Chemosphere 81 (2010) 387–393

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Chemosphere

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Transport of metal oxide nanoparticles in saturated porous media

Tal Ben-Moshe, Ishai Dror *, Brian BerkowitzDepartment of Environmental Sciences and Energy Research, Weizmann Institute of Science, Rehovot 76100, Israel

a r t i c l e i n f o

Article history:Received 8 July 2010Accepted 9 July 2010Available online 3 August 2010

Keywords:NanoparticlesTransportMetal oxidesPorous media

0045-6535/$ - see front matter � 2010 Elsevier Ltd. Adoi:10.1016/j.chemosphere.2010.07.007

* Corresponding author. Tel.: +972 8 934 4230; faxE-mail address: ishai.dror@weizmann.ac.il (I. Dror

a b s t r a c t

The behavior of four types of untreated metal oxide nanoparticles in saturated porous media was studied.The transport of Fe3O4, TiO2, CuO, and ZnO was measured in a series of column experiments. Vertical col-umns were packed with uniform, spherical glass beads. The particles were introduced as a pulse sus-pended in aqueous solutions and breakthrough curves at the outlet were measured using UV–visspectrometry. Different factors affecting the mobility of the nanoparticles such as ionic strength, additionof organic matter (humic acid), flow rate and pH were investigated. The experiments showed that mobil-ity varies strongly among the nanoparticles, with TiO2 demonstrating the highest mobility. The mobilityis also strongly affected by the experimental conditions. Increasing the ionic strength enhances the depo-sition of the nanoparticles. On the other hand, addition of humic acid increases the nanoparticle mobilitysignificantly. Lower flow rates again led to reduced mobility, while changes in pH had little effect. Overall,in natural systems, it is expected that the presence of humic acid in soil and aquifer materials, and theionic strength of the resident water, will be key factors determining nanoparticle mobility.

� 2010 Elsevier Ltd. All rights reserved.

1. Introduction

The nanotechnology market is developing rapidly and newapplications for nanoparticles are emerging constantly. As a resultof increased exposure through consumer use and environmentalreleases, it is becoming necessary to consider the effects of nano-particles on human health and the environment. Recent investiga-tions have shown that the small dimensions and enhancedreactivity of nanoparticles may pose risks to human health(Dreher, 2004; Hoet et al., 2004), and the potentially devastatingeffects of nanoparticles on the environment are just beginning tobe recognized (Colvin, 2003; Maynard, 2006; Vaseashta et al.,2007).

Because of the concern over potential threats of nanoparticle re-leases into the soil–water environment, a number of studies havebeen carried out to investigate the transport, retention and deposi-tion of nanoparticles in saturated porous media. Many of thesestudies are based on measurements of transport in columns packedwith idealized porous media consisting of spherical glass beads orsand. The nanoparticles are usually introduced into the columnand breakthrough curve concentrations are measured at the col-umn outlet. These nanoparticles include C60 (Lecoanet et al.,2004; Lecoanet and Weisner, 2004; Cheng et al., 2005; Espinasseet al., 2007; Wang et al., 2008a,b) and single-walled carbon nano-tubes (Jaisi et al., 2008). Generally, the mobility of the nanoparti-cles was found to be highly variable and strongly dependent on

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the experimental setup. Significantly, due to their enhanced sur-face area and reactivity, nanoparticles tend to aggregate rapidlyin aqueous solutions, creating stable suspensions only at verylow concentrations. The stability of such suspensions can in somecases be increased by, e.g., addition of surfactants or exposure toprolonged sonication.

Few studies have attempted to investigate the transport of me-tal oxide nanoparticles in porous media. Lecoanet et al. (2004) andLecoanet and Weisner (2004) studied the effect of flow on trans-port and deposition of several varieties of fullerenes and oxidenanoparticles. The authors found that nanoparticles are relativelymobile, but that deposits formed by these materials in the columnover the long term may be highly variable, often blocking large re-gions of the porous medium. The mobility of these nanoparticlesmay increase over time as deposition sites become saturated overprogressively larger distances within the porous medium. Severalstudies have demonstrated that different surface properties affectnanoparticle mobility. For example, Amlrbahman and Olson(1993) measured deposition rates of iron oxide particles coatedwith different types of humic substances in stable suspensions thatwere allowed to flow continuously through a closed column con-taining quartz sand, while Kretzschmar and Sticher (1997) injectedpulses of stable suspensions of humic-coated hematite nanoparti-cles into a closed column packed with sandy soil. In both studies,the ionic strength and the type and amount of humic substanceswere found to be key factors controlling the mobility and deposi-tion of the nanoparticles. Moreover, the surface potential wasshown to have a large effect on the transport of titanium dioxidenanoparticles, with enhanced aggregation near the point of zero

388 T. Ben-Moshe et al. / Chemosphere 81 (2010) 387–393

charge (Dunphy Guzman et al., 2006). Earlier works by Puls andPowell, 1992); Puls et al. (1993) investigated the transport of ironoxide colloids in closed glass column packed with natural porousmedia and found that the transport and particle stability are highlydependent upon a number of factors such as flow rate, pH, ionicstrength, surface chemistry, particle size and concentration.

In this study we focus on the transport of several metal oxidenanoparticles, namely magnetite (Fe3O4), copper oxide (CuO), tita-nium dioxide (TiO2), and zinc oxide (ZnO), in saturated columnscontaining glass bead packs. Because of the critical influence ofsurface properties on nanoparticle transport and stability in solu-tion, the nanoparticles were not treated and used as received.The effect of the inlet boundary condition – with nanoparticlesintroduced either as a dry powder or as a pulse suspended in aque-ous solution – was first tested using magnetite. Experiments withmagnetite nanoparticles were designed to investigate different fac-tors affecting the transport of the nanoparticles, such as ionicstrength, addition of organic matter (humic acid), flow rate andpH. Subsequent experiments allowed a comparative analysis ofmobility among the four types of metal oxide nanoparticles, as afunction of ionic strength, presence of humic acid, flow rate andpH.

2. Materials and methods

2.1. Porous medium

Spherical borosilicate glass beads (Aldrich) with an averagediameter of 1 mm were used as the porous medium. The beadswere cleaned with hydrochloric acid, washed repeatedly withdeionized water and dried at 60 �C in air. Before each experiment,the beads were equilibrated with the influent solution for 24 h andthen packed into a vertical 20 cm cylindrical acrylic column. Theinner diameter of the column was 3.5 cm, and the glass beads werepacked to a height of 15 cm. The porosity of the packed columnwas 0.4.

2.2. Characterization of nanoparticles

Nanosized magnetite (Fe3O4), copper oxide (CuO), titaniumdioxide (TiO2, rutile), and zinc oxide (ZnO) nanoparticles were pur-chased from Aldrich. The nanoparticles were analyzed by transmis-sion electron microscopy (TEM) (Philips CM120). The sizes andzeta potentials of the nanoparticles in a solution with 0.01 M NaClat nanoparticle concentration of 10 mg L�1 at pH 7 were measuredby dynamic light scattering (DLS) (Zetasizer Nano, Malvern Instru-ments Ltd.). Sedimentation experiments of nanoparticles were alsoperformed (see Supplementary Material). The possible dissolutionof metal oxide in water was investigated by filtering samples ofsuspended nanoparticles and measuring the concentration of me-tal ion by ICP-AES.

2.3. Transport experiments with magnetite

All experiments were performed with an open column. Flowwas controlled at a constant flow rate by two peristaltic pumps,at the inlet and outlet of the column, maintaining a constant headof 2.5 cm. At least 10 pore volumes of solution were initially passedthrough the porous medium. The nanoparticles were then intro-duced either suspended in 10 mL of the aqueous solution or aspowder to the column. The solution was pumped through the col-umn at a constant flow rate of 5 mL min�1 (Darcy velocity0.52 cm min�1). The pH of the solution in all experiments was 7.Deionized water (18 MX cm) was used in all experiments.

To measure the effect of ionic strength on the transport of thenanoparticles the first experiment was performed with four differ-ent concentrations of NaCl: 0, 0.001, 0.01 and 0.1 M. Magnetitenanoparticles were added to the column in each experiment andthe concentration at the outlet was determined by measuring theabsorption at discrete time intervals in a Cary 100 UV–Vis spectro-photometer against a blank sample.

Humic acid was used to test the effect of natural organic matteron the transport. The humic acid was obtained from Aldrich. Twoconcentrations of NaCl were chosen (0.01 and 0.1 M), and for eachNaCl concentration, five concentrations of humic acid were tested:0, 10, 30, 60 and 100 mg L�1.

The effect of flow rate on the transport was tested by perform-ing experiments at four different flow rates: 0.6, 1, 2.5 and5 mL min�1 (Darcy velocities 0.062, 0.10, 0.26 and 0.52 cm min�1).The experiments were performed with a humic acid concentrationof 60 mg L�1 and two different concentrations of NaCl (0.01 and0.1 M).

To measure the effect of pH, the pH value of the solution wasadjusted to 10 and 12 by addition of NaOH. The experiments wereperformed with a humic acid concentration of 60 mg L�1 and twodifferent concentrations of NaCl (0.01 and 0.1 M). In most experi-ments, 10 mg of nanoparticles were used; however in experimentswith humic acid at ionic strength of 0.1 M, 100 mg of nanoparticleswere added.

Following completion of some of the column experiments, themass of nanoparticles retained in each column was measured byaddition of a known volume of water to the porous medium andsonication for 10 min. The concentration of nanoparticles in thesupernatant was then measured and the mass balance was calcu-lated. The transport experiments were repeated twice.

2.4. Comparison of mobility among metal oxide nanoparticles

The mobility of different metal oxide nanoparticles was studiedby performing the same experiment with four different types ofmetal oxides. In each experiment 2 mg of the tested metal oxidewas added to the column. The solution was pumped through thecolumn at a constant flow rate of 5 mL min�1 and at pH 7. The con-centrations of nanoparticles at the outlet of the column weredetermined by measuring the UV–Vis absorption of the nanoparti-cles. The optimal wavelength for each material was determined inpreliminary experiments. For each metal oxide, two ionic strengthswere tested, 0.01 and 0.1 M NaCl. The effect of organic matter wastested by addition of 60 mg L�1 of humic acid. The experiment wasrepeated with flow rate of 1 mL min�1 and pH 12.

3. Results and discussion

3.1. Properties of metal oxide nanoparticles

The average size of the nanoparticles as stated by the manufac-turer and confirmed by TEM is shown in Table 1. TEM images areshown in Fig. S1. Upon suspension in aqueous solution largeraggregates were formed. The size and zeta potential of these aggre-gates were measured by DLS. The results are presented in Table 1.TiO2 formed the smallest aggregates (190 nm). The size of the CuOnanoparticles was found to be 342 nm and both ZnO and Fe3O4

formed very large aggregates (1106 nm and 1281 nm, respec-tively). The zeta potential is an indication of the stability of the sus-pension. TiO2 and Fe3O4 have negative zeta potential values,indicating that the nanoparticles are negatively charged, whileZnO and CuO have positive values, indicating that they are posi-tively charged. Higher absolute values indicate increased stabilityof the suspensions. Values that are larger than 30 mV are consid-

Table 1Characteristics of nanoparticles used for transport experiments with 0.01 M NaCl atpH 7.

Nanoparticles Size according tomanufacturer(nm)

Sizeaccording toDLS (nm)

Zetapotential(mV)

g0

Fe3O4 <50 1281 �8.51 3.87 � 10�2

TiO2 (rutile) <100 190 �33.53 1.03 � 10�2

ZnO <100 1106 8.19 3.46 � 10�2

CuO <50 342 17.13 9.66 � 10�3

T. Ben-Moshe et al. / Chemosphere 81 (2010) 387–393 389

ered stable (Riddick, 1968); of the four materials tested, TiO2 wasthe only particle with such a value. The zeta potential results arein agreement with the points of zero charge reported for these me-tal oxides (Kosmulski, 2001). The points of zero charge for TiO2 andFe3O4 are lower than 7 (5.9 and 6.5, respectively) so at pH 7 theyare negatively charged. For ZnO and CuO the values are higher than7 (9.5 and 9.4, respectively) so the nanoparticles are positivelycharged. Sedimentation curves of the nanoparticles are presentedin Fig. S2.

Dissolution of metal ion from the nanoparticles was measuredby ICP-EAS. For all four metal oxides very low concentration of me-tal ions were detected (<1%); therefore the effect of metal ions wasneglected.

3.2. Magnetite transport experiments

The nanoparticles were introduced into the column in twoways: (1) as a powder and (2) suspended in 10 mL of solution. Inan initial set of experiments, the nanoparticles were introducedto the column as a powder. The dry nanoparticles were placed onthe inlet surface and the hydraulic head was built up above them.Using water heads of 2.5 cm, the nanoparticles remained virtuallyimmobile, with complete retention at the top 5 mm near the col-umn inlet; there was no flow of nanoparticles in the column. Asa consequence, all of the remaining experiments were carried outwith an inlet flow condition that introduced nanoparticles dis-persed in 10 mL of aqueous solution. The experiments were re-peated twice and were highly reproducible as demonstrated inFig. S3.

The effect of ionic strength on nanoparticle transport was inves-tigated by repeating the experiment with different concentrationsof NaCl. In each measurement an initial mass of 10 mg of magne-tite was added to the column. Breakthrough curves of nanoparti-

0 1 2 3 4 50.00000

0.00005

0.00010

0.00015

0.00020

0.00025

0.00030

0.00035

0.00040

rela

tive

mas

s

pore volume

0 M NaCl 0.001 M NaCl 0.01 M NaCl 0.1 M NaCl

Fig. 1. Breakthrough curves for iron oxide nanoparticles with different concentra-tions of NaCl at pH 7.

cles at the column outlet are presented in Fig. 1. The relativemass (mass of nanoparticles exiting the column/initial mass in-jected to the column) was plotted vs. number of pore volumes.The plot has a peak at approximately one pore volume. Signifi-cantly, the mobility of the magnetite nanoparticles in the porousmedia is very low, which may be attributed to the poor stabilityof the suspensions: without the addition of salt, only 3.8% of thenanoparticles emerged from the column.

The addition of salt enhances the deposition of the nanoparti-cles, with only 1.8%, 1.5% and 1.2% of the nanoparticles exitingthe column for NaCl concentrations of 0.001, 0.01 and 0.1 M,respectively. This behavior can be related to the suppression ofthe electrical double layer by the added ions. Under conditions ofhigher ionic strength, attractive van der Waals forces are dominantover repulsive electrostatic interactions, leading to enhancedaggregation – and thus reduced mobility – of the nanoparticles(Brant et al., 2005; Wang et al., 2008a,b).

To increase the mobility of the nanoparticles, humic acid wasadded to the solution. The same concentration of humic acid wasalso added to the reference sample in the spectrophotometer. Nointerference from the humic acid was observed during the mea-surements. Addition of humic acid leads to stronger electrostaticrepulsion as well as steric hindrance, which increase the stabilityof the suspension and prevent aggregation (Tipping and Higgins,1982; Xie et al., 2008). Two concentrations of salt, 0.01 and0.1 M, were chosen for the experiments and different concentra-tions of humic acid were added in each case. The humic acid con-centrations, 0–100 mg L�1, are typical of dissolved organic matterin natural soils. For the lower concentration of salt the initial massof magnetite nanoparticles added to the column was 10 mg. Forthe higher salt concentration, the mobility of the nanoparticles islower (Fig. 1). Addition of 10 mg of nanoparticles resulted in com-plete retention of the nanoparticles in the column. To enable mea-surement of a breakthrough curve, a larger initial mass of 100 mgnanoparticles was used.

The resulting breakthrough curves are shown in Fig. 2A and Bfor 0.01 and 0.1 M, respectively. For the lower salt concentration,the plots have one peak after one pore volume. The mobility ofthe nanoparticles increases strongly with the increase in humicacid concentration. A total of 1.5%, 29%, 71.5% and 75% of the nano-particles eluted from the column for solutions containing 0, 10, 30and 60 mg L�1 of humic acid, respectively.

For all of the humic acid concentrations, the first peak appearsafter about one pore volume; however additional peaks appearfollowing continuous flow of the solution through the columnfor larger numbers of pore volumes in the case of the three highesthumic acid concentrations. The number of pore volumes of theadditional peaks is different for the different concentrations. A to-tal of 0.2%, 0.65%, 7.4%, 19.4% and 21% of the nanoparticlesemerged from the column for 0, 10, 30, 60 and 100 mg L�1 of hu-mic acid, respectively. When the experiments were repeated, thegeneral shape and total relative mass were similar; however theadditional peaks appeared after different numbers of pore vol-umes. The mechanism for generating the multiple peaks is stillnot fully understood. One possible explanation for this phenome-non is physical straining, in which large aggregates are formedand trapped in pores, and later disintegrate into smaller nanopar-ticles assemblies that can exit the column. As a result nanoparticleadvance within the column is slower than smaller particles, sothat they emerge from the column after longer times. Recently,Mulvihill et al. (2009) reported that the bonding between organicmolecules and nanoparticles is a reversible process even when thebond is covalent. This may indicate that a reversible aggregation/disintegration of colloids is possible because of dynamic changesin the surfactant coating of the particles and may explain the ob-served pattern of pulses.

0.0000

0.0002

0.0004

0.0006

0.0008

0.0010

0 5 10 15 20

0 1 2 3 4 50.000

0.001

0.002

0.003

0.004

0.005

0.006

0.007

B

rela

tive

mas

s

pore volume

0 mg/L humic acid 10 mg/L humic acid 30 mg/L humic acid 60 mg/L humic acid 100 mg/L humic acid

A

rela

tive

mas

s

0 mg/L humic acid 10 mg/L humic acid 30 mg/L humic acid 60 mg/L humic acid

Fig. 2. Breakthrough curves for iron oxide nanoparticles with: (A) 0.01 M and (B)0.1 M NaCl and different concentrations of humic acid at pH 7.

0.000

0.002

0.004

0.006

0.008

0.0000

0.0002

0.0004

0.0006

0.0008C

B

A

rela

tive

mas

s

pH 7 pH 12

pore volume

rela

tive

mas

s pH 7 pH 10 pH 12

0 1 2 3 4 5

0 5 10 15 20

0 1 2 3 4 50.000

0.002

0.004

0.006

0.008

rela

tive

mas

s

5 mL/min 2.5 mL/min 1 mL/min 0.6 mL/min

Fig. 3. Breakthrough curves for iron oxide nanoparticles with 60 mg L�1 humic and(A) 0.01 M NaCl at different flow rates at pH 7, (B) 0.01 M NaCl at different pHvalues and (C) 0.1 M NaCl at different pH values.

390 T. Ben-Moshe et al. / Chemosphere 81 (2010) 387–393

The effect of flow rate on the mobility of the nanoparticles wastested with 60 mg L�1 of humic acid and two concentrations ofNaCl, 0.01 and 0.1 M. In each case, four different flow rates weretested. For the lower concentration of salt, 10 mg of magnetitenanoparticles were added, while for the higher concentration,100 mg were added.

The results for 0.01 M are shown in Fig. 3A. For all flow rates onepeak appears after one pore volume. The retention of nanoparticlesis stronger for slower flow rates. A total of 5.4%, 6.4%, 50% and 75%of the nanoparticles emerged from the column for flow rates of 0.6,1, 2.5, 5 mL min�1, respectively. This suggests that the time scalefor attachment of nanoparticles is larger than the time scale ofthe transport of the nanoparticles to the collector grains. The mea-surements also in accord with, e.g., Jeong and Kim (2009), whovisualized aggregation of copper oxide nanoparticles in porousmedia and found that mobility is enhanced with increasing flowrates and surfactants.

For the 0.1 M NaCl experiments, at flow rates slower than5 mL min�1, negative absorbance was measured (not shown) afterabout 1 pore volume, indicating a decrease in the concentration ofhumic acid in the solution. This is probably due to sorption of thehumic acid on the surface of the nanoparticles. This phenomenoncannot be attributed to sorption of the humic acid on the glassbeads or the column walls as it was not observed for lower NaClconcentrations when a smaller mass of nanoparticles was used(10 mg) or for tracer experiments when no nanoparticles wereadded. There is a partial overlap between the increase in UV–Vis

absorption due to the removal of nanoparticles from the columnand decrease in absorption due to sorption of humic acid on thenanoparticles; therefore it is not possible to quantify the concen-tration of nanoparticles exiting the column.

The effect of pH on the nanoparticle mobility was also tested.The results for 60 mg L�1 humic acid and two concentrations ofNaCl, 0.01 and 0.1 M at different pH values are presented inFig. 3B and C, respectively. For the lower concentration of salt,10 mg of magnetite nanoparticles were added, while for the higherconcentration, 100 mg were added. At higher pH values, the rela-tive mass eluting from the column was lower for both salt concen-trations. In Fig. 3B, 61% and 75% of the nanoparticles exited thecolumn during the experiment at pH values of 12 and 7, respec-tively. In Fig. 3C, 4.8%, 12.3% and 19.4% of the nanoparticlesemerged from the column for pH 12, 10 and 7, respectively. ForpH 10, a multiple peak elution pattern is observed; in contrast, atpH 12, only a single peak elution of particles is found after aboutone pore volume. At high pH values, both the nanoparticles andthe humic acid are negatively charged, resulting in less sorptionof humic acid to the nanoparticles (Amlrbahman and Olson,1993; Kretzschmar and Sticher, 1997; Illes and Tombacz, 2006;Baalousha et al., 2008).

A mass balance was calculated for several of the experimentsconsidering both particles eluted from the column during theexperiment and post experiment examination of the particles re-tained in the column. In all cases the mass of nanoparticles thatemerged from the column together with the mass of nanoparticlesretained in the column accounted for >95% of the initial mass.

T. Ben-Moshe et al. / Chemosphere 81 (2010) 387–393 391

3.3. Comparison of mobility among metal oxide nanoparticles

The mobility of four types of metal oxide nanoparticles in por-ous media is now compared. In Fig. 4A, breakthrough curves forexperiments with 0.01 M NaCl were plotted. TiO2 had the highestmobility, with 62% of the nanoparticles exiting the column; 52%of the CuO nanoparticles and 16% Fe3O4 nanoparticles exited thecolumn. ZnO showed the lowest mobility with only 1.4% of thenanoparticles emerging from the column.

To investigate the effect of ionic strength on the mobility of thefour metal oxide nanoparticles, the experiment was repeated with0.1 M NaCl. Breakthrough curves were plotted in Fig. 4B. As shownin Section 3.2, addition of salt increases the retention of nanopar-ticles in the column, with only 13%, 8.3%, 6.2% and 1.2% of theTiO2, CuO, Fe3O4 and ZnO nanoparticles, respectively, being eluted.An increase in salt concentration (to 0.1 M) has the largest effect onCuO mobility, which is reduced by factor of �6.3 compared to thesame solution with 0.01 M NaCl. TiO2 mobility was reduced by afactor of �4.8, while reduced effects were found for ZnO (factor�2.6) and Fe3O4 (almost no change). The addition of salt affectsstable suspensions more strongly than unstable ones. In stable sus-pensions the electrostatic repulsive forces are stronger and aretherefore more affected by addition of ions. In unstable suspen-sions the repulsive forces are weak so they are less affected.

Based on the results of Section 3.2 and the sedimentation exper-iments in the supplementary material (Fig. S2), the addition of hu-mic acid is expected to increase the mobility of colloids. Fig. 5Ashows breakthrough curves for the nanoparticles with 0.01 M NaCland 60 mg L�1 humic acid. The mobility of the nanoparticles is

0.000

0.002

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0.006

0 1 2 3 4 5

0 1 2 3 4 50.0000

0.0004

0.0008

0.0012

0.0016B

A

rela

tive

mas

s TiO2 ZnO Fe3O4 CuO

rela

tive

mas

s

pore volume

TiO2 ZnO Fe3O4 CuO

Fig. 4. Breakthrough curves for metal oxide nanoparticles at pH 7 with (A) 0.01 Mand (B) 0.1 M NaCl.

higher, with 98%, 98%, 74% and 62% of the nanoparticles exitingthe column for TiO2, CuO, ZnO and Fe3O4, respectively. Here thestrongest effect is on the ZnO (factor of �53 times) and then onFe3O4 (factor of �3.9), while the other two show milder increases(�1.6 and �1.9 factor); even the smaller increases are sufficientto yield maximum (98%) elution. Here it seems that the humic acidstabilizes the dispersion of the nanoparticles, which in turn leadsto increased particle elution. It should also be noted that the humicacid better stabilizes ZnO compared to Fe3O4, possibly because ofthe different surface charges of the nanoparticles: the negativelycharged humic acid (pKa 4.2, taken from Thurman, 1986) is betteradsorbed to the positively charged ZnO nanoparticles (point of zerocharge 9.5, as reported in Section 3.1, which is higher than theexperimental pH) than to the negatively charged Fe3O4 (point ofzero charge 6.5, lower than the experimental pH).

Fig. 5B shows the breakthrough curves for metal oxide nanopar-ticles with 0.01 M NaCl and 60 mg L�1 at a slower flow rate of1 mL min�1. A total of 98%, 98%, 68% and 30% of the nanoparticlesemerged from the column for TiO2, CuO, ZnO and Fe3O4, respec-tively. The relative mass of Fe3O4 decreased by half, compared tothe flow rate of 5 mL min, suggesting that the time scale for nano-particle attachment is larger than that for transport. The other oxi-des were not affected, suggesting the time scale for attachment issmaller than that for transport.

The breakthrough curves for metal oxide nanoparticles with0.01 M NaCl and 60 mg L�1 at pH 12 are plotted in Fig. 5C; 98%,98%, 71% and 67% of the nanoparticles exited the column forTiO2, CuO, ZnO and Fe3O4, respectively. There are small differencesin particle elution from the column for the less stable solution, i.e.,

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TiO2 ZnO Fe3O4 CuO

rela

tive

mas

s ZnO

CuO

C

B

A

rela

tive

mas

s

pore volume

ZnO

CuO

TiO2

Fe3O4

Fe3O4

TiO2

Fig. 5. Breakthrough curves for metal oxide nanoparticles with: (A) 0.01 M NaCland 60 mg L�1 humic acid at pH 7, (B) at 1 mL min�1 flow rate at pH 7 and (C) at pH12.

40200

-300

-200

-100

0

100

tota

l pot

entia

l ene

rgy

(kT)

separation distance (nm)

TiO2 ZnO Fe3O4 CuO

Fig. 6. Total potential energies among colloids with 0.01 M NaCl.

392 T. Ben-Moshe et al. / Chemosphere 81 (2010) 387–393

a 4% decrease for ZnO and a 8% increase for Fe3O4. At high pH val-ues nanoparticle suspensions are expected to be less stable be-cause of reduced sorption of negatively charged humic acid tothe negatively charged nanoparticles. This is indeed the case forZnO; however Fe3O4 demonstrates an increased amount of nano-particles eluting from the column. This latter result is in contrastto the finding in Section 3.2, where nanoparticles elution was re-duced at high pH values.

In preliminary batch experiments the TiO2 suspension was themost stable, and had the highest zeta potential. The CuO nanopar-ticles displayed similar behavior to TiO2; however the nanoparti-cles exited the column after shorter times. ZnO had the lowestmobility without addition of humic acid; addition of humic acidled to a significant increase in mobility, due to better adsorptionof humic acid to the ZnO surface compared to Fe3O4. Fe3O4 showedsimilar behavior to that described in Section 3.2: addition of humicacid led to increased mobility. It was also the only type of nanopar-ticle affected by the flow rate: at lower flow rate fewer nanoparti-cles emerged from the column. It is noted that while TiO2

demonstrated the highest mobility and recovery percentage in allexperiments, Fig. 5 shows that the TiO2 nanoparticles emergedafter the longest times (considering both the peaks and the latetime tails). It is suggested that this is due to, reversible interactionsbetween the TiO2 nanoparticle aggregates and the porous medium.TiO2 is not expected to have specific interactions with the glassbeads. However, the TiO2 nanoparticles are smaller than the othermetal oxides; they may therefore be able to enter pores that areinaccessible to the other oxides, thus delaying their progress inthe column. An alternative explanation is possible capture ofaggregates, and migration only of non-aggregated CuO, ZnO andFe3O4 nanoparticles.

3.4. Calculation of colloid filtration efficiencies

The transport and deposition of colloids in porous media are of-ten described by the colloid filtration model which states that col-loid deposition consists of two separate steps: (1) transport ofsuspended particles to the vicinity of the collector, and (2) attach-ment of the particles to the surface of the collector. The particlesmay come into contact with the collector by three mechanisms,depending on particle size: diffusion, interception and gravity(Yao et al., 1971).

In this work only collector efficiencies were calculated. The sin-gle collector efficiency g0 is the ratio of the rate at which particlesstrike the collector divided by the rate at which particles flow to-wards the collector; it has been calculated according to Tufenkjiand Elimelech (2004). While transport is affected by several addi-tional factors such as attachment efficiencies and sedimentation,the calculation of collector efficiencies can still be used to help as-sess the mobility of the different oxide nanoparticles inside the col-umn. The results of the calculations are presented in Table 1. TiO2

and CuO have small collector efficiencies relatively to ZnO andFe3O4. These results are in agreement with the transport experi-ments, where for TiO2 and CuO retention was lower than for ZnOand Fe3O4.

3.5. Calculation of DLVO potential energies

The potential energies of the metal oxide nanoparticles werecalculated according to the classical Derjaguin–Landau–Verwey–Overbeek (DLVO) theory which states that the particles are subjectto electrostatic repulsion forces and van der Waals attractiveforces. The particles are assumed to be spherical (as seen in TEMimages in Fig. S1). The electric double layer potential was calcu-lated according to Gregory (1975)

Eedl ¼64pee0k2T2a2

e2z2 � tanh2 zeW4kT

� �� expð�jdÞ

2aþ dð1Þ

where e is the dielectric constant of water, e0 is the permittivity ofvacuum, k is Bolzmann constant, T is absolute temperature, a is theparticle radius, e is electron charge, z is the charge number, W is thesurface potential of the particles, j is the reciprocal length and d isthe separation distance between particles. At low ionic strengthsthe surface potential is assumed to be equal to the zeta potential.The reciprocal length is calculated as

j ¼ 2000e2NAIee0kT

� �ð2Þ

where NA is Avogadro’s number and I is the ionic strength. The vander Waals potential was calculated according to Gregory (1981)

Evdw ¼ �A6

2a2

dð4aþ dÞ þ2a2

ð2aþ dÞ2þ ln

dð4aþ dÞð2aþ dÞ2

" #ð3Þ

where A is the particle–water–particle Hamaker constant.The resulting total interaction energies as a function of distance

are plotted in Fig. 6. The calculations were done for the set ofexperimental conditions with 0.01 M NaCl. For TiO2 there is anelectrostatic barrier indicating the suspension is stable. There is asmall electrostatic barrier CuO and no barrier for Fe3O4 and ZnO,suggesting rapid aggregation may take place due to attractivevan der Vaals forces. These results are in agreement with the re-sults obtained from the transport experiments. TiO2 demonstratedthe highest stability in solution and highest mobility in the column,with CuO showing lower stability. Fe3O4 demonstrated higher sta-bility than expected from the simple DLVO theory.

4. Conclusions

The mobility of untreated metal oxide nanoparticles in porousmedia under different conditions was investigated, to assess thepotential risks that such nanoparticles might pose to both the envi-ronment and human health. The transport properties of the differ-ent nanoparticles vary significantly; under the conditionsinvestigated here, the TiO2 nanoparticles are the most mobile, withCuO somewhat less mobile, and with ZnO and Fe3O4 being the leastmobile. The method of preparation of nanoparticles as well as pre-liminary treatment may change the mobility of the nanoparticlesstrongly. The mobility was also found to be strongly dependenton the experimental conditions. For most cases the mobility ofthe nanoparticles is relatively low; the mobility is increased inthe presence of humic acid.

T. Ben-Moshe et al. / Chemosphere 81 (2010) 387–393 393

Acknowledgments

The financial support of the Environment and Health Fund isgratefully acknowledged. BB holds the Sam Zuckerberg Chair inHydrology. We thank Tatyana Belenkova for her assistance withsize and zeta potential measurements.

Appendix A. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.chemosphere.2010.07.007.

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