Environmental Pollution 236 (2018) 195e207

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

Transport and retention of surfactant- and polymer-stabilizedengineered silver nanoparticles in silicate-dominated aquifer
material*
Yorck F. Adrian a, *, Uwe Schneidewind a, Scott A. Bradford b, Jirka Simunek c,Tomas M. Fernandez-Steeger d, Raﬁg Azzam aaDepartment of Engineering Geology and Hydrogeology, RWTH Aachen University, Lochnerstr. 4-20, 52064 Aachen, Germany
US Salinity Laboratory, USDA, ARS, Riverside, CA 92507, United States
Department of Environmental Sciences, University of California, Riverside, CA 92521, United StatesdDepartment of Engineering Geology, TU Berlin, Ernst-Reuter-Platz 1, 10587 Berlin, Germanybca r t i c l e i n f o

a b s t r a c t

Article history:
Received 1 September 2017
Received in revised form
4 December 2017
Accepted 4 January 2018

Packed column experiments were conducted to investigate the transport and blocking behavior of surfactant- and polymer-stabilized engineered silver nanoparticles (Ag-ENPs) in saturated natural aquifer
media with varying content of material < 0.063 mm in diameter (silt and clay fraction), backgroundsolution chemistry, and ﬂow velocity. Breakthrough curves for Ag-ENPs exhibited blocking behavior thatfrequently produced a delay in arrival time in comparison to a conservative tracer that was dependent on
the physicochemical conditions, and then a rapid increase in the efﬂuent concentration of Ag-ENPs. This
breakthrough behavior was accurately described using one or two irreversible retention sites that
accounted for Langmuirian blocking on one site. Simulated values for the total retention rate coefﬁcientand the maximum solid phase concentration of Ag-ENPs increased with increasing solution ionicstrength, cation valence, clay and silt content, decreasing ﬂow velocity, and for polymer-instead of
surfactant-stabilized Ag-ENPs. Increased Ag-ENP retention with ionic strength occurred because ofcompression of the double layer and lower magnitudes in the zeta potential, whereas lower velocities
increased the residence time and decreased the hydrodynamics forces. Enhanced Ag-ENP interactions
with cation valence and clay were attributed to the creation of cation bridging in the presence of Ca2þ.
The delay in breakthrough was always more pronounced for polymer-than surfactant-stabilized AgENPs, because of differences in the properties of the stabilizing agents and the magnitude of theirzeta-potential was lower. Our results clearly indicate that the long-term transport behavior of Ag-ENPs innatural, silicate dominated aquifer material will be strongly dependent on blocking behavior thatchanges with the physicochemical conditions and enhanced Ag-ENP transport may occur when retention
sites are ﬁlled.
© 2018 Elsevier Ltd. All rights reserved.

Keywords:
Engineered silver nanoparticles
Contaminant transport
Groundwater
Column experiments
Blocking

1. Introduction
Engineered silver nanoparticles (Ag-ENPs) are among the mostwidely used nanoparticles in consumer products due to theirantimicrobial properties (Maillard and Hartemann, 2013; Zhang
et al., 2016). Their use has among others been documented fortextiles, paints, cleaning agents, electrical appliances, medical*

This paper has been recommended for acceptance by B. Nowack.
* Corresponding author.
E-mail address: yorck.adrian@rwth-aachen.de (Y.F. Adrian).

https://doi.org/10.1016/j.envpol.2018.01.011
0269-7491/© 2018 Elsevier Ltd. All rights reserved.

technology and cosmetics (Goswami et al., 2017 for review). AgENPs can be released into the environment during manufacturing
processes, product distribution, product use, and disposal (Farkas
et al., 2011; Kaegi et al., 2010; McGillicuddy et al., 2017). Once inthe environment Ag-ENPs can become bioavailable (Navarro et al.,2008) and are potentially toxic or detrimental to a wide variety oforganisms (Andrei et al., 2016; Juganson et al., 2017; Katsumiti
et al., 2015; Makama et al., 2016; Mallevre et al., 2014; Siller
et al., 2013; Zuykov et al., 2011).
One major route for environmental release is through wastewater (Nowack and Bucheli, 2007; Nowack et al., 2012; Troester

196

Y.F. Adrian et al. / Environmental Pollution 236 (2018) 195e207

et al., 2016). Ag-ENPs can be retained in activated sewage sludge in
wastewater treatment plants (Kaegi et al., 2011, 2013; Maier et al.,2012), which is then used as agricultural fertilizer or disposed ofat landﬁlls (Blaser et al., 2008). Ag-ENPs can subsequently beleached into the vadose zone and transported toward groundwater.
Groundwater can exhibit variations in solution ionic strength (IS)because of changes in aquifer material composition, temporal variations in recharge, groundwater-surface water interactions,increased salinization, and mixing of groundwater of different age
and compositions. In many countries, groundwater is a major
source of drinking water serving millions of people (Danish
Ministry of the Environment, 2013; Federal Statistical Ofﬁce ofGermany, 2013; United States Environmental Protection Agency,2008). Thus, understanding Ag-ENP transport processes in thesaturated zone is essential to the protection and future use ofgroundwater resources.
Colloid and nanoparticle transport studies have typically been
conducted under clean bed conditions using highly idealized
porous media and solution chemistries (Flory et al., 2013; Kanel
et al., 2007; Lin et al., 2011; Liu et al., 2009; Mattison et al., 2011).
For example, glass beads and/or coarse textured sand that havebeen rigorously cleaned and monovalent electrolyte solutions arecommonly employed in these studies (Bradford et al., 2002; Linet al., 2011; Liu et al., 2009). Clean bed conditions imply a constant rate of retention and an inﬁnite retention capacity (Yao et al.,1971). Colloid ﬁltration theory (CFT) is commonly employed tocharacterize colloid and nanoparticle retention under clean bed
conditions (Bayat et al., 2015; Park et al., 2016). Filtration theory
describes retention as a ﬁrst-order process that depends on the rateof mass transfer (diffusion, interception and sedimentation) fromthe bulk aqueous phase to the solid surface, and a sticking or
collision efﬁciency that is controlled by adhesive interactions between the nanoparticle and solid (Tufenkji and Elimelech, 2004a;
Yao et al., 1971). Nanoparticle transport studies that apply CFT
typically assume that lower efﬂuent concentrations imply less riskof contamination (Tufenkji and Elimelech, 2004b). It is demonstrated in this work that this assumption is inaccurate in many
instances for Ag-ENPs.
In contrast to the CFT assumption, soil and aquifer material always have a ﬁnite retention capacity (Johnson and Elimelech, 1995;
Leij et al., 2015; Sasidharan et al., 2014; Torkzaban et al., 2012), andthe retention rate coefﬁcient, therefore, decreases over time asavailable retention sites ﬁll (also referred to as blocking). Retention
is completely eliminated when all of the available retention sites
are ﬁlled, and the retained solid phase concentration reaches amaximum, thus enhancing the long-term potential for Ag-ENP
transport (Leij et al., 2015). Langmuirian (Adamczyk et al., 2013)
and random sequential adsorption blocking (Johnson andElimelech, 1995) models assume that the retention rate coefﬁcient decreases in a linear and nonlinear manner with increasing
retention, respectively. This has been observed not only for AgENPs but also for other colloids (e.g. Kuhnen et al., 2000). An
alternative approach to account for nonlinear blocking dynamics is
to employ Langmuirian blocking on two retention sites, withseparate retention and release rate coefﬁcients and maximum
retention capacities on each site (Sasidharan et al., 2014).
The rate of ﬁlling of retention sites increases with the input
concentration, input pulse duration, the clean bed retention rateand decreasing values of the maximum solid phase concentration(Leij et al., 2015). In addition, the retention rate and the maximum
solid phase concentration are strong functions of many physicochemical variables (Sasidharan et al., 2014). Consequently, the selection of experimental conditions can have a large impact onwhether or not blocking is apparent in transport experiments.
Previous research on Ag-ENP transport has focused on thedetermination of retention rate coefﬁcients for varying physicochemical conditions, including grain size (Liang et al., 2013b), watervelocity (Braun et al., 2015), solution IS (Liang et al., 2013b; Wanget al., 2014) and pH (Flory et al., 2013), ionic composition (Lianget al., 2013a), organic matter (Hou et al., 2017; Mitzel andTufenkji, 2014; Park et al., 2016), or stabilizing agent for the AgENPs (El Badawy et al., 2013). These studies typically were notdesigned to investigate blocking dynamics that control the longterm potential of Ag-ENP transport. A limited number of studies
have examined the transport and retention of Ag-ENPs in naturalsoils (Cornelis et al., 2013; Liang et al., 2013a; Sagee et al., 2012;
Wang et al., 2014, 2015; Makselon et al., 2017. Some of thesestudies neglected the inﬂuence of blocking altogether (Cornelis
et al., 2013; Sagee et al., 2012), whereas those that did consider
blocking (Liang et al., 2013a; Wang et al., 2014; Wang et al., 2015)
did not systematically investigate the role of stabilizing agent type,small amounts of silt and clay in silicate-dominated aquifer material, and the coupling of these factors with monovalent and divalentcations, IS, and water velocity. These gaps in knowledge are
addressed in this research.
The objective of our work was to study the transport andblocking behavior of surfactant- and polymer-stabilized Ag-ENPs
in silicate-dominated aquifer material, a material that can befound around the world in many unconsolidated aquifers
essential to drinking water supply. To achieve this objective, we
conducted laboratory column experiments and employed
analytical methods (inductively coupled plasma mass spectrometry, dynamic light scattering) as well as numericalmodeling techniques. During the transport experiments, we
speciﬁcally focused on situations that are more representative of
natural conditions than previous studies (Hou et al., 2017; Liet al., 2008; Mattison et al., 2011; Mitzel and Tufenkji, 2014),
including (i) IS and major cation type (Ca2þ or Naþ); (ii) stabilizing agent (polymer or surfactant) for Ag-ENPs in the absence
and presence of ﬁne particle size fractions (<0.063 mm); and (iii)changing ﬂow velocities in the column.
2. Materials and methods
2.1. Electrolyte solutions and aquifer material
All electrolyte solutions were prepared using ultrapure water(Merck Millipore Milli-Q 18.2 MU$cm, TOC: 1e2 ppb, 0.22 mm
membrane ﬁlter) that was unbuffered with a pH of 5.8e6.2. Solutions of selected IS and composition were prepared by adding
NaNO3 (Sigma Aldrich, St. Louis, Missouri, USA) or Ca(NO3)2$4H2O(Merck KGaA, Darmstadt, Germany) to the ultrapure water.
The silicate-dominated aquifer material was collected in
Dormagen-Gohr, NRW, Germany from a depth between 16 and19.5 m below surface during the drilling of a groundwater
monitoring well. The shallow unconﬁned aquifer at that site
consists mainly of unconsolidated ﬁne to coarse Quaternarysands and gravels deposited during the Saale glaciation (Pleistocene). A sample of the aquifer material (0e2 mm grain size)
was oven-dried at 40  C, and the mineral and clay composition
were determined by means of X-ray powder diffraction (XRD)
using a Siemens D5000 (Table S1). The oven-dried aquifer material was also sieved into grain size fractions of 1e2, 0.5e1,
0.025e0.5, 0.125e0.25, 0.063e0.125, and <0.063 mm to obtain arepresentative grain size distribution (Fig. S1) with a mediangrain diameter of 0.7 mm. Hydrometer analysis was carried out
on the fraction <0.063 mm to determine silt (fraction of
0.002e0.063 mm) and clay (<0.002 mm) percentages, and to
recover them for studies examining their inﬂuence on Ag-ENP
transport. The pH of the soil solution was measured according

Y.F. Adrian et al. / Environmental Pollution 236 (2018) 195e207

to the German standard DIN EN 15933 (2012) in 0.01 mol L1
CaCl2 (Merck KGaA, Darmstadt, Germany). Brunauer-EmmettTeller (BET) measurements were conducted in triplicates on
samples of aquifer material using N2 to determine the surface
area in the presence and absence of ﬁnes.
2.2. Ag-ENPs
Two types of commercial Ag-ENPs were employed in thisresearch, namely AgPURE™ W-10 (ras materials GmbH,Regensburg, Germany) and polyvinylpyrrolidone (PVP) coated
Ag-ENPs (Getnanomaterials GNM, OOCAP SAS, France, stocknumber: 7023HZ). The stock suspension of the sterically stabilized AgPURE™ W-10 contained a silver nanoparticle concentration of 10.16% (weight/weight, wt/wt) and corresponds to
the OECD reference material NM300K, in which the silver
nanoparticles are stabilized with 4% (wt) of each polyoxyethylene glycerol trioleate and Tween 20 (Klein et al., 2011).
Furthermore, AgPURE™ W-10 contains 7.5% (wt/wt) ammonium nitrate (Menzel et al., 2013). The PVP-coated Ag-ENP
powder consisted of 10% (wt) silver with a purity of 99.99%, as
well as of 89.8% (wt) PVP and 0.2% (w) moisture. For experiments discussed below, the stock suspension of AgPURE was
diluted to 10 mg Ag/L in the desired background solution andsonicated for 15 min. Similarly, the PVP coated Ag-ENP powder
was dispersed in the desired background solution and sonicated for 10 min in a sonication bath. Afterwards, the dispersion was diluted to 10 mg Ag/L and sonicated for 5 min.
AgPURE Ag-ENPs have a spherical shape and 99% of the particle
size is in the range of 15e20 nm, determined by transmission
electron microscopy (Klein et al., 2011). Similarly, according to the
manufacturer, the size of the PVP coated Ag-ENPs was 20 nm. A
Zetasizer Nano ZS (Malvern GmbH) was used to determine theelectrophoretic mobility at 25  C of the Ag-ENPs and the aquifer
material that was <10 mm in size in the corresponding backgroundsolution as well as the hydrodynamic diameter of the Ag-ENPs. The
electrophoretic mobility was then converted to the zeta potential[mV] using the Smoluchowski equation.
2.3. Interaction energies
Section S1 of the supporting information provides details pertaining to the calculation of the total interaction energy of Ag-ENPs
upon approach to the aquifer material under the various solution
chemistries. In brief, the total interaction energy was determined as
the sum of electrostatic (Hogg et al., 1966), van der Waals (Gregory,1981), and Born (Ruckenstein and Prieve, 1976) interactions. These
calculations employed zeta potentials in place of surface potentials,
a Hamaker constant of 5.3  1020 J (Bhattacharya et al., 2007), anda collision diameter of 0.26 nm to achieve a primary minimum
depth at 0.157 nm (Van Oss, 1994). All interaction energies weremade dimensionless by dividing by the product of the Boltzmann
constant and the absolute temperature.
2.4. Transport experiments
Borosilicate glass columns (inner diameter of 2.6 cm, length of
15 cm and volume of 79.6 mL) were wet packed with the ovendried aquifer material following the German standard DIN 19258(2009) as described by Braun et al. (2015). Some of the transport
experiments considered the inﬂuence of a 2% increase in the ﬁnesoil fraction <0.063 mm, while keeping grain diameters of the
distribution (Fig. S1) greater than 0.125 mm constant. Column
inlets and outlets were equipped with a 2 mm thick layer ofquartz wool to prevent very ﬁne grains from being ﬂushed out of197

the material matrix. Transport experiments were carried out inan up-ﬂow mode at an average pore-water velocity of 4.32 or
8.64 m d1 using a peristaltic pump (ICP High Precision Multichannel Dispenser, Ismatec). These water velocities were selectedbased on measurements of the saturated hydraulic conductivity
from falling head permeameter tests (DIN, 18130-1, 1998).
Columns were ﬂushed with at least 10 pore volumes (PV) of
ultrapure water before conducting a NaBr (Merck KGaA, Darmstadt,
Germany) tracer test. The tracer test consisted of ﬂushing 3 PV of
200 mg Br/L solution through the column, followed by continued
elution with 3 PV of ultrapure water. The bromide concentration
was measured using ion selective electrodes (DX280-Br, Mettler
Toledo GmbH, Gieben, Germany) and a reference electrode InLab®
Reference (DX280-Br, Mettler Toledo GmbH, Gieben, Germany)
connected to a conductivity meter (WTW pH/Cond 340i meter,
Weilheim, Germany).
Before initiating an Ag-ENP transport experiment, columns
were ﬂushed with at least 10 PV of background electrolyte
solution (sodium nitrate, Sigma Aldrich, USA; calcium nitrate
tetrahydrate, Merck KGaA, Darmstadt, Germany), and the AgENP suspension was sonicated for 15 min in an ultrasonicbath (Retsch UR-1, Retsch Technology GmbH, Germany). At
least 3 PV of Ag-ENP suspension was then injected into thecolumns followed by ﬂushing with at least 3 PV of Ag-ENP freebackground electrolyte solution with the same IS and composition. The inﬂuent Ag-ENP suspension was placed on a magnetic stirrer during long-term experiments. Column efﬂuent
fractions were collected in borosilicate vials using a fraction
collector. The total Ag concentration in efﬂuent samples wasdetermined using ICP-MS (Agilent 7900 ICP-MS, Agilent Technologies). In brief, 1 mL of the collected efﬂuent samples wastransferred into 15 mL polypropylene centrifuge tubes (VWR
International GmbH, Germany) and acidiﬁed with 1 mL 32.5%
HNO3 (Merck KGaA, Darmstadt, Germany) to dissolve the particles and minimize sorption onto the centrifuge tubes. Samples were then diluted as needed for ICP-MS analysis. Eachsample was measured three times and average values are reported here. The pH of inﬂuent and efﬂuent solutions wasmonitored using a SenTix 41 pH electrode (WTW, Germany)and indicator strips for comparison.
The focus of this research is to investigate the transport andblocking behavior of Ag-ENPs under a range of physicochemical
conditions that are more representative of natural aquifer material. Table 1 provides a summary of the considered experimental conditions including: (i) IS; (ii) ionic composition (Naþ orCa2þ); (iii) stabilizing agent (surfactant or PVP coating) for the
Ag-ENPs; (iv) absence or presence of the ﬁne aquifer material
fraction (i.e. 2% increase in the material fraction <0.063 mm insize); and (v) pore water velocity (4.32 and 8.64 m d1). The
arrival time, shape, magnitude, and efﬂuent mass balance of the
Ag-ENP breakthrough curves (BTCs) were quantiﬁed in thisstudy. The shape of the Ag-ENP retention proﬁles is inﬂuenced by
the extent of blocking (Leij et al., 2015). The presence of multiple
retention mechanisms and sites, retention rates, and retention
capacities that are dependent on various physicochemical conditions further complicates the effects of blocking on retention
proﬁles. Similar to other published blocking studies (Sasidharan
et al., 2014; Torkzaban et al., 2012), retention proﬁles were
therefore not considered in this work.
Most Ag-ENP transport experiments were replicated, and results are shown in Table S2. Illustrative examples of replicate AgENP BTCs are shown in Fig. S2. The agreement between replicate
experiments can be assessed by comparison of ﬁtted model parameters and efﬂuent mass balance information for Ag-ENPs thatare presented in Table S2. Differences in efﬂuent mass balance for

198

Y.F. Adrian et al. / Environmental Pollution 236 (2018) 195e207

Table 1
Summary of experimental conditions and simulated parameter values for the graphs shown in Figs. 1e6.
Figure Ag-ENP

IS

Ion f

[mM]
1
1
1
2
2
2
2
3
3
4
4
5
5
5
5
6
6
6
6

AgPURE
PVPAgNP
AgPURE
AgPURE
AgPURE
AgPURE
AgPURE
PVPAgNP
PVPAgNP
PVPAgNP
PVPAgNP
AgPURE
PVPAgNP
AgPURE
PVPAgNP
AgPURE
AgPURE
PVPAgNP
PVPAgNP

[-]

d50

dx q

[mm] [%] [ms1]  105lR2Tracertracer recovery

Smax1/C0 ksw1

ksw2

R2

[m]  102 [-]

[%]

[cm3
g1]

[s1]  104 [s1]  104 [-]Ag-ENP Recovery
Efﬂuent

Ag-ENP
Input

[%]

[mL]

1
1

Na 0.38 0.7
Na 0.37 0.7

0
0

3.8
3.7

0.95
0.51

1.00
0.98

100.2
99.3

0.15
0.66

1.1
31.2

e
1.8

1.00 92.6
0.99 51.1

90.3
299.7

1
0.05
0.1
0.5
1
1

Ca 0.37 0.7
Ca 0.38 0.7
Ca 0.38 0.7
Ca 0.38 0.7
Ca 0.37 0.7
Na 0.37 0.7

0
0
0
0
0
0

1.9
3.8
3.7
3.8
3.9
3.7

0.51
1.50
0.77
0.34
1.43
0.97

0.96
0,98
0.83
0.91
0.62
0.98

109.4
107.3
97.7
93.5
105.0
94.4

11.40
0.28
0.29
1.60
0.77
0.57

40.1
5.0
8.5
35.2
453.0
71.7

1.9
e
e
e
e
e

0.97 25.3
0.97 66.6
0.95 60.1
0.54 13.9
0.82 2.2
0.99 23.1

3363.0
88.4
87.9
89.9
91.6
94.6

0.1

Ca 0.38 0.7

0

3.7

0.51

0.97

104.7

0.65

151.0

e

0.96 15.6

87.7

0.05

Ca 0.37 0.7

2

3.7

3.81

0.99

96.3

0.66

81.4

e

0.93 10.1

89.9

0.05

Ca 0.37 0.7

0

3.7

0.85

0.79

89.7

0.44

33.1

e

0.98 34.7

89.0

1
1

Na 0.38 0.7
Na 0.37 0.7

0
0

3.8
3.7

0.95
0.97

1.00
0.99

100.2
102.9

0.15
0.52

1.1
48.8

e
e

1.00 92.6
0.98 23.1

90.3
89.5

1
1

Na 0.37 0.7
Na 0.37 0.7

2
2

3.7
3.7

1.26
1.12

0.98
0.99

105.9
94.8

0.21
1.01

3.2
117.5

e
e

0.97 76.1
0.93 0.4

87.8
88.4

1
1
1

Na 0.37 0.7
Na 0.37 0.7
Na 0.38 0.7

0
0
0

1.9
3.6
2.5

0.83
0.43
0.41

0.96
1.00
1.00

95.8
95.4
94.1

0.18
0.09
0.81

23.3
31.5
56.1

0.6
0.9
e

0.99 61.6
1.00 78.4
0.96 12.9

122.0
122.3
62.8

1

Na 0.37 0.7

0

3.7

0.97

0.99

102.9

0.52

48.8

e

0.98 23.1

89.5

IS: Ionic strength; f: porosity, determined gravimetrically; d50: mean grain size diameter; dx: fraction of grains < 0.063 mm; q: Darcy velocity (discharge per unit area); l:ﬁtted dispersivity obtained from tracer experiments; Smax1: maximum solid phase concentration; ksw1: ﬁrst-order retention coefﬁcient for the ﬁrst sorption site; ksw2: ﬁrstorder retention coefﬁcient for the second sorption site; and R2: Coefﬁcient of determination.

replicate experiments (<22.7%) were controlled by the physicochemical conditions and the uncleaned aquifer material which
determine variations in the retention capacity that inﬂuence theamount and extent of blocking.

The value of j1 is given as (Adamczyk et al., 1992, 1994):

j1 ¼ 1 
2.5. Mathematical and numerical modeling
Bromide tracer and Ag-ENP transport experiments weremodeled using the numerical ﬁnite element code HYDRUS 1D, version 4.16 (Simunek et al., 2008, 2016). The Ag-ENP transport wasmodeled using one or two kinetic retention sites with Langmuirian
blocking on site 1 as:vðqw CÞ
v
vC
vðqCÞ
¼
Dqw

 qw ðksw1 j1 þ ksw2 ÞC
vt
vz
vz
vz

(1)

vðrb S1 Þ¼ qw ksw1 j1 C
vt

(2)vðrb S2 Þ¼ qw ksw2 C
vt(3)

where qw [L3 L3] is the volumetric water content, rb [ML3] is thematerial bulk density, t [T] is the time, z [L] is the distance, D [L2T1]
is the hydrodynamic dispersion coefﬁcient, q [LT1] is the Darcy
ﬂux, C [ML3] is the aqueous phase concentration of Ag-ENP, S[MM1] is the solid phase concentration of Ag-ENP, ksw [T1] is theﬁrst order Ag-ENP retention coefﬁcient for the solid-water interface, j [] is a dimensionless Langmuirian blocking function, andthe subscripts 1 and 2 on parameters indicate sites 1 and 2,
respectively.

S1
Smax1

(4)

where Smax1 [M M1] is the maximum solid phase concentration of
Ag-ENPs on site 1. The fraction of the solid surface area that isavailable for retention (Sf1) on site 1 was calculated from Smax1 as(Kim et al., 2009):

Sf 1 ¼

Ac rb Smax1
ð1  gÞAs

(5)where Ac [L2N1] is the cross sectional area of an Ag-ENP, As [L1]
is the solid surface area per unit volume, and g is the porosity ofa monolayer packing of nanoparticles on the solid surface thatwas taken from the literature to be 0.5 (Johnson and Elimelech,
1995).
Transport of the conservative bromide tracer was modeled using
HYDRUS-1D by setting the ksw terms in Eq. (1) to zero. HYDRUS-1D
includes a provision for inverse parameter optimization to experimental data based on the Levenberg-Marquardt nonlinear leastsquares algorithm. This option was employed to determine thedispersivity and porosity from the bromide tracer data, andretention parameters (ksw1 , ksw2 and Smax1 ) from the Ag-ENP data.
The parameter ksw2 was only ﬁtted when Ag-ENP BTCs exhibited adelay in breakthrough, increased in concentration, and thenreached a plateau concentration.

Y.F. Adrian et al. / Environmental Pollution 236 (2018) 195e207

199

Table 2
Zeta-potential of the Ag-ENPs and the material fraction <10 mm in the corresponding background solution.
Type

IS

Ion

[mM]
Gohr
Gohr
Gohr
Gohr
AgPURE
AgPURE
AgPURE
AgPURE
AgPURE
PVP-Ag-ENP
PVP-AgNP
PVP-AgNP

0.05
0.1
0.5
1
0.05
0.1
0.5
1
1
0.05
0.1
1

Ca
Ca
Ca
Na
Ca
Ca
Ca
Ca
Na
Ca
Ca
Na

z-potential

Hydrodynamic diameterPrimary minimum

Energy barrier

Secondary minimum

[mV]

[nm]

[-]

[-]

[-]

17.4
18.9
19.1
35.6
25.1
10.8
7.8
6.5
14.0
7.1
6.8
3.6

53.1 ± 1.3
54.5 ± 5.2
56.3 ± 1.2
56.4 ± 1.5
51.0 ± 3.1
64.0 ± 1.2
61.8 ± 0.9
66.9 ± 4.4

248.58257.55
261.89289.34
263.09380.27
382.56434.37

11.01
3.68
0.93
0.69
5.18
2.82
2.33
0.11

0.00
0.00
0.03
0.07
0.05
0.00
0.00
0.15

IS: ionic strength.

3. Results and discussion

with X-ray diffraction analysis and a patch-wise iron-oxide coatingon the quartz sand surfaces was visible even to the naked eye.

3.1. Characterization of Ag-ENPs and porous media
3.2. Interaction energies
The zeta-potential and hydrodynamic diameter of the Ag-ENPs
in the considered background solutions are presented in Table 2.
Measurements show that PVP-coated Ag-ENPs are less negatively
charged compared to AgPURE. The sterically stabilized PVP-coated
Ag-ENPs showed only little changes in their zeta potential evenunder varying IS. This was also encountered by El Badawy et al.
(2010) for PVP-coated Ag-ENP from the same manufacturer. In
general, the zeta potential becomes less negative for both Ag-ENP
types with increasing IS and ion valence. Hydrodynamic diameters
for PVP-coated Ag-ENPs and AgPURE were found to be
61.79e66.89 nm and 51.03e56.41 nm, respectively. Additional size
measurements taken over several days show that both Ag-ENP
suspensions were stable (see Figs. S3 and S4). Similarly, Lianget al. (2013b) reported a hydrodynamic diameter of 45.1 ± 4.5 nm
in a 1 mM KNO3 background solution for AgPURE that was stable
over a period of 24 h. Furthermore, they found Agþ release to be lessthan 1% of the total mass within three days.
The average surface area of the aquifer material was determined
to be 2.69 and 3.26 m2 g1 in the absence and presence of ﬁnes,
respectively. The pH of the soil solution was determined to be 6.6.
Hydrometer analysis results showed that the fraction <0.063 mm
consisted of 90% silt and 10% clay-sized particles. The electrophoretic mobility of the aquifer material that was <10 mm in size wasmeasured at ISs of 0.05, 0.1, and 0.5 mM Ca2þ, and 1 mM Naþ. The
zeta potential of the aquifer material was more negative than thatof the Ag-ENPs at a given IS (Table 2). X-ray diffraction analysis
indicated that quartz was the dominant mineral by weight (seeTable S1) for all experiments. Quartz and feldspar are negatively
charged in groundwater environments, making them less favorable
for Ag-ENP attachment than minerals with positively charged sites
such as clays, iron oxides and iron hydroxides (Johnson et al., 1996;
Liang et al., 2013b; Molnar et al., 2015). However, patch-wise
geochemical surface heterogeneity may also be found on quartz
surfaces in groundwater environments due to the presence of Fe, Al
and Mn-oxides that have contrasting isoelectric points (Johnson
et al., 1996). For example, ferric and aluminum oxyhydroxides are
positively charged minerals that are often found on grain surfaces.
Consequently, iron-containing soil colloids (Liang et al., 2013b) or
subsurface material with locally high iron oxide/hydroxide content(Neukum et al., 2014) are expected to form regions that are electrostatically favorable for the attachment of negatively charged AgENPs and thus contribute to their retention. Indeed, iron oxides, aswell as the clay minerals muscovite and kaolinite, were detected

Table 2 presents a summary of calculated interaction parameters
for AgPURE and PVP coated Ag-ENPs with the aquifer material
under selected solution chemistry conditions. Interaction energy
calculations predict the presence of a negligible secondary minimum (>-0.15), a small energy barrier (<11.0), and a deep primary
minimum (<-248.6). These parameters indicate that Ag-ENPs willinteract with the aquifer material in a deep primary minimum. A
decrease in the energy barrier height increases the probability for
Ag-ENPs to diffuse over the energy barrier into the primary minimum (Shen et al., 2007; Simoni et al., 1998). Consequently, calculated energy barriers predict increasing Ag-ENP retention withincreasing IS and for PVP coated Ag-ENPs in comparison with
AgPURE.
The XDLVO calculations in Table 2 assume that the Ag-ENPs andaquifer material are perfectly smooth and chemically homogeneous, and neglect the potential inﬂuence of electrosteric interactions. Electrosteric repulsion has commonly been employed to
explain the enhanced stability of PVP or surfactant coated Ag-ENPs(Grasso et al., 2002). Indeed, XDLVO calculations can be modiﬁed toconsider the inﬂuence of electrosteric repulsion using information
about the adsorbed polymer or surfactant layer thickness anddensity (Fritz et al., 2002; Phenrat et al., 2007; Song et al., 2011;
Vincent et al., 1986). For example, Liang (2014) considered the inﬂuence of electrosteric repulsion on interaction energies between
AgPURE and quartz sand, and reported that adsorbed surfactant
increased the dimensionless energy barrier by around 1000 for
similar solution chemistry conditions to this work. In this case, no
Ag-ENP retention is expected on the aquifer material. Consequently, steric interactions cannot explain retention of Ag-ENPs on
the aquifer material, and other explanations need to be considered.
In particular, we discuss the roles of XDLVO interactions shown in
Table 2, charge and roughness heterogeneity, and cation bridging
below.
3.3. Ag-ENP blocking
Table 1 provides a summary of the considered physicochemical
conditions, measured and/or ﬁtted model parameters and massbalance information for bromide tracer and Ag-ENP transport experiments, and the coefﬁcient of determination for the goodness ofﬁt (R2) for Ag-ENP BTCs. The pH of inﬂuent and efﬂuent solutions
was determined to be between 5.8 and 6.2. Fitted values of Smax1

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Y.F. Adrian et al. / Environmental Pollution 236 (2018) 195e207

Fig. 1. Illustrative examples of long term transport behavior for Ag-ENPs under various physicochemical conditions, including varying stabilizing agent (surfactant and polymer
coating) and background solution.

were used to calculate Sf1 (Table S3) according to Eq. (5) when using
measured values of the aquifer material surface area and Ag-ENP
hydrodynamic diameters. Consistent with previous literature(Sasidharan et al., 2014), calculated values of Sf1 were very small(<5.4  105). This indicates that only a minor fraction of the solid
surface area contributed to Ag-ENP retention in these studies.
Fig. 1 presents observed and simulated Ag-ENP BTCs fordifferent physiochemical conditions and an example BTC for thebromide tracer. Relative efﬂuent concentrations (C/Co, where Co is
the inﬂuent concentration) are plotted as a function of the numberof PV ﬂushed through the columns on a log scale. Bromide tracer
tests showed nearly complete recovery (89.7e109.4%), and breakthrough occurred at 1 PV. All of the Ag-ENPs BTCs were welldescribed (R2 > 0.97) using either a one- or two-site retention
model that neglected detachment and accounted for Langmuirian
blocking on site 1. Blocking always produced an increase in the
efﬂuent concentration with continued Ag-ENP injection due toﬁlling of a limited number of retention sites, and this behavior ismanifested in several ways. In the AgPURE (IS ¼ 1 mM, Na) experiment the value of ksw1 is small enough that breakthrough occurs at
1 PV, and then the relative concentration rapidly increases to 0.94
as Smax1 is reached due to continued Ag-ENP injection. In contrast,
ksw1 is larger in the other two experiments and this causes a delay
in breakthrough that depends on the values of Smax1, Co, and the
input pulse duration (Leij et al., 2015). Here, breakthrough of AgENPs in the PVP-Ag-ENP (IS ¼ 1 mM, Na) and AgPURE (IS ¼ 1 mM,Ca) experiments occurred after about 4 and 76 PV, respectively, anda corresponding increase in the input pulse duration was needed toobserve blocking. Larger values of Smax1 and smaller values of Co
cause a longer delay in breakthrough. If the input pulse duration is
too small, breakthrough will not occur. If blocking occurs only on
one retention site, the relative efﬂuent concentrations will rapidly
approach a C/C0 of 1 following breakthrough due to ﬁlling of theretention sites. Conversely, the modeled relative efﬂuent concentrations approach a plateau concentration of 0.76 in the PVP-AgENP (IS ¼ 1 mM, Na) experiment and 0.58 in the AgPURE(IS ¼ 1 mM, Ca) experiment with continued injection. This isindicative of a second retention site with a lower ksw2 and higher

Smax2 than on site 1. Note that it was not possible to accurately
determine the values of Smax2 in PVP-Ag-ENP (IS ¼ 1 mM, Na) and
AgPURE (IS ¼ 1 mM, Ca) experiments because of the slow rate ofﬁlling.
Fig. 1 clearly demonstrates that temporal changes in the
breakthrough time and the peak efﬂuent concentration will occur
due to blocking that is a strong function of the physicochemical
conditions. Below, we systematically study the inﬂuence of Ag-ENP
blocking under different physicochemical conditions that are more
representative of natural environments than previous studies,including: the role of stabilizing agent type, small amounts of silt
and clay in silicate-dominated aquifer material, and the coupling ofthese factors with monovalent and divalent cations, IS, and watervelocity.
3.4. Ionic strength
Soil solution and groundwater can exhibit variations in IS
because of changes in aquifer material composition, temporal variations in recharge, groundwater-surface water interactions,increased salinization, and mixing of groundwater of different age
and compositions. Fig. 2 presents observed and simulated BTCs for
AgPURE when the calcium concentration was varied such that theIS equaled 0.05, 0.1, 0.5, and 1 mM Ca2þ. An increase in IS produced
an increase in Ag-ENP retention, and a corresponding increase in
ksw1 and Smax1 (Table 1). Similar to Fig. 1, blocking is evident in all
BTCs and a greater delay in breakthrough occurs with higher valuesof ksw1 and Smax1. An explanation for this behavior can be obtainedby considering factors that inﬂuence the adhesive interaction between the Ag-ENPs and the porous medium. In particular, themagnitude of the zeta potential of the Ag-ENPs decreases with anincrease in IS (Table 2). Furthermore, the double layer thickness
decreases with an increase in IS (Elimelech et al., 1998). Both ofthese factors reduce the energy barrier between the Ag-ENPs andthe porous medium (Table 2) and cause greater retention. Also,
spatial variations in nanoscale roughness and chemical heterogeneity can locally reduce or eliminate the energy barrier to Ag-ENP
retentionunderotherwiseelectrostaticallyunfavorable

Y.F. Adrian et al. / Environmental Pollution 236 (2018) 195e207

201

Fig. 2. Effect of ionic strength on AgPURE transport in the absence of ﬁnes. Pore water velocity ¼ 8.64 m d1, d50 ¼ 0.7 mm.

conditions (Elimelech et al., 2000; Song et al., 1994). It should be
mentioned that adsorption of calcium is known to produce charge
neutralization and/or reversal on the solid phase (Israelachvili,2011). Consequently, increased amounts of calcium sorption canenhance the apparent amount of nanoscale chemical heterogeneity
on the solid surface. Nanoparticle retention can also be enhanced
by calcium bridging between negatively charged Ag-ENPs and theporous medium. Huynh and Chen (2011) and Hoppe et al. (2014)indicated that calcium can bridge soil organic matter and thecapping agent of Ag-ENPs. In addition, Liang et al. (2013a) suggested that Ca2þ can induce bridging between AgPURE surfactants
and collector surfaces. Bridging complexation is also suggested by
Torkzaban et al. (2012) who studied the transport behavior of carboxylic ligand-modiﬁed latex particles.
3.5. Cation type
Many Ag-ENP transport studies have been conducted using

monovalent electrolyte solutions (El Badawy et al., 2013; Lin et al.,2011). Conversely, groundwater can be dominated by divalentions such as calcium. Fig. 3 presents observed and simulated BTCs
for PVP-coated Ag-ENPs when the solution IS was 1 mM Naþ or
0.1 mM Ca2þ. In contrast to Fig. 2, greater Ag-ENP retention
occurred in the lower IS solution that contained 0.1 mM Ca2þ incomparison to 1 mM Naþ. Blocking was observed for both 1 mM
Naþ and 0.1 mM Ca2þ systems, but greater delay in breakthroughoccurred for the 0.1 mM Ca2þ data because of higher values of ksw1
and Smax1 (Table 1). Other researchers have similarly observed
greater nanoparticle retention in the presence of divalent
compared to monovalent cations (Sasidharan et al., 2014; Wanget al., 2016). In contrast to Naþ, Ca2þ produces a larger reductionin the magnitude of the zeta potential and double layer thickness(Elimelech et al., 1998; Israelachvili, 2011). These effects were
accounted for in the interaction energy calculations and predicted
a larger energy barrier in 0.1 mM Ca2þ than 1 mM Naþ (Table 2).
However, these interaction energy calculations do not consider

Fig. 3. Effect of Ca ¼ 0.1 mM (solid) and Na ¼ 1 mM (dashed) on PVP-Ag-ENP transport in absence of ﬁnes. Pore water velocity ¼ 8.64 m d1, d50 ¼ 0.7 mm.

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Y.F. Adrian et al. / Environmental Pollution 236 (2018) 195e207

Fig. 4. Effect of presence (dashed line) and absence (solid) of ﬁnes (<0.063 mm) on PVP-Ag-ENP transport when Ca ¼ 0.05 mM. Pore water velocity ¼ 8.64 m d1, d50 ¼ 0.7 mm.

the potential inﬂuence of Ca2þ on charge neutralization orreversal (Israelachvili, 2011) and cation bridging (Liang et al.,2013a) which all contribute to an increased retention of AgENPs, even at a lower IS.
3.6. Fine grain fraction
Clay and silt particles are a result of chemical weathering in soils
and aquifer materials (Blume et al., 2010). Additional transport
experiments were therefore conducted to assess the inﬂuence ofclay and silt particles on Ag-ENP transport. Fig. 4 presents observed
and simulated BTCs for PVP-coated Ag-ENPs in the absence andpresence (2%) of ﬁne grained particles (<0.063 mm) when the solution IS was 0.05 mM Ca2þ. Similar to Figs. 1e3, a delay in Ag-ENP
breakthrough was observed as a result of blocking. However, thepresence of a small amount of ﬁnes signiﬁcantly enhanced theretention of the Ag-ENPs and produced larger values of ksw1 andSmax1 (Table 1).
Enhanced retention of Ag-ENPs in the presence of ﬁnes can becaused by several effects. In general, the presence of ﬁne material
increases the reactive surface area (see also section 3.1) andpotentially the number of sites for Ag-ENP retention. Cabal et al.
(2010) and Cornelis et al. (2013) reported that Ag-ENPs preferentially attach to positively charged edges of clay minerals, thenumber of which can increase with an increasing amount of ﬁne
grains. Furthermore, cation bridging between the stabilizing
agent of nanoparticles and the solid phase has been reported to beenhanced by clay particles (Cabal et al., 2010; Han et al., 2008).
This is especially the case for background solutions containing
increased amounts (increased IS) of Ca2þ leading to a decrease of
the size of the diffuse electrical double layer and increased possibility for charge reversal so that Ag-ENPs are more likely to
attach also to the previously negatively charged clay layers. Whenﬁne grains are heterogeneously coated with positively charged
minerals such as iron oxides, Ag-ENP attachment also becomes
more favorable and retention capacity increases (Cabal et al.,2010). Furthermore, the inter-particle structure can inﬂuence
nanoparticle retention. For example, the possibility of the presence of dead pore volumes and small pore spaces increases withincreasing silt and clay content. Water can ﬂow through thesepore structures which may be inaccessible to the nanoparticles(Sagee et al., 2012) and induce physical straining (Xin et al., 2016)or microﬁltration (Azzam, 1993).
3.7. Stabilizing agent
Suspensions of Ag-ENPs are frequently stabilized using various
surfactant and/or polymer coatings (El Badawy et al., 2010; El
Badawy et al., 2012). Additional experiments were carried out toexplore the inﬂuence of the stabilizing agent on Ag-ENP transport.
Fig. 5 presents observed and simulated BTCs for AgPURE and PVPstabilized Ag-ENPs in the absence (Fig. 5a) and presence (Fig. 5b) of
ﬁne-grained material (2% < 0.063 mm) when the solution IS was
1 mM Naþ. Surfactant-coated Ag-ENPs always exhibited lessretention and delay in BTCs than those coated with PVP. This corresponds to smaller values of ksw1 and Smax1 for AgPURE than for
PVP-coated Ag-ENPs. This can be explained in part by the morenegative zeta potential for AgPURE (14.0 mV) than PVP-coated
Ag-ENPs (3.55 mV) in 1 mM Naþ solution, which produces
greater amounts of electrostatic repulsion from the negatively
charged aquifer material (Table 2). Similar to Fig. 4, greater amountsof retention and delay in BTCs were observed in the presence(Fig. 5b) than the absence (Fig. 5a) of ﬁnes for both AgPURE and
PVP-coated Ag-ENPs. However, the inﬂuence of ﬁnes was mostpronounced for the less negatively charged PVP coated Ag-ENPs.
Differences in the amount and conﬁguration of adsorbed stabilizing agent on the Ag-ENPs and the aquifer material will also play
an important role in the transport and blocking behavior of AgENPs. Section 3.2 provides a discussion on why steric interactions
cannot explain Ag-ENP retention on the aquifer material. An
alternative explanation for the enhanced stability and low amountsof retention for polymer or surfactant coated Ag-ENPs is due tonanoscale heterogeneity (Bradford et al., 2017). All natural surfaces
contain nanoscale roughness and chemical heterogeneity (Sureshand Walz, 1996; Vaidyanathan and Tien, 1991). Nanoscale roughness and chemical heterogeneity can have a controlling inﬂuence
on interaction energy parameters (Bendersky and Davis, 2011;
Huang et al., 2010). In particular, nanoscale roughness tends tohave a greater inﬂuence on interaction energy proﬁles than charge
heterogeneity, and can locally reduce the energy barrier height andthe magnitudes of secondary and primary minima (Bradford et al.,2017; Bradford and Torkzaban, 2013), especially when roughness
occurs on both the colloid and the solid-water interface (Bradford
et al., 2017). In contrast to the inﬂuence of electrosteric repulsion

Y.F. Adrian et al. / Environmental Pollution 236 (2018) 195e207

203

Fig. 5. Effect of stabilizing agent (solid ¼ AgPURE; dashed ¼ PVP) in the absence (5a) and presence (5b) of ﬁnes (<0.063 mm). Pore water velocity ¼ 8.64 m d1, d50 ¼ 0.7 mm.

on the energy barrier height, nanoscale roughness creates colloid
stability and low amounts of retention by producing shallow primary minima that are subject to diffusive release. Spatial differences in roughness parameters on the aquifer material will alter thedepth of the primary minimum to produce Ag-ENP retention only
on some locations. Consistent with this hypothesis, calculated
values of Sf1 were very small (<5.4  105). In addition to nanoscaleroughness, Liang et al. (2013b) report that the original AgPURE
solution contains 5% unbound surfactant. Similarly, PVP coated AgENPs are also expected to contain a small percentage of unboundpolymer (Poda et al., 2011). Unbound stabilizing agents maycompete for the same positively charged (e.g., Al- and Fe-oxides)
retention sites as Ag-ENPs and enhance their mobility throughcompetitive blocking (Liang et al., 2013b; Becker et al., 2015).
Consequently, differences in the amount and sorption behavior ofunbound stabilizing agent can also contribute to observed differences in the AgPure and PVP coated Ag-ENP transport and blocking.
Additional research is needed to fully address issues of nanoscaleroughness and competitive blocking, but is beyond the scope of thismanuscript.

3.8. Flow velocity
The subsurface environment commonly exhibits variations inwater velocity due to heterogeneity in hydraulic properties andtemporal changes in the hydraulic gradient, e.g. because of recharge
and pumping (Domenico and Schwartz, 1998). Fig. 6 presents
observed and simulated BTCs for AgPURE (Fig. 6a) and PVP-coated
Ag-ENPs (Fig. 6b) when the IS was 1 mM Naþ and the pore watervelocity was 4.32 or 8.64 m d1. Greater Ag-ENP retention anddelay in the BTCs occurs at the lower pore water velocity. In
particular, the recovery of AgPURE in the efﬂuent decreased fromaround 80 to around 62% when the pore water velocity was halved.
Similarly, the breakthrough of PVP-coated Ag-ENPs occurred after
around 2.8 and 4.3 PV when the pore water velocity was 8.64 and4.32 m d1, respectively. Other researchers have also previously
observed greater Ag-ENP retention at lower pore water velocities(Sagee et al., 2012; Taghavy et al., 2013). Results in Fig. 6 demonstrate that the inﬂuence of velocity on Ag-ENP retention also depends on the stabilizing agent.
The inﬂuence of pore water velocity on nanoparticle retention

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Y.F. Adrian et al. / Environmental Pollution 236 (2018) 195e207

Fig. 6. Effect of velocity on transport for AgPURE (6a) and PVP-Ag-ENP (6b). All experiments were conducted at an ionic strength of 1 mM with Naþ and for d50 ¼ 0.7 mm.

and delay depends on a number of factors, including: (i) the
resulting residence time of Ag-ENPs in the porous medium (Sharma
et al., 2014); (ii) the mass transfer rate of Ag-ENPs from the bulk
solution to the solid phase (Liang et al., 2013a); and (iii) the velocity
dependence of the sticking efﬁciency and Smax1 (Liang et al., 2013b).
Similar to Fig. 6, greater Ag-ENP transport and less retention are
expected at a higher pore water velocity because of a decrease in
the advection controlled residence time, even though colloid
ﬁltration theory predicts that ksw1 increases with increased porewater velocity when the colloid sticking efﬁciency is constant (Yaoet al., 1971). The values of the colloid sticking efﬁciency and Smax1
are predicted to increase with decreasing pore water velocity
because of a decrease in the hydrodynamic forces that act on the
Ag-ENPs adjacent to the solid surface (Bradford and Torkzaban,2015). Fitted values of Smax1 are consistent with these expectations (Table 1). However, it should be noted that the inﬂuence ofvelocity on the BTCs is more pronounced for the PVP-coated than
AgPURE Ag-ENPs (Fig. 6b). This difference is related to the velocity
dependency of the colloid sticking efﬁciency and Smax1. These parameters are functions of the water velocity and the depth of the

primary minimum which is inﬂuenced by charge heterogeneity andthe distribution of nanoscale roughness height and density on thesurface of Ag-ENPs and aquifer material, as well as unbound stabilizing agent (see section 3.7).
4. Conclusions
The ﬁndings from this study provide important insight into therole of blocking in controlling the long-term transport behavior of
Ag-ENPs in natural, saturated, silicate-dominated aquifer material
under different physicochemical conditions. Observed Ag-ENP
transport and blocking behavior were well described using theadvection dispersion equation and irreversible kinetic retention
sites that included Langmuirian blocking. Increasing retention anddelay in Ag-ENP transport was observed at higher IS, in the presence of divalent cations and ﬁne-grained particles, at lower watervelocities, and for polymer-stabilized compared to surfactantstabilized Ag-ENPs. These observations were explained bychanges in double layer behavior, measured zeta potentials, interaction energies, charge reversal, cation bridging, residence time,Y.F. Adrian et al. / Environmental Pollution 236 (2018) 195e207

and hydrodynamic forces. A special focus of this research wasinvestigating the roles of cation valence and the ﬁne-grained material fraction on Ag-ENP transport, and enhanced retention anddelay of breakthrough in the presence of Ca2þ and ﬁnes was
attributed to cation bridging which was more pronounced forpolymer- than surfactant-stabilized Ag-ENPs because of differencesin stabilizing agent properties and zeta potentials.
Additional research is warranted to transfer results from thislaboratory-scale study to the ﬁeld. If and how Ag-ENP transport inaquifers occurs under ﬁeld conditions depends partly on the parameters tested during our experiments but also on characteristicsof the vadose zone overlying the aquifer, on the absence/presenceof geological heterogeneity, on the absence/presence of substances(e.g. organic matter) that could induce, slow down or speed up AgENP transformation, as well as on the absence/presence of substances that potentially compete with Ag-ENPs for the existing
retention sites (e.g., phosphorus, surfactants, and dissolved organic
matter). Additionally, the chemical composition of groundwatermight differ from the background solution used in our experiments.
However, our results clearly demonstrate the need for long-term
injection experiments of Ag-ENPs to better understand theirblocking behavior in varying background solutions and under more
realistic hydrogeochemical conditions. We also show that with
sufﬁcient Ag-ENP input all retention sites are ﬁlled, and a breakthrough occurs, so in theory, even under ﬁeld conditions excessive
exposure to Ag-ENPs could impact the quality of groundwater used
for potable water production.
Conﬂicts of interest
The authors declare no competing interests.
Acknowledgements
The contributions of Yorck F. Adrian and Uwe Schneidewind
were funded through the Federal Ministry of Education andResearch (BMBF), Germany, Project Nanomobil (03X0151A). The€ rfer and Bruno Ko€hlerauthors would like to thank Moritz Grenzdo
from RWTH Aachen University, Department of Engineering Geology and Hydrogeology for help with some of the laboratory work
and Claudia Walraf form Jülich Research Center for the BET
measurements.
Appendix A. Supplementary data
Supplementary data related to this article can be found athttps://doi.org/10.1016/j.envpol.2018.01.011.
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