Retention and Release of Graphene Oxide in Structured

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Retention and Release of Graphene Oxide in Structured Heterogeneous Porous Media under Saturated and Unsaturated Conditions Shunan Dong, Xiaoqing Shi, Bin Gao, Jianfeng Wu, Yuanyuan Sun, Hongyan Guo, Hongxia Xu, and Jichun Wu Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b01948 • Publication Date (Web): 02 Sep 2016 Downloaded from http://pubs.acs.org on September 2, 2016

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Environmental Science & Technology

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Retention and Release of Graphene Oxide in Structured Heterogeneous Porous Media

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under Saturated and Unsaturated Conditions

3

Shunan Dong1, Xiaoqing Shi1, Bin Gao3, Jianfeng Wu1, Yuanyuan Sun1*, Hongyan Guo2, Hongxia Xu1,

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Jichun Wu1*

5 6

1

Key Laboratory of Surficial Geochemisty, Ministry of Education, School of Earth Sciences

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and Engineering, Hydrosciences Department, Nanjing University, Nanjing 210023, China

8

2

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Nanjing University, Nanjing 210093, China,

State Key Laboratory of Pollution Control and Resource Reuse, School of Environment,

10

3

Department of Agricultural and Biological Engineering, University of Florida, Gainesville,

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FL 32611

12 13 14 15 16 17 18 19 20 21 22

__________________________

23

*

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E-mail address: [email protected] (Y. Sun), [email protected] (J. Wu).

Corresponding authors. Tel.: +86 25 89680835; fax: +86 25 8368 6016.

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ABSTRACT ART Schematic

Transport

Fast Flow Domain

Slow Flow Domain

Saturated

Exchange

Slow Flow Domain

Fast Flow Domain

Unsaturated

Exchange

Release

Coarse Sand (700-850 µm) Fine Sand (450-500 µm)

27 28

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In this work, saturated and unsaturated structured heterogeneous sand columns were used to

30

examine the fate of graphene oxide (GO) nanoparticles in heterogeneous porous media under

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various conditions. A two-domain model considering mass exchange between zones was

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applied to describe GO retention and transport in structured, heterogeneous porous media,

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which matched the transport experimental breakthroughs well. Experimental and model

34

results showed that GO retention and transport in all the heterogeneous columns were

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dominated by the preferential flow phenomena. Under saturated conditions, the coarse sand

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with higher hydraulic conductivity was the fast-flow domain (FFD) and the fine sand was the

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slow-flow domain (SFD), and both FFD and SFD affect GO particles fate in structured

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heterogeneous media. When the heterogeneous columns were drained, the fine sand with

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higher moisture content became the FFD and the coarse sand was the SFD, however,

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preferential flows in the FFD dominated GO retention and transport processes. For all the

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columns, the mobility of GO decreased with the increasing ionic strength (IS), and the

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previous retained particles were released by reducing solution IS, indicating part of the

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retained particles were trapped in the secondary minimum energy well.

ABSTRACT:

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INTRODUCTION

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As a new carbon nanomaterial with exceptional physical and chemical properties,

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graphene oxide (GO) has received increasing attention in many fields of applications,1,2 such

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as nanoelectronics, conductive thin films, supercapacitors, nanosensors, and nanomedicine.3-9

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Given the wide applications and rapid growth in production, it is expected that GO will

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inevitably be released into the environment, even in groundwater systems with its relatively

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high mobility in soils.10 Previous studies have already shown that GO nanoparticles are toxic

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to organism and can reduce the activity of cells.11, 12 Understanding the transport behaviors of

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GO in porous media is thus critical to evaluate the environmental impact and the potential

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risk of this new nanomaterial.

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A number of laboratory studies have been reported that the mobility of GO in porous

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media is controlled by several subsurface environmental factors, including solution chemistry

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(e.g., ionic strength and pH), flow rate, moisture content, particle concentration and surface

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property, and media characters.13-22 These studies demonstrate that GO has the higher

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mobility with lower ionic strength, higher flow rate, and the presence of natural organic

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matter or anionic surfactant, meanwhile the transport of GO also may be limited by multiple

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mechanisms, such as the decreasing media grain size, moisture content and input particle

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concentration, and the presence of biofilms. In addition, it has been reported that GO can

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serve as an effective carrier to facilitate the transport of polycyclic aromatic hydrocarbons in

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saturated soils.23 Findings from previous studies also suggested that established theories and

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models of colloid/nanoparticle transport in porous media can be applied to describe the

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transport behaviors of GO particles.10, 13-16, 18-21 However, all of the previous studies of GO

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fate and transport were conducted in homogenous porous media, which may not represent the

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complex natural soil and groundwater systems well.24 3 ACS Paragon Plus Environment


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In fact, preferential flow is widely accepted from field and lysimeter observations as the

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rule rather than the exception in various types of soils because of the natural heterogeneities.

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25, 26

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preferential flow phenomena and demonstrated that region with larger hydraulic conductivity

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provides a fast path for solute transport (fast-flow domain) that dominates the mass transfer in

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the heterogeneous porous media.24 Similarly, packed column experiments have shown that

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the present of preferred flow paths within structured media may dominate colloid

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transmission even though they occupy a small fraction of the porous media.27-29 Recently

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studies also found that heterogeneities strongly affect the fate and transport of

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microorganisms and engineered nanoparticles in porous media under different solution

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chemistry conditions.30-32 These observational studies have been complemented by the

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development of mathematical models using dual-permeability concepts or stochastic

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approaches to describe preferential flow and the fate and transport of solute and particles in

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heterogeneous porous media.30, 33-35 To the best of the authors’ knowledge, however, none of

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the previous studies have systematically investigated the effect of structured heterogeneities

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on the fate and transport of GO nanoparticles in porous media, which extremely limits the

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prediction and monitoring on the fate of GO in the environment. Therefore, additional

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investigations are still needed to promote the knowledge of retention and transport process

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for GO in structured heterogeneous porous media.

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Laboratory experiments with packed sand columns have also been used to examine the

The overarching objective of this work is to understand the effect of physical

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heterogeneities on the transport and release of GO nanoparticles in saturated and unsaturated

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porous media. Structured heterogeneous porous media was created by packing sand of two

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different grain sizes in laboratory columns and GO transport behaviors were examined under

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conditions of different moisture content and IS combinations. The specific objectives were as 4 ACS Paragon Plus Environment

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follows: (1) determine the coupled effects of physical heterogeneity and solution chemistry

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(IS) on the retention and transport of GO in saturated and unsaturated porous media; (2)

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examine the release (reentrainment) of previously retained GO as a result of IS perturbations

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in the structured heterogeneous porous media; and (3) model GO retention and transport in

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structured heterogeneous pore media under conditions of different moisture content and IS

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combinations.

100 101 102

MATERIALS AND METHODS GO Suspension. Single-layer GO was purchased from ACS Material (Medford, MA).

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As reported by the manufacturer, the lateral diameter of the GO is 1-5 µm and the layer

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thickness is 0.8-1.2 nm. The actual physical dimensions of the GO have been determined

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with atomic force microscopy (AFM) in a previous study with the average thickness of 0.92 ±

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0.13 nm and average square root of the area of 582 ± 112 nm.36

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To prepare the stock solution, 250 mg of GO were added into 1000 mL deionized (DI)

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water and the mixture was then sonicated for 2 h for thorough dispersion. Prior to each

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experiment, the stock solution was diluted to 25 mg L-1 with DI water and electrolyte solution.

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Relatively high levels of GO were used in this work to better elucidate the interactions

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between GO and porous media under various conditions. This practice is commonly used in

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the literature and has successful advanced the knowledge of the environmental fate and

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transport of GO.16, 17, 22 NaCl was used as the background electrolyte at two different

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concentrations (1 and 20 mM). The pH for all the experimental solutions was adjusted to 5.6

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with 1.0 mM HCl or NaOH. Only a small amount of HCl or NaOH solution was used in pH

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adjustment, which had negligible effect on the solution IS. The GO suspensions prepared

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under the experimental conditions were very stable.21, 36 5 ACS Paragon Plus Environment


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Concentration of the GO in the solution was determined by measuring the total

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absorbance of light at a wavelength of 230 nm with a UV-2000 Spectrophotometer (UNICO

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Instrument Co., Ltd. China) followed the method of Liu et al.18 The zeta potential values and

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average hydrodynamic diameters of GO particles under varying solution chemistry conditions

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were determined using a ZetaPALS (Brookhaven Instruments Corporation, NY, USA), and

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the average hydrodynamic diameters of the particles were 474.2 ± 20 and 577.4 ± 24 nm for

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1 mM and 20 mM IS conditions, respectively.

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Sand. Quartz sand purchased from Unimin Corporation (Unimin-Le Sueur, MN, USA)

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was used to make the experimental porous media. The sand was sieved into the different size

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ranges: 700-850, 450-500, 350-450, 250-350, 150-200, and 110-150 µm. They were all

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washed sequentially by tap water, 10% nitric acid (v: v) and deionized water, following the

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procedures of Tian et al.37 The zeta potentials of the sand under different solution chemistry

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conditions were measured following the method developed by Johnson et al.38 Briefly,

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colloidal quartz sand suspensions were obtained by ultrasonication of sand in different

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solution chemistry conditions for 10 min, and their zeta potential values were then measured

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by the ZetaPALS. The surface morphological features of the sand were characterized with a

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Scanning Electron Microscope equipped with Energy Dispersive X-ray (SEM-EDX, JEOL

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JSM-6490, Japan).

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Column Experiments. Vertical acrylic columns (20 cm long and 2.5 cm inside diameter

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for saturated experiments, 16.7 cm long and 2.6 cm inside diameter for unsaturated

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experiments) were used in the transport experiments. Stainless steel membranes with 50 µm

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pores were used at both inlet (bottom) and outlet (top) to seal the columns and to distribute 6 ACS Paragon Plus Environment

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the flow. For the unsaturated column, six vent holes were drilled on opposite sides at 3, 7.5,

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and 12 cm from the top of the column. The vent holes were sealed with gas-permeable porous

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PTFE membranes (Milliseal Disk, Millipore) to allow air to enter under unsaturated

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conditions. Solutions were pumped through the column at a constant rate of 2.0 mL min-1

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using the peristaltic pump (BT100-1F, Longer Pump, Hebei, China). Relatively high flow rate

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used in this work to better elucidate the transport process of GO in structured heterogeneous

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porous media under various conditions, which is a common practice in literature to study the

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fate and transport of nanoparticles and other contaminants.17, 39-41 All the transport

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experiments were performed in duplicate.

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Columns with a single structured, heterogeneity were constructed by placing a

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thin-walled acrylic plate (thickness < 1 mm) in the center of the column to separate it into

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two identical regions. To make a saturated, heterogeneous porous media column, sand of two

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different size classes was carefully wet-packed into the two regions of the column using the

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procedure similar to Wu et al.24 After the column was packed, the acrylic plate was then

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slowly withdrawn. Six types of saturated, structured heterogeneous columns (labeled as

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S1-S6) packed with different types of sands were used in the experiments. Table 1 lists

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arrangement of the columns and the basic properties of the sand.

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To make an unsaturated column, two peristaltic pumps (BT100-1F, Longer Pump, Hebei,

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China) connected at the column inlet and outlet were used first to drain the column and then

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to maintain steady-state flow using the procedure similar to Liu et al.18 Initially, a saturated

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column was drained by elevating the outflow rate 5% higher than the inflow rate. When the

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target moisture content was reached, the inflow and outflow rates were equalized to 2.0 mL

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min-1. The average moisture content of the entire unsaturated structured columns was about

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0.20. Three types of unsaturated, heterogeneous columns (U1-U3) packed with different

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types of sand combinations were used in the experiments (Table 1).

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Each of the packed sand column was first flushed with ~4 pore volumes (PVs) of DI

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water and then ~4 PVs of particle-free electrolyte solution (1 or 20 mM NaCl). A

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breakthrough experiment was then initiated by injecting a ~2 PV pulse of the GO suspension,

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followed by several PVs of particle-free background solution to flush out unretained GO in

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porewater. For selected columns (i.e., IS of 20 mM ones), after flushing with the background

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solution, DI water was applied to them to mobilize the previously deposited particles.

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Effluent samples were collected using a fraction collector (BS-100A, Puyang Scientific

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Instrument Research Institute, China). The concentrations of GO were measured immediately

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after sample collection with the methods mentioned previously.

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A tracer solution with 9.75 mM NaCl and 0.25 mM KNO3 (NO3− as the tracer) was

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injected to the pre-equilibrated columns and the concentrations of nitrate in the effluent was

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determined at a wavelength of 220 nm using a UV-2000 Spectrophotometer (UNICO

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Instrument Co., Ltd. China).15 Additional tracer experiments for saturated and unsaturated

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homogeneous sand columns (packed uniformly with each type of the sand) were also

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conducted to determine the longitudinal dispersivity of GO for all the tested grain size and

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moisture conditions (values are listed in Table 1).

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XDLVO Theory. The extended DLVO (XDLVO) theory was used to quantify the

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interaction energy between GO and sand grains, GO and GO, and GO and air-water interface.

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The theory considers the effects of van der Waals attraction, electrical double layer repulsion

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and Lewis acid-base interactions.15, 18, 36 Details of the XDLVO theory can be found in the

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Supporting Information S1. 8 ACS Paragon Plus Environment

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GO Retention and Transport Model. The two-domain conceptualization42 was applied

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in this work to simulate GO retention and transport in the columns, which are usually

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described with two advection-dispersion equations:24, 30

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∂ C FFD ∂ 2 C FFD ∂ C FFD ∂ C ' FFD + = D FFD − v FFD − αβ 2 ∂t ∂t ∂z ∂z

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∂ C SFD ∂ 2 C SFD ∂ C SFD ∂ C ' SFD + = D SFD − v SFD + αβ 2 ∂t ∂t ∂z ∂z

FFD

SFD

( C FFD − C SFD ) (1)

( C FFD − C SFD )

(2)

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where the subscripts FFD and SFD refer to the fast flow and slow flow domains in the

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column, respectively; C is the GO concentration in pore water (M L-3); D is the dispersion

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coefficient (L2 T-1); v is the velocity of pore water (L T-1); α is a first-order mass transfer

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coefficient for GO exchange between the fast-flow and slow-flow domains (L T-1); β is a

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geometry coefficient (L-1), which is described below; and C’ is the concentration of GO

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retained in the porous media (M L-3). For unsaturated porous media, C’ accounts for GO

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retention that takes place due to the presence of both air-water and solid-water interfaces.

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The retention of GO in porous media can be described with various types of kinetics

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expressions.15, 21, 43 To avoid over-parameterization, a second-order, irreversible kinetics

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expression was used to describe the concentration of GO retained in two domains:

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∂ C ' FFD C ' FFD = k FFD C FFD (1 − ) ∂t X FFD

(3)

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∂ C ' SFD C ' SFD = k SFD C SFD (1 − ) ∂t X SFD

(4)

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where k is a retention rate constant (T-1); X is the maximum retention capacity of the porous

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media (M L-3). When the retention capacity greatly exceeds the retained GO concentration



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(i.e., X >> C’), equations (3) and (4) reduce to first-order kinetic expressions, in which the

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retention rate varies linearly with the pore water GO concentration (C).

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The first-order mass transfer coefficient, α, is an empirical parameter that quantifies the

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rate of colloid exchange between the adjacent domains. Gerke and van Genuchten44

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suggested that the magnitude of this parameter depends on the size and shape of the soil

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matrix and on the permeabilities at the interfaces of the two domains. The geometry

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coefficient, β, reflects the ratio of total contact surface area between the two domains to the

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total amount of water within a specific domain (FFD or SFD), can be written as:

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β FFD =

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β SFD =

S V FFD θ FFD

S V SFD θ SFD

(5)

(6)

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where S is the contact area between coarse and fine grains packed in the column (L2); V is the

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volume of each domain (L3); and θ is the moisture content.

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The governing equations of this two-domain model (i.e., (1)-(6)) were solved

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numerically with zero initial concentrations, a pulse-input boundary condition at the column

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inlet, and a zero-concentration-gradient boundary condition at the outlet. The simulated GO

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concentrations in effluents were calculated with:30

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C =

C SFD v SFD V SFD θ SFD + C FFD v FFD V FFD θ FFD v SFD V SFD θ SFD + v FFD V FFD θ FFD

(7)

The Gauss-Levenberg-Marquardt algorithm implemented in a gradient-based, model

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independent, auto-optimization program PEST45 was used to optimize the value of the model

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parameters that minimized the sum-of-the-squared differences between model-calculated and

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measured breakthrough concentrations. This model optimization method was first applied to

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the tracer breakthrough-curve data to obtain the best-fit values of the first-order mass transfer 10 ACS Paragon Plus Environment

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coefficient (α) for the heterogeneous columns prior to initiating the model simulation of GO

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for optimized retention parameters. The first-order mass transfer rate (α) of GO particles were

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assumed to be the same as those of the tracer, and GO concentrations in the effluents were

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then simulated to determine the best-fit values of k and X. The pore water velocity (v),

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dispersion coefficient (D) and moisture content (θ) of FFD and SFD were determined through

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experimental measurements and model calculations, which were detailed in Supporting

237

Information S2.

238 239 240

RESULTS AND DISCUSSION XDLVO Results. The zeta potential values of GO and the six types of sand were

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consistently negative under all the tested experimental conditions (Table S1, Supporting

242

Information), which were consistent with the results of previous studies that both GO and

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quartz sand are negatively charged under normal conditions.18 The zeta potentials of GO and

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sand at low IS (1 mM) were all lower than those at high IS (20 mM), which can be attributed

245

to the increase of IS compressed the electrical double layer.

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The XDLVO interaction energy profiles between GO and GO showed energy barriers

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around 1.0 × 106 kT µm-2 at both IS conditions and a secondary minimum of -152 kT µm-2 at

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high IS (Figure S2, Supporting Information). These results confirmed that the GO

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suspensions were stable under the experimental conditions, particularly when the IS was low.

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The presence of secondary minimum at the high IS might cause tentative aggregation of GO

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particles in the long run. Nevertheless, previous studies have demonstrated that GO

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suspensions are stable enough for the period of column transport studies under similar or

253

even higher IS conditions.15, 18, 21



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The XDLVO energy profiles between GO and sand also showed strong primary energy

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barriers (> 2.7 × 106 kT µm-2) under the two IS conditions (Figure S1, Supporting

256

Information), suggesting the experimental conditions were unfavorable for GO deposition

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onto the sand grains in porous media. At the high IS (i.e., 20 mM), all the XDLVO curves

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showed secondary minimum wells with depths ranged between -161 and -168 kT µm-2 (Table

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S1, Supporting Information). In this work, GO particles thus may be retained in porous media

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through deposition into the secondary minima under the high IS conditions. The retention,

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however, is reversible if the secondary minimum well diminish during IS reduction.46

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The XDLVO energy profiles between GO and air-water interface showed much lower

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primary energy barriers (< 4.8 × 104 kT µm-2) and no sign of secondary energy minimum

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under both IS conditions. Previous study with bubble column experiments has demonstrated

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that GO particles do not attach to the air-water interfaces,18 which is consistent with the

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XDLVO results in this work.

267 268

GO Retention and Transport in Saturated Heterogeneous Porous Media. All the

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breakthrough curves (BTCs) were plotted as normalized effluent concentration (C/C0) as a

270

function of cumulative volume of flow through the column. Under saturated conditions, the

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BTCs of GO under 1 mM had similar shapes with those of tracers in the six columns, which

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demonstrated the two-peak (S2, S3, and S6) or two-stage (S1, S4, and S5) transport behaviors

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depending on grain size arrangements (Figure 1), reflecting the typical preferential flow

274

phenomena.24 In general, the two-peak phenomena appeared when the two types of sand in

275

the packed columns had relatively large size differences, corresponding to large differences in

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hydraulic conductivities (Table 1). In the S2, S3 and S6 columns (Figure 1b,c, and f,

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KFFD/KSFD > 5.5), the two separated BTCs of GO under 1 mM corresponded to the quick 12 ACS Paragon Plus Environment

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(preferential) breakthrough from the fast flow domain (FFD, i.e., coarse-grained matrix) and

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the slow breakthrough from the slow flow domain (SFD, i.e., fine-grained matrix),

280

respectively. In S1, S4 and S5 (Figure 1a, d, and e, KFFD/KSFD = 1.7~3.3) columns, the BTCs

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showed a different transport behavior: (1) a period of rapidly increasing concentrations,

282

reflecting the delivery of GO through the FFD flow path, (2) a brief period of slowly

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increasing concentrations, suggesting the fully breakthrough of the GO in the FFD and the

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transmission of GO from SFD to FFD, and (3) a second period of rapid concentration

285

increasing, reflecting the delivery of GO through the SFD flow path in addition to the fully

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breakthrough in the FFD. The descending limbs of the BTCs also exhibited this stair-step

287

pattern, presumably due to the flushing of the coarse-grained FFD flow path with

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particle-free electrolyte solution, followed by displacement of the particle-free electrolyte

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solution from the fine-grained SFD. These results demonstrate that heterogeneity in hydraulic

290

conductivity is one of the dominant physical factors governing the preferential flow and

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transport behavior of both tracer and GO in structured heterogeneous porous media. The

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BTCs of GO in the columns at 1 mM conditions were only slightly lower than those of the

293

tracers (Figure 1), indicating low retention of the particles in the saturated heterogeneous

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porous media. Because the experimental conditions were unfavorable for GO deposition onto

295

the sand grains, more than 90% of the GO were recovered in the effluents after the flushing

296

with background solution for all the columns (Table S3, Supporting Information).

297

When the solution IS was high (20 mM), there were more retention of GO in the

298

saturated heterogeneous columns and the BTCs were much lower than those of the tracer and

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GO at low IS (Figure 1). Mass balance calculations indicated that the recovery of GO in the

300

effluent of all the saturated heterogeneous columns dropped dramatically to 31.0%-57.2%

301

(Table S3, Supporting Information). The reduced mobility of the GO in columns was due to 13 ACS Paragon Plus Environment


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the deposition of particles onto the sand surfaces in secondary minimum wells, as indicated

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by the XDLVO calculations (Figure S1, Supporting Information). SEM-EDX analysis of the

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sand excavated from the column inlet at the end of the transport experiments confirmed the

305

attachment of the particles onto the grain surfaces (Figure S4, Supporting Information). The

306

importance of secondary minimum deposition to GO fate and transport in sand porous media

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has been demonstrated in several previous studies.15, 18, 21 It is worth noting that increase of IS

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almost eliminated GO transport out from the slow-flow dominants in all the six structured

309

heterogeneous columns (Figure 1), which might be attributed to several reasons: 1) the

310

retention of GO significantly increased with the decreasing of grain sizes at 20 mM;21 2)

311

compared to the FFD, only small amount of GO entered the SFD, increasing the retention of

312

GO in SFD;21, 47 and 3) in comparison with the FFD, the resident times of GO in the SFD

313

were long due to the low velocity, increasing the transmission of GO from SFD to FFD.

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The two-domain model reproduced these breakthrough characteristics of all the

315

saturated experiments closely (Figure 1), with computation of R2 exceeding 0.94 (Table 2).

316

The model parameters of the retention and transport of the tracer and GO are listed in Table

317

2. The flow velocity (v) varied from 0.177 to 1.95 cm min-1 and the dispersion coefficients

318

(D) varied by a factor ranging from 0.0044 to 0.253 cm2 min-1. For all of the saturated

319

treatments, v values in the FFD were all greater than those in the SFD, confirming the

320

preferential flow phenomena. Similarly, all the D values in FFD also greater than those in the

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SFD, which is consistent with previous observations that dispersion varies proportionately

322

with flow velocity.48 Calculations of the Peclet number ( Pe =

323

the column) ranged from 1.54 × 102 to 8.06 × 102 (Table S2, Supporting Information),

324

indicating that advection processes dominated the transport processes in both FFD and SFD

325

in the columns. The best-fit values of the mass-transfer coefficient (α) were sensitive to the

vH , where H is the height of D


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experimental conditions and decreased with the grain sizes in the SFD (Table 2). Calculations

327

of the Damkohler number for mass transfer ( Da MT =

328

(Table S2, Supporting Information). These computations revealed that inter-domain exchange

329

contributed to the mass transfer process in the saturated heterogeneous columns, as the time

330

scale for this mass exchange was comparable to that for advective transport in the columns.

331

βα H v

) ranged from 0.05 to 0.84

The simulated BTCs of GO were computed with the values of α obtained from the tracer

332

studies without adjustment. At 1 mM conditions, the deposition of GO onto the sand grains

333

was little and the deposition kinetics thus were described with the first-order expression. For

334

the same grain sizes, the best-fit k values of FFD were almost the same and ranged from

335

0.00214 to 0.00227 min-1 and 0.00416 to 0.00421 min-1 for S1-S3 and S4-S6, respectively

336

(Table 2). The best-fit k values of SFD (ranged from 0.00331 to 0.00514 min-1 for S1-S3 and

337

from 0.00486 to 0.00559 min-1 for S4-S6, Table 2) were increased with the decreasing grain

338

sizes, suggesting that, under the same chemistry conditions, grain size mainly affected GO

339

retention and k values.21 Consequently, for all the saturated columns, kFFD was always less

340

than the kSFD for all of the saturated treatments. The Damkohler numbers for GO deposition

341

( Da CD =

342

the time scales for particles deposition were relatively large and, for some cases, might not

343

have a pronounced effect on transporting through the saturated columns. This result is

344

consistent with the mass recovery calculations and the predictions of the XDLVO theory.

345

kH ) ranged from 0.0219 to 0.625 (Table S2, Supporting Information), indicating v

When the solution IS was 20 mM, the best-fit kSFD values were much larger than those at

346

IS of 1 mM (Table 2). Similar to that under 1 mM conditions, the best-fit k of FFD also very

347

similar and ranged from 0.0613 to 0.0655 min-1 for S1-S3 and from 0.130 to 0.134 min-1 for

348

S4-S6 under 20 mM (Table 2). In SFD, k increased and ranged from 0.179 to 0.225 min-1 and 15 ACS Paragon Plus Environment


349

0.187 to 0.313 min-1 for S1-S3 and S4-S6 with the decreasing grain sizes, respectively (Table

350

2). All the k values under 20 mM IS were higher than the corresponding ones under 1 mM,

351

which were consistent with the previous results.15, 18 The Damkohler numbers for GO

352

deposition at 20 mM ranged from 0.63 to 35.0 with most of were higher than 1 (Table S2,

353

Supporting Information). This calculation indicated the deposition process played an

354

important role in controlling the fate and transport of GO in the columns under the tested

355

conditions, confirming the importance of secondary minima to the fate and transport of GO in

356

structured heterogamous porous media. The model-estimated maximum retention capacities

357

X for all domains in the saturated heterogeneous columns ranged from 34.4 to 49.8 mg L-1

358

with the XSFD were also all larger than XFFD (Table 2), which is similar to the values of

359

previous studies.21

360

The model simulations also provide the opportunity to quantify the mass recovery rates

361

for each domain of the structured heterogeneous columns (Table S3, Supporting

362

Information). The results indicated that most of the particles in effluents were from the FFD,

363

further indicating the dominance of preferential flow to the fate and transport of nanoparticles

364

in saturated heterogeneous porous media.

365 366

GO Retention and Transport in the Unsaturated Heterogeneous Porous Media. The

367

BTCs of the tracer and GO in the unsaturated heterogeneous columns (U1, U2, and U3) did

368

not show the two-peak or two-stage behaviors (Figure 2). The moisture content of the two

369

area in unsaturated columns were obtained from the simulation results of draining process

370

(Supporting Information S2), which were both very low (0.067-0.121) (Table 1) in the coarse

371

sand area within the three unsaturated heterogeneous columns, suggesting limited flow in the

372

coarse sand during the transport experiments. For this reason, the fine sand structure became 16 ACS Paragon Plus Environment

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373

the FFD and dominated the flow and mass transfer process; while the coarse sand was the

374

SFD. As the retained water barely remained in the SFD, almost all GO were transported

375

through FFD by the water current, demonstrated the dominance of preferential flow in

376

structured heterogeneous porous media under unsaturated conditions. This also explained

377

why the BTCs in unsaturated heterogeneous porous media were similar to the typical BTCs

378

observed in homogenous porous media.27

379

Consistent with the results of saturated columns, GO also showed higher retention in

380

the columns at 20 mM than that at 1 mM conditions. Mass balance calculations showed that

381

89.4%-90.6% and 46.6%-56.2% of GO were collected from the outlet at 1 and 20 mM IS,

382

respectively (Table S3, Supporting Information). Although the moisture of the FFD in

383

column U1 was lower than those in U2 and U3, the mass recovery rate of U1 was similar (IS

384

= 1 and 20 mM), indicating no/little deposition of GO onto the air-water interface. This is

385

consistent with the XDLVO calculations and the findings of previous studies.18

386

The two-domain model reproduced the GO breakthrough characteristics in the

387

unsaturated heterogeneous columns fairly well (Figure 2), with R2 larger than 0.94 (Table 2).

388

The best-fit values of the flow velocity in FFD were much greater than those in SFD for all

389

treatments with the ratio higher than 44 (Table 2). The contrast was biggest for column U2

390

(~65), where the flow velocity in the SFD was barely 0.036 cm min-1 (Table 2). These model

391

results also confirmed that fine-grained matrix changed to the FFD and dominated the flow in

392

the unsaturated heterogeneous columns. As the fitted velocity profiles for SFD was negligible

393

compared with the FFD, the model was simplified by neglecting the dispersion processes in

394

SFD when describing tracer and GO transported in all the unsaturated treatments. This

395

simplification did not reduce the accuracy of the model predictions of tracer transport in the

396

unsaturated columns. The dispersion coefficients (D) from unsaturated homogeneous sand 17 ACS Paragon Plus Environment


397

columns (Supporting Information S2) for the FFD under the tested conditions varied from

398

0.099 to 0.291 cm2 min-1 (Table 2). Calculations of the Peclet number ranged from 1.57 × 102

399

to 4.15 × 102 (Table S2, Supporting Information), indicating the dominance of advection

400

process. The Damkohler number for mass transfer in the FFD and SFD ranged from

401

0.30-0.55 and 54.2-83.0 (Table S2, Supporting Information), respectively, indicating the

402

importance of the exchange process to the mass transfer in the two domains, especially the

403

SFD.

404

Similarly, the values of v, and D used in tracer study were same as in simulating GO

405

BTCs in unsaturated heterogeneous porous media (Figure 2). The model-estimated values of

406

the retention rate constants (k) in FFD were increased from 0.00405 to 0.00420 min-1 at IS of

407

1 mM and from 0.136 to 0.209 min-1 at 20 mM with the grain size decreased (Table 2). The

408

Damkohler numbers for GO particle deposition in the unsaturated columns ranged from

409

0.0247 to 15.6 under 1mM condition and 0.83 to 84.0 under 20mM condition (Table S2,

410

Supporting Information), suggesting that particles retention rates were comparable to their

411

transport speeds in the unsaturated columns. Again, because GO deposition in the unsaturated

412

columns at IS of 1 mM was very low, the first-order kinetics were used in the simulations. At

413

the IS of 20 mM, the model-estimated maximum retention capacities X ranged from 36.1 to

414

66.1 mg L-1 (Table 2), within the ranges of the values reported in previous studies.21

415 416

Release of Previously Retained GO. Under saturated conditions, reduction in IS

417

remobilized the previously retained GO in the six structured heterogeneous columns and all

418

the release curves showed two peaks (Figure 3), indicating GO release from both FFD and

419

SFD. The peak release concentrations of GO from the FFD (12.4 mg L-1-22.2 mg L-1), which

420

was higher than those from the SFD (1.3 mg L-1-13.2 mg L-1). Mass balance calculation also 18 ACS Paragon Plus Environment

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421

showed that FFD (14.1%-17.8%) released more GO particles than SFD (5.1%-14.7%) (Table

422

S4, Supporting Information), probably because more particles were retained in the

423

preferential paths during the deposition experiments. In addition, mass balance calculation

424

also showed that reduction of solution IS released 19.2%-32.0% of the total GO applied to

425

the columns, corresponding to 42.8%-69.0% of the previously retained particles (Table S4,

426

Supporting Information). This result indicated the IS perturbation remobilized most of the

427

particles retained on the sand grains in the saturated heterogeneous porous media. Previous

428

studies have demonstrated that the retention of colloids and nanoparticles in porous media is

429

reversible if the attachment of particles on the media is through secondary minimum.37, 49 In

430

this work, both the XDLVO calculations and column experimental data, particularly the

431

release BTCs, suggested that secondary minimum governed the retention and release of GO

432

particles in structured heterogeneous porous media. Several previous studies have also

433

demonstrated the importance of secondary minimum to GO fate and transport in homogenous

434

porous media under similar conditions.15, 17

435

Because most of the flow processes were in the FFD under unsaturated conditions, the

436

release curves of the three unsaturated columns only showed one peak (Figure 4), consistent

437

with the breakthrough curves. In comparison to those of the corresponding saturated

438

experiments, the peak release concentrations of the three unsaturated columns were slightly

439

lower and ranged from 7.6 mg L-1 to 13.5 mg L-1. Mass balance calculation showed that the

440

unsaturated columns (12.1%-22.8%) released less GO particles than the corresponding

441

saturated columns (21.1%-29.8%) (Table S4, Supporting Information). Furthermore, mass

442

balance calculation also showed that reduction of solution IS only released 27.6%-42.7% of

443

the previously retained GO particles in unsaturated columns. This result confirmed that, in



444

addition to deposition onto grain surface, other mechanisms might contribute the retention of

445

GO in structured heterogeneous porous media under unsaturated conditions.18

446 447

ENVIRONMENTAL IMPLICATIONS

448

Findings from this work indicated that structured heterogeneities have strong effects on

449

GO retention, release, and transport in the porous media. Because structured heterogeneities

450

caused by natural and anthropological activities, are ubiquitous in the subsurface environment,

451

accurate characterizations of media structures thus are crucial to the prediction and

452

monitoring of the fate and transport of GO and other nanoparticles in soil and groundwater

453

systems. In particular, preferential flow arising from structured heterogeneities may dominate

454

the flow and mass transfer processes in both vadose zone and the groundwater, which may

455

cause the quick delivery of GO into aquifers and thus impose potential risks to public health.

456

The two-domain model was applied in this work and described the retention and transport of

457

GO in the structured, heterogeneous porous media very well. Nevertheless, further

458

investigations are needed to develop, refine, and optimize mathematical models based on the

459

two-domain conceptualizations, and thus to expand current capacities to better understand

460

and predict the fate and transport of GO in the subsurface.

461 462 463

ASSOCIATED CONTENT Details of XDLVO theory and relevant results, the determination of pore water velocity,

464

dispersion coefficient and moisture content, summary of Peclet and Damkohler numbers,

465

characterization of GO and sand and other additional information is available in the

466

supporting information.

467 20 ACS Paragon Plus Environment

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468


469

ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of

470

China-Xianjiang project (U1503282), and the National Natural Science Foundation of China

471

(41372234, 41172207 and 41172206).

472 473 474

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Page 28 of 31

Table 1. Summary of Conditions for All Experiments

630 Saturated Column

Overall Pore Volume

dCS

dFS

θFFD

θSFD

KSFD

KFFD -1

(µm, FFD)

(µm, SFD)

700-850 700-850 700-850 350-450 350-450 350-450

450-500 250-350 150-200 250-350 150-200 110-150

0.354 0.354 0.354 0.354 0.354 0.354

0.344 0.357 0.364 0.357 0.364 0.384

dCS

dFS

θFFD

θSFD

(µm, SFD)

(µm, FFD)

(cm min )

(cm min-1)

19.8 19.8 19.8 6.0 6.0 6.0

7.8 3.6 1.8 3.6 1.8 0.6

pH

ω

5.6 5.6 5.6 5.6 5.6 5.6

0.53 0.55 0.54 0.54 0.55 0.58

pH

ω

(mL)

S1 S2 S3 S4 S5 S6 Unsaturated Column

38.3 37.9 38.6 38.1 39.2 39.5 Overall Pore Volume

KFFD

KSFD

(cm min-1)

(cm min-1)

(mL)

U1 33.6 700-850 450-500 0.292 0.121 --5.6 0.54 U2 33.5 700-850 250-350 0.346 0.067 --5.6 0.55 U3 34.3 350-450 150-200 0.315 0.094 --5.6 0.53 Where dCS, dFS, θ, K and ω represent diameter of coarse sand, diameter of fine sand, moisture content, saturated hydraulic conductivity, and the ratio of the volumes of the coarse sand area and the total sand system, respectively; FFD and SFD represent fast flow domain and slow flow domain. In this work, coarse sand and fine sand in saturated columns were FFD and SFD, respectively. In the unsaturated columns, however, coarse sand and fine sand became SFD and FFD, respectively. K were determined by the constant head method based on the Darcy’s Law. θ of FFD and SFD were determined indirectly, which were detailed in Supporting Information S2.

631 632


Page 29 of 31

633 634


Table 2. Summary of Model Parameters for All Experiments

Column

vFFDa

vSFDa -1

DFFDa -1

2

-1

DSFDa 2

α* -1

-1

k FFD**

IS 1 mM kSFD**

2

R

k FFD**

kSFD**

IS 20 mM XFFD**

XSFD**

(min-1)

(min-1)

(mg L-1)

(mg L-1)

R2

(cm min )

(cm min )

(cm min )

(cm min )

(cm min )

(min-1)

(min-1)

S1

1.64

0.644

0.212

0.0615

0.00586

0.00227

0.00331

0.97

0.0655

0.179

34.4

38.2

0.96

S2

1.81

0.329

0.234

0.0168

0.00294

0.00218

0.00474

0.95

0.0649

0.188

36.1

39.6

0.96

S3

1.95

0.177

0.253

0.0069

0.00244

0.00214

0.00514

0.98

0.0613

0.225

38.0

39.9

0.98

S4

1.40

0.842

0.085

0.0431

0.00848

0.00421

0.00486

0.97

0.134

0.187

40.3

46.7

0.97

S5

1.65

0.496

0.100

0.0192

0.00409

0.00418

0.00508

0.94

0.133

0.231

41.5

48.0

0.97

S6

1.79

0.179

0.108

0.0044

0.00165

0.00416

0.00559

0.95

0.130

0.313

44.1

49.8

0.97

U1

2.74

0.057

0.291

--

0.0247

0.00405

0.0336

0.98

0.136

0.180

53.8

36.1

0.94

U2

2.35

0.036

0.132

--

0.0135

0.00417

0.0337

0.99

0.141

0.181

55.2

36.7

0.94

U3

2.46

0.055

0.099

--

0.0183

0.00420

0.0348

0.99

0.209

0.246

66.1

39.1

0.94

where v, D, α, k, and X represent velocity of pore water, the dispersion coefficient, the first-order mass transfer coefficient, retention rate constant, and the maximum retention capacity of the porous media, respectively; FFD and SFD represent fast flow domain and slow flow domain; superscript “a” means parameters were determined indirectly (Supporting Information S2); superscript “*” means parameters determined from the tracer experiments of Column S1 to S6 and Column U1 to U3; superscript “**” means parameters determined from the GO transport experiments. In this work, coarse sand and fine sand in saturated columns were FFD and SFD, respectively; in the unsaturated columns, however, coarse sand and fine sand became SFD and FFD, respectively.

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Figure Captions

636

Figure 1. Observed and fitted breakthrough curves of tracer and GO transport in saturated

637

heterogeneous pore media under various solution chemistry conditions (a: S1; b: S2; c: S3; d:

638

S4; e: S5; and f: S6).

639

Figure 2. Observed and fitted breakthrough curves of tracer and GO transport in unsaturated

640

heterogeneous pore media under various solution chemistry conditions (a: U1; b: U2; and c:

641

U3).

642

Figure 3. Observed breakthrough curves of GO during the release process in saturated

643

heterogeneous pore media (a: S1; b: S2; c: S3; d: S4; e: S5; and f: S6).

644

Figure 4. Observed breakthrough curves of GO during the release process in unsaturated

645

heterogeneous pore media (a: U1; b: U2; and c: U3).

646 647

Figure 1

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Figure 2 (a)

(b)

(c)

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Figure 3

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Figure 4 (a)

(c)

(b)

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Retention and Release of Graphene Oxide in Structured

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