council, 1994, 1997). Reliable predictions of the fate and transport of HOCs in soils under various conditions are critical for proper risk assessment and remediation. Although extensive studies have been conducted to evaluate sorption and desorption kinetics of polycyclic aromatic hydrocarbons (PAHs) in soil and sediments (e.g., Schlautman and Morgan, 1994; Kan et al., 1997; Totsche et al., 1997; Kögel-Knabner et al., 2000; Karapanagioti and Sabatini, 2000), studies investigating the influence of solution chemistry on sorption and transport behavior of HOCs are few. Soil solution chemistry such as pH and ionic strength as well as flow conditions such as pore water velocity are important factors that influence the sorption and transport of HOCs in soils.
Kan and Tomson (1990) studied the effect of solution pH on the sorption and transport of NAP in saturated aquifer material. They measured a series of NAP breakthrough curves at pH 5, 7, and 9, and reported less sorption with increasing pH. They related the result to the surface charge of soil humic materials. With increasing surface charge, humic materials are thought to become less coiled by charge repulsion. Increasing surface charge with increasing pH could thus make humic materials more hydrophilic, reducing the sorption affinity for hydrophobic solutes like NAP. Stauffer and MacIntyre (1986) examined the sorption of four low-polarity organic compounds on three oxide minerals and on a low-carbon aquifer material. For two of the four sorbents, they observed slightly increased sorption with increasing ionic strength. This result was mainly due to the inconsistent solubility of the different ionic strengths, and they attributed this to a "salting out" effect (i.e., lower aqueous solubility of HOCs at higher ionic strength).
It is also well documented that the transport of most solutes is a function of pore water velocity (e.g., Bouchard et al., 1988; Brusseau, 1992; Kelsey and Alexander, 1995; Langner et al., 1998). But the influence of the ionic strength and pore water velocity on sorption and transport of HOCs may be amplified and further complicated in structured soils. In aggregated soils, not all of the soil particles and pores appear to be equally involved in chemical–physical processes of solutes (Pignatello, 1989; Selim and Ma, 1998). Soil aggregates can create a wide range of variation in sorption–desorption and transport of solutes due to the intra-aggregate pore structure as well as the chemical nature of soil organic matter (Carmo et al., 2000) and accessibility to clay surfaces (Hundal et al., 2001). These phenomena result in physical and chemical nonequilibrium (Selim and Ma, 1998).
Many researchers have attempted to compare the sorption parameters of HOCs calculated from batch and column studies, but their findings have been inconsistent. For example, Bayard et al. (1998) reported that NAP sorption parameters obtained from column studies were in good agreement with the results obtained in batch studies. MacIntyre et al. (1991) also reported that good agreement was found among NAP sorption coefficients measured by batch, column, and dynamic box methods (miniature unconfined aquifer system with sampling wells). In contrast, Maraqa et al. (1998) reported that their batch study consistently overestimated retardation coefficients of benzene and dimethylphthalate compared with the results from their column study.
Therefore, there is a great need to investigate further the influence of ionic strength and flow velocity on sorption and transport of NAP in aggregated soil materials with both batch and column techniques. The objectives of this study were to (i) examine the influence of ionic strength (i) and pore water velocity (v) on sorption and transport of NAP in an aggregated soil and (ii) compare sorption parameters obtained from batch experiments with those obtained from column experiments. Simulation studies were conducted to predict effluent breakthrough curves with batch-determined sorption parameters.
|
MATERIALS AND METHODS
|
|---|
Sorbent
All experiments were performed with 1- to 2-mm aggregates from the A horizon of a Sparta soil (sandy, mixed, mesic Entic Hapludoll) collected near Ames, Iowa. After collection, the soil was air-dried and sieved through 1- to 2-mm (U.S. no. 18 and 10) standard sieves. This soil contained 17% clay, 34% silt, and 49% sand and had 19 g kg-1 organic C, C to N ratio of 6.5, and a soil pH of 6.2. The dominant clay mineral was smectite. A more detailed physical and chemical description of the soil material can be found in Carmo et al. (2000).
Batch Experiments
Batch sorption studies were conducted with NAP (99% purity) purchased from Aldrich Chemical (Milwaukee, WI). The stock solutions were prepared by shaking excess amounts of NAP overnight in electrolyte solution (0.01 or 0.5 M CaCl2 + 0.01 M NaN3). The solutions were subsequently filtered with Whatman (Maidstone, UK) no. 42 filter paper to remove insoluble NAP. Eight different NAP solutions with concentrations ranging from 2 to 60% of the original stock solution concentration were prepared by diluting with the background electrolyte solution. These concentrations are equivalent to 0.5 and 20 mg L-1, respectively. To eliminate any possibility of "salting out" of higher ionic strength on NAP solubility, we used only 60% of the maximum aqueous solubility of NAP, 31.7 mg L-1 at 20°C, in this study, which allowed a strict comparison of NAP sorption behavior at two ionic strengths.
Approximately 200 mg of 1- to 2-mm aggregates separated from Sparta soil were weighed into 10-mL Pyrex centrifuge tubes and a 10-mL aliquot of NAP solution was added. The centrifuge tubes were tightly sealed with Teflon-lined screw caps. Teflon tape was used on the threads of the centrifuge tubes to minimize possible losses by volatilization. Controls without any soil materials were also prepared in the same way and used to account for possible losses due to volatilization and sorption of NAP to the centrifuge tubes. The batch experiments were conducted in triplicate.
The samples were allowed to equilibrate in the dark at 25°C for 48 h by continuous mixing on a reciprocating shaker. After the 48-h equilibration period, the samples (including controls) were centrifuged for 30 min at 2100 x g, and the supernatant was sampled for analysis with high performance liquid chromatography (HPLC). Sorption data were calculated on a mass basis. For HPLC analysis, a 1-mL aliquot of the clear supernatant was placed into a 2-mL amber borosilicate glass vial, which was sealed with an Al-crimp cap and Teflon-lined rubber-butyl septum. The HPLC system (Hewlett-Packard [Palo Alto, CA] 1050 series) consisted of an Alltech (Deerfield, IL) C-18 reversed phase column and a mixture of acetonitrile and H2O (90:10) mobile phase at a flow rate of 1.2 mL min-1. The analytes were detected spectrophotometrically with a variable-wavelength UV-visible detector at 254 nm and quantified by comparisons with high-purity standards of NAP prepared in HPLC-grade methanol. Details of HPLC analysis and analytical conditions are given elsewhere (Carmo et al., 2000).
The Freundlich equation was used to model the sorption data with nonlinear regression. The form of Freundlich equation used was:
 | [1] |
where Cs is the mass of solute sorbed per unit dry weight of solid (mg kg-1), Ce is the liquid-phase equilibrium concentration in solution (mg L-1), Kf is a constant related to sorbent capacity, and n is a constant related to the degree of deviation from isotherm linearity. The Freundlich parameters, Kf and n, were calculated with a nonlinear regression technique, Marquardt–Levenberg, with SigmaStat (SPSS Science, 2001).
Column Transport Experiments
An on-line high performance liquid chromatography system that allowed continuous sampling and analysis of volatile chemicals was used for the miscible-displacement experiments. Briefly, the flow-through system consisted of a binary pump and a soil column, and the analytical system consisted of an isocratic pump, a C18 reverse phase column, and a diode array detector. The effluent was analyzed for NAP at certain intervals and was regulated by an electronically controlled six-port valve. Details of this system are given elsewhere (Casey et al., 2000). Four soil columns were prepared by uniformly packing the Sparta 1- to 2-mm aggregates into stainless steel columns (22-mm diameter and 124-mm length). Placed at each column end were distribution plates, wire mesh, and a 2-µm frit, all made of stainless steel. The distribution plates and wire mesh assured flow uniformity and distribution in and out of each soil column, while the frits prevented large particles from leaving the column. Calculated with a particle density of 2.65 Mg m-3, the bulk density ranged from 0.96 to 1.04 Mg m-3 and porosity ranged from 0.61 to 0.64.
Effect of Ionic Strength
Solutions of 0.01 and 0.5 M CaCl2, equivalent to 0.03 and 1.5 M ionic strengths, were used for the column transport studies to compare with the results from the batch studies. Each soil column was slowly saturated (flow rate = 0.01 mL min-1) with either 0.03 or 1.5 M ionic strength solution from the bottom. After saturation, each column was placed horizontally and connected to the on-line high performance liquid chromatography system. The column was flushed with at least 10 pore volumes of the appropriate CaCl2 solution to establish steady state conditions. A step pulse of NAP solution (20 mg L-1) was introduced into the column for about 20 pore volumes. Then the column was flushed with either 0.03 and 1.5 M ionic strength solution for another 20 pore volumes. After each 0.05 pore volume increment, column effluent was analyzed with the on-line high performance liquid chromatography.
Effect of Pore Water Velocity
Two different pore water velocities (v), 12 and 24 cm h-1, were used with both 0.03 and 1.5 M ionic strengths. Effluent NAP BTCs were obtained with the two different pore water velocities. Thus, a total of eight BTCs were generated: two ionic strengths, two flow velocities, and two replicates.
A computer model, HYDRUS-1D Version 2.0 (
im
nek et al., 1998), was used to curve-fit measured breakthrough curves by optimizing parameters so that the model's solution fit to the measured data. Freundlich sorption coefficients, Kf and n, and the hydrodynamic dispersion coefficient (D), were calculated and the estimated Kf and n were compared with those determined from batch experiments.
Breakthrough Curve Predictions
The batch-determined Kf and n values and column-determined D were used to calculate effluent BTCs of NAP with HYDRUS-1D. By comparing calculated BTCs with the observed BTCs, we tested how well the Kf and n obtained from batch studies could be used to predict effluent NAP BTCs from column studies. For quantitative comparison, the root mean square error (RMSE) was computed for the calculated and observed BTCs following the method of Willmott et al. (1985).
|
RESULTS AND DISCUSSION
|
|---|
Batch Experiments
Figure 1
shows NAP sorption isotherms for Sparta soil materials obtained for 0.03 and 1.5 M ionic strengths. In this study, the Freundlich equation adequately described the sorption of NAP, with an average coefficient of determination (r2) of 0.99 for the fitted curves (Table 1). The Kf value of the isotherm for the 1.5 M ionic strength was greater than the Kf value at 0.03 M ionic strength.
View larger version (17K):
[in this window]
[in a new window]
|
Fig. 1. Isotherms for the sorption of naphthalene for two ionic strengths (0.03 and 1.5 M). Nonlinear fit of a Freundlich equation (Eq. [1]) to the sorption data is represented by the solid lines.
|
|
View this table:
[in this window]
[in a new window]
|
Table 1. Sorption and transport parameters from batch and column studies for different ionic strengths and pore water velocities.
|
|
Previous studies have reported both linear and nonlinear sorption isotherms to describe the retention of NAP by soil materials and sediments in aqueous systems. The degree of nonlinearity is an index of the heterogeneity of sorption sites or mechanisms. A number of mechanisms have been suggested to explain nonlinear isotherms in the sorption of polycyclic aromatic hydrocarbons by soil materials. These include incomplete attainment of true equilibrium—such that the rate of desorption is slower than the rate of sorption (Pignatello and Xing, 1996), sorption to multiple domains of organic matter with differing affinities for polycyclic aromatic hydrocarbons (Weber and Huang, 1996; Chefetz et al., 2000), sorption-induced swelling of organic domains (Chefetz et al., 2000), retention by a "high-surface-area carbonaceous material" such as soot (Chiou and Kile, 1998), filling of micro- and nanopores (Xia and Ball, 1999), and competition from soil lipids for sorption sites (Kohl and Rice, 1999). The distinction between mechanisms related to the physical organization of the soil material and its chemical composition is extremely difficult to draw. In many soil systems, multiple sorption mechanisms probably occur simultaneously, and their relative importance is unknown.
Our experiments were not designed to definitively identify any particular sorption mechanism. The sorption isotherms reported here were more nonlinear at higher ionic strength than at lower ionic strength (n = 0.68 vs. 0.80), suggesting that sorption mechanisms or sites were more heterogeneous at higher ionic strength. Because the chemical composition did not vary with ionic strength, an explanation for the increased nonlinearity may be related to the physical organization of the soil materials. We hypothesize that larger, more stable soil aggregates at higher ionic strength probably have a more heterogeneous distribution of pores in terms of size and continuity, leading to concentration-dependent local equilibrium and the lower value of n.
Column Transport Experiments
Effect of Ionic Strength
Figure 2
shows the effluent BTCs of NAP input for the 0.03 and 1.5 M ionic strengths. After applying 20 pore volumes of NAP solution, the BTC for lower ionic strength had earlier breakthrough and higher concentration of NAP as compared with the BTC for higher ionic strength. The total amount of NAP in the effluent after 20 pore volumes was lower for higher ionic strength than for lower ionic strength. Greater retardation of NAP BTC for the higher ionic strength can be attributed to enhanced sorption affinity. This observation was consistent with the batch studies.
View larger version (20K):
[in this window]
[in a new window]
|
Fig. 2. Naphthalene breakthrough curves (BTC) for 0.03 and 1.5 M ionic strengths. The pore water velocity of the columns was 24 cm h-1.
|
|
Effect of Pore Water Velocity
Figure 3
shows the influence of two different flow velocities and ionic strengths on the effluent BTCs of NAP. The BTCs at 24 cm h-1 showed earlier breakthrough and lower total concentrations after 20 pore volumes compared with the BTCs at 12 cm h-1 for both ionic strengths. This type of behavior was anticipated because greater dispersion of flow pathways caused by the fast flow velocity may restrain NAP interactions with sorbent in both space and time, resulting in reduced sorption. The observation was consistent for the desorption process–decreasing limb of the BTCs. It is noteworthy that the maximum relative concentrations on the y axes for all BTCs were less than unity at 20 pore volumes, having an average of 0.89. This implied that true equilibrium was not reached during the transport experiments. This may, in part, explain why the sorption parameters determined from the batch studies poorly predicted the effluent BTCs (Langner et al., 1998; Maraqa et al., 1998). Generally, BTCs obtained from column studies represent dynamic and often nonequilibrium sorption and transport processes of solutes in soils while batch studies characterize an equilibrium process. Further discussion is included in the Breakthrough Curve Predictions section, below.
Table 1 shows the Freundlich parameters and other transport parameters determined from the effluent BTCs in combination with HYDRUS-1D. For both flow velocities, the Kf values obtained at higher ionic strength were larger than those obtained at lower ionic strength, which supports the results obtained from the batch study. The transport-modeled n values for the high and low ionic strengths were not significantly different. The 95% confidence intervals (CI) of n values for lower ionic strength encompassed the CI values for higher ionic strength, and vice versa.
The sorption parameters obtained from the column study for the BTCs at pore water velocity of 12 cm h-1 were generally in good agreement with those obtained from the batch study. However, for the flow velocity of 24 cm h-1, the BTCs were best fitted only when a two-site chemical nonequilibrium model was used. When an equilibrium model was used, the 95% confidence intervals of estimated parameters were very large, indicating inaccuracy of fitting. In the two-site sorption nonequilibrium model (Selim et al., 1977), sorption on labile exchange sites (Type 1) was assumed to be instantaneous, while sorption on remaining Type 2 sites was considered to be time dependent. In the two-site model, the total sorbed concentration, S, is the sum of sorbed concentrations on the Type 1 and Type 2 sites:
 | [2] |
where S1 and S2 represent sorption (mg kg-1) on Type 1 and Type 2 sites, respectively. Because Type 1 sites are always at equilibrium, the sorption rate for the Type 1 equilibrium sites is:
 | [3] |
Sorption on the Type 2 nonequilibrium sites is assumed to follow first-order kinetics. Ignoring production and decay, the one-dimensional, advective–dispersive transport under steady state flow conditions can be written:
 | [4] |
 | [5] |
where C is the solute concentration (mg L-1), t is the time (h), x is the distance (cm), v is the pore water velocity (cm h-1), f represents the fraction of exchange sites assumed to be at equilibrium with the solution phase, 
is the first-order kinetic rate constant for sorption, 
is the bulk density (Mg m-3), k is a distribution coefficient, 
is volumetric water content, and S2 is the concentration in the sorbed phase for Type 2 sites (mg kg-1). The average value of the estimated f was 0.5, implying that a considerable amount of sorption was rate limited when the flow velocity was 24 cm h-1. This observation reconfirms that chemical and/or physical nonequilibrium of solute transport must be included in modeling and interpreting transport data, especially for aggregated sorbents. Pignatello and Xing (1996) reviewed the causes of slow sorption and desorption processes of organic solutes. A list of sorbent properties that might favor nonequilibrium sorption–desorption processes includes: association of HOCs with different functional groups in soil organic matter, sorption to specific sites, soluble complex formation in solution, the presence of steric hindrances from fine pores of varying size, and complex microscopic hydrodynamic conditions near particle surfaces. The nonequilibrium sorption behavior of NAP in this study seems to be associated with latter two processes.
In addition to Kf and n, the hydrodynamic dispersion coefficient (D) was calculated for the column study. The values of D ranged from 48 to 110 cm2 h-1 with an average of 77 cm2 h-1. The average dispersivity (d = D/v) value obtained from conservative tracer (Cl-) BTC experiments for the same soil columns was 3.4 ± 0.2 cm. The D values obtained from the two different ionic strengths were not significantly different from each other (Table 1). But D values obtained from BTCs at 24 cm h-1 were significantly larger than those obtained from BTCs at 12 cm h-1. The results indicate that there was a greater range of dispersion of NAP in the flow regime as it flows through the column when flow was relatively fast.
Breakthrough Curve Predictions
It is beneficial but challenging to accurately predict transport of solutes with limited information about the transport system. Several mechanistic models are available for predicting solute transport in a soil with the relevant physical and chemical parameters. Figure 4
shows calculated NAP BTCs along with measured BTCs. The parameters obtained from the batch study—which is easier to conduct than a column study—were used to calculate the effluent BTCs. The calculated BTCs compared poorly with the measured BTCs, except for the BTCs obtained from 0.03 M ionic strength and 12 cm h-1 pore water velocity where the calculated and predicted BTCs were in relatively good agreement. In particular, BTCs at 24 cm h-1 were poorly predicted (root mean square error = 0.34). Note that f was set to 1 and was set to 0 for the calculation of BTCs at 24 cm h-1. Thus, the poor prediction of BTCs for the higher velocity was because the chemical and physical nonequilibrium were not accounted for. This was somewhat anticipated because the batch-determined parameters represent equilibrium conditions while the column-determined parameters represent dynamic and nonequilibrium sorption and transport conditions.
View larger version (29K):
[in this window]
[in a new window]
|
Fig. 4. Observed and predicted naphthalene breakthrough curves (BTC). Predicted BTCs were calculated with the sorption parameters, Kf and n, determined from the batch study with the hydrodynamic dispersion coefficient (D) obtained from the column study.
|
|
In summary, results from this study demonstrate that ionic strength and pore water velocity have a significant effect on sorption and transport of NAP in an aggregated soil. Predictions of BTCs based on batch-determined parameters did not agree with the measured BTCs, especially at high ionic strength or when pore water velocity was relatively fast. Thus, these factors should be incorporated for reliable risk assessment and efficient remediation of contaminated sites. The potential for nonequilibrium sorption and transport processes should be accounted for in modeling of NAP behavior in heterogeneous sorbents.
|
ACKNOWLEDGMENTS
|
|---|
The authors thank J. imnek for help on HYDRUS-1D modeling, Robert P. Ewing for helpful discussion on column study, and Linda Schultz for laboratory assistance. This is Journal Paper no. J-19227 of the Iowa Agriculture and Home Economics Experiment Station, Ames, IA, and Project no. 3287, supported by Hatch Act and State of Iowa funds. This work was funded by the Iowa State University Agronomy Department Endowment.
|
REFERENCES
|
|---|
- Bayard, R., L. Barna, B. Mahjoub, and R. Gourdon. 1998. Investigation of naphthalene sorption in soils and soil fractions using batch and column assays. Environ. Toxicol. Chem. 17:2383–2390.
- Bouchard, D.C., A.L. Wood, M.L. Campbell, P. Nkedi Kizza, and P.S.C. Rao. 1988. Sorption nonequilibrium during solute transport. J. Contam. Hydrol. 2:209–223.
- Brusseau, M.L. 1992. Nonequilibrium transport of organic chemicals: The impact of pore-water velocity. J. Contam. Hydrol. 9:353–368.
- Carmo, A.M., L.S. Hundal, and M.L. Thompson. 2000. Sorption of hydrophobic organic compounds by soil materials: Application of unit equivalent Freundlich coefficients. Environ. Sci. Technol. 34:4363–4369.
- Casey, F.X.M., R.P. Ewing, and R. Horton. 2000. Automated system for miscible displacement through soil of multiple volatile organic compounds. Soil Sci. 165:841–847.
- Chefetz, B., A.P. Deshmukh, P.G. Hatcher, and E.A. Guthrie. 2000. Pyrene sorption by natural organic matter. Environ. Sci. Technol. 34:2925–2930.
- Chiou, C.T., and D.E. Kile. 1998. Deviations from sorption linearity on soils of polar and nonpolar organic compounds at low relative concentrations. Environ. Sci. Technol. 32:338–343.
- Hundal, L.S., M.L. Thompson, D.A. Laird, and A.M. Carmo. 2001. Sorption of phenanthrene by reference smectites. Environ. Sci. Technol. 35:3456–3461.[Medline]
- Kan, A.T., G. Fu, M.A. Hunter, and M.B. Tomson. 1997. Irreversible adsorption of naphthalene and tetrachlorobiphenyl to Lula and surrogate sediments. Environ. Sci. Technol. 31:2176–2185.
- Kan, A.T., and M.B. Tomson. 1990. Effect of pH concentration on the transport of naphthalene in saturated aquifer media. J. Contam. Hydrol. 5:235–251.
- Karapanagioti, H.K., and D.A. Sabatini. 2000. Impacts of heterogeneous organic matter on phenanthrene sorption: Different aquifer depths. Environ. Sci. Technol. 34:2453–2460.
- Kelsey, J.W., and M. Alexander. 1995. Effect of flow rate and path length of p-nitrophenol biodegradation during transport in soil. Soil. Sci. Soc. Am. J. 59:113–117.[Abstract/Free Full Text]
- Kohl, S.D., and A.J. Rice. 1999. Contribution of lipids to the nonlinear sorption of polycyclic aromatic hydrocarbons to soil organic matter. Org. Geochem. 30:929–936.
- Kögel-Knabner, I., K.U. Totsche, and B. Raber. 2000. Desorption of polycyclic aromatic hydrocarbons from soil in the presence of dissolved organic matter: Effect of solution composition and aging. J. Environ. Qual. 29:906–916.[Abstract/Free Full Text]
- Langner, H.W., W.P. Inskeep, H.M. Gaber, W.L. Jones, B.S. Das, and J.M. Wraith. 1998. Pore water velocity and residence time effects on the degradation of 2,4-D during transport. Environ. Sci. Technol. 32:1308–1315.
- MacIntyre, W.G., T.B. Stauffer, and C.P. Antworth. 1991. A comparison of sorption coefficients determined by batch, column, and box methods on a low organic carbon aquifer material. Ground Water 29:908–913.
- Maraqa, M.A., X. Zhao, R.B. Wallace, and T.C. Voice. 1998. Retardation coefficients of nonionic organic compounds determined by batch and column techniques. Soil. Sci. Soc. Am. J. 62:142–152.[Abstract/Free Full Text]
- National Research Council. 1994. Alternatives for ground water cleanup. Natl. Academy Press, Washington, DC.
- National Research Council. 1997. Innovations in ground water and soil cleanup: From concept to commercialization. Natl. Academy Press, Washington, DC.
- Pignatello, J.J. 1989. Sorption dynamics of organic compounds in soils and sediments. p. 45–80. In B.L. Sawhney and K. Brown (ed.) Reactions and movement of organic chemicals in soil. SSSA Spec. Publ. 22. SSSA, Madison, WI.
- Pignatello, J.J., and B.S. Xing. 1996. Mechanisms of slow sorption of organic chemicals to natural particles. Environ. Sci. Technol. 30:1–11.
- Schlautman, M.A., and J.J. Morgan. 1994. Sorption of perylene on a nonporous inorganic silica surface: Effects of aqueous chemistry on sorption rates. Environ. Sci. Technol. 28:2184–2190.
- Selim, H.M., J.M. Davidson, and P.S.C. Rao. 1977. Transport of reactive solutes through multilayered soils. Soil. Sci. Soc. Am. J. 41:3–10.[Abstract/Free Full Text]
- Selim, H.M., and L. Ma. 1998. Physical nonequilibrium in soils: Modeling and application. Ann Arbor Press, Chelsea, MI.
- SPSS Science. 2001. SigmaStat. Version 2.03. SPSS, Chicago, IL.
- imnek, J., M. Sejna, and M.T. van Genuchten. 1998. The HYDRUS-1D software package for simulating the one-dimensional movement of water, heat, and multiple solutes in variably-saturated media. U.S. Salinity Lab., Riverside, CA.
- Stauffer, T.B., and W.G. MacIntyre. 1986. Sorption of low-polarity organic compounds on oxide minerals and aquifer material. Environ. Toxicol. Chem. 5:949–955.
- Totsche, K.U., J. Danzer, and I. Kögel-Knabner. 1997. Dissolved organic matter–enhanced retention of polycyclic aromatic hydrocarbons in soil miscible displacement experiments. J. Environ. Qual. 26:1090–1100.[Abstract/Free Full Text]
- Weber, W.J., Jr., and W.L. Huang. 1996. A distributed reactivity model for sorption by soils and sediments. 4. Intraparticle heterogeneity and phase-distribution relationships under nonequilibrium conditions. Environ. Sci. Technol. 30:881–888.
- Willmott, C.J., S.G. Ackleson, R.E. Davis, J.J. Feddema, K.M. Klink, D.R. Legates, and C.M. Rowe. 1985. Statistics for the evaluation and comparison of models. J. Geophys. Res. 90:8995–9005.
- Xia, G., and W.P. Ball. 1999. Adsorption-partitioning uptake of nine low-polarity organic chemicals on a natural sorbent. Environ. Sci. Technol. 33:262–269.
TOP
ABSTRACT
INTRODUCTION
