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Aggregation, dissolution and transformation of copper nanoparticles in natural waters Jon Robert Conway, Adeyemi S. Adeleye, Jorge L Gardea-Torresdey, and Arturo A. Keller Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/es504918q • Publication Date (Web): 09 Feb 2015 Downloaded from http://pubs.acs.org on February 11, 2015
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Environmental Science & Technology
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Aggregation, dissolution and transformation of
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copper nanoparticles in natural waters
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Jon R. Conway1,3, Adeyemi S. Adeleye1,3, Jorge Gardea-Torresdey2,3, Arturo A. Keller1,3,*
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Bren School of Environmental Science and Management, University of California, Santa
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Barbara, CA 93106 2
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Department of Chemistry, University of Texas at El Paso, El Paso, TX 79968
University of California Center for the Environmental Implications of Nanotechnology (UC
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CEIN), USA
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ABSTRACT
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Time-dependent aggregation, sedimentation, dissolution and transformation of three copper-
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based engineered nanomaterials (ENMs) of varied properties were measured in eight natural and
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artificial waters. Nano-Cu and Cu(OH)2 aggregated rapidly to >103 nm while the aggregate size
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of nano-CuO averaged between 250 to 400 nm. Aggregate size for both nano-Cu and nano-CuO
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showed a positive correlation with ionic strength with a few exceptions. Aggregate size did not
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correlate well with sedimentation rate, suggesting sedimentation was influenced by other factors.
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Controlling factors in sedimentation rates varied by particle: Cu(OH)2 particles remained stable
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in all waters but groundwater, nano-Cu was generally unstable except in waters with high
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organic content, and nano-CuO was stabilized by the presence of phosphate, which reversed
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surface charge polarity at concentrations as low as 0.1 mg PO43- L-1. Dissolution generally
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correlated with pH, although in saline waters dissolved copper formed insoluble complexes.
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Nano-Cu was rapidly oxidized, resulting in dissolution immediately followed by the formation of
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precipitates. These results suggest factors including phosphate, carbonate, and ENM oxidation
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state may be key in determining Cu ENM behavior in natural waters.
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TEXT
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1. Introduction
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Although copper-based engineered nanomaterials (ENMs) currently comprise a relatively
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small fraction of global ENM production (~200 metric tons per year as of 2010),1 their toxicity
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and life cycle characteristics raise concerns regarding their environmental risk. For example, a
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common use for Cu-based ENMs is as the active ingredient in marine anti-fouling paints or
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agricultural biocides2, where they are directly introduced into the environment as intentionally
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toxic substances. Copper-based ENMs are somewhat unique amongst the most widely-used
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ENMs in that they can participate in redox reactions to form three oxidation states: Cu0, Cu1+,
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and Cu2+. Copper can also participate in a number of inorganic complexes with compounds
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found in natural waters, such as sulfate, sulfide, phosphate, chloride, and carbonate. The
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behavior of different Cu species in the environment is not well understood, and the formation of
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these various complexes may cause precipitation of ionic copper and alter the surface charge and
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therefore aggregation and dissolution kinetics of nanoparticulate copper. Solubility for the
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copper-based ENMs tested in this study have been seen to be enhanced at low pH and by the
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presence of organic coatings in previous research3. Additionally, several copper nanomaterials
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including Cu2O and CuO have been shown to possess photocatalytic properties,4-6 which may
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pose greater hazard to organisms if suspended in photic surface waters than if sedimented into
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aphotic sediments.
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Size,7 coating,8 solubility,9 and photoactivity10, 11 have all been implicated as playing roles in
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ENM toxicity, and are all affected by water chemistry. Aggregate size (and consequently,
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sedimentation rate) is influenced by ionic strength (IS) and pH via charge regulation,12,
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whereby the effective repulsive surface charge of the ENMs is decreased through ionic shielding
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and surface de/protonation. Depending on their composition, organic surface coatings can
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stabilize14,
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interactions between organisms and ENMs.16, 17 Previous research has shown that copper-based
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ENMs are toxic to a wide range of organisms, including fungi,18 aquatic19 and terrestrial plants,20
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estuarine amphipods,21 daphnids and protozoa,22 marine worms and clams,23 and mussels.24 It is
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therefore necessary to develop our understanding of how these materials behave once released
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into the environment in order to predict at risk populations and properly regulate their
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manufacture, use, and disposal.
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or destabilize8 particles in suspension, and through the same mechanisms alter
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In this study, the physiochemical behaviors of three different species of Cu-based ENMs were
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quantified in eight natural and artificial waters covering a range of IS, pH, and organic content to
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gain insight into how these particles may behave in the environment. Additionally, equilibrium
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speciation modeling was performed to predict transformations of the Cu ENMs. Based on
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previous work, we hypothesized that aggregation would largely be controlled by the IS of the
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water, with more saline waters having greater aggregation due to surface charge shielding, and
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by the presence of dissolved organic matter that will increase electrostatic and steric repulsion
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between particles. Due to the propensity for larger, heavier aggregates to settle more rapidly, we
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hypothesized that sedimentation would be directly related to aggregation kinetics and hence
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controlled by IS and total organic content (TOC). We hypothesized that pH would be the key
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factor in dissolution with more dissolution occurring at lower pH and that the presence of TOC
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would also cause a small amount of dissolution. Additionally, we hypothesized that nano-Cu (as
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Cu0) would have the greatest dissolution in oxic waters as it oxidized to Cu2+.
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2. Methods
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2.1. Characterization (Particles and waters)
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Three particles were used this study: nano-Cu (Sigma Aldrich), nano-CuO (US Research
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Nanomaterials), and Cu(OH)2 particles in the form of the commercial biocide Kocide 3000
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(Dupont). A full characterization of the particles can be found in Adeleye et al (2014)3 and the
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Supplementary Information for this paper (Figures S1-S7), and a summary is provided in Table
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1. Briefly, the nano-Cu and nano-CuO ENMs were in the form of a high purity powder with
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primary particle sizes of 100-1000 and 20-100 nm, respectively. Kocide 3000 is composed of
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spherical composites on the order of 50 μm made up of irregular nano- to micro-scale Cu(OH)2
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particles embedded in a primarily carbon-based matrix that rapidly breaks down in water to
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release the Cu(OH)2 particles. These can be seen in the inset of Figure S1. Kocide 3000 was
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chosen as a representative of commercially available nano-copper containing biocides, which
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often contain other ingredients like dispersants.
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Properties of the five natural and three artificial waters used here can be found in Table 2, and
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details on collection and preparation can be found in the Supplementary Information. Total
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organic carbon (TOC) content of the eight waters was determined using a Shimadzu TOC 5000
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analyzer. Conductivity was measured with a Traceable bench conductivity meter (Fisher
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Scientific) and pH was measured using a HACH HQ 40d portable meter. Elemental contents of
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water samples were quantified via ICP-AES (iCAP 6300, Thermo Scientific) except for Cl,
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which was measured with a chloride test kit (Hanna Instruments), and bicarbonate, which was
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measured with an alkalinity titration kit (LaMotte). Detection limits for TOC and PO43- were
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0.004 and 0.02 mg L-1, respectively, and the detection limit for Al, Cu, and Fe was 0.05 mg L-1.
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Ionic strength was calculated from the concentration of Ca2+, Mg2+, K+, Na+, HCO3-, SO42-, and
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Cl- using Equation 1.
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= ∙ ∑ ∙
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Where I is the ionic strength in mM, ci is the concentration of the ith species in mM, and Z2i is
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Eq. 1
the oxidation number of the ith species.
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2.2. Physicochemical kinetics
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Aggregation kinetics of Cu-based ENMs were measured by preparing 10 mg L-1 ENM
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suspensions in each water through dilution of a 100 mg L-1 stock, probe sonicating for 2 sec at
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20% amplitude (sufficient to disperse aggregates) with a Misonix Sonicator S-4000 (QSonica
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LLC, Newtown, CT), then measuring size trends over time at 20oC via dynamic light scattering
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(DLS, Zetasizer Nano ZS-90, Malvern Instruments). Measurements were taken every 30 sec for
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1 h. To measure sedimentation over time, the optical absorbency (Shimadzu 1601 UV-Vis
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spectrophotometer) of suspensions identical to those described above were determined in
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triplicate every 6 min for 6 h at 320 nm with the exception of nano-Cu in lagoon water, seawater,
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and diluted seawater, which were measured at 520 nm at a concentration of 20 mg L-1. Nano-Cu
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is the only of the three particles where copper is primarily in the zero valent state, and as such it
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is able to participate in unique chemical reactions prior to oxidation to the 1+ and 2+ states. One
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of these is the temporary formation of copper (I) chloride compounds in saline waters (Figure
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S4), which absorbs strongly at 320 nm, the spectral wavelength that was used to detect solid
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copper. To test the effects of phosphate on nano-CuO, the sedimentation rates, ζ-potential (DLS,
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Zetasizer Nano ZS-90, Malvern Instruments), and pH of 10 mg L-1 nano-CuO in Nanopure water
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with the addition of 0, 0.1, 0.2, 0.5, 1, and 2 mg PO43- L-1 (from NaH2PO4) were measured in
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triplicate.
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To measure dissolution ENM suspensions were prepared and stored at room temperature for 0,
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1, 7, 14, 21, 30, 60, or 90 days, at which point they were transferred to Amicon® Ultra-4 10 kDa
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centrifugal filter tubes (maximum pore size ~3 nm, Millipore, Ireland) and centrifuged (Sorvall
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RC 5B Plus, CT) at 4000 x g for 40 min with a swinging bucket rotor. Filter retention was
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insignificant.25 The filtrate was analyzed using a copper ion selective electrode (ISE, Cole
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Parmer, IL) under consistent lighting conditions to minimize light-induced interference. The
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filtrate was then oxidized with 1.2 vol% HNO3 and 0.9 vol% H2O2 and analyzed for total copper
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content via inductively coupled plasma atomic emission spectroscopy (ICP-AES, iCAP 6300
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Thermo Scientific, Waltham, MA), with a detection limit of 50 µg L-1. Standard solutions were
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measured every 15 samples for quality assurance.
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Two parameters related to dissolution were quantified: dissolved copper ([Cu]dis) – the total
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copper content of the ENMs present as free ions (Cu1+ and Cu2+), and aqueous phase copper
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([Cu]aq) – the total copper content of the ENMs in the filtrate, which includes dissolved copper,
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complexed copper (e.g., CuCl, CuCO3, Cu3(PO4)2, etc.), and copper bound by ligands under 10
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kDa. The ISE that was used to detect free ionic copper was capable of detecting both Cu1+ and
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Cu2+, both of which may have been shed by the nano-Cu ENMs, but since Cu1+ undergoes rapid
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disproportionation26 into Cu(0) and Cu2+ (E0cell = +0.37V) and is readily oxidized to Cu2+ in oxic
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water (E0cell = +1.08V) it is unlikely to be present as a free ion in any significant amount. Visual
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MINTEQ (v3.0) was used to predict speciation and complex formation in the natural waters
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based on the parameters given in Table 2. Additional information on model parameters can be
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found in the Supplementary Information.
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2.3 Statistical analyses
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To determine the effect of water type on aggregate size, one-way ANOVA or Kruskal-Wallis
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tests with post-hoc Tukey’s or multiple comparisons were performed. To verify the effect of time
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linear models were fitted to each aggregation trend. All analyses were performed in Excel
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(Microsoft Office 2010) or RStudio (0.96.316).
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3. Results & Discussion
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3.1. Aggregation kinetics
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Aggregation of nano-Cu and Cu(OH)2 particles (Figure 1) was characterized by three phases in
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the 1 h time period measured: 1) immediate aggregation to roughly 5-10 µm in the first few
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seconds post-sonication; 2) a downward trend in aggregate size from 0-10 min that was likely
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due to sedimentation of the largest aggregates out of the water column; 3) a stable phase in
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which aggregate diameters averaged 700-2000 nm. Aggregation of nano-Cu and nano-CuO
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followed the trends outlined in our hypothesis (i.e., enhanced aggregation at high IS and low
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TOC) with a few instructive exceptions discussed below, but Cu(OH)2 had similar aggregation
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behaviors in all waters.
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The polydispersity indices (PDIs) reported from the DLS analysis for Cu(OH)2 and nano-Cu
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were near the arbitrary cutoff value of 1 at all time points in all waters, indicating very broad size
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distributions. Average aggregate size and statistical groupings for all three ENMs can be found
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in Table 3. Average Cu(OH)2 aggregate size in the third phase did not vary significantly with
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water type (ANOVA, F7,803 = 0.854, p > 0.5), which may be due to the large proportion (>70
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wt%) of dispersants and other non-Cu ingredients in Kocide 3000. However, despite its high
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polydispersity nano-Cu aggregate size correlated significantly with water type (Kruskal-Wallis,
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H = 149.3, 7 d.f., p
