WATER RESOURCES RESEARCH, VOL. 41, W10404, doi:10.1029/2004WR003675, 2005

Straining of colloids at textural interfaces
Scott A. Bradford,1 Jirka Simunek,2 Mehdi Bettahar,3 Yadata F. Tadassa,1Martinus T. van Genuchten,1 and Scott R. Yates1
Received 22 September 2004; revised 22 April 2005; accepted 23 June 2005; published 11 October 2005.

[1] Although natural soil and aquifer systems often contain layers and lenses ofcontrasting soil texture, relatively little research has focused on the mechanisms of colloid
deposition at textural interfaces. Saturated column studies were undertaken to characterize
the straining behavior of negatively charged latex colloids (1.1 and 3.0 mm) at texturalinterfaces. Mechanisms of colloid transport and retention were deduced from measured
effluent concentration curves, final spatial distributions in the columns, mass balance
information, microscopic examination of deposition behavior in micromodel experiments,
and numerical modeling. Transport and deposition of colloids were found to be highly
dependent upon the textural interface. Deposition of colloids in a given sand was always
most pronounced at the sand (inlet) surface. Here colloids enter a new pore network andare more likely to encounter smaller pores or dead-end regions of the pore space that
contribute to straining. Less deposition occurred at textural interfaces within the column
than at the sand surface. We believe that this is due to the fact that advection, dispersion,and size exclusion tend to confine colloid transport to the larger pore networks, thus
limiting accessibility to straining sites. Increasing the textural contrast at an interface
produced greater colloid deposition when water flowed from coarser- to finer-textured
sands. Conversely, when water flowed from finer- to coarser-textured sands, little
deposition occurred. Numerical modeling indicates the need to account for blocking(filling) and accessibility of straining sites in layered systems. A previously developed
straining model was modified to account for this behavior.
Citation: Bradford, S. A., J. Simunek, M. Bettahar, Y. F. Tadassa, M. T. van Genuchten, and S. R. Yates (2005), Straining of colloids
at textural interfaces, Water Resour. Res., 41, W10404, doi:10.1029/2004WR003675.

1. Introduction[2] Considerable research has been devoted to the transport and fate of colloids in porous media [Schijven and
Hassanizadeh, 2000; Harvey and Harms, 2002; Jin and
Flury, 2002; Ginn et al., 2002; de Jonge et al., 2004;
McCarthy and McKay, 2004; DeNovio et al., 2004].
Knowledge of mechanisms that control colloid migrationis required to protect drinking water supplies from
pathogenic microorganisms [Bitton and Harvey, 1992], todevelop engineered bioaugmentation and bioremediation
strategies [Wilson et al., 1986; Rockhold et al., 2004], andto devise microbially enhanced oil recovery systems[MacLeod et al., 1988]. The environmental fate of manyorganic and inorganic contaminants can also be influenced
by colloid-facilitated transport due to partitioning onto highsurface area colloids that are mobile [Kretzschmar et al.,
1999; Ouyang et al., 1996; de Jonge et al., 2004].
[3] Attachment (adsorption) is a mechanism for colloid
retention that involves collision with and fixation to theporous medium. Attachment depends on colloid-colloid,1
George E. Brown, Jr., Salinity Laboratory, ARS, USDA, Riverside,
California, USA.
2
Department of Environmental Sciences, University of California,
Riverside, California, USA.
3
Parsons, Pasadena, California, USA.

Copyright 2005 by the American Geophysical Union.
0043-1397/05/2004WR003675$09.00

colloid-solvent, and colloid-porous media interactions[Elimelech and O’Melia, 1990]. Clean bed attachment
behavior is traditionally described as a first-order process,which implies that retained colloids will be distributed in an
exponential manner versus distance. Attachment theory
predicts an optimum size for colloid transport in a given
porous medium, with diffusion controlling the transport ofsmaller particles, and sedimentation and interception thetransport of larger colloids [Logan et al., 1995].
[ 4 ] Experimental effluent concentration curves andspatial distributions of retained colloids in porous media
have not always been in agreement with colloid attachment
theory [Camesano and Logan, 1998; Bolster et al., 1999;
Redman et al., 2001; Bradford et al., 2002; Tufenkji et al.,
2003; Li et al., 2004; Tufenkji and Elimelech, 2005]. Someof these discrepancies have been attributed to soil surface
roughness [Redman et al., 2001; Kretzschmar et al., 1997]
and charge variability [Johnson and Elimelech, 1995],
heterogeneity in colloid characteristics [Bolster et al.,
1999; Li et al., 2004], colloid detachment [Tufenkji etal., 2003], time-dependent attachment behavior [Johnson
and Elimelech, 1995], deposition of colloids in a secondary
energy minimum [Redman et al., 2004; Tufenkji andElimelech, 2005], and straining [Bradford et al., 2002,
2003, 2004; Li et al., 2004; Tufenkji et al., 2004; Bradford
and Bettahar, 2005; Foppen et al., 2005].
[5] Straining involves the entrapment of colloids in down
gradient pores and at grain junctions that are too small toallow particle passage. The critical pore size for straining

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will depend on the size of the colloid and the pore size
distribution of the medium [McDowell-Boyer et al., 1986;
Bradford et al., 2002, 2003]. Matthess and Pekdeger [1985]
presented theoretical criteria suggesting that the ratio of thecolloid (dc) to median grain diameter (d50) needs to begreater than 0.18 for straining to occur in uniform sand;increasing sand gradation would somewhat lower thisthreshold. For this reason most previous studies on colloidtransport have neglected straining as a mechanism forretention [cf. Schijven and Hassanizadeh, 2000; Harveyand Harms, 2002; Jin and Flury, 2002; Ginn et al., 2002].
Experimental observations, however, suggest that straining
may occur for much lower values of dc/d50. Sakthivadivel[1966, 1969] reported that straining produced a permeability
reduction of between 10 and 50% when dc/d50 was around0.05. Bradford et al. [2002, 2003] observed systematic
trends of lower effluent concentrations and increasing
colloid retention in sand near the column inlet withdecreasing sand grain size or increasing colloid size.
Mathematical modeling indicated that straining alreadyoccurred for dc/d50 > 0.005. Data from Li et al. [2004]
indicates that straining may have occurred for dc/d50 =0.002, but decreased with increasing pore water velocity.
Results from Tufenkji et al. [2004] suggest that irregularityof the sand grain shape significantly contributes to thestraining potential of porous media. Foppen et al. [2005]
found that the rate of filling of straining sites was dependent
on the concentration of colloids (bacteria) in suspension.
[6] Measured capillary pressure curves and residual saturations can be related to pore size distributions according
to Laplace’s equation of capillarity. The percentage of porespace where straining and size exclusion occurs can beinferred from this pore size distribution information. Carsel
and Parrish [1988] present average capillary pressure curveparameters for the 12 major soil textural groups. Depending
on soil texture, straining is predicted in 10.5 to 70.8% of thesoil pore space for 0.1 mm size colloids; larger colloids
produce even greater percentages. Conversely, mobile colloids that are not strained may be physically excluded (sizeexclusion) from this same fraction of the pore space.
[7] Size exclusion affects the mobility of colloids byconstraining them to more conductive flow domains andlarger pore networks that are physically accessible [Ryanand Elimelech, 1996; Ginn, 2002]. As a result, colloids canbe transported faster than a conservative solute tracer[Reimus, 1995; Cumbie and McKay, 1999; Harter et al.,
2000; Bradford et al., 2003]. Differences in the dispersive
flux for colloids and a conservative solute tracer are also
anticipated as a result of size exclusion [Scheibe and Wood,2003]. Bradford et al. [2002] observed that the dispersivityof 3.2 mm carboxyl latex colloids was up to 7 times greaterthan bromide in saturated aquifer sand. Conversely, Sinton
et al. [2000] found in a field microbial transport experimentthat the apparent colloid dispersivity decreased withincreasing particle size.
[8] Straining and size exclusion have significant implications for colloid transport in the field. Increased straining
near the column inlet is deemed especially noteworthy since
it may have ramifications for layered soil profiles, heterogeneous subsurface formations, artificially constructed
media such as landfills, and water treatment techniques thatare based on soil passage (riverbank filtration, infiltration

W10404basins and trenches, and sand filters). Much of the transportof colloids will then occur in the ‘‘hydraulically’’ active
network of the larger pores. We postulate that straining ismost pronounced at the soil surface or at the boundary ofdifferent soil textures where colloids are encountering a(new) pore network. At such boundaries, colloids are more
likely to encounter a pore smaller than the critical straining
size or one larger than the critical size that steers colloids
toward ‘‘dead-end regions’’ of the pore space. Once colloids
have entered the hydraulically active network, transport
processes such as advection, dispersion, and size exclusion
make it more likely for the colloids to remain confined to
the network.
[9] Although natural soil and aquifer systems often
contain layers and lenses of contrasting soil texture,
relatively little research attention has focused on the mechanisms of colloid retention at textural interfaces [Saiers etal., 1994; Silliman, 1995; Bradford et al., 2004]. Saiers etal. [1994] found that colloid transport and deposition could
be adequately described with an advection-dispersion transport model that accounted for first-order kinetic attachment/
detachment. In contrast, Silliman [1995] found significant
colloid retention at textural interfaces where water moved
from larger to smaller diameter sands. This observation was
attributed to straining initiated by colloid attachment.
Bradford et al. [2004] found that colloid transport inheterogeneous systems was controlled primarily by straining when dc/d50 > 0.005, but that attachment and theaqueous phase flow field (flow bypassing) also played
important roles.
[10] The objective of this work is to investigate the mainprocesses controlling the transport and fate of colloids
across textural interfaces. While such information is neededto accurately assess colloid transport in heterogeneous
aquifer formations, few studies have thus far systematicallyfocused on this topic. It seems logical to anticipate thatstraining will be most pronounced at locations wherecolloids encounter a new pore network (e.g., texturalinterfaces). Colloid transport experiments were conductedusing homogeneous and layered sand systems (using bothcolumns and micromodels). Transport and retention wereassessed by measuring temporal changes in colloid effluent
concentrations and by studying the final spatial distributionof colloids remaining in the sand columns, as well as bymicroscopically studying locations of colloid deposition inhomogeneous and layered sand experiments conducted in a
glass micromodel (0.2 cm  2.0 cm  7.0 cm). The column
transport data were described and analyzed using a transportmodel that accounts for advective, dispersive, and diffusive
colloid fluxes, and two-site kinetic deposition. One deposition site is used to account for conventional first-orderattachment and detachment, while the second depositionsite includes a formulation for accessibility straining sites.

2. Materials and Methods
2.1. Colloids[ 11 ] Yellow-green fluorescent latex microspheres(Interfacial Dynamics Company, Portland, OR) were used
as model colloid particles in the experimental studies(excitation at 490 nm, and emission at 515 nm). Two sizesof microspheres were used in the transport experiments, 1.1

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and 3.0 mm. The uniformity of the colloid size distributions
was verified using with a Horiba LA 930 (Horiba Instruments Inc., Irvine, California) laser scattering particle sizeand distribution analyzer. These microspheres had sulfate
surface functional groups, a density of 1.055 g cm3
(provided by the manufacturer), and an equilibrium contact
angle (air-water-lawn of colloids) of 101 (measured with a
Tantec Contact Angle Meter, Tantec Inc., Schaumburg,
Illinois). The 1.1 and 3.0 mm colloids had a surface charge
density of 5.2 and 14.3 mC cm2 (provided by manufacturer)
and a zeta potential of 66.5 and 75.5 mV (measured witha ZetaPALs Instrument), respectively. The initial influent
concentration (Ci) for the 1.1 and 3.0 mm colloids forthe experiments was 3.3  1010 and 1.5  109 Nc L1(where N c denotes number of colloids), respectively.
One experiment was conducted using 1.1 mm particles at
0.5*Ci = 1.65  1010 Nc L1.
2.2. Sand[12] Aquifer material used for the column experiments
consisted of various sieve sizes of Ottawa (quartz) sand
(U.S. Silica, Ottawa, IL). The porous media were selected toencompass a range in grain sizes, and are designated bytheir median grain size (d50) as: 710, 360, 240, and 150 mm.
Specific properties of the 710, 360, 240, and 150 mm sands
include: the coefficient of uniformity (d60/d10; here x% of
the mass is finer than dx) of 1.21, 1.88, 3.06, and 2.25;
and intrinsic permeabilities of 4.08  1010, 6.37  1011,
1.12  1011, and 4.68  1012 m2, respectively. Ottawa
sands typically consist of 99.8% SiO2 (quartz) and trace
amounts of metal oxides, have spheroidal shapes, andcontain relatively rough surfaces. The vast majority of thesands possess a net negative charge at a neutral pH.
[13] Bradford and Abriola [2001] presented capillarypressure – saturation curves for the 710, 360, 240, and
150 mm sands. An estimate of the pore size distribution ofdrained pores (that may produce straining) can be obtained
from capillary pressure – saturation curves using Laplace’s
equation of capillarity. Unfortunately, it is relatively difficult
to use this method to characterize the small pore sizes ofsands because of the presence of residual water (due todiscontinuities in the wetting films). Alternatively, Herzig etal. [1970] calculated the volume of spherical colloids that
could be retained in pores based on geometric considerations. The percentage of the total column volume retainedby straining was calculated (assuming a coordination number of 7, a porosity of 0.35, a colloid diameter of 1.1 mm, anda grain diameter equal to d10) to be 0.0002% for the 710 mmsands, 0.0020% for the 360 mm sands, 0.0129% for the
240 mm sands, and 0.0225% for the 150 mm sands. Althoughthese straining volumes are quite small, significant numbersof colloids are required to fill the sites [Foppen et al., 2005].
For example, 6.3  1010 colloids (1.1 mm) would be
required to fully saturate (fill) all the straining sites in
uniform 150 mm sand packed in a column that is 10 cmlong and has an inside diameter of 5 cm. This corresponds tocomplete retention of 1.1 mm colloids in 27.9 pore volumes(PV) of suspension at a concentration of 3.3  1010 Nc L1.
2.3. Aqueous Phase[14] The aqueous phase chemistry (pH, ionic strength,
and composition) of the experimental solutions utilized in
the column studies consisted of deionized water with its pH

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buffered to 6.98 using 5  105 M NaHCO3 (ionic strength
equal to 5  105 M). This solution was chosen to create astabilized monodispersed suspension with the selected colloids, and to minimize electrostatic interactions between thecolloids and porous media (highly unfavorable attachment
conditions). The colloid tracer solution consisted of thissame solution but with the previously indicated initial
colloid concentration.
2.4. Column Experiments[15] Procedures and protocols for the packed column
experiments were previously discussed in detail by Bradford
et al. [2002]. Only an abbreviated discussion is provided
below. Kontes Chromaflex chromatography columns(Kimble/Kontes, Vineland, New Jersey) made of borosilicate glass (15 cm long and 4.8 inside diameter were
equipped with an adjustable adapter at the top) were usedin the transport studies. The columns were wet packed(water level kept above the sand surface) with the various
porous media. For the layered experiments, equal massfractions of the two sand types were successively packed
into a column, taking care to minimize the disturbance at the
textural interface. Table 1 provides porosity (e) values[Danielson and Sutherland, 1986] and column length (Lc)for each experimental system. The colloid suspension was
pumped upward through the vertically oriented columns at
a steady flow rate for 77.5 (for Ci experiments) or
150 (0.5*Ci experiment) min, after which a three-way
valve was used to switch to the background solution fora total experimental time of 250 min. The average Darcian
flux densities (q) for the various experiments are given in
Table 1. Effluent samples were collected and analyzed forcolloid concentration using a Turner Quantech fluorometer(Barnstead/Thermolyne, Dubuque, Iowa). The averageof three measurements were used to determine eachcolloid concentration (reproducibility was typically within
1% of Ci).
[16] Following completion of the colloid transport experiments, the spatial distributions of colloids in the packed
columns were determined. The saturated sand was carefully
excavated into 50 mL Falcon centrifuge tubes containing
excess deionized water. The tubes were slowly shaken for
15 min using a Eberbach shaker (Eberbach Corporation,
Ann Arbor, Michigan) to liberate retained colloids. The
concentration of the colloids in the excess aqueous solution
was measured with a Turner Quantech fluorometer using thesame experimental protocol as followed for the effluent
samples. These concentrations were corrected for colloid
release efficiency determined from batch experiments. The
release efficiencies for 1.1 mm colloids were 0.78 in the
710 mm sand, 0.75 in the 360 mm sand, 0.71 in the 240 mm
sand, and 0.68 in the 150 mm sand, while the 3.0 mm
colloids had release efficiencies of 0.80 in the 710 mm sandand 0.78 in the 150 mm sand.
[17] A colloid mass balance was conducted at the endof each column experiment using effluent concentration
data and the final spatial distribution of retained colloids
in the sands. The calculated number of effluent andcolloids retained in the sand was normalized by the total
number of injected particles into a column. Table 1
presents the calculated effluent (Me), sand (Ms), and thetotal (Mt = Me + Ms) colloid mass fractions recovered forthe various experiments.

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Table 1. Packed Column Properties (Porosity, e, Darcy Water
Velocity, q, and Column Length, Lc) and the Recovered Effluent(Me), Sand (Ms), and the Total Colloid Mass Fraction (Mt)
Systemdc, mmeq, cm min1

Lc, cm

Me

Ms

Mt

710
710
360
240
150
150a
150
150/710150/710150/360
150/240710/360
710/240710/150710/150360/240360/150240/150

1.1
3.0
1.1
1.1
1.1
1.1
3.0
1.1
3.0
1.1
1.1
1.1
1.1
1.1
3.0
1.1
1.1
1.1

0.350
0.348
0.333
0.309
0.338
0.345
0.344
0.335
0.356
0.342
0.326
0.345
0.345
0.353
0.356
0.323
0.327
0.328

0.094
0.096
0.108
0.117
0.105
0.106
0.103
0.113
0.116
0.123
0.133
0.085
0.097
0.101
0.098
0.108
0.102
0.092

12.8
12.8
12.5
12.1
12.6
12.7
12.7
12.5
13.0
12.7
12.4
12.7
12.7
12.9
13.0
12.3
12.4
12.4

0.775
0.782
0.641
0.534
0.566
0.572
0.039
0.650
0.062
0.622
0.549
0.703
0.669
0.676
0.384
0.485
0.516
0.386

0.079
0.124
0.247
0.369
0.434
0.463
0.978
0.359
0.530
0.320
0.433
0.233
0.270
0.286
0.634
0.594
0.568
0.679

0.854
0.906
0.888
0.903
1.000
1.035
1.017
1.009
0.592
0.942
0.982
0.936
0.939
0.962
1.018
1.079
1.084
1.065

a

Input concentration equal to 0.5 Ci.

2.5. Micromodel Experiments[18] Several transport experiments were conducted in a
specially designed micromodel to examine the deposition
behavior of the 1.1 and 3.0 mm sulfate colloids in homogeneous (150 mm sand) and layered (710/150) sand systems.
The micromodel consisted of a 0.2 cm thick by 2.0 cm wideby 7 cm long glass chamber (inside dimensions), with aglass tube (0.5 cm inside diameter) and septum assembly
joined at both ends of the chamber. The tubing wasconnected to the chamber by a glass blower at an angle ofabout 45, so that the micromodel could lay flat on ahorizontal surface. During packing the micromodel chamber
was oriented vertically without the top septum. The desired
sands were then wet packed in the chamber (homogeneousor layered configurations). Hypodermic needles and Teflon
tubing were used to connect the inlet side of the chamber toa LabAlliance chromatography pump (State College, Pennsylvania) and a reservoir on the outlet side of the chamber.
To be comparable to the column experiments, the colloid
suspension was pumped at a steady rate of 0.04 ml min1(Darcy velocity of 0.1 cm min1) for about 60 min (around
2.5 pore volumes), followed by deionized water for an
additional 60 min. After completion of a transport experiment, the hypodermic needles were removed and the final
deposition behavior of the fluorescent colloids was microscopically examined at several locations using a Leica DM
IRB epifluorescent microscope (Leica Microsystems Inc.,
Bannockburn, Illinois). Images were captured by connecting the microscope to a video monitor and computer system.
Photographs (600 times magnification) were takenusing various intensities of both UV and visible light sothat sand grains and fluorescent colloids could be visualized
simultaneously.
2.6. Theory and Model[19] The aqueous phase colloid mass balance equation is
written as@ ðqw C Þ
att
str
 Esw
¼ r  JT  Esw@t

ð1Þ

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where C [Nc L3] is the colloid concentration in the aqueous
phase, t [T] is time, qw (dimensionless) is the volumetricwater content, JT [Nc L2 T1] is the total colloid flux (sumof the advective, dispersive, and diffusive fluxes), and Eattsw
3 1
[Nc L3 T1] and Estr
T ] are the colloid masssw [Nc L
transfer terms between the aqueous and solid phases due tocolloid attachment/detachment and straining, respectively.
An expression for Eattsw can be written as
att
Esw
¼ rb

@ ðSatt Þ¼ qw katt yatt C  rb kdet Satt@t

ð2ÞHere rb [M L3] is the soil bulk density, Satt [Nc M 1] is thesolid phase concentration of attached colloids, yatt (dimensionless) is a dimensionless colloid attachment function, andkatt [T1] and kdet [T1] are the first-order colloid
attachment and detachment coefficients, respectively. Whenyatt = 1 and kdet = 0, clean bed attachment is assumed(leading to an exponential spatial distribution), while
traditional filtration theory [Logan et al., 1995] can be usedas needed for katt [e.g., Bradford et al., 2003]. In contrast, toaccount for colloid blocking (filling of favorable attachment
sites) the value of yatt decreases with increasing Satt.
According to the Langmuirian approach [e.g., Deshpandemax
and Shonnard, 1999], yatt = 1  Satt/Smax
att ; where Satt [NcM 1] is the maximum solid phase concentration of attachedcolloids. For given values of katt and kdet, a decreasing Smax
att
tends to produce higher effluent concentrations and lower
values of Satt.
[20] Straining is modeled according to a slightly modified
form of the approach described by Bradford et al. [2003].
The mass balance equation for strained colloids is given as
str
Esw
¼ rb

@ ðSstr Þ¼ qw kstr ystr C@t

ð3Þ

where kstr [T1] is the straining coefficient, ystr (dimensionless) is a dimensionless colloid straining function, and Sstr
[Nc M1] is the solid phase concentration of strained
colloids. The value of ystr for each layer is a function of
distance and described as



Sstr
d50 þ z  zo bystr ¼ H ð z  zo Þ 1  max
Sstr
d50

ð4Þ

where H(z  zo) is the Heaviside function, z [L] is depth, zo[L] denotes the depth of the column inlet or textural[Nc M1] is the maximum solid phaseinterface, Smax
str
concentration of strained colloids, and b (dimensionless) is aparameter that controls the shape of the colloid spatial
distribution. The Heaviside function is equal to 0 for z < zoand 1 for z greater than or equal to zo. In homogeneous
systems, the value of zo equals the z coordinate of the sandsurface. In layered systems, the value of zo equals the z
coordinate of the sand surface for the first layer, and the z
coordinate of the interface for the second layer.
[ 21 ] The second term on the right hand side ofequation (4) is included to account for filling and accessibility of straining sites in a manner similar to theLangmuirian blocking approach. For given values of kstr
and b, decreasing Smax
tends to produce higher effluent
str
concentrations and lower values of Sstr. The remaining

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Figure 1. (a) Effluent concentration curves and (b) spatial distributions for 1.1 mm sulfate colloids in
710, 360, 240, and 150 mm sand. In Figure 1a, relative effluent concentrations (C/Ci) are plotted as afunction of pore volumes, whereas in Figure 1b the normalized concentration (number of colloids, Nc,
divided by the total number added to the column, Ntc) per gram of dry sand is plotted as a function ofdimensionless distance (distance from the column inlet divided by the column length).
terms on the right-hand side of equation (4) assume thatcolloid mass retention by straining occurs primarily at thecolumn inlet or textural interface because of retention ofcolloids in dead end pores and/or at grain junctions that aresmaller than some critical size. The apparent number ofdead-end pores is hypothesized to decrease with increasing
distance since advection, dispersion, and size exclusion tend
to keep mobile colloids within the larger networks, thus
bypassing smaller pores. The potential roles of size exclusion and dispersion on colloid transport to small pores isrelatively easy to understand. Water relative permeability
functions for sandy soils [e.g., van Genuchten et al., 1991]

also suggests that water flow to the smaller regions of thepore space accounts for only a small fraction of the total
permeability (saturated flow) once the flow field has been
established.
[22] The HYDRUS-1D computer code [Simunek et al.,1998] simulates the movement of water, heat, and multiple
solutes in one-dimensional variably saturated porous media.
This code was modified [Bradford et al., 2003] to accountfor colloid attachment, detachment, straining, and blocking
as outlined above. Although attachment and straining are
likely to occur simultaneously in natural systems, theseprocesses were considered separately in this work to facil-

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Figure 2. (a) Effluent concentration curves and (b) spatial distributions for 1.1 mm sulfate colloids in
150 mm sand at input concentrations of Ci and 0.5*Ci.
itate the determination of unique parameter estimates for thelayered systems. Bradford et al. [2003] and Bradford andBettahar [2005] discuss several ways to estimate the magnitude of attachment and straining in homogeneous column
experiments. HYDRUS-1D is coupled to a nonlinear leastsquares optimization routine based upon the MarquardtLevenberg algorithm [Marquardt, 1963] to facilitate theestimation of solute transport parameters from experimental
data.

3. Results and Discussion
3.1. Transport of 1.1 Mm Colloids in
Homogeneous Systems[23] Figures 1a and 1b present effluent concentration
curves and spatial distributions, respectively, for 1.1 mm
sulfate colloids in 710, 360, 240, and 150 mm sands. In

Figure 1a the relative effluent concentrations (C/Ci) areplotted as a function of pore volumes, whereas in Figure 1b
the normalized concentration (number of colloids, Nc,
divided by the total number added to the column, Ntc) per
gram of dry sand is plotted as a function of dimensionlessdistance (distance from the column inlet divided by thecolumn length). The recovered colloid mass fractions in theeffluent and the sand column, as well as the total recovered
mass fraction are shown in Table 1. High recovery rates
were obtained using the outlined experimental materials andprotocols.
[24] Figures 1a and 1b indicate that decreasing themedian grain size of the sand tended to produce slightly
lower effluent concentrations, and greater retention ofcolloids in the sand near the column inlet. Slight differencesin effluent concentration curves also occurred as a result ofvariations in the column porosity and Darcy velocity

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Figure 3. (a) Observed and simulated effluent concentration curves and (b) spatial distributions for
1.1 mm sulfate colloids in 150 mm sand. One of the simulations considered attachment and Langmuirian
blocking (kdet = 0 and kstr = 0) according to equations (1) and (2). The other simulation consideredstraining (katt = 0 and kdet = 0) according to equations (1), (3), and (4). Fitted model parameters arepresented in Tables 2 and 3.
(Table 1). The transport results were consistent with the
behavior of similarly sized carboxyl colloids in these same
Ottawa sands as shown by Bradford et al. [2002]. Simulations presented by Bradford et al. [2003] suggests thatstraining was the dominant mechanism of colloid retention
in these systems. Straining occurred primarily at the column
inlet, presumably due to the high accessibility of potential
straining sites (small pores) to flowing colloid suspensions
at this location. Size exclusion and advection were hypothesized to increasingly restrict the flow of colloids to large
pore networks (bypassing small, low-permeability straining
sites) as the transport distance increased.

[25] After the initial colloid breakthrough, Figure 1ashows that effluent concentrations continued to slowly
increase with continued colloid addition. This behavior
has previously been reported in many studies [Tan et al.,
1994; Liu et al., 1995; Johnson and Elimelech, 1995;
Rijnaarts et al., 1996; Camesano and Logan, 1998;
Camesano et al., 1999], and is referred to as blocking.
Blocking implies that as favorable attachment sites become
filled, attachment decreases and colloid transport isenhanced. This same explanation can also be applied tofilling of straining sites. As straining sites become filled,enhanced transport occurs.

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Table 2. Fitted (Hydrodynamic Dispersivity, lH; Attachment Coefficient, katt, and Maximum Solid Phase*max) Parameters for the Attachment (Equations (1) and (2)) Model in
Concentration of Attached Colloids, Satt
Homogeneous Systems (1.1 mm Colloids)a
Sanddc, mmlH, cmkatt, min1*max, Nc Ntc1 g1
Satt

re2

rs2

710
360
240
150
150b

1.1
1.1
1.1
1.1
1.1

0.26 (0.04)
0.49 (0.23)
0.20 (0.15)
0.28 (0.18)
0.28

0.0047 (0.0007)
0.0110 (0.0028)
0.0231 (0.0042)
0.0156 (0.0011)
0.0246 (0.0051)

0.014 (0.023)
0.031 (0.117)
0.004 (0.004)
0.005 (0.003)
0.003 (0.002)

1.00
0.99
0.99
0.98
0.92

0.69
0.51
0.43
0.40
0.42

a

Standard error values for the parameter fits are provided within the parentheses.
Input concentration equal to 0.5*Ci. The value of lH was taken from the Ci experiment.

b[26] The rate of filling of straining sites was anticipated todepend on the concentration of colloids in suspension[Foppen et al., 2005]. To further examine this hypothesis,
an additional transport experiment was conducted at an
input concentration of 0.5*Ci. Figure 2 presents effluent
concentration curves (Figure 2a) and spatial distributions(Figure 2b) for 1.1 mm sulfate colloids in 150 mm sand at
input concentrations of Ci and 0.5*Ci. Notice that theeffluent concentration curve for the 0.5*Ci system exhibitsa more gradual increase in relative concentration than the Ci
system. Similar relative effluent concentrations occurred,however, after adding equal colloid masses (twice thenumber of pore volumes for 0.5 Ci than Ci systems). Slightdifferences were also observed between the Ci and 0.5*Ci
spatial distributions. The 0.5*Ci system exhibited slightly
lower retained concentrations near the column inlet then theCi system, while further in the column (dimensionlessdistance > 0.25) this trend was reversed. These observations
can be explained by the higher deposition rate that occurredin the 0.5*Ci system (it takes longer to fill the straining
sites). For the colloids used in this study, the total retention
capacity was independent of the input concentration (similarvalues of Ms in Table 1 after addition of equal colloid mass).
[27] Figures 3a and 3b present observed and simulated
effluent concentration curves and spatial distributions, respectively, for 1.1 mm sulfate colloids in 150 mm sand. Oneof the simulations (dotted line) considered attachment andLangmuirian blocking (kdet and kstr were set equal to zero)according to equations (1) and (2). Table 2 presents attachment and blocking model parameters (hydrodynamic dispersivity, lH; attachment coefficient, katt; and maximummax= Smaxsolid phase concentration of attached colloids, S*
att
att /
Ntc) that were fitted to the transport data for the various
homogeneous systems, along with statistical parameters (SEis standard error, r2e is the coefficient of linear regression for
the effluent data, and r2s is the coefficient of linear regression
for the spatial distribution data) reflecting the goodness offit. The other simulation in Figure 3 considered only
straining (kdet and katt terms were set equal to zero) according to equations (1), (3), and (4). Table 3 presents straining*max = Smax
model parameters (kstr and Sstr
str /Ntc were fitted, lH
is the same as in Table 2, whereas b was obtained by fitting
to transport data for the 150 mm system) and statisticalinformation for the various homogeneous systems. In
Figure 3 the straining model provided a much better
description of the effluent and spatial distribution data than
the attachment model (see r2e and r2s values in Tables 2 and
3). The straining model also gave improved descriptions of
the colloid transport behavior for the coarser 710, 360, and
240 mm sand systems (see Tables 2 and 3). Other numericalsimulations (not shown) revealed that differences in thepredicted colloid migration and fate for the attachment andstraining models will increase with increasing transportdistance.
[28] As briefly mentioned in the introduction, various
explanations for nonexponential colloid deposition havebeen proposed in the literature. Since the focus of this study
was on colloid straining, the experimental conditions were
designed to minimize the potential for colloid attachment(i.e., using uniformly sized and charged colloids, negatively
charged colloids and porous media, and simple aqueous
chemistry having a very low ionic strength). The mechanisms of colloid deposition were further deduced by meansof a micromodel experiment. Figure 4a presents a photo of
1.1 mm colloid deposition near the micromodel chamber
inlet in 150 mm sand. This photo demonstrates that many
fluorescent colloids can be deposited at a given grainjunction due to straining. The shape and surface roughness

Table 3. Fitted (Straining Coefficient, kstr, and Maximum Solid Phase Concentration of Strained Colloids,*max) and Estimated (Hydrodynamic Dispersivity, lH, and b) Parameters for the Straining (Equations (1), (3),Sstrand (4)) Model in Homogeneous Systems (1.1 mm Colloids)a
Sanddc, mmlH, cmb

kstr, min1*max, Nc Ntc1 g1
Sstr

re2

rs2

710
360
240
150
150b

1.1
1.1
1.1
1.1
1.1

0.264
0.490
0.203
0.283
0.283

1.31
1.31
1.31
1.31
1.31

1.065 (0.303)
2.561 (0.317)
10.99 (0.970)
13.86 (6.080)
20.29 (0.001)

0.001 (0.001)
0.020 (0.009)
0.011 (0.002)
0.014 (0.005)
0.013

0.99
0.98
0.98
0.96
0.92

0.65
0.84
0.97
0.97
0.95

a
Standard error values for the parameter fits are provided within the parentheses. Here lH is from Table 2; b is obtained fromfitting to transport data for the 150 mm system.
bmax
Input concentration equal to 0.5*Ci. The value of Sstr
was taken from the Ci experiment.

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W10404of the sand grains are also apparent in this photo. The large
number of colloids retained at this location supports our
hypothesis that filling of straining sites can occur during thecourse of our transport experiments. Aggregation of colloids
in suspension cannot explain this behavior since the uniformity of the colloid size distribution was experimentally
verified with a laser scattering particle size and distribution
analyzer.

Figure 4. Photos (magnified 600 times) of colloid
deposition in the micromodel experiments. (a) The 1.1 mm
deposition in 150 mm sand near the chamber inlet. (b) The
1.1 mm deposition in 150 mm sand near the 710/150 texturalinterface. (c) The 3.0 mm deposition in 150 mm sand near the
710/150 textural interface. See color version of this figure atback of this issue.

3.2. Transport of 1.1 Mm Colloids in Layered Systems:
Fine to Coarse[29] This section discusses the transport behavior of
1.1 mm sulfate colloids in layered sand systems when waterflows from a finer-textured (150 mm sand) to a coarsertextured (710, 360, or 240 mm sand) medium. Figures 5aand 5b present relative effluent concentration curves(Figure 5a) and spatial distributions (Figure 5b) for 1.1 mm
sulfate colloids in systems consisting of 150/710, 150/360,
and 150/240 mm sand layers. The effluent concentration
curves and spatial distributions were quite similar for thevarious layered systems. Decreasing the median grain sizeof the coarser-textured layer resulted in a slight decrease in
the peak effluent concentration (Figure 5a). Figure 5b
indicates that colloid retention was controlled by the finer
150 mm first layer. Little colloid retention occurred at the
textural interface when flow occurs from the finer to thecoarser-textured sand. Possible explanations will be discussed below.
[30] Figures 5a and 5b also show simulated effluent
concentrations and spatial distributions, respectively, forthe 1.1 mm sulfate colloid transport experiment (150/710,
150/360, and 150/240 mm sand layers) assuming straining(kdet and katt were set equal to zero) in accordance withequations (1), (3), and (4). Straining model parameters,
including the spatial distribution model parameter b, weretaken from the corresponding homogeneous systems pre*max for
sented in Table 3, with the one exception of Sstr
the coarser-textured layer, which was fitted directly to thelayered transport data (Table 4). As for the homogeneous
systems, the straining model provided a good description ofboth the effluent (Figure 5a) and deposition (Figure 5b)
data.
max
(Table 4) was[31] For a given sand, the value of S*
str
always significantly smaller for the layered system than forthe corresponding homogeneous system (Table 3). We
max
for the layered system
hypothesize that the value of S*
strshould be lower because of diminished colloid accessibility
to straining sites as a result of transport processes such as
size exclusion, advection, and dispersion that tend to
confine colloids to the hydraulically active pore networkand the larger pores spaces. Similar processes were thought
to occur in the homogeneous systems away from thecolumn inlet (Figure 1b). Straining sites at the texturalinterfaces could also be partially filled with natural colloids
that may have been mobilized during the sand cleaning
process. In contrast, concentration-dependent colloid transport (Figure 2) could not account for the deposition behavior in the layered systems (Figure 5b) because of higher
rates of colloid deposition at the lower input concentration(see Table 3). We will show later that straining was much
more pronounced for systems involving flow from coarse tofiner-textured layers.

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Figure 5. (a) Observed and simulated effluent concentration curves and (b) spatial distributions for
1.1 mm sulfate colloids in systems consisting of 150/710, 150/360, and 150/240 mm sand layers. Heresimulations considered only straining (equations (1), (3), and (4)).
[32] When straining and attachment both occur in porous
media it is difficult to separately estimate the magnitudes ofthese deposition processes. Colloid attachment is therefore
probably best estimated in systems with little straining.
Figures 5a and 5b suggest that very little straining occurredin the second layer when water flowed from a finer to acoarser-textured sand. This provides an opportunity to better
estimate the magnitude of attachment in the second layer
sand. For this purpose, straining was modeled only in thefirst layer (kdet = 0 and katt = 0) using parameters taken fromthe corresponding homogeneous systems (Table 3). In thesecond layer only attachment was modeled (kstr = 0 and
kdet = 0) by fitting a value of katt to the spatial distribution

data in this layer. To estimate the magnitude of katt in thefinest 150 mm sand, the homogeneous transport data wasanalyzed as a layered system (first half only straining, thesecond half only attachment). Simulated behavior for thefiner- to coarser-textured layered systems using thisapproach was quite similar to that presented in Figures 5aand 5b and is therefore not shown here. The fitted values ofkatt using this approach were 0.002, 0.002, 0.004, and
0.005 min1 for the 710, 360, 240, and 150 mm sandsystems, respectively. The r2s values in these systems were
all greater than 0.97, suggesting accurate characterization of
the deposition behavior. Values of katt in the homogeneous
systems (Table 2) were 2.9– 5.9 times greater than in these

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W10404*max (for Second Sand Layer) for the
Table 4. Fitted Values of Sstr
Layered Systems (1.1 mm Colloids)a
Systemdc, mm*max, Nc Ntc1 g1
Sstr

*max
Percent Sstr

re2

rs2

150/710150/360
150/240710/360
710/240710/150360/240360/150240/150

1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1

0.000 (0.001)
0.000 (0.000)
0.001 (0.000)
0.001 (0.000)
0.002 (0.001)
0.002 (0.000)
0.002 (0.001)
0.001 (0.000)
0.001 (0.001)

1.3
0.1
6.0
5.8
15.4
16.4
15.2
10.5
8.7

1.00
0.98
0.99
0.97
0.95
0.94
0.93
0.97
0.79

0.97
0.98
0.97
0.86
0.87
0.96
0.63
0.74
0.97

a
*max’’ is used to denote the percentage of
The quantity ‘‘Percent Sstr*max in the second sand layer relative to the corresponding homogeneous
Sstrsand system (see Table 3). Standard error values for the parameter fits areprovided within the parentheses.

‘‘layered’’ systems, thus indicating that significantly lessdeposition occurred in the ‘‘layered’’ systems.
3.3. Transport of 1.1 Mm Colloids in Layered Systems:
Coarse to Fine[33] This section discusses the transport behavior of
1.1 mm sulfate colloids in layered sands when water
flowed from a coarser to a finer-textured medium.
Figures 6a and 6b present relative effluent concentration
curves (Figure 6a) and spatial distributions (Figure 6b) for
1.1 mm sulfate colloids in systems consisting of 710/360,
710/240, and 710/150 mm sand layers. Effluent concentration curves were quite similar for the various layered
systems. The peak effluent concentration for the layered
systems approached that of the homogeneous 710 mm sand(around 0.77). In contrast to the finer homogeneous sandsystems (360, 240, and 150 mm data in Figure 1a), theeffluent concentrations for the layered systems exhibited afaster rate of concentration increase with increasing colloid
addition (i.e., PV). This observation suggests a more rapid
filling of accessible deposition sites for the layered systems.
[34] Inspection of Figure 6b revealed similar retention of
the 1.1 mm sulfate colloids in the first 710 mm layer. In
contrast, the retention behavior in the second layer
depended on the sand texture. The finer-textured 150 and
240 mm layers exhibited greater retention at the interface
than the 360 mm layer. As for the homogeneous systems, adecrease in the median grain size of the finer-textured layer
was hypothesized to produce more straining and therefore
greater retention. In contrast, the layered systems exhibited
significantly less retention at the textural interface than at
the column inlet for the corresponding homogeneous systems (see Figure 1b). As discussed in the previous section,
fewer accessible straining sites were hypothesized to exist
within the layered than in homogeneous systems. This may
occur as a result of transport processes (size exclusion andlimited advection) as well as partial filling (deposition ofnatural colloids during cleaning) of straining sites at texturalinterfaces.
[35] An additional micromodel experiment was conducted to further support our hypothesis that straining
occurred at textural interfaces. Figure 4b presents a photoof 1.1 mm colloid deposition in 150 mm sand adjacent to a
710/150 textural interface. Similar to Figure 4a, this photodemonstrates that many fluorescent colloids can be depos-

W10404

ited at grain junctions due to straining. Very little deposition
was observed in the 710 mm sand on the other side of thisinterface.
[36] To further illustrate the role of straining at texturalinterfaces, consider Figure 7, which shows relative effluent
concentration curves (Figure 7a) and spatial distributions(Figure 7b) for 1.1 mm sulfate colloids in systems consistingof 710/150, 360/150, and 240/150 mm sand layers. Inspection of Figure 7 reveals a distinct trend of decreasing
effluent concentration and increasing colloid retention near
the column inlet with decreasing median grain size of thecoarser-textured layer. These results are consistent withthose for the homogeneous systems. Figure 7b indicatesthat colloid retention is controlled by the (first) coarsertextured layer in the 360/150 and 240/150 layered systems.
Colloid retention in the 710/150 layered system, however,
was dominated by the finer-textured layer due to the greater
textural (permeability) contrast at this interface. Hence
increasing the textural (permeability) contrast in the sandlayers leads to a transition in the location of predominantstraining from the column inlet to the textural interface.
[37] Figures 7a and 7b also present simulated effluent
concentration curves and spatial distributions, respectively,
for 1.1 mm sulfate colloids in 710/150, 360/150, and240/150 mm sand layers. The simulations again consideredstraining (katt = 0 and kdet = 0) according to equations (1),max
for the (second) finer(3), and (4). The value of the S*
str
textured layer was fitted directly to the transport data
(Table 4), whereas other model parameters were obtained
from the homogeneous systems (Table 3). The straining
model did a reasonable job of describing both the effluent(Figure 7a) and spatial distribution (Figure 7b) data. Table 4
max
increased with decreasing
indicates that the value of S*
strsize of the finer-textured sand (more straining sites), andtended to increase with increasing contrast in sand texture(increased accessibility to available straining sites).
[38] The ability of the attachment model to describe
colloid transport and deposition in the layered systems
was also investigated. Figures 8a and 8b present observed
and simulated effluent concentration curves and spatial
distributions, respectively, for 1.1 mm sulfate colloids in
710/150, 360/150, and 240/150 layered systems. In thismaxwere taken from Table 2. The
case, values of katt and S*
att
attachment model significantly underestimated colloid deposition at the column inlet and tended to overestimateddeposition in the second layer. The simulated effluent
concentrations tended to overestimate the transport potential. The values of r2e and r2s for the 710/150, 360/150, and240/150 systems were 0.97 and 0.18, 0.99 and 0.11, and0.89 and 0.47, respectively. Recall that values of katt in thehomogeneous systems (Table 2) were 2.9– 5.9 times greaterthan in the finer to coarser ‘‘layered’’ systems. Hence
utilization of katt values determined in the finer to coarser‘‘layered’’ systems would have predicted significantly lessdeposition at the column inlet and textural interface thanshown in Figure 8b. Similarly, the predicted effluent concentrations would have been much higher than that shownin Figure 8a.
3.4. Transport of 3.0 Mm Colloids in Homogeneous andLayered Systems[39] This section discusses several additional experimentsthat were carried out with 3.0 mm sulfate colloids using both

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Figure 6. (a) Effluent concentration curves and (b) spatial distributions for 1.1 mm sulfate colloids insystems consisting of 710/360, 710/240, and 710/150 mm sand layers.

homogeneous (150 and 710 mm sand) and layered (150/710
and 710/150 mm sand) systems. On the basis of results by
Bradford et al. [2002, 2003], greater straining was anticipated for 3.0 than 1.1 mm colloids in a particular sand.
Transport and deposition behavior across textural interfaces
was therefore expected to be more pronounced using 3.0
than 1.1 mm colloids.
[40] Figures 9a and 9b present observed effluent concentration curves and spatial distributions, respectively,
for 3.0 mm colloids in systems consisting of homogeneous 150 and 710 mm sands, as well as 150/710 and
710/150 mm layered systems. As anticipated for straining
behavior in the homogeneous sands, significantly more

retention occurred in the 150 than the 710 mm sand.
Consistent with this observation, transport and depositionin the layered systems was controlled by the 150 mm sandlayer. The effluent and spatial distributions data for thelayered systems, however, depended strongly on the
textural order (150/710 compared to 710/150). Transport
in the 150/710 layered system was similar (in terms ofpeak effluent concentrations, with colloid deposition
occurring primarily near the column inlet) to the homogeneous 150 mm sand system. In contrast, higher effluent
concentrations and significantly less deposition occurred
for the 710/150 layered system compared to the homogeneous 150 mm sand or the 150/710 system. As for the

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Figure 7. (a) Observed and simulated effluent concentration curves and (b) spatial distributions for
1.1 mm sulfate colloids in systems consisting of 710/150, 360/150, and 240/150 mm sand layers. Heresimulations considered only straining (equations (1), (3), and (4)).
1.1 mm colloids, this behavior can be explained bytransport processes (size exclusion and limited advection)or partial filling (deposition of natural colloids during
cleaning) that limit accessibility of straining sites at
textural interfaces. Significantly more deposition occurredat the textural interface in the 710/150 system for the
3.0 mm (Figure 9b) than the 1.1 mm (Figure 7b) colloids,
suggesting increased accessibility of straining sites
at textural interfaces with increasing colloid size. To
further support our hypothesis that straining occurred at
the 710/150 textural interface, Figure 4c presents a photoof 3.0 mm colloid deposition in 150 mm sand adjacent toa 710/150 textural interface in a micromodel experiment.

Similar to Figures 4a and 4b, this photo demonstrates thatfluorescent colloids can be deposited at a grain junction
due to straining.

4. Summary and Conclusions[41] Natural soil and aquifer systems frequently containlayers and lenses of contrasting soil texture. In comparison
to homogeneous systems, relatively few studies have examined colloid transport and deposition at textural interfaces. Saturated packed column studies were undertaken tocharacterize colloid transport processes in layered sandsystems. Special attention was given to the roles of colloid

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Figure 8. (a) Observed and simulated effluent concentration curves and (b) spatial distributions for
1.1 mm sulfate colloids in systems consisting of 710/150, 360/150, and 240/150 mm sand layers. Heresimulations considered only attachment (equations (1) and (2)).
straining and size exclusion. Mechanisms of colloid transport and retention were deduced from measured effluent
concentration curves, final spatial distributions in the columns, mass balance information, microscopic examinationof deposition behavior in micromodel experiments, andnumerical modeling.
[42] For a given sand and colloid, deposition was always
most pronounced at the sand surface than at a texturalinterface. Colloids enter a new pore network at the sandsurface and are therefore more likely to encounter smaller
pores or dead-end regions of the pore space that contributeto straining. In contrast, we hypothesize that transport
processes such as advection, dispersion and size exclusion

tend to confine colloid transport to the larger pore networks
at textural interfaces, and thus limit accessibility to straining
sites. Increasing the textural contrast at an interface, however, produced greater colloid deposition when water
flowed from coarser to finer-textured sands, suggesting an
increased accessibility to straining sites in these (new) pore
networks. Conversely, when water flowed from finer tocoarser-textured sands, little deposition occurred. Hencecolloid effluent and spatial distribution data for layered
systems depended strongly on the textural order, especiallyfor larger colloids and greater textural contrasts.
[43] Simulation of the 1.1 mm colloid transport data using
a conventional attachment/detachment and blocking (Lang-

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Figure 9. (a) Observed effluent concentration curves and (b) spatial distributions for 3.0 mm sulfate
colloids in systems consisting of homogeneous 150 and 710 mm sands as well as 150/710 and 710/150 mm
sand layers.
muirian) model provided a poor description of the spatial
distribution data. A previously developed straining model
was therefore modified to account for blocking (filling) andaccessibility of straining sites. This model provided asatisfactory characterization of colloid effluent and spatial
distribution data in both homogeneous and layered systems.
[44] Findings from this study have important implications
for many colloid transport scenarios such as the design ofefficient water treatment techniques based upon soil passage(riverbank filtration, infiltration basins and trenches, andsand filters), as well as the transport and fate of microorganisms and contaminants (colloid-facilitated transport) inheterogeneous systems. Knowledge of colloid transport
processes across textural interfaces in unsaturated systems

is, however, very limited. In this case, the topology andgeometry of the hydraulically active network will greatly
depend on the degree of saturation. Additional research isneeded to quantify the influence of many physical (watervelocity, flow bypassing, water saturation, and dimensionality), chemical (aqueous phase solution composition, surface charge of colloid and porous media), and biologicalfactors on colloid transport and to incorporate these processes into mathematical models.
[45] Acknowledgments. This research was supported by the 206
Manure and Byproduct Utilization Project of the USDA-ARS. Mentionof trade names and company names in this manuscript does not imply any
endorsement or preferential treatment by the USDA.

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M. Bettahar, Parsons, 100 West Walnut Street, Pasadena, CA 91124,
USA.
S. A. Bradford, Y. F. Tadassa, M. T. van Genuchten, and S. R. Yates,
George E. Brown, Jr., Salinity Laboratory, ARS, USDA, 450 West Big
Springs Road, Riverside, CA 92507-4617, USA. (sbradford@ussl.ars.
usda.gov)
J. Simunek, Department of Environmental Sciences, University ofCalifornia, Riverside, CA 92521, USA.

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Figure 4. Photos (magnified 600 times) of colloid deposition in the micromodel experiments. (a) The
1.1 mm deposition in 150 mm sand near the chamber inlet. (b) The 1.1 mm deposition in 150 mm sand near
the 710/150 textural interface. (c) The 3.0 mm deposition in 150 mm sand near the 710/150 texturalinterface.

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