Environmental Pollution 258 (2020) 113803

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Environmental Pollution
journal homepage: www.elsevier.com/locate/envpol

Evidence for the critical role of nanoscale surface roughness on theretention and release of silver nanoparticles in porous media* 
Yan Liang a, b, Jini Zhou a, Yawen Dong a, Erwin Klumpp c, Jirí Sim
unek d,Scott A. Bradford e, *aSchool of Resources, Environment and Materials, Guangxi University, Nanning, China
Guangxi Key Laboratory for Agro-Environment and Agro-Product Safety, Nanning, China
Agrosphere Institute, IBG-3, Forschungszentrum Jülich GmbH, Jülich, GermanydDepartment of Environmental Sciences, University of California, Riverside, CA, United Statese
US Salinity Laboratory, USDA, ARS, Riverside, CA, United Statesbca r t i c l e i n f o

a b s t r a c t

Article history:
Received 23 August 2019
Received in revised form
9 December 2019
Accepted 10 December 2019
Available online 13 December 2019

Although nanoscale surface roughness has been theoretically demonstrated to be a crucial factor in theinteraction of colloids and surfaces, little experimental research has investigated the inﬂuence ofroughness on colloid or silver nanoparticle (AgNP) retention and release in porous media. This study
experimentally examined AgNP retention and release using two sands with very different surface
roughness properties over a range of solution pH and/or ionic strength (IS). AgNP transport was greatly
enhanced on the relatively smooth sand in comparison to the rougher sand, at higher pH, and lower ISand ﬁtted model parameters showed systematic changes with these physicochemical factors. Complete
release of the retained AgNPs was observed from the relatively smooth sand when the solution IS was
decreased from 40 mM NaCl to deionized (DI) water and then the solution pH was increased from 6.5 to
10. Conversely, less than 40% of the retained AgNPs was released in similar processes from the rougher
sand. These observations were explained by differences in the surface roughness of the two sands whichaltered the energy barrier height and the depth of the primary minimum with solution chemistry.
Limited numbers of AgNPs apparently interacted in reversible, shallow primary minima on the smoothersand, which is consistent with the predicted inﬂuence of a small roughness fraction (e.g., pillar) on
interaction energies. Conversely, larger numbers of AgNPs interacted in deeper primary minima on therougher sand, which is consistent with the predicted inﬂuence at concave locations. These ﬁndings
highlight the importance of surface roughness and indicate that variations in sand surface roughness cangreatly change the sensitivity of nanoparticle transport to physicochemical factors such as IS and pH due
to the alteration of interaction energy and thus can strongly inﬂuence nanoparticle mobility in theenvironment.
© 2019 Elsevier Ltd. All rights reserved.

Keywords:
Surface roughness
AgNPs
XDLVO
Retention
Release

1. Introduction
The transport and retention of colloids (e.g., microorganisms,
clays, organic matter, and nanoparticles) in porous media strongly
inﬂuences their fate in the environment (Bradford et al., 2002;
Wang et al., 2016, Fazeli Sangani et al., 2018; Molnar et al., 2019).
Colloid ﬁltration theory considers that retention in porous media isdependent on the mass transfer rate from the bulk solution to the*This paper has been recommended for acceptance by Baoshan Xing.
* Corresponding author.
E-mail address: scott.bradford@ars.usda.gov (S.A. Bradford).

https://doi.org/10.1016/j.envpol.2019.113803
0269-7491/© 2019 Elsevier Ltd. All rights reserved.

collector surface, and the sticking efﬁciency on the collector (grain)
surface (Yao et al., 1971). Several correlation equations have beendeveloped to predict the colloid mass transfer rate to collector
surfaces as a function of the water velocity, the size of the colloid
and the collector, and the colloid density (Tufenkji and Elimelech,
2004; Messina et al., 2015). The sticking efﬁciency has commonly
been related to the solution chemistry (e.g., pH, ionic strength,
cation type), ﬂow velocity (Torkzaban et al., 2007; Shen et al., 2010),
and the size and surface properties (charge, surface coating) of thecollector and colloid (Lin et al., 2011; Flory et al., 2013; Park et al.,2016).
The sticking efﬁciency of colloids on collector surfaces is normally related to interaction energy calculations which are used to2

Y. Liang et al. / Environmental Pollution 258 (2020) 113803

determine the favorability and strength of colloid adhesion. Theinteraction energy is frequently assumed to depend on the
Derjaguin-Landau-Verwey-Overbeek (DLVO) theory (Derjaguin
and Landau, 1941; Verwey and Overbeek, 1948). Interaction energy calculations normally assume that the colloid and collector
surfaces are chemically homogeneous and smooth. In contrast, thesurface of natural porous media exhibits pronounced roughness,
which can be as high as several hundreds of nanometers or micrometers for a sand surface (Shellenberger and Logan, 2002; Shenet al., 2011; Konopinski et al., 2012; Jin et al., 2015; Rasmuson et al.,2017; Johnson et al., 2018; Rasmuson et al., 2019; Ron et al., 2019). It
has been widely acknowledged that surface roughness is one of theimportant factors causing deviations between experimental andtheoretical results (Rabinovich et al., 2000; Katainen et al., 2006).
The roughness properties of a collector and colloid are importantfor predicting colloid retention (Jin et al., 2015; Ron et al., 2019).
Surface roughness can dramatically alter the colloid retention andrelease by altering the interaction energy proﬁles. For example, therepulsive energy barrier and depths of the primary and secondary
minima are lowered or eliminated on top of nanoscale convex asperities, and the energy barrier can be eliminated and the depth ofthe primary minimum can be increased at the bottom of nanoscaleconvex asperities (Suresh and Walz, 1996; Bhattacharjee et al.,
1998; Hoek et al., 2003; Hoek and Agarwal, 2006; Bradford and
Torkzaban, 2013; Shen et al., 2019). In addition, surface roughness
will modify the ﬂow ﬁeld adjacent to the solid surface, increase thelever arm for the resisting adhesive torque, and decrease and/or
eliminate the lever arm for the applied hydrodynamic torque(Burdick et al., 2005; Bradford et al., 2013). These roughness effects
can enhance colloid retention on electrostatically repulsive surfaces
and diminish retention on electrostatically attractive surfaces(Bradford et al., 2017). Weaker adhesive interactions on roughsurfaces contribute to colloid removal by diffusion and/or hydrodynamics (Bradford and Torkzaban, 2015) and can explain colloid
release from primary minima under increasingly unfavorable
conditions (Shen et al., 2018). Coupled effects of hydrodynamic slip
and colloid-surface interactions with asperities can decrease thegap between favorable and unfavorable conditions and inﬂuence
colloid detachment during ionic strength (IS) and ﬂow perturbations (Rasmuson et al., 2019; Ron et al., 2019). Bradford et al. (2017)
demonstrated that roughness conditions that contribute to colloid
retention change with the solution chemistry and charge of surfaces. Although theoretical calculations have demonstrated that
surface roughness has a large inﬂuence on colloid retention andrelease, relatively little experimental research has examined theseissues, especially under different solution chemistry conditions(Shen et al., 2011; Shen et al., 2012; Torkzaban and Bradford, 2016;
Rasmuson et al., 2019). Furthermore, this experimental research
has not been compared with theoretical calculations that accountfor nanoscale roughness.
Silver nanoparticles (AgNPs) are one of the most widely usednanomaterials (Nowack et al., 2011; Vance et al., 2015). There isconcern about the inevitable release of AgNPs into the environment(Yu et al., 2013; McGillicuddy et al., 2017) and the potential adverse
 n-Silva et al.,effect on human health and the environment (Leo2016; Rezvani et al., 2019). Various physicochemical factors havebeen demonstrated to strongly inﬂuence the transport of AgNPs,
e.g., grain size of the collector, the solution IS and pH, and thepresence of stabilizers (Lin et al., 2011; Flory et al., 2013; Liang et al.,2013b; Park et al., 2016; Adrian et al., 2018; Neukum, 2018). However, previous transport studies may provide incorrect or incomplete interpretations because they have largely neglected the roleof nanoscale surface roughness on AgNP retention and release. In
this work, AgNP transport experiments were therefore conductedin mixtures of two sands with the same size range and surface
chemical properties, but very different surface roughness conditions. The retention behavior of AgNPs on these sands was studied
under various solution IS and pH. Interaction energy calculations
that accounted for various sand roughness properties and numerical simulations were performed to deduce the governing mechanisms of retention and release. The ﬁndings from this study
improve our understanding and description of colloid interactions
and transport behavior in the environment.
2. Materials and methods
2.1. Solution chemistry
Ultrapure water and KNO3 were used to make electrolyte solutions with an IS of 5, 10, 20, 40, and 50 mM. The unadjusted pH ofthese solutions was around 6.5. NaOH and HNO3 were employed toadjust the pH values in some 5 mM KNO3 solutions to 4, 8, 8.5, 9.0,
and 10.
2.2. Quartz sandTwo analytically pure quartz sands were employed in column
experiments. One was purchased from Quarzwerke GmbH, Germany (denoted as QW sand) and was prepared by cleaning andsieving of natural raw materials, whereas the other was obtained
from Tianjin Guangfu Fine Chemical Research Institute, China(denoted as GF sand) and was produced by comminution ofquartzite. To minimize the inﬂuence of chemical heterogeneities on
the sand surfaces, puriﬁcation procedures for sands were performed, including boiling in HNO3 and H2O2 in a high borosilicate
glass reactor with constant stirring, rinsing with deionized water,and drying to minimize the trace amount of metal oxides andorganic impurities (Liang et al., 2013b). Characterization of thesands for physicochemical properties including surface
morphology (images and roughness parameters), grain size distribution parameters, speciﬁc surface area, streaming potential, andchemical composition (Al, Fe, Mg, and Ca) on the surface wasdescribed in section S1 of the supporting information (SI).
2.3. AgNPs
Raw AgNP suspension (10.16% w/w) was purchased from
AgPURE™, rent a scientist ® GmbH, Germany. This product wasOECD reference NM-Series of representative manufactured nanomaterials (NM-300 silver). The manufacturer reported that the
AgNPs were stabilized using a mixture of two non-ionic surfactants,
4% w/w each of Polyoxyethylene Glycerol Trioleate and Polyoxyethylene (20) Sorbitan mono-Laurat (Tween 20). The stability, homogeneity, and solubility of this material were characterized anddescribed in detail in previous research (Kaegi et al., 2011; Klein
et al., 2011; Liang et al., 2013b). In general, the AgNPs were spherical and the size measured by the transmission electron microscope(TEM) was 15e20 nm (Liang et al., 2013b). AgNP suspension foreach experiment was freshly prepared by diluting the raw
concentrated suspension into KNO3 solutions and then sonicatedfor 15 min in a sonication bath. The initial AgNP suspension concentration was determined to be approximately 10 mg L1 using an
inductively coupled plasma-mass spectrometry (ICP-MS) after
dissolving with 30% HNO3. The zeta potentials and the hydrodynamic diameters of AgNPs in selected solution chemistries were
measured with a ZetaSizer Nano ZS90 (Malvern Instruments,
Worcestershire, U.K.) and then used in interaction energy
calculations.
Concentrations of AgNPs in transport studies were determinedY. Liang et al. / Environmental Pollution 258 (2020) 113803

using a UVeVis spectrophotometer (Thermo Scientiﬁc, TM Evolution 300, U.S.) with a ﬁxed scan at a wavelength of 413 nm (R2 ofcalibration curves  0.9995 and the detection limit was
0.05 mg L1). The AgNP suspension was determined to be stable bycomparison of UVevis absorbance readings of input AgNP suspensions for the considered solution chemistries (pH from 4 to 10
and IS from 5 to 50 mM KNO3) over the duration of experiments.
The dissolution of AgNPs was also found to be negligible (less than
1% of the total mass) for similar conditions (Kaegi et al., 2011; Klein
et al., 2011; Liang et al., 2013b).
2.4. Transport experiments
Water saturated column experiments were performed following
the protocols outlined in Liang et al. (2013b). In brief, quartz sandwas wet-packed in a stainless-steel column with a 3 cm innerdiameter and 12 cm length. A peristaltic pump was used to injectsolution and AgNP suspension into the columns in an upﬂow mode.
The input concentration of AgNPs was ﬁxed at 10 mg L1 and theDarcy velocity was kept constant at around 0.7 cm min1 in allcolumn experiments. Transport experiments were conducted in thefollowing steps: (1) the packed column was conditioned witharound 50 pore volumes (PVs) of KNO3 background solution; (2)100 mL tracer (KNO3 solution at 2 to 5-fold concentration of the
background solution) was introduced into the column followed byirrigation of at least 5 PVs background solution; (3) 100 mL AgNP
suspension was then injected into the column and rinsed by around
3 PVs of the same KNO3 solution until the normalized concentration was less than 1%. Breakthrough curves (BTCs) of tracer were
determined from conductivity measurement on collected efﬂuent
samples, whereas BTCs of AgNPs were obtained by determining theconcentrationsof
efﬂuent
samplesusinga
UVeVisspectrophotometer.
Mixtures of QW and GF sands - Two types of sand withdifferent surface structures and properties at mass ratios of
QW:GF ¼ 0:1, 1:2, 1:1, 2:1, and 1:0 were homogeneously mixed
before they were packed into the columns for transport experiments. The IS was 5 mM KNO3 and the other experimental procedures were the same as described above.
Transport of AgNPs under different IS - Column experiments
were carried out to investigate the retention of AgNPs on a relatively smooth GF sand surface under different IS (5, 10, 20, 40, and
50 mM KNO3) conditions.
Different pH values of the column system - pH values of 4.0,
6.5 (unadjusted), 8.0, 8.5, 9.0, and 10 were selected for each column
experiment using rough QW sand at IS of 5 mM, while pH values of
6.5 (unadjusted) and 8.0 were selected for experiments with GF
sand at IS ¼ 50 mM. The pH in KNO3, tracer, and AgNP suspension
were all adjusted to a selected value in a given column experiment.
2.5. Release experiments
AgNPs were initially retained in the presence of 5 mM KNO3 onrough QW sand and 40 mM KNO3 on relatively smooth GF sand in asimilar manner to section 2.4 and then subject to a 20-h ﬂow
interruption (phase I). The release of AgNPs was then initiated byﬂushing the column with several PVs of ultrapure water: (i) with an
unadjusted pH (pH 6.5) (phase II); (ii) at pH ¼ 10 (phase III); and(iii) at pH ¼ 10 after a 20 h ﬂow interruption (phase IV). Finally, thesand was excavated from the column and placed into a container
containing excess amounts of ultrapure water at pH 10 (phase V).
The container was slowly shaken for several minutes to investigate
the release of the remaining retained AgNPs by determination of
the AgNP concentration, the volume of water, and the mass of dry
sand.

3

2.6. Theory and modelInteraction energy calculations that considered various surface
roughness properties and numerical simulations were performed
to better understand mechanisms contributing to AgNP retention
and release under the tested solution chemistries. The interactionenergy calculations based on conventional DLVO theory (smoothsurface) was applied with and without consideration of steric interactions. The approach of Bradford et al. (2017) was employed todetermine the interaction energy (Fr, MLT1) between AgNP andsand with nanoscale roughness as a linear combination of interaction energies for various nanoscale roughness components.
Section S2 of the SI provides details pertaining to these calculations
for AgNP-sand interactions. The dimensionless depths of the primary (F1min) and secondary (F2min) minima, the energy barrierheight (Fmax) and the energy barrier to detachment from the primary minimum (DFd ¼ Fmax-F1min) were obtained by analyzing theinteraction energy proﬁles.
Section S3 in the SI describes the modeling approach in detail.
The retention rate coefﬁcient (k1) and the normalized maximum
solid phase concentration of deposited AgNPs (Smax/Co, where Co is
the AgNP input concentration) for blocking were optimized. The
ﬁtted values of Smax were then used to calculate the fraction of thegrain surface area that contributes to AgNP retention (Sf).
3. Results and discussion
3.1. Characterization of AgNPs and quartz sands
Table S1 lists measured zeta potentials of AgNPs and quartz
sands, and hydrodynamic diameters (dp) of AgNPs over the range ofsolution chemistries that were used in column experiments. The
zeta potential of AgNPs gradually increased from 22.6 ± 1.6
to 7.4 ± 1.0 mV when the IS increased from 5 to 50 mM KNO3 at
pH ¼ 6.5 and became more negative as the pH increased from 4.0 to
10.0 at 5 mM KNO3. The AgNP dp values slightly increased as the IS
increased from 5 to 50 mM KNO3 at pH ¼ 6.5 and decreased as the
pH increased from 4.0 to 10.0 at 5 mM KNO3. These relatively minorchanges in dp over a large range in pH and IS reﬂect the stability of
the AgNP suspensions in the presence of adsorbed surfactants(Adrian et al., 2018), which is normally attributed to steric interactions (Hotze et al., 2010). Note that the size determined by the
Zeta-sizer is normally larger than by TEM because measurement by
the Zeta-sizer is biased toward a larger size fraction and takes avalue of hydrodynamic diameter that can also be inﬂuenced by the
thickness of the surfactant coating (Diegoli et al., 2008; Klein et al.,2011). The zeta potential of the QW sand decreased
from 29.0 ± 0.8 to 57.3 ± 3.8 mV when the solution pH increased
from 4.0 to 10.0 under 5 mM KNO3 due to deprotonations of thesurface. The zeta potentials of GF sand became less negative whenthe IS was increased from 5 to 50 mM KNO3 under pH 6.5 due tocompression of the double layer thickness and charge screening.
The mean grain sizes (d50) of mixtures with different proportions of rough and relatively smooth sand (mass ratios of 0:1,
1:2, 1:1, 2:1, and 1:0) ranged between 503 and 519 mm, indicatingthat the two sands were almost at the same size. Microscope images (Figs. S1 and 1) show the signiﬁcant difference of the surface
topography of the two sands. Table S2 presents surface morphological parameters, chemical analysis, and BET surface areas forboth puriﬁed sands. The average roughness was 418 ± 150 and
78 ± 41 nm for the relatively rough QW and smoother GF sand,respectively, while the surface chemistry and surface area of bothsands were generally comparable. Surface roughness is therefore
the main difference between the surface properties of these twosands.

4

Y. Liang et al. / Environmental Pollution 258 (2020) 113803

3.2. Interaction energy calculations
Measured values of dp and zeta potential were used to calculate
the conventional interaction energy proﬁles for different IS with
(Fig. S2a) and without steric interactions (Fig. S2b). The magnitudeof F2min (<0.33) was always much less than the average kinetic
energy ﬂuctuations for diffusing colloids (e.g, 1.5) (Bradford and
Torkzaban, 2015) and was therefore not considered to contributeto AgNP retention. Parameter values of F1min, Fmax, andDFd ¼ Fmax-F1min for the AgNP-sand interactions without consideration of steric interaction are given in Table S1. Table S1 shows ageneral trend of decreasing Fmax with decreasing pH andincreasing IS because of less negative values of the zeta potentials
and compression of the double layer thickness at higher IS. However, AgNPs can only diffuse over Fmax into F1min when Fmax < 6 to
10 (Bradford and Torkzaban, 2015). Primary minimum interactions
are therefore predicted in GF sand when IS  40 mM and in QW
sand when pH ¼ 4. No retention is predicted for other solution
chemistry conditions. Additionally, if steric interactions from theadsorbed surfactant layer on the AgNPs are included in the interaction energy calculations then a very large energy barrier occurs(Fig. S2b) and no AgNP retention is predicted for all consideredsolution chemistry conditions. These ﬁndings reveal the deviations
between experimental results and theoretical calculations based on
the conventional interaction energy calculations even if the stericinteractions are included.
3.3. AgNP retention in the sand with a rough surface
Column experiments were carried out to investigate the inﬂuence of sand roughness on AgNP transport and retention bycreating quartz sand with different mass ratios of relatively roughQW and smoother GF sands. Fig. 2 shows observed and simulated
AgNP BTCs for mixtures of QW and GF sand with mass ratios of 0:1,
1:2, 1:1, 2:1, and 1:0 when the IS ¼ 5 mM KNO3 and pH ¼ 6.5(unbuffered). BTCs were plotted as normalized efﬂuent concentrations (C/Co) versus pore volumes. Table 1 summarizes theexperimental conditions, the mass recoveries from BTCs, and theﬁtted model parameters.
Fig. 2 clearly demonstrates that AgNP retention is signiﬁcantly
different for various mass ratios of these two sands. The mass recovery of AgNPs in the efﬂuent (Meff) and the ﬁtted parameters of k1
and Smax/Co present an approximately linear correlation with themass percentage of the relatively rough QW sand to the total
amount of quartz sand (MQW) (Fig. S3 A1, B1, and C1). Larger MQW
resulted in stronger AgNP retention and larger values of k1 andSmax/Co (Table 1). Fig. 2 also shows systematic blocking trends (thegradual ascent trend of the BTCs due to a decrease in AgNP retention over time as retention sites are blocked or ﬁlled) which exhibit
a delay in AgNP breakthrough and then increasing concentrationsof AgNPs in the efﬂuent. These blocking effects can be explained by
the rate of ﬁlling of a limited number of retention sites. In particular,
blocking/ﬁlling of retention sites is expected to occur more rapidly
for larger k1 and smaller Smax (Leij et al., 2015). The value of Sf (Eq.
[S11]) shown in Table 1 was less than 5.3% and 0.8% for geometricand BET surface area estimates, respectively. Consequently, only avery small fraction of the QW sand surface area contributed to
AgNP retention. SEM images taken from the samples for both QW
and GF sand after completion of transport experiments show large
AgNP-free areas (Fig. S4) and this information is consistent with thecalculated values of Sf.
AgNP retention in Fig. 2 is not consistent with interaction energy
calculations for smooth and chemical homogeneous surfaces(Fig. S2 and Table S1). In particular, no AgNP retention on therelatively rough QW and GF sands is predicted when the pH ¼ 6.5
and the IS ¼ 5 mM KNO3 because Fmax > 10. Furthermore, differences in AgNP retention on QW and GF sands are not predictedbecause values of Fmax were nearly identical (39.4 and 40.1 for QW
and GF sand, respectively). Potential explanations for these discrepancies include nanoscale charge heterogeneity and roughness
which can locally reduce and/or eliminate the energy barrier(Suresh and Walz, 1996; Bhattacharjee et al., 1998; Hoek et al.,
2003; Hoek and Agarwal, 2006; Bradford and Torkzaban, 2013;
Bradford et al., 2017; Bradford et al., 2018). Nanoscale chemical

Table 1
Experimental Parameters and Fitted/Calculated Values (k1, Smax/Co, and Sf) of AgNP Transport under Various Experimental Conditions.

Fig. 2

Fig. 3Fig. 4

Fig. S5Exp. Name

MQW

IS mM

pH

Meff,
%

k1,
min1

Smax/Co, cm3 g1

Sf, % BET

Sf, %Geometric

R2

QW:GF ¼ 0:1
QW:GF ¼ 1:2
QW:GF ¼ 1:1
QW:GF ¼ 2:1
QW:GF ¼ 1:0
pH ¼ 4.0
pH ¼ 6.5
pH ¼ 8.0
pH ¼ 8.5
pH ¼ 9.0
pH ¼ 10.0
5 mM
10 mM
20 mM
40 mM
50 mM
pH 6.5pH 8.0

0.00
0.33
0.50
0.67
1.00
1.00
1.00
1.00
1.00
1.00
1.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00

5
5
5
5
5
5
5
5
5
5
5
5
10
20
40
50
50
50

6.5
6.5
6.5
6.5
6.5
4.0
6.5
8.0
8.5
9.0
10.0
6.5
6.5
6.5
6.5
6.5
6.5
8.0

GF sand
QW sand

0
1.00

5
40

6.5
6.5

79.2
45.3
21.2
8.5
1.5
0.2
1.5
17.8
51.2
71.8
86.3
79.2
49.6
39.7
8.8
0.0
0.0
78.1
Meff
8.8
1.3

0.346
0.409
0.485
0.741
1.026
1.378
1.026
0.383
0.234
0.148
0.049
0.346
0.751
1.091
1.313
1.622
1.622
0.632
MI
0.1
0.1

0.166
0.443
0.713
0.964
1.467
2.199
1.467
1.195
0.424
0.233
0.114
0.166
0.436
0.537
0.767
1.947
1.947
0.183
MII
18.2
2.1

0.236
0.445
0.584
0.669
0.800
1.272
0.800
0.693
0.252
0.145
0.069
0.236
0.880
0.846
1.164
2.953
2.953
0.378
MIII
70.6
14.7

0.645
1.787
2.722
3.549
5.279
8.393
5.279
4.571
1.659
0.955
0.453
0.645
2.401
2.310
3.177
8.060
8.060
1.031
MIV
5.0
12.8

0.997
0.966
0.949
0.979
0.951
0.443
0.951
0.981
0.984
0.977
0.981
0.997
0.970
0.969
0.965
0.406
0.406
0.967
MV
<0.1
5.2

Fig. 5QW and GF denote rough and relatively smooth sand, respectively; MQW, mass percentage of rough QW sand in columns; Meff, the mass percentages of AgNPs recovered from
efﬂuent; MI e MV, the mass percentages of AgNPs recovered from phase I e V in release experiments; k1, the ﬁrst-order retention coefﬁcient; Smax/Co, normalized maximum
solid phase concentration of deposited NPs; Sf, the fraction of the grain surface area that contributes to AgNP retention, BET and geometric denote Sf calculation based on BET
measurements and geometric estimates, respectively; R2, Pearson’s correlation coefﬁcient. Constant Darcy velocity ¼ 0.7 cm min1 and Co ¼ 10 mg L1 were employed in all
experiments.

Y. Liang et al. / Environmental Pollution 258 (2020) 113803

5

Fig. 1. Laser scanning confocal microscope images of rough sand (a) and relatively smooth sand (b) used for column experiments.

heterogeneity that is larger than a critical size can create regions on
a net unfavorable surface that are favorable for interaction between
the colloid and the solid surface due to a local reduction in theenergy barrier and an increase in the depth of the primary minimum. However, differences in nanoscale chemical heterogeneity
are not expected to be the primary cause for the observed AgNP
retention behavior on QW and GF sands because: (i) both sands
were chemically treated to minimize chemical heterogeneity; (ii)concentrations of major cations in the acid digest of the sands weresimilar (Table S2); (iii) the predicted energy barrier was nearly
identical when using measurements of sand streaming potential(Table S1); and (iv) previous studies have demonstrated thatinteraction energy proﬁle properties are more sensitive to nanoscale roughness than charge heterogeneity (Bradford et al., 2017).
Signiﬁcant differences in the roughness properties of QW and GF
sands (Fig. 1, Fig. S1, and Table S2) provide a plausible alternative
explanation for differences in AgNP retention in Fig. 2. The energy
barrier to the primary minimum at IS ¼ 5 mM and pH ¼ 6.5 washigh enough to inhibit most AgNP retention on the relatively
smooth GF sand (Table S1). Conversely, the roughness properties of
the QW sand greatly enhanced AgNP retention. Interaction energy
calculations have demonstrated that the tops of nanoscale roughness pillars can locally reduce and/or eliminate the energy barrier
and the depth of the primary minimum (Shen et al., 2012; Bradford

et al., 2017). These roughness effects on interaction energies are
magniﬁed for locations with smaller roughness fractions (e.g., pillar
diameters) and when roughness occurs on both the colloid andsand surface (Bradford et al., 2017). Diffusive or hydrodynamic
removal of colloids from a primary minimum may occur in somecases depending on the local roughness properties (Torkzaban and
Bradford, 2016; Bradford et al., 2017). Concave locations between
protruding roughness asperities also inﬂuence the interaction energy proﬁles (Shen et al., 2012; Li et al., 2017). The energy barrier
can be reduced or eliminated at the vertices of these locations
because repulsive forces on AgNPs act in opposite directions andcancel out (Li et al., 2017). Colloids that are retained in concave
locations are less susceptible to removal by hydrodynamic forces
and/or IS reduction than on pillar tops (Li et al., 2017). These observations indicate that the greater k1, larger Smax/Co, and stronger
retardation in the QW sand (Fig. S3) were mainly produced by sandsurface roughness properties.

Fig. 2. Observed and ﬁtted breakthrough curves of AgNPs in various mixture ratios ofrough and relatively smooth sand (QW and GF denote rough and relatively smoothsand, respectively) when the IS ¼ 5 mM KNO3 and pH ¼ 6.5. Lines were ﬁtted results.

Fig. 3. Observed and ﬁtted breakthrough curves of AgNPs under various pH values inrough sand (QW denotes rough sand) when the IS ¼ 5 mM KNO3. Lines were ﬁtted
results.

3.4. Sensitivity of AgNP retention to pH in rough QW sandTransport experiments were carried out to better understandthe pH dependence of AgNP retention on relatively rough QW sand.
Fig. 3 presents observed and simulated BTCs for AgNPs in therelatively rough QW sand when the solution IS ¼ 5 mM KNO3 and6

Y. Liang et al. / Environmental Pollution 258 (2020) 113803

the pH ¼ 4.0, 6.5, 8.0, 8.5, 9.0, and 10.0. Results show that an increase in pH resulted in gradual enhancement of AgNP transport.
Fitted values of k1 and Smax/Co when the solution pH ¼ 4.0 were
nearly 30-fold higher than those obtained when the pH ¼ 10.0
(Table 1). Moreover, the ﬁtted k1 and Smax/Co were inversely proportional to the pH values (Fig. S3 B2 and C2). Additionally, theretardation of the AgNP breakthrough was gradually diminishedwhen the solution pH was increased.
AgNP attachment is inhibited or eliminated when Fmax isgreater than around 5.7 (Bradford and Torkzaban, 2015). The valueof Fmax tends to increase with pH because of more negative zeta
potentials and greater electrostatic repulsion (Table S1). This increase in Fmax with pH will therefore decrease the roughness effects that contribute to AgNP retention. Table S3 gives an exampleof the inﬂuence of roughness on Fmax when pH ¼ 4 and 10 and the
IS ¼ 5 mM. Table 1 also indicates that the fraction of the geometricsurface area that contributed to AgNP retention (Sf) dramaticallydecreased from 8.39% to 0.45% as the pH was increased from 4 to 10,
respectively. BET estimates of Sf were even smaller.

3.5. AgNP retention in the sand with a relatively smooth surface
Fig. 4 shows observed and simulated AgNP BTCs in the relatively
smooth GF sand when the solution IS equaled 5, 10, 20, 40, 50 mM
KNO3 at pH 6.5. Experimental results indicate that the AgNP
retention and retardation of the BTCs were signiﬁcantly increased
with the IS. No breakthrough was observed when the IS was 50 mM
KNO3. A number of column studies have previously observed thetrend of increasing AgNP retention (Lin et al., 2011; Liang et al.,2013a; Liang et al., 2013b; Braun et al., 2015) and retardation
with IS (Liang et al., 2013a; Adrian et al., 2018). Generally, theoptimized simulations provided a good description of the BTCs
when AgNPs broke through (R2 > 0.96). Fitted values of k1 and Smax/
Co systematically increased with IS, whereas calculated Meffdecreased with IS (Table 1). Similar blocking behavior was observed
and discussed in section 3.3.
Trends for AgNP BTCs, and ﬁtted and calculated parameters with
IS can be partially explained by the decrease in energy barrier with
IS when the double layer was compressed (Fig. S2a). However,these interaction energy calculations predict that the entire surface
area of the GF sand will equally contribute to AgNP retention and allparticles will be retained when the IS ¼ 40 and 50 mM. In contrast,
Fig. 4 and Table 1 show a systematic difference in the AgNP
transport behavior and ﬁtted and calculated parameters withincreasing IS. In particular, k1 and Smax/Co increase with IS. In
addition, calculated values of Sf in Table 1 indicate that only a small
fraction of the GF sand surface area contributed to AgNP retention,even for the favorable condition when the IS ¼ 50 mM (Sf is lessthan 8.06% and 2.95% for geometric and BET estimates of surface
area, respectively).
Signiﬁcant amounts of nanoscale surface roughness occur evenon the relatively smooth GF sand (Table S2). Particularly, thegradual variation of AgNP retention with increasing IS (Fig. 4)
further demonstrates the important role of surface roughness,
which results in differences in the energy barrier high and thedepth of the primary minimum depending on IS. Otherwise, the
AgNP retention would vary sharply with increasing IS due to thetransition from unfavorable (no retention) to favorable (complete
retention) interactions. Research has also demonstrated that thenanoscale roughness fraction has a larger inﬂuence on the shape of
the interaction energy proﬁle than the roughness height and that asmall roughness fraction and height can produce shallow primary
minimum on pillar tops that are susceptible to diffusive or hydrodynamic release (Bradford et al., 2017). This can produce portions of
the surface area that are unfavorable for AgNP, even when favorable
conditions are predicted on smooth surfaces (Zhang et al., 2016;
Bradford et al., 2017). Furthermore, the roughness parameters that
contribute to irreversible colloid retention have been observed tochange and increase with the solution IS (Bradford et al., 2017).
Consequently, roughness may also help to explain the trends of
AgNP retention with IS (e.g., increasing k1 and Smax/Co with IS), evenon the relatively smooth GF sand (Bradford et al., 2017).
Fig. S5 presents observed and simulated AgNP BTCs in therelatively smooth GF sand when the solution IS ¼ 50 mM KNO3 andthe pH ¼ 6.5 and 8.0. The AgNP transport was greatly enhanced
when the solution pH was increased from 6.5 (no breakthrough) to
8.0 (78.1% recovered in the efﬂuent). Note that this enhancement in
AgNP transport with increasing pH on the relatively smooth GF
sand at IS ¼ 50 mM (Fig. S5) was much greater than for the roughQW sand at IS ¼ 5 mM (Fig. 3). This implies that changes in theinteraction energy proﬁle when the pH changed from 6.5 to 8.0 had
a larger inﬂuence on AgNP retention with the relatively smooth GF
sand at IS ¼ 50 mM than on the rougher QW sand at IS ¼ 5 mM. The
probability of AgNPs to diffuse into the primary minimum rapidly
increases from 0 to 1 as the energy barrier decreases from around
5.7 to 0 (Bradford and Torkzaban, 2015). Consequently, thisincreased sensitivity to pH likely reﬂects differences in the energy
barrier heights. In particular, AgNP attachment occurs more readily
for the lower energy barrier on the GF sand at IS ¼ 50 mM than forthe higher energy barrier on the QW sand at IS ¼ 5 mM (Table S1).
3.6. Release of retained AgNPs from quartz sands with different
roughness

Fig. 4. Observed and ﬁtted breakthrough curves of AgNPs under various ionic strength
in relatively smooth sand (GF denotes relatively smooth sand) when the pH ¼ 6.5.
Lines were ﬁtted results.

Additional experiments were conducted to study the release
behavior of AgNPs from QW and GF sands. To achieve similar
amounts of AgNP retention, the initial deposition occurred at an
IS ¼ 5 mM KNO3 and pH ¼ 6.5 in the relatively rough QW sand, andfor the relatively smooth GF sand an IS ¼ 40 mM KNO3 and pH ¼ 6.5
was employed. Fig. 5 presents the release behavior of retained
AgNPs under various solution and ﬂow interruption conditions thatare summarized in the ﬁgure caption. Release phase I consisted of a
20 h ﬂow interruption followed by continued elution with the same
particle-free electrolyte solution as during the deposition phase.
There was only a negligible amount (0.1%) of AgNPs detected in the
efﬂuent for both sands (Table 1). This implies that the retained

Y. Liang et al. / Environmental Pollution 258 (2020) 113803

Fig. 5. AgNP release from relatively smooth and rough sand (QW and GF denote roughand relatively smooth sand, respectively). AgNP retention occurred at 40 and 5 mM
KNO3, respectively; release of AgNPs was initiated by 20 h interruption ﬂow with 40
and 5 mM KNO3 (phase I, pH ¼ 6.5), eluting with ultrapure water (phase II, pH ¼ 6.5;
phase III, pH ¼ 10) and 20 h interruption ﬂow with ultrapure water (phase IV,
pH ¼ 10).

AgNPs were interacting on the collector surface in a primary minimum that was strong enough to overcome the strength of diffusion; e.g., the energy barrier to detachment was larger than 5.7.
The eluting solution IS was reduced from 5 to 40 mM KNO3 for
the QW and GF sands, respectively, to that of ultrapure water at
pH ¼ 6.5 during release phase II (Fig. 5). Only a small fraction of theretained AgNPs was released from the relatively rough QW sand
(2.1%), whereas a much larger fraction was released from therelatively smooth GF sand (18.2%). Furthermore, the AgNP release
pulse occurred very rapidly from the smoother GF sand and thenexhibited lower amounts of release. Note that release with areduction in IS cannot be explained by the elimination of the secondary minimum because it was not deep enough for colloid
immobilization in 5 or 40 mM KNO3 solution. Furthermore, colloid
release with IS reduction from a deep primary minimum fromcharge heterogeneity on a smooth grain surface is not possible due
to an increase in the energy barrier (Shen et al., 2018). Conversely,
colloid release with IS reduction may occur from shallow primary
minima that happen on tops of nanoscale roughness asperities likepillars (Shen et al., 2018) or fractal surfaces (Shen et al., 2018; Wanget al., 2019), but not from concave locations between roughness
asperities because attachment (in primary minima) is irreversible
to IS reduction in these valley areas (Li et al., 2017; Wang et al.,2019). The difference in the AgNP release with IS reduction
apparently reﬂects retention on asperities with a shallower primary minimum on the smoother GF sand than the rougher QWsand, e.g., GF sand may contain a smaller roughness fraction ormore nanoscale asperities (Wang et al., 2019) than the rougher QW
sand.
The pH was increased from 6.5 to 10 while maintaining very low
IS conditions (ultrapure water) during phase III of the release
experiment (Fig. 5). An additional 14.7% and 70.6% of the retained
AgNPs were released from the rougher QW and smoother GF sands,
respectively (Table 1). Similar to phase II, AgNP release from thesmoother GF sand was again very rapid, and then exhibited lower
amounts of release. Conversely, the release of AgNPs from therougher QW sand was slower than the smoother GF sand, and it
gradually reached a peak concentration value at a later time due toslow diffusive release from deeper primary minima. These trends

7

are generally consistent with those observed during phase II, whichwere attributed to shallower primary minima on the smoother GF
sand due to a smaller roughness fraction. The additional AgNP
release when the pH was increased from about 6.5 during phase II
to 10 during phase III can be explained by a further decrease and/or
elimination of the energy barrier to detachment for certain
roughness conditions (Torkzaban and Bradford, 2016) when thezeta potential magnitudes were increased (Table S1). Phase IV of
the release experiment (Fig. 5) employed a 20 h ﬂow interruption
and was followed by continued elution of ultrapure water at
pH ¼ 10. About 12.8% and 5.0% of the retained AgNPs were released
from the rougher QW and smoother GF sands, respectively. Similar
release kinetics were observed during phases I through IV. However, a higher release pulse was obtained for the rougher GW than
the smoother sand. This occurs because all injected AgNPs wererecovered after phase IV from the smoother GF sand (Table 1),
while the 20 h ﬂow interruption (after eluting with water at pH 10)
allowed for increased time for diffusive release from the shallow
primary minima or from low ﬂow regions such as concave locations
on the rougher QW sand.
Only 5.2% of retained AgNPs was recovered when the rougher
QW sand was excavated from the column and placed in a container
with ultrapure water at pH 10 and gently shaken for a few minutes(phase V). Furthermore, less than 40% of the retained AgNPs werecollected during release phases I-V for the rougher QW sand. The
low total recovery of the AgNPs from the QW sand indicates thatremaining AgNPs were retained in a deep primary minimum thatwas stronger than forces from random kinetic energy ﬂuctuations
and/or hydrodynamic shear (Torkzaban and Bradford, 2016). Such
conditions may occur in surfaces with larger roughness fractions or
nanoscale charge heterogeneity on smooth surfaces (Bradford et al.,2018), and/or at concave locations (Shen et al., 2018).
4. Conclusions
Natural porous media commonly exhibit pronounced surface
roughness. Experimental results, ﬁtted model parameters, andinteraction energy calculations demonstrated that nanoscaleroughness on the collector surface controlled AgNP retention andrelease and that these effects were dependent on the solution
chemistry. In particular, limited amounts of AgNPs retention
occurred in shallow primary minima (e.g., the tops of smallroughness asperities) on the relatively smooth sand that was
rapidly released when the IS was reduced and the pH increased.
Conversely, much more AgNP retention occurred in deeper primary
minima (e.g., concave locations between roughness asperities) on
the rougher sand that was mainly irreversible to changes in solution chemistry. Collected data from this study provide valuable
information and insight on the importance of roughness on thetransport and release of AgNPs, the conditions that enhance or
reduce the inﬂuence of surface roughness, and the correlation of
AgNP deposition parameters with surface roughness. This information also indicates that surface roughness properties of porous
media can be optimized to enhance or diminish the retention ofcolloids and nanoparticles for speciﬁc engineering or environmental applications.
Acknowledgments
This research was funded by the National Natural Science
Foundation of China (Grant NO. 21507015; 51561135012), Guangxi
NaturalScienceFoundation,
China(GrantNO.
2015GXNSFCA139015; 2017GXNSFBA198076), and Cultivation Baseof Guangxi Key Laboratory for Agro-Environment and Agro-Product
Safety (17-259-82). The authors would like to acknowledge the8

Y. Liang et al. / Environmental Pollution 258 (2020) 113803

assistance of Dr. Huijun Yao for SEM measurement.
Appendix A. Supplementary data
Supplementary data to this article can be found online athttps://doi.org/10.1016/j.envpol.2019.113803.
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