Simulating Multiwalled Carbon Nanotube Transport in Surface Water

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Simulating Multiwalled Carbon Nanotube Transport in Surface Water Systems Using the Water Quality Analysis Simulation Program (WASP) Dermont C. Bouchard, Christopher Daniel Knightes, Xiaojun Chang, and Brian Avant Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 06 Sep 2017 Downloaded from http://pubs.acs.org on September 6, 2017

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Environmental Science & Technology

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Simulating Multiwalled Carbon Nanotube Transport in Surface

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Water Systems Using the Water Quality Analysis Simulation

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Program (WASP)

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Dermont Bouchard*, †, Christopher Knightes†, Xiaojun Chang¶, Brian Avant§

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†

USEPA Office of Research and Development, National Exposure Research Laboratory

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960 College Station Road, Athens, GA 30605

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¶

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§

National Research Council Research Associate, Athens, GA 30605 Oak Ridge Institute for Science and Education, Athens, GA 30605

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* Corresponding author phone: (706) 355-8333; email: [email protected]

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Abstract

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Under the Toxic Substances Control Act (TSCA), the Environmental Protection Agency (EPA)

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is required to perform new chemical reviews of nanomaterials identified in pre-manufacture

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notices. However, environmental fate models developed for traditional contaminants are limited

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in their ability to simulate nanomaterials’ environmental behavior by incomplete understanding

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and representation of the processes governing nanomaterial distribution in the environment and

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by scarce empirical data quantifying the interaction of nanomaterials with environmental

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surfaces. In this study, the well-known Water Quality Analysis Simulation Program (WASP)

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was updated to incorporate particle collision rate and particle attachment efficiency to simulate

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multiwalled carbon nanotube (MWCNT) fate and transport in surface waters. Heteroaggregation

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attachment efficiencies (αhet) values derived from sediment attachment studies are used to

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parameterize WASP for simulation of MWCNTs transport in Brier Creek, a coastal plain river

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located in central eastern Georgia, USA and a tributary to the Savannah River. Simulations using 1

ACS Paragon Plus Environment


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a constant MWCNT load of 0.1 kg d-1 in the uppermost Brier Creek water segment showed that

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MWCNTs were present predominantly in the Brier Creek water column, while downstream

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MWCNT surface and deep sediment concentrations exhibited a general increase with time and

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distance from the source, suggesting that MWCNT releases could have increasing ecological

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impacts in the benthic region over long time frames.

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1. INTRODUCTION

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The unique electronic, mechanical, and structural properties1-3 of carbon nanotubes (CNTs),

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their potential in drug delivery and other biomedical applications,4,5 as well as utilization in

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polymer composites,6 has led to increasing production of these versatile materials. In a 2014

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report, the President’s Council of Advisors on Science and Technology (PCAST) identified

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engineered nanomaterials as substantial components of future global economic activity.7 There

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are currently more than 1,600 consumer products reported to contain nanoscale materials; and

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the use of carbon-based nanomaterials (fullerenes, CNTs, and graphene family materials) in

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these products trails only nano-scale silver and titanium.8 Carbon-based nanomaterials are also

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referenced in 40% of the nanotechnology patent applications submitted to the US Patent and

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Trademark Office from 1/2010–3/2011,9 and upper estimates for US CNTs production are in

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excess of 1000 tons per year.10 Clearly, as more CNTs are produced and utilized in commerce,

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the potential for human and ecological exposures also increases11,12 underscoring the importance

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of developing models for simulating CNT transport and transformation in the environment.

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Studies on CNT behavior in aqueous media have focused on the effects of solution

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parameters, primarily ionic strength and dissolved organic carbon (DOC) concentration, on CNT

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aggregation state and deposition on surfaces.13-15 General conclusions from these studies are that

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CNT aggregation follows Derjaguin-Landau-Verwey-Overbeek (DLVO) theory16 and that

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dispersed CNTs may be quite stable at ionic strengths commonly observed in fresh waters,

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particularly at high DOC concentrations. In addition, one-dimensional transport of CNTs in

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porous media columns has indicated that CNTs are significantly retained in porous media under

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environmentally representative background solution conditions.17,18

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Using life cycle analysis approaches and production estimates, the distribution of CNTs

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and other engineered nanomaterials (ENMs) in key environmental compartments have been

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modeled.19-24

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environmental distributions and provide a valuable first-tier assessment tool for high level risk

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assessments.

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medium models that provide higher levels of resolution25

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laboratory and field-based measurement data. Reports are available on modeling streambed-

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water column exchange for TiO226 nanoparticles and naturally occurring colloidal materials.27

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The approaches used included particle-particle interactions and stream bed filtration processes in

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addition to gravitational settling and hydrodynamic exchange. In applying an environmental fate

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model that utilized heteroaggregation attachment efficiencies (αhet) to quantitate TiO2 attachment

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to suspended particulate matter (SPM), TiO2 concentrations in the ng L-1 range for the water

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column and the mg kg-1 range for sediments, were estimated.28

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These multimedia modeling approaches provide valuable estimates on ENM

However, these multimedia approaches need to be complemented by single and preferably utilize available

The status of current approaches for simulating ENM fate and uptake in the environment

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has been recently reviewed.29

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modeling, it is unlikely that a unique nanomaterials transport code will need to be constructed

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from the ground up. Rather, a much more efficient approach is to modify existing codes to

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accommodate the unique properties of nanomaterials. Hendron et al.30 have assessed the utility

Given the historical investment made in contaminant fate

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and limitations of traditional and emerging exposure modeling techniques for their application to

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engineered nanomaterials. For the surface water exposure models reviewed, which included the

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Water Quality Analysis Simulation Program (WASP), they concluded that the model’s ability to

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simulate nanomaterial behavior in surface waters is limited by the availability of both process

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knowledge and empirical nanomaterial characterization data. In addition, even when processes

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are understood, there are differences in approaches for model parameterization.31-33

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The objectives of this work are to develop and apply an enhanced version of WASP that

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incorporates particle collision rate and particle attachment efficiency to simulate multiwalled

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carbon nanotubes (MWCNTs) transport in surface water using laboratory and field measured

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input data.

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sediment and in the water column.34 In that work, all nanoparticles were assumed to completely

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heteroaggregate in all media, which is reasonable given the system under study. In the current

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study, αhet values for MWCNTs with the sediment from the aquatic system under study are

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measured under a range of background solution conditions using the natural surface water

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amended to achieve a range of ionic strengths. This is the first published report where the

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heteroaggregation attachment kinetics of MWCNTs and sediments under systematically varying

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background solution conditions are used to parameterize a surface water quality model for

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dynamic simulation of MWCNTs transport in a surface water body.

WASP has been used to simulate ZnO and Ag nanoparticle concentrations in

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2. MATERIALS AND MODELING

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2.1 Materials, MWCNT Suspension Preparation, and Characterization. MWCNTs were

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purchased from CheapTubes Inc. (Grafton, VT) with a reported 95% purity, outside diameter of

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20-30 nm and length of 10-30 µm (Table S1). The as-received MWCNTs were analyzed for 4


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metals content by inductively coupled plasma-atomic emission spectrometry (ICP-AES) and for

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surface functionality by X-ray photoelectron spectroscopy (XPS). Details for ICP-AES and XPS

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analyses are available in a prior study.35 Analytical grade sodium chloride (NaCl) and calcium

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chloride (CaCl2) were purchased from Thermo-Fisher (Fremont, CA).

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prepared with deionized water (DI) with a resistivity = 18.2 mΩ·cm. Sediment from Brier

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Creek, a coastal plain river located in central eastern Georgia (USA) and a part of the Savannah

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River drainage basin, was collected and characterized for particle size distribution, mineralogical

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composition and organic carbon content. The bulk sediment was wet sieved and the 125-250 µm

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size fraction was utilized for the MWCNTs-particulates attachment studies. Brier Creek water

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was analyzed for major naturally occurring ions by ICP-MS, for particulate organic matter

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(POM, suspended organic materials retained on 0.45 µ filter), and DOC content. Additional

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information on water and sediment characterization techniques are available in SI and

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characterization results are presented in Tables S2 (water) and S3 (sediment).

All solutions were

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MWCNTs were dispersed in Brier Creek water (initial MWCNTs concentration: 100 mg

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L-1) via ultrasonication with a probe sonicator (Sonic & Materials, Newton, CT) in an ice-water

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bath for 10 min at an average energy level of ~32 Watts. The resulting mixture was centrifuged

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at 10,000 RCF at 4°C (Beckman Coulter, Brea, CA) for 30 min and MWCNTs concentration

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([MWCNTs]) in the supernatant determined using UV-vis absorbance at 500 nm (Enspire

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Multimode Reader 2300, PerkinElmer, MA) and a pre-determined calibration curve (Figure

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S1).13 Electrophoretic mobility (EPM) was determined using phase analysis light scattering, and

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the intensity-averaged (Z-average) hydrodynamic diameter (Dh) and polydispersity index (PDI)

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were determined using dynamic light scattering [DLS, Nano ZetaSizer (Malvern Instruments,

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Worcestershire, U.K.)].13 Instrument performance for EPM and Dh measurements were verified

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using NIST-traceable polystyrene nanosphere standards (Thermo-Fisher, Fremont, CA) and a ζ-

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potential transfer standard (Malvern Instruments, Worcestershire, U.K.), respectively.

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2.2 Modeling.

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2.2.1 WASP8 Development. Manufacturers or importers of a new chemical substance for

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commercial use are required by Section 5 of the Toxic Substances Control Act (TSCA) to

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provide EPA with a pre-manufacture notice (PMN) prior to manufacture or import of the

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chemical.36 WASP is an attractive candidate for MWCNT aquatic fate simulation in support of

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the TSCA new chemical review process and other regulatory applications as WASP has been

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used for a variety of regulatory37,38 and research applications39-41 over the past several decades.

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However, WASP7 and prior versions, like most current water quality models, were not

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appropriate for simulating the environmental fate of nanomaterials as they employed classic

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solute partitioning theory to describe contaminant interactions with environmental surfaces.

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An enhancement of the original WASP,42,43 WASP8 is a flexible, dynamic, mass-balance

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framework for developing mechanistic surface water models that simulate the fate and transport

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of environmental contaminants. In WASP8, the older WASP7 TOXI module is upgraded to the

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new Advanced Toxicant module, which is a significant advancement from previous releases of

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WASP. The Advanced Toxicant module incorporates nanomaterials explicitly as a new state

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variable with ENM kinetic attachment to naturally occurring particulates. The ENM-particulate

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collision rate is calculated internally based on parameters described in equation 2 and varies

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depending on stream segment-specific characteristics. Attachment efficiency, equation 1, is

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specified by the user (experimentally measured in this study) as a constant for each WASP

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segment.

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Figure 1B shows the governing processes for this WASP application which simulates

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eight state variables: free MWCNT, four classes of solids (sand, silt, clay, and POM), and

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MWCNT associated with SPM, MWCNT-SPM (MWCNT-silt, MWCNT-clay, and MWCNT-

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POM). Due to its high settling rate, sand is modeled as a sediment substrate not active in the

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heteroaggregation process. Clays, silts, and POM are modeled as ‘solids’ and settling,

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resuspension, burial, and advection with the aqueous phase govern their transport. Like most

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water quality models, WASP doesn’t simulate the aggregation and disaggregation of silts and

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clays, so MWCNT transport in association with SPM is characterized by constant particle size

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classes.

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heteroaggregate’s fate and transport follows that of the SPM.

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heteroaggregation with SPM and MWCNT-SPM and these aggregates do not aggregate further

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to form higher-order heteroaggregates.

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according to the dynamics of the SPM transport so that, for example, MWCNT-clay settles, re-

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suspends, buries, and advects as a clay particle. WASP surface water segments are linked

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through the flow field, connecting upstream segments to downstream segments. Since the Brier

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Creek WASP model operates at steady state, volume, velocity, and depth are constant and flow

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into and out of each cell is constant. Further details and information on the WASP model are

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contained in the WASP8 documentation in SI.

Once MWCNTs attach to SPM to form a MWCNT-SMP heteroaggregate, the WASP simulates MWCNT

MWCNT-SPM aggregates are then transported

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2.2.2 WASP8 Parameterization with Heteroaggregation Attachment Efficiencies (αhet).

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Kinetics of MWCNTs heteroaggregation with Brier Creek particulates were measured in batch

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systems similar to prior studies44,45 and as described in SI. Brier Creek water was amended with 7



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the two major, naturally occurring cations (Na, Ca) to yield final concentrations of 1, 5, and 10

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mM NaCl; or 0.4, 0.6 and 1.0 mM CaCl2 and heteroaggregation monitored for approximately 8

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days by measuring the change in MWCNT concentration in the supernatant using UV-vis

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absorbance at 500 nm. To account for the potential confounding effects of homoaggregation and

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subsequent aggregate precipitation on heteroaggregation determination, Dh was monitored in all

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samples for the duration of the experimental period.

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The heteroaggregation attachment efficiency (αhet) for a given particulate-MWCNT-

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electrolyte combination is estimated:

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ߙ௛௘௧ = ௞

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where khet is the experimentally measured heteroaggregation rate constant (T-1), kcoll is the

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ௌ௉ெ MWCNT-particle collision rate (V T-1), and ‫ܥ‬௣௔௥௧௜௖௟௘ is the concentration of suspended particles

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(V-1). In the event of a MWCNTs release to a surface water body the concentration of naturally

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occurring SPM will be much greater than the particle concentration of MWCNTs. Therefore, it

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is assumed that the SPM concentration does not change significantly as a result of

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heteroaggregation and the MWCNT-SPM heteroaggregation rate may be described by a first-

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order rate constant, khet.

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decrease over time as heteroaggregation with SPM proceeds, and then determining the slope of

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ln [MWCNT] vs time plots. In this study, khet is measured for one particle size fraction (125-250

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µm size fraction of Brier Creek sediment) yielding an αhet value for all particulate surfaces in a

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specific background solution, and kcoll values are calculated for each different SPM size class.

௞೓೐೟ ೄುಾ ೎೚೗೗ ∙஼೛ೌೝ೟೔೎೗೐

(1)

Experimentally, khet may be estimated by measuring [MWCNT]

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The collision frequency, kcoll, is the rate of MWCNTs-SPM collision and is dependent on

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Brownian motion (perikinetic aggregation), fluid motion (orthokinetic aggregation), and

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differential settling:46

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݇௖௢௟௟ =

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Where kB is the Boltzmann constant (1.38 × 10-23 JK-1), T, µ, and G are the absolute temperature

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(298 K), dynamic viscosity (1.002 mPa·s), and the shear rate of water (10 s-1, the estimation of

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ெௐே் ௌ௉ெ , ‫ݒ‬௦௘௧ are the radii this value is depicted in Figure S3), respectively. ‫ݎ‬ெௐே் , ‫ݎ‬ௌ௉ெ and ‫ݒ‬௦௘௧

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and settling velocities of the MWCNTs and SPM, respectively. Since ‫ݎ‬ெௐே் was not constant

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across treatments, kcoll was calculated for each MWCNT-solution chemistry combination. For

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calculation of particle concentrations (Cparticle) and settling velocities (vset), densities of 2100 and

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2650 kg m-3 were used for the MWCNTs and Brier Creek SPM, respectively.

ଶ௞ಳ ் (௥ಾೈಿ೅ ା௥ೄುಾ )మ ଷఓ

௥ಾೈಿ೅ ∙௥ೄುಾ

ସ

ெௐே் ௌ௉ெ + ଷ ‫ݎ(ܩ‬ெௐே் + ‫ݎ‬ௌ௉ெ )ଷ + ߨ(‫ݎ‬ெௐே் + ‫ݎ‬ௌ௉ெ )ଶ ∙ |‫ݒ‬௦௘௧ − ‫ݒ‬௦௘௧ | (2)

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2.2.3 WASP 8 Verification. The development of WASP8 required architecture redesign

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to incorporate the nanomaterial state variable and to increase the number of state variables of

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each class. The heteroaggregation kinetics module incorporated into WASP8 was verified by

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comparing simulated results to analytical solution results for three different scenarios with four

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different cases. The three scenarios investigated the three components that comprise kcoll

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(equation 2). The scenarios were 1) Brownian motion, 2) Brownian motion and fluid motion, and

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3) Brownian motion, fluid motion, and differential settling. The four cases used a range of αhet

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values (0.1, 0.01, 0.001, and 1x10-6). These scenarios demonstrated that WASP8’s simulated

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results matched analytical results exactly for all cases of scenarios 1 and 2. For scenario 3, the

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results had POM > silt (Figure 3A). Solids concentrations in

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the sediments are dominated by the sand fraction which decreases with river distance as silt,

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clay, and POM increase (Figure 3C).

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[MWCNT] in the water column decreases with distance from the MWCNT source (Figure

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3B) primarily due to dilution as incoming tributaries feed into Brier Creek. As a consequence of

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the low αhet value (1.04 x 10-6) measured for MWCNTs in the Brier Creek system, 99 and 95%

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of the MWCNT mass in the water column in the upstream and midstream water column

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segments, respectively, is not attached to suspended particulates but exists as stable MWCNT-

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DOC complexes (Figure 4). MWCNT mass attached to water column particulates follows the

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order of particulate mass in the water column, clay > POM > silt (Figures 3A, 4), but the

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combined mass fractions of MWCNTs attached to particulates in the water column never exceed

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1.0 x 10-5. In the final Brier Creek downstream segment, the MWCNT water column mass

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fraction is reduced to 0.76 as MWCNTs deposit in the sediments (Figure 4).

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The water column MWCNT concentration in the first stream segment (0 – 9.7 km, 551 ng L-1)

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drops to 400 ng L-1 in the second segment (9.7 – 16.3 km) and eventually to 78.3 ng L-1 in the

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last segment (113 – 132 km). Using cumulative probability distributions to describe CNT

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ecotoxicity in fresh water, Garner et al.61 found that at < 3.5 mg L-1 less than 5% of the surveyed

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species would be affected. In a study on the effects of MWCNT dosing at 15 and 30 mg L-1 on

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algae growth, it was observed that humic acid significantly reduced MWCNT-induced oxidative

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stress as well as MWCNT cell internalization.62 In the current study, the observed MWCNT

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stability in Brier Creek water is likely due to the coating of MWCNTs by Brier Creek DOC

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which would also lead to a decrease in algae oxidative stress and cell internalization. So, at the

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MWCNT loadings simulated in this study effects on water column biota would likely be

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minimal.

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Adjusting the ionic strength of Brier Creek water through the addition of NaCl and CaCl2 to

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vary αhet had little effect on MWCNT concentration in the water column (Figure S5A) likely due

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to steric stabilization by DOC. These results indicate that estimation, rather than site-specific

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measurement, may be acceptable for simulating water column concentrations for ENMs

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characterized by very low αhet values. Interestingly, de Klein et al.58 also observed that output of

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the NanoDUFLOW model was relatively insensitive to αhet, but for a different reason: their

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ENMs were rapidly heteroaggregating metal nanoparticles.

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In lower DOC fresh waters, or in the high ionic strength regions of estuaries, higher αhet

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values are likely. Varying αhet over a wide range (1.0 × 10-7 to 1.0) indicates that αhet had a

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significant effect on MWCNT water column concentration when αhet ≥ 0.10 (Figure 5A). Setting

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αhet = 1, where every MWCNT-particulate collision results in attachment, results in a MWCNT

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water column concentration that is 40% lower in the first stream segment than in the actual Brier

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Creek system simulated using the measured αhet value. At αhet = 1 the MWCNTs continue to

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attach to particulates moving downstream, and water column MWCNT concentration decreases

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95% by stream segment 4 (22.1 – 31.2 km).

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3.3.2 MWCNT Concentration in Sediments at Steady State. The MWCNT fractional mass

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distribution in the sediments for three Brier Creek stream segments are presented in Figure 4.

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Moving downstream, the fraction of MWCNT mass in the surface sediment increases in each

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river segment with mass fractions in the clay > silt > POM. Unlike MWCNT mass associated

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with water column particulates, the clay contained the highest mass fraction of MWCNTs

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(Figure 4) although it is the smallest component of the total sediment mass (Figure 3C).

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However, clay is the highest concentration particulate in the water column (Figure 3A) and

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settling of MWCNT-clay particulates results in the higher MWCNT-clay mass fraction in the

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sediment.

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It is evident in Figure 3D that [MWCNT] in the Brier Creek surface sediment fluctuates

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moving downstream but follows an overall increasing trend with distance as total MWCNT

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concentration in the surface sediment increases from 1.9 ng kg-1 in the first stream segment to a

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maximum of 46.5 ng kg-1 in the last segment. This trend reflects the kinetics of particle

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attachment moving downstream: as residence time in Brier Creek increases there is more time

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for attachment to occur and for particulate-attached MWCNTs to deposit in the surface sediment.

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In addition, silt, clay, and POM deposition also increase with river distance (Figure 3C). The

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effects of varying ionic strength and αhet on MWCNT sediment concentrations follows the same

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pattern of increasing MWCNT sediment concentration with distance when αhet < 1.0 (Figure 5B,

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S5B) but deviates from this trend at αhet = 1.0 where high MWCNT deposition in the midstream

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sediments results in midstream MWCNT concentrations being higher than those in the

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downstream sediments.

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The modeled MWCNT sediment concentrations in this study are below levels of concern

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identified in ecotoxicity studies. MWCNTs did not bioaccumulate in oligochaetes when ingested

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from sediments spiked at near 30 and 300 mg kg-1,63,64 which are much higher values than the

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simulated Brier Creek concentrations. However, in a more recent study using much lower

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concentrations, MWCNTs were observed to bioaccumulate in protozoans, which could make

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MWCNTs bioavailable to higher trophic levels.65 To reach a 1 mg kg-1 MWCNT concentration

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in the Brier Creek sediment would require a Brier Creek release rate of near 2000 kg d-1. A

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release rate of this magnitude would likely be unintentional and of relatively short duration.

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However, for ENM’s with αhet ≥ 0.1, mg kg-1 concentrations in Brier Creek sediments are

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attainable at 100 g day-1 release rates (Figure 5B). The Brier Creek system hydraulic residence

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time is 2.5 days, but for other fresh water bodies, like lakes and impoundments, residence times

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can be much longer. For example, hydraulic residence times in near coastal lakes in North

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Carolina and Florida can range from 100 days to 32 years39 which would result in much longer

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MWCNT-particulate contact times and potentially much higher MWCNTs accumulation in

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sediments.

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3.3.3 Source Control and System Response. For any contaminant release it is important to

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evaluate systems response and recovery when the contaminant source is controlled. In Figures 6,

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S6, and S7, the MWCNT source is removed and concentrations in the water column, surface and

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deep sediments simulated over time. Under these conditions, [MWCNT] in the water column

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falls rapidly when the MWCNT source is removed (Figure S6). Since most of the MWCNT

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mass exits the Brier Creek system in the water soon after the source is removed, the water

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column ecological response to a release of MWCNTs in Brier Creek will be primarily acute

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when source control is timely and only chronic when the source is long term as there is no

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significant release from the sediments to the water column.

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WASP8 and the NanoDUFLOW model66 incorporate multiple SPM particle sizes and the

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effects of hydrodynamics on ENM deposition; in addition, WASP8 simulates both a surface, and

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a deep sediment layer which acts as a long term ENM storage zone over time. Irreversible, or

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very slowly reversible, MWCNT attachment to sediments coupled with MWCNT’s chemical

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stability results in a slower decrease in sediment concentrations post source removal (Figures 6,

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S7). With source control, total MWCNT concentrations in the surface sediments are reduced to

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50% of the peak load concentrations after 3.6, 12, and 29 years for the upstream, midstream, and

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downstream river segments, respectively. MWCNT mass loss from the 5-cm thick surface

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sediment layer results from burial as sediment is deposited over time and from re-suspension and

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subsequent transport of the sediment from the Brier Creek system. Burial was the dominant

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process in the Brier Creek system as it was responsible for 86% of the MWCNT mass loss from

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surface sediments averaged over all the river segments. With source control, total MWCNT

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concentrations in the deep sediments are reduced to 50% of the peak load concentrations after

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16, 52, and 133 years for the upstream, midstream, and downstream river segments, respectively

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(Figure 6, Table S10). The slower MWCNT concentration reduction in the deep sediments

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indicates potential long term exposures of benthic organisms to MWCNTs, and a potential

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source for MWCNTs during large scale flooding events when deep sediments may be exposed

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and resuspended in the water column.

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4.0 Environmental Implications of this Study. As prior authors have postulated28,67 and

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corroborated here through both measured and modeled results, ENM deposition on natural

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environmental surfaces will be an important determinant of ENM environmental fate.

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facilitate the exposure modeling of MWCNT in a surface water system, an ENM specific

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process, ENM attachment to naturally occurring particulate matter, has been incorporated into

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the WASP8 water quality model. Though this research utilized a specific ENM and water body

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system for a case study, WASP8 is now a publically available tool for simulating a diverse array

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of ENM-water body combinations (SI). While this work addresses an important facet of ENM

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transport and fate in environmental systems, future work is needed to incorporate the

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transformation and ecosystem response processes that are specific to ENMs to make models as

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representative of an actual ecosystem as possible.

To

419 420

Supporting Information

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Additional measurement, model parameterization, and WASP8 implementation and verification

422

information is available in SI.

423 424

Disclaimer

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This paper has been reviewed in accordance with the U.S. Environmental Protection Agency’s

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peer and administrative review policies and approved for publication. Mention of trade names or

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commercial products does not constitute endorsement or recommendation for use. The views

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expressed in this article are those of the authors and do not necessarily represent the views or

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policies of the USEPA.

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607

List of Table and Figures

Figure 1

(A) Site map, location, and model domain of Brier Creek, GA, USA, and (B) conceptual model describing processes captured in each river segment. Map constructed using USGS (10 m National Elevation Dataset (NED), National Hydrography Dataset (NHD), and National Water Information System (NWIS) Gage Stations) and NCDC Weather Stations. Downloaded 2016. The location map was created using the USA State Boundaries layer by Esri, TomTom North America, Inc.

Figure 2

First-order heteroaggregation of MWCNTs and Brier Creek 125-250 µm sediment size fraction in Brier Creek waters with varying ionic composition; MWCNT hydrodynamic diameter (Dh) is monitored in background solutions (no sediment) during heteroaggregation experimental time period.

Figure 3

Steady state particulates and MWCNT concentrations versus river distance [km]. A) Particulate concentrations in the water column: total, silt, clay, and POM, B) MWCNT concentrations in the water column: total and associated with particulates (silt, clay, POM), C) Particulate concentrations in the surface sediment layer: total, sand, silt, clay, and POM, D) MWCNT concentrations in the surface sediments: total and associated with particulates (silt, clay, POM).

Figure 4

Mass fractions of MWCNT in different media with distance downstream. This figure presents the distribution of MWCNT mass for Brier Creek river segments 1, 6, and 12. The mass fraction is determined by taking the mass associated with a phase and dividing it by the total mass in that segment. Each figure presents the

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water column and surface sediment for a particular river reach. Figure 5

Total MWCNT concentration in the (A) water column and (B) surface sediments with distance for a range of different αhet values.

Figure 6

Silt, clay, POM and total MWCNT concentrations in the surface (A, B) and deep (C, D) sediments for Brier Creek segments 1 (upstream) and 12 (downstream) post MWCNT source removal.

608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625

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626 627 628 629 630 631 632 633

Figure 1. (A) Site map, location, and model domain of Brier Creek, GA, USA, and (B) conceptual model describing processes captured in each river segment. Map constructed using USGS (10 m National Elevation Dataset (NED), National Hydrography Dataset (NHD), and National Water Information System (NWIS) Gage Stations) and NCDC Weather Stations. Downloaded 2016. The location map was created using the USA State Boundaries layer by Esri, TomTom North America, Inc.

634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650

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651 652 653 654 655

Figure 2. First-order heteroaggregation of MWCNTs and Brier Creek 125-250 µm sediment size fraction in Brier Creek waters with varying ionic composition; MWCNT hydrodynamic diameter (Dh) is monitored in background solutions (no sediment) during heteroaggregation experimental time period.

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656

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657 658 659 660


Figure 3. Steady state particulates and MWCNT concentrations versus river distance [km]. A) Particulate concentrations in the water column: total, silt, clay, and POM, B) MWCNT concentrations in the water column: total and associated with particulates (silt, clay, POM), C) Particulate concentrations in the surface sediment layer: total, sand, silt, clay, and POM, D) MWCNT concentrations in the surface sediments: total and associated with particulates (silt, clay, POM).

661 662 663 664

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665 666 667 668

Figure 4. Mass fractions of MWCNT in different media with distance downstream. This figure presents the distribution of MWCNT mass for Brier Creek river segments 1, 6, and 12. The mass fraction is determined by taking the mass associated with a phase and dividing it by the total mass in that segment. Each figure presents the water column and surface sediment for a particular river reach.

669

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670

671 672 673 674 675

Figure 5. Total MWCNT concentration in the (A) water column and (B) surface sediments with distance for a range of different αhet values.

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676 677 678 679 680

Figure 6. Silt, clay, POM and total MWCNT concentrations in the surface (A, B) and deep (C, D) sediments for Brier Creek segments 1 (upstream) and 12 (downstream) post MWCNT source removal.

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131x74mm (96 x 96 DPI)


Simulating Multiwalled Carbon Nanotube Transport in Surface Water

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