# Characterizing Concentrations
and Size Distributions of Metal-Containing Nanoparticles

in Waste Water

APM 272

R E S E A R C H A N D D E V E L O P M E N TEPA/600/R-10/117
October 2010

www.epa.gov



# Characterizing Concentrations
and Size Distributions of Metal-Containing Nanoparticles

in Waste Water

APM 272

Edward M. Heithmar a


### Spiros A. Pergantis b

a U.S. Environmental Protection Agency National Exposure Research Laboratory
Environmental Sciences Division

944 E. Harmon Ave. Las Vegas, NV 89119

b NRC Senior Research Fellow U.S. Environmental Protection Agency National Exposure Research Laboratory
Environmental Sciences Division

944 E. Harmon Ave. Las Vegas, NV 89119

Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy. Mention of trade names and commercial products does not constitute endorsement or
recommendation for use.

U.S. Environmental Protection Agency Office of Research and Development Washington, DC 20460

## Abstract

Nanomaterials containing me tals are finding increasing use in consumer, industrial, and medical products, and they are subs equently being releas ed into the environment. Methods for detecting, quantifying, and characteri zing these materials in complex matrices are critical for the eventual understanding of their implications to environmental qua lity and human health. This report describes recent progress in the development of new metr ology tools. Single particle – inductively coupled plasma mass spectrometry (SP -ICPMS) is used to analyze complex aqueous samples. SP-ICPMS simultaneously quantifies th e concentration of nanoparticles containing an analyte metal and measures the metal mass in i ndividual nanoparticles. The accuracy of SPICPMS is assessed over a range of nanoparticle sizes. The utility of the technique in a number of applications is examined. Nanoparticles cont aining the analyte element can be measured accurately and precisely in th e presence of a 10,000-fold grea ter concentration of other nanoparticles. SP-ICPMS is used to assess tran sformation of nanoparticle s induced by changes in ionic strength. A screening- level assessment of metal-contai ning nanoparticles in urban runoff using SP-ICPMS is demonstrated, and prel iminary studies of c oupling SP-ICPMS with online nanoparticle size separati on methods are presented.

ii

## Notice

The United States Environmental Protection Agency’s (EPA) Office of Research and Development performed and funded the research described here. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

iii

## Table of Contents

Abstract...................................................................................................................... ..................... ii

Notice........................................................................................................................ ..................... iii

Table of Contents............................................................................................................. .............. iv Abbreviations and symbols ..................................................................................................... ........ v Acknowledgments................................................................................................................ .......... vi

Introduction.................................................................................................................. ................... 1 Uses of engineered nanomaterials. ............................................................................................. 1 Environmental implications of increase d use of engineered nanomaterials ............................... 2 Rationale for the development of metr ology tools for metal- containing ENMs ........................ 3 Methods for characterizing engineered nanomaterials ............................................................... 4 Theory of SP-ICPMS............................................................................................................ ...... 7 Experimental .................................................................................................................. ................. 9

Materials ..................................................................................................................... ................ 9

Instrumentation ............................................................................................................... ............ 9

Methods........................................................................................................................ ............... 9

Results and Discussion ........................................................................................................ ......... 10 Assessment of SP-ICPMS accuracy ......................................................................................... 10

Precision and selectiv ity of SP-ICPMS .................................................................................... 11 Nanoparticle transformation study ............................................................................................ 11 Screening urban runoff using SP-ICPMS................................................................................. 12 Coupling SP-ICPMS with separation methods ......................................................................... 13

Conclusions and Future Work ................................................................................................... ... 14

References.................................................................................................................... ................. 16

Tables........................................................................................................................ .................... 22 Figure Captions............................................................................................................... .............. 26

iv

## Abbreviations and symbols

AFM Atomic force microscopy

c a Analyte concentration in aqueous sample (g mL -1 ) CAPS 3-(cyclohexylami no)propanesulfonic acid

CDF Cumulative distribution function CE Capillary electrophoresis

c p Particle concentration in aqueous sample (mL -1 ) DLS Dynamic light scattering EDS Energy dispersive X-ray spectrometry EHS Environmental health and safety

ε n Nebulization transport efficiency (dimensionless) ENM Engineered nanomaterials EPA Environmental Protection Agency

ESD Environmental Sciences Division

FFF Field flow fractionation

Flow-FFF Flow field flow fractionation HDC Hydrodynamic chromatography ICPMS Inductively coupled plasma mass spectrometry

IRZ Initial radiation zone

m a
, p Analyte element mass in the particle (g) NAZ Normal analytical zone Number of analyte ions detected (unitless number) n i

, p NOM Natural organic matter NTA Nanoparticle tracking analysis

q i

, a Ionized analyte flux (s -1 )

q p Particle flux (s -1 )

q s Sample uptake rate (mL s -1 )

r g Radius of gyration

r h Hydrodynamic radius SDS Sodium dodecyl sulfate

Sed-FFF Sedimentation fi eld flow fractionation SEM Scanning electron microscopy SLS Static light scattering SP-ICPMS Single particle - inductively coupled plasma mass spectrometry

t d Dwell time (s) TEM Transmission electron microscopy

τ p Plume pulse transit time (s)

v

## Acknowledgments

I am grateful to PerkinElmer for providi ng the DRCe inductively coupled plasma mass spectrometer used for some of th is research. Charlita Rosal of EPA developed and performed the capillary electrophoresis separation shown in this report.

vi

## Introduction

The National Nanotechnology Initiative define s nanotechnology as “the understanding and

control of matter at dimensions between a pproximately 1 and 100 nanometers”(Council 2010),

and nanomaterials are defined as materials with at least one characteristic dimension in this range. Nanomaterials can be natural (e.g., hum ic and fulvic acids) (Thurman and Malcolm 1981), incidental to human activity (e.g., diesel emissions, welding fumes) (Peters, Elzey et al. 2009), or engineered. Engineered nanomaterials (E NMs) exhibit optical, el ectrical, and chemical

characteristics different from either their bulk or dissolved forms. Because of this, they are the

source of the so called nanotechno logy revolution. Most ENMs can be divided into two general classes, depending on whether they are carbon- based (e.g., carbon nanotube s and fullerenes) or metal-containing (e.g., Ag, TiO 2 , CeO 2 , Fe).



### Uses of engineered nanomaterials.

The use of ENMs in consumer, industrial, and agricultural produc ts, as well as in environmental technology is rapidly increasing (Ponder, Darab et al. 2001; Chaudhry, Scotter et al. 2008; Nanotechnologies 2010). Th is is largely due to the un ique optical, electrical, and chemical properties of nano-scale particles. Ofte n, the benefit of using nanomaterials stems from the increased surface area per unit mass of materi al, which increases with the inverse of the diameter in the case of spherical pa rticles. This results in faster rates of chemical reactions such as oxidative catalysis that occur at surfaces. Some times the benefit of nanomaterials arises from the quantum nature of energy states at the nanomet er scale, as in the wa velength tuning of the fluorescence of quantum dots (Michale t, Pinaud et al. 2005). In the he alth sciences, the ability of

ENMs to bind to cell walls can be utilized for drug delivery (L ai, Trewyn et al. 2003; Zhang, Pornpattananangkul et al. 2010).

The Project on Emerging Nanotechnologies mainta ins a database of consumer products that

manufacturers claim contain EN Ms (Nanotechnologies 2010). Current ly the database contains over 1000 products. Consumer products containi ng nano-scale silver dominate current ENM usage (Table 1). Note that of the carbon-ba sed ENMs, nearly 3⁄4 of the products are durable goods that incorporate carbon nanotubes in the construction material. The nanotubes are bound in this matrix for the lifetime of the product. Conversely, the metal- containing ENMs are most often used in dispersive applications, where they are intentionally releas ed from the product or

where incidental release is substantial. For ex ample, fabrics containing nano-scale silver release silver during washing at varying rates, depe nding on the type of fabric and the washing conditions (Benn and Westerhoff 2008; Geranio, Heuberger et al. 2009). Of the products using carbon-based ENMs only 7 very low-volume uses of fullerenes are documented. Although there is only one product listed using ceriu m oxide, it is as a diesel fuel additive that potentially could entail high-volume dispersive use.

1

### Environmental implications of increased use of engineered

nanomaterials

The unusual properties that result in unique benefits from the us e of ENMs have also elicited

intense interest in the environmental behavior of these materials. The environmental transport, transformation, fate, exposure potential, and effects of ENMs cannot be predicted by the behavior of either the correspond ing dissolved or neat chemicals. In addition, the metrics that affect all these environmental properties are different and more complex than those of conventional pollutants. The num ber of funded research projects on the environmental health and safety (EHS) implications of ENMs (Figur e 1) increased drama tically from 1998 to 2007 (Nanotechnologies 2010). There has been some d ecline in newly initiated projects in the past two years (although data for 2010 are incomplete); nonetheless, research into EHS of ENMs remains intense. The level of research activity is roughly evenly apportioned to carbon-based and metal containing ENMs. For the former, th ere are currently about 54 investigations of

nanotubes and 29 of fullerenes. Of the metal- containing ENMs, most i nvestigations involve titanium dioxide and iron, followed by quantum dots, silver, and then the remaining metal oxides. The interest in carbon nanotubes stems from the known toxicity of these materials that is mediated by the particle aspect ratio. Research focus on the metal-containing ENMs is prompted by their high likelihood to be released from products . This leads to a grea ter potential loading of the metal-containing ENMs in environmental compartments.

An essential capability for any successful rese arch into the environmental behavior of ENMs is a set of metrology tools for the several metric s of the materials that control their release transport, transformation, fate, and effects. Th ese tools would also be required for determining

the occurrence and distribution of ENMs in the environment, and they would permit the temporal trends in these to be assessed. A previous re port by the Environmental Sciences Division (ESD) described the importance of characterization of metal-containing ENMs in the exposure research of these potential environmental stressors (Hei thmar 2009). It discusse d the several methods currently available for the char acterization of various exposur e metrics and why the current methods are inadequate. The report introduced single particle – inductively coupled plasma mass spectrometry (SP-ICPMS) as a method for bot h screening-level and selective determination of metal-containing ENM dispersions. The poten tial of SP-ICPMS to become the first practical analytical method for characteri zation of metal-contai ning ENMs in environmental matrices was

demonstrated.

This report describes recent progress in the development of SP-ICPMS, which can simultaneously quantify the concentration of na noparticles containing an analyte metal and measure the metal mass in individual nanopartic les. The report briefly reviews the current metrology methods discussed in th e previous report and introduces two not covered there. The introduction concludes with a conceptual descri ption of SP-ICPMS, with a real analytical example, and the equations and associated assumptions to calibrate the method. The experiments discussed in this report first a ssess the accuracy of SP-ICPMS over a range of nanoparticle sizes. The utility of the technique in a number of a pplications is then examined.

2Nanoparticles containing the analyte element can be measured accurately and precisely in the presence of a 10,000-fold greater concentration of other nanoparticles. SP-ICPMS is used to assess transformation of nanopartic les induced by changes in ioni c strength. Limitations in sampling and sample handling of real environmental water samples for nanoparticle

measurements are demonstrated. A screen ing-level assessment of metal-containing nanoparticles in urban run-off using SP-ICPMS is demonstrated. Finally, preliminary studies of coupling SP-ICPMS with on-line nanoparticle si ze separation methods are presented.



### Rationale for the development of metrology tools for metal-containing

ENMs

A 2009 workshop of approximately 50 scientists involved in EHS research of ENMs was sponsored by the International Council on Nanot echnology (ICON). The charge of the workshop was to identify and rank the key research prio rities for informed decisions on developing ENMs with minimal potential adverse en vironmental impacts. The workshop report (Alvarez, Colvin et al. 2009) identified fourteen research priorities, which were ranke d according to two criteria: (1) the importance of each issue in advancing our ability to design ENMs responsibly, and (2) the current development of scientific understanding of the issue. Tools to detect, measure and characterize ENMs ranked highest in importance. This area was also determined to be the most poorly developed. Consequently, development of metrology tools, es pecially for real environmental matrices, was the hi ghest ranked research priority.

The first reason for the critical need for re search to develop me trology tools is their central role in every area of EHS research. Th ese areas include (1) measuring the environmental occurrence and distribution of ENMs, (2) determin ing temporal trends in environmental loads, (3) laboratory studies of transport, transformati on, and fate, and (3) toxicity studies. Ultimately, exposure models must be developed for EN Ms (Mueller and Nowack 2008), and these will require measuring releases for source terms, as well as measuring ENM distributions in the environment to verify the models.

Another reason for developing ENM metrology tool s is the complex set of metrics. For conventional pollutants, mass con centration is often the only rele vant metric for determining exposure. In the case of ENMs, exposure potential is affected by particle size. Depending on the exposure model, measurement of size distributio ns in terms of particle mass, volume, or equivalent hydrodynamic radius may be most relevant (Hassellöv, Readman et al. 2008). Specific surface area (area/mass ratio) is important to the catalytic activity of ENMs such as

TiO 2 , and it can influence toxicity (Schulte, Geraci et al. 2008). Surface charge and the related property of ζ potential can determine th e degree ENMs tend to aggregat e (Kim, Lee et al. 2008). As previously discussed, particle shape, characterized by aspect ratio, can dramatically affect toxicity of carbon nanotubes (Magrez, Kasas et al. 2006; Takagi, Hi rose et al. 2008).

A third factor fueling the high interest in developing ENM metrology tools is the current lack of many practical methods. There are a nu mber of techniques for measuring concentrations and size distributions of ENMs in pure suspension s used as starting materials in laboratory

3studies. However, very few met hods exist for detection, quantific ation, and characterization of suspensions after they are introduced into test syst ems. Such techniques are critical, because the ENM can transform in the test sy stem (Alvarez, Colvin et al. 2009). Going one step further in complexity, virtually no practical methods have been published for measur ing concentration and

size distributions of ENMs in re al environmental samples (Handy, von der Kammer et al. 2008).

There are two reasons for this s ituation. First, concentrations of ENMs in the real environment are very low (Benn and Westerhoff 2008). Compoundi ng this low concentration is the presence

of natural colloids that interfere (Klaine, Alvarez et al. 2008 ), especially in the case of metalcontaining ENMs. Detection and quantification of metals usually involves measuring total element concentration, and natural colloids often include minerals that contain the same element

as the ENM of interest. In a ddition, analyte elements can also adsorb on natural organic matter (NOM) in colloids.

Advances in understanding th e environmental behavior of metal-containing ENMs can only be made if detection, quantification, and characte rization methods are de veloped, especially

for the concentration and size dist ribution metrics of the nanomaterials. In the short term, these methods must be effective at least in laboratory test systems, and at least screening-level methods must be available to detect the proba ble presence of metal-containing ENMs in real environmental samples. Ultimately, selective dete rminative methods that greatly minimize false positives in real-world samples must be developed. The development of characterization methods for metrics other than nanoparticle c oncentration and size distribution may never be attainable for these systems.



### Methods for characterizing engineered nanomaterials

Methods that are currently available to measure several common ENM characterization metrics (Table 2, adapted from Heithmar 2009a) ge nerally work well in simple matrices. One general class of characterizati on techniques is single particle imaging. The most common of these methods are scanning electron microsc opy (SEM) or transmission electron microscopy (TEM) (Lin and Yang 2005; Pyrz and Buttrey 2008). In well controlled systems, atomic force microscopy (AFM) can be advantageous, becau se interaction forces between ENMs and substrates can be studied (Ebe nstein, Nahum et al. 2002). When combined with X-ray emission spectroscopy, usually in the en ergy dispersive mode (EDS), SEM or TEM can definitively identify ENMs in a simple sample matrix. Howeve r, particle concentration must be generally at

least 10 9 mL -1 with current sampling methods, ma king the use of this method for environmentally relevant concentrations of ENMs infeasible. Representative sampling of the test material is generally not attainable, so quantific ation is impossible. In environmental samples, distinguishing metal-containing ENMs from colloids containing the same metal is difficult (Tiede, Hassellöv et al. 2009). Finally, sampli ng methods can introduce ar tifacts, especially in the size distribution of ENMs (Tang, Wu et al. 2009).

An alternative to single-particle imaging for characterizing nanoparticle concentration and size distribution is the genera l class of ensemble measurement techniques, in which a signal produced by a sample population of particles is measured. Several light scattering methods are

4among the ensemble approaches, and they can provide representative size distribution characterization at relatively low concentrations (ca. 10 7 -10 8 mL -1 ). Dynamic light scattering (DLS), also called photon correlation spectroscopy, measures the decay of the autocorrelation of laser light scattering to calc ulate the hydrodynamic radius (r h ) distribution (Filella, Zhang et al. 1997). DLS combined with applying an os cillating electric fiel d also can measure ζ potential ,

which is related to the surface char ge of an ENM. Static light scattering (SLS), which measures the continuous scatter signal at various scatte ring angles, provides the complementary size characteristic of radius of gyration (r g ) (Kammer, Baborowski et al. 2005). The ratio r g /r h can provide an estimation of ENM shape (Schurtenberge r, Newmen et al. 1993). Unfortunately, both these ensemble laser light sca ttering methods are prone to er rors in widely polydisperse suspensions, because scatter signal is exponentia lly related to size. Nanoparticle tracking analysis (NTA) is a single partic le light scattering technique that does not suffer this limitation. None of the light scattering techniques are eff ective in complex media with multiple particle types, because they do not measur e particle elemental composition.

Field flow fractionation (FFF) has beco me popular for physical separation of nanoparticles of different sizes. It can be used with an ensemble detector, such as inductively coupled plasma mass spectrometry (ICPMS), that can provide el emental concentration for each size fraction. Therefore, the FFF-ICPMS combinati on is applicable in co mplex systems. FFF is actually a general technique w ith several implementations. All the FFF methods use the application of a laminar flow of eluent thr ough a narrow channel combin ed with an orthogonal force field (hence the term field flow). In mo st implementations of FFF, the orthogonal force field results in bigger pa rticles having an average position closer to the channel wall than smaller particles, resulting in a lower average velocity for the bigger particle s, and a resulting size separation at the channel outlet. The tw o commonly used FFF techniques for ENM

characterization are flow field (flow-FFF) (Stolpe, Hassellöv et al. 2005; Lesher, Ranville et al. 2009) or, to a lesser extent, a sedi mentation (gravity) field (sed-FFF) (Taylor, Garbarino et al. 1992; Hassellöv, Lyvén et al. 1999 ). Flow-FFF separates nan oparticle sizes by hydrodynamic radius, while sed-FFF separates by buoyant mass. Flow-FFF combined with ICPMS detection has recently been used to study the adsorption of uranium ions on iron oxide nanoparticles (Lesher, Ranville et al. 2009).

Another technique for physically separating nan oparticle size fractions that has recently been applied to ENMs is hydrodynamic chromat ography (HDC) (Tiede, Hassellöv et al. 2009). HDC can be coupled on-line with ICPMS to pr ovide an ensemble characterization method (Tiede, Boxall et al. 2010). In HDC, the sample is passed through a column of inert material such as silica with a mobile phase. The inter-par ticle channels in the stationary phase approach the size of the nanoparticles, so that nanopartic les with larger hydrodynami c radius experience a higher average velocity of the lami nar flow of mobile phase than sm aller particles. Thus, larger particles elute before smaller ones. HDC poten tially has less likelihood for artifacts due to

interactions with the stationa ry phase than FFF methods, which use semi-permeable polymer membranes. On the other hand, FFF provide s separations of higher size resolution.

Capillary electrophoresis (CE) has recently b een applied to separation of engineered nanomaterials (Liu and Wei 2004; Li u, Lin et al. 2005). CE has the advantage of relatively fast

5analysis compare with FFF and HDC, and very good theoretical resolving power. It separates nanoparticles based on electrophoretic mobility (P etersen and Ballou 1992; Huff and McIntire 1994; Quang, Petersen et al. 1996). Therefore, nanoparticle charge and size both affect retention time. This can lead to compli cations in data interpretation.

Ensemble methods based on size separation coupled on-line with elemental detection (i.e., hyphenated methods) provide elemental inform ation in addition to size distribution. This level of specificity makes them effective tools in moderately complex systems like laboratory test media. However, they can only give screen ing-level characterization of real environmental samples. They provide the information on total an alyte element content associated with different size particles. Therefore, they cannot distingui sh a large concentrati on of nanoparticles, each containing a small fraction of analyte element, from a lower concentration of the same size particles, each with a high anal yte element fraction. For example, a large background of natural organic matter of 20 nm hydrodynamic radius with adsorbed silver ions cannot be distinguished

from a low concentration of 20 nm silver nanoparticles.

The lack of any practical methods for de tecting, quantifying, and characterizing metalcontaining ENMs in environmental media has resu lted in the adaptation of a single particle technique from aerosol analysis and colloid chemistry. This method, as modified in our laboratory for aqueous suspensions of metal- containing ENMs, is called single particleinductively coupled plasma mass spectrometry. A related technique was originally developed to characterize airborne particulates (Nomizu, Na kashima et al. 1992; Nomizu, Hayashi et al. 2002). That technique was late r adapted for characterizing zirconia colloids (Degueldre, Favarger et al. 2004), thoriu m oxide (Degueldre and Favarger 2004), and gold particles (Degueldre, Favarger et al. 2006). Recently, the technique was applied to characterize silver nanoparticles in municipal waste water (Monseru d, Lesher et al. 2009), and preliminary results of the technique coupled with flow-FFF have been presented (Hassellöv 2009). ESD presented a study of the performance of SP-ICPMS and how ICPMS acquisition and plasma parameters control performance (Heithmar 2009).

SP-ICPMS relies on the fact that metal-co ntaining nanoparticles entering an ICPMS plasma produce intense ion plumes of the metal isot opes in very short time periods (< 1 ms). If the ICPMS signal is monitored very fast ( ≤ 10 ms data points), any moderate background from dissolved analyte metal, or plas ma matrix ions (Lam and Horlic k 1990), diminishes to an average count of less than 1 ion detected per data point . The ion plume pulses from the nanoparticles are easily distinguished. The fr equency of the pulses is pr oportional to the nanoparticle concentration in the sample, and the number of ions detected in each pulse is proportional to the analyte mass in the nanopart icle creating the pulse.

SP-ICPMS is a single particle rather than an ensemble method, so it analyzes individual nanoparticles (Table 3). SP-ICPMS does not measur e particle size, but rather analyte mass for each particle and the nanopa rticle concentration. The hyphenated methods do not give information on individual nanoparticles, but rather on each size fraction of nanoparticles as a group. One other difference between SP-ICPMS and the hyphenated methods is that the former measurement is made on a time scale of several seconds to a minute depending on the

6concentration, while the latter t ypically require 10 – 30 minutes. It can be seen that SP-ICPMS and the hyphenated approaches are complementar y, and preliminary results of coupling the two will be discussed in this report.



### Theory of SP-ICPMS

A detailed description of ICPMS processes in the conventional mode as well as in the SP mode was given in our previous report (Hei thmar 2009). This report gives a conceptual description of the techniques w ith real analytical results to demonstrate the concepts.

In conventional ICPMS, an aerosol of droplets is produced from the sample usually using some form of pneumatic nebulizer (Taylor 2001). The larger aerosol droplets are removed by collisions within a spray chambe r before a tertiary aerosol of droplets enters the plasma. The flux of droplets is typi cally greater than 10 6 s -1 . Each droplet contains a few hundred to a few thousand analyte atoms. The efficiency of the sampling process from aqueous sample to aerosol flux in the plasma is quantified by th e nebulization transport efficiency, ε n , which is generally between 2% and 30%, depending on the nebulizer and spray chamber used. The aerosol is evaporated in the preheating zone of the plasma , within the load coil region. The salt residues containing the analye begin to vaporize in this region. The salts are atomized in the initial radiation zone (IRZ), which extends from the load coil several mm (Koirtyohann, Jones et al. 1980). Ionization occurs in the normal an alytical zone (NAZ) (Thomas 2004). The vaporization, atomization, and ionization processes are usually >80% efficient for most elements (O'Connor and Evans 1999).

In conventional ICPMS, the above processes resu lt in a fairly constant flux of analyte ions reaching the detector, due to the large number of droplets and the small number of analyte atoms dissolved in each droplet. The resulting ICPM S signal for 30 pg/mL dissolved gold with a short measurement window (known as the dwell time, t d ) of 10 ms is very low and somewhat noisy (Figure 2a). Therefore, a longer measurement window is usually used in conventional ICPMS (Figure 2b). The signal for the 30 pg/mL dissolv ed gold is roughly constant at about 80 s -1

.

When the same 30 ng of gold in 50 nm nanopart icles are suspended in each mL of sample, very few aerosol droplets contain an y gold, and a few contain ca. 4 x 10 6 gold atoms (one nanoparticle). The result ing signal (Figure 3a) for the conventional long t d (2 s in this example) is somewhat noisier than for dissolved gold, whic h is expected by the episodic nature of the gold flux. The average signal intensity is the same as for the same concentration of dissolved gold (Figure 2b). Each gold nanoparticle produces a plume of millions of i ons that enter the mass spectrometer interface over a pe riod of less than 500 μs (Gray, Olesik et al. 2009; Heithmar 2009). In SP-ICPMS, this discrete nature of the ion signal is exploited by using very short dwell

times. With t d = 10 ms, each gold nanoparticle ion plume reaching the detector contains about 30 ions (the rest of the ions entering the in terface are lost in the spectrometer), producing a corresponding pulse (Figure 3b). The number of ions detected in each pulse is directly proportional to the gold mass in the correspondi ng single nanoparticle. The frequency of pulses is proportional to the co ncentration of nanoparticles in the sample (in this case, ca. 2 x 10 4 mL -1 ).

7This theory of SP-ICPMS that results in an easily calibrated signal relies on two assumptions. First, every nanopartic le that reaches the plasma is detected. This also depends on a sufficiently long residence time, so the ion pl ume expands enough to subs tantially fill the cross

section of the central channel of the plasma. If so, equation 1 is valid.

(1) q p / c p = q s ε n ,

where q p = flux of particles detected in plasma (s -1 ), c p = concentration of nanoparticles containing the detected metal in the sample (mL -1 ), q

s = sample uptake rate (mL s -1 ), and ε n = nebulization efficiency (dimensionless). Note that q

s and ε n are properties of the ICPMS instrument conditions, and independent of the elem ent. Therefore, equation 1 can be used to calculate their product usi ng any type of nanopartic le suspension of known c p .

The second assumption of the SP-ICPMS theory is that ICPMS sensitivity is constant for an analyte, irrespective of whether it is disso lved or contained in nanoparticles. Again, this requires that the residence time in the plasma to be sufficiently long. If so, equation 2 is valid.

(2) m a,p = [q
s ε n c a / q i,a ] n i,p = k n i,p ,

where m a,p = mass of analyte element in a single nanoparticle (g), n i,p = number of ions of analyte

element detected in the corres ponding plume (number of ions detected in a single SP-ICPMS pulse – see Figure 3 b), c

a = the analyte concentration in a di ssolved standard of the analyte (g

mL -1 ), q i,a = ion flux measured for the dissolved standard (s -1 ). For each analyte element, calibration of the element mass in individual part icles (calculation of the response factor k) requires only the q

s ε n product from Equation 1 and analys is of a known concentration of dissolved analyte element using a conventional ICPMS standard).

Equation 2 provides calibration of nanopartic le element mass. The calibration of nanoparticle concentration is provided by re arrangement of equa tion 1 for any unknown nanoparticle suspension, once q

s ε n has been determined:

(3) c p = q p / q

s ε n .

8

## Experimental

Most of the materials, instru mentation and methods used in the present study are found in our previous report (Heithmar 2009). Only t hose added or modified are described here.



### Materials

Sodium dodecyl sulfate (SDS ), Triton X-100, and 3-(cyclohexylamino)propanesulfonic acid (CAPS) were obtained from Sigma-Aldrich, St . Louis, MO. Calcium chloride was obtained from EMD Chemicals, Darmstadt, Germany. Syringe filters (0.45 μ m and 5.0 μ m nylon) were obtained from Sterlitech, Kent , WA. Urban runoff water fo r SP-ICPMS experiments were obtained from Las Vegas Wash, Las Vegas, NV (36° 6.826’ N, 115° 8.741’ W, ca. 2 km east of Las Vegas Blvd.).



### Instrumentation

ICPMS analyses were performed on both the DRC e (PerkinElmer, Waltham, MA) described previously and on a 7500c e (Agilent, Santa Clara, CA), with an upgraded 7500cx lens system. HDC-SP-ICPMS experiments were conducted with a hydrodynamic chromatography column (5-300 nm size range, Polymer Laboratorie s, Shropshire, UK) with either an Agilent 1200 HPLC pump or an 100DM syringe pump (ISC O, Lincoln, NE). CE-ICPMS experiments were conducted with a MDQ capillary electrophoresi s instrument (Beckman-Coulter, Brea, CA).



### Methods

Because of limitations in software, SP-IC PMS measurements on the 7500ce with dwell times less than 10 ms had to be acquired by entering multiple elements, so the total integration

time was at least 10 ms.

Silver nanoparticle transformation studies were conducted on either 500 ng/mL (4.5 x 10 8

mL -1 particle concentration) or 0.25 ng/mL (2.2 x 10 5 mL -1 ) silver nanoparticle suspensions in water. The samples were spiked to final concentration of 200 mM CaCl 2 . Subsamples were taken at designated times after spiking and diluted to 1 x 10 4 mL -1 for SP-ICPMS analysis.

Urban runoff water (10 mL) was collected in polypropylene syringes and filtered on-site

with 5.0 μ m syringe filters. One sample was spik ed with gold and silver nanoparticle suspensions prior to filtering. Samples were analyzed by SP-ICPMS within 36 hours, usually

within three hours.

HDC separations were conducted using 10 mM SDS buffer optimized for the nanomaterial. Triton X-100 (0.1%) was added in some experiments. Eluent flow was 1.0

9mL/min. The column eluent was split 60/40 with a tee and a PEEK capill ary tube to waste in order to match the optimum uptake ra te of the nebulizer (400 μL/min).

The 30 and 50 nm gold nanoparticle CE separation was conducted in 75 μm ID x 80 cm fused capillary with 40 mM SD S and 10 mM CAPS, pH 7.3. The SP-ICPMS dwell time was 10

ms.



## Results and Discussion

Assessment of SP-ICPMS accuracy

The validity of the SP-ICPMS theory as de scribed in this report was evaluated by applying it to a series of gold nanoparticles (30, 50, 80, and 200 nm nominal diameter). A suspension of 30 nm gold at 2 x 10 4 mL -1 was analyzed by SP-ICPMS with a 10 ms dwell time to calculate q

s ε n from Equation 1, and a 1.0 ng/mL dissolved gold ICPMS standard was analyzed to calculate k in Equation 2. This was then applied to the SP-ICPMS responses (mean n i,p of suspensions of the four nanopartic le standards). The resulting m a,p values were used to calculate the theoretical diameters of corresponding spheri cal gold nanoparticles. The linear least square fit of the calculated diameters from this proced ure against the nominal va lues (Figure 4) is:

d calculated = 1.00 d nominal + 0.73; (r 2 = 0.9989).

The agreement between the SP-ICPMS calculated diameters and the nominal values demonstrates that the SP-ICPMS theory is valid fo r gold nanoparticles up to at least 200 nm. At some point, larger particles will not vaporize, atomize and ionize with the same efficiency as dissolved analyte, or their ion plume will not be collected with the same efficiency. At that point, calculated m a,p values will be negatively biased, so quantitative analysis by SP-ICPMS should be evaluated with standards of the larg est nanoparticles expecte d. When nanoparticle

standards of well characterized size distribution are not available for a given material, SP-ICPMS should be considered a semi-quantitative techni que for measuring particle elemental mass.

There are published studies of the behavior of ion populations in th e interface region of the ICPMS mass spectrometer (Macedone, Gammon et al. 2001; Mills, Macedone et al. 2006; Farnsworth, Spencer et al. 2009) and of ion clouds in the plas ma produced by single particles (Hobbs and Olesik 1993; Hobbs and Olesik 1997; Gray, Olesik et al. 2009). These studies present the vaporization and ioni zation, as well as the transmissi on of ions thr ough the interface, as complex processes influence by many factors. They might be used to hypothesize that the assumptions made by the SP-ICPMS theory ar e suspect. However, the results of our investigation demonstrate that the assumptions are valid, at l east for gold nanoparticles up to 200

nm diameter.

10

### Precision and selectivity of SP-ICPMS

The precision of SP-ICPMS was assessed by replicate analyses of 50 nm gold nanoparticle suspensions (4 x 10 3 mL -1 ; 5.0 pg/mL). No significant di fferences in the slopes or positions of the cumulative distribution functions (CDFs) of the detected ion pulses (Fgure 5) are

detectable. The relative standa rd deviation of 2.4% for the mean ion counts reflects good precision of the calculated mean particle element mass (Table 4). The relative standard deviation of the pulse count (11%) is consis tent with Poisson statistics for a mean of 101, the best precision attainable for the nanoparticle concentration metric.

The selectivity of SP-ICPMS in complex matrices was evaluated by spiking the suspension analyzed in the last two replicates w ith 60 nm silver nanoparticles at a concentration

of 5 x 10 7 mL -1 . Neither the mean particle gold mass nor the gold nanoparticle concentration metric were affected by a greater than 10 4 ratio of silver to gold nanoparticles (Table 4).



### Nanoparticle transformation study

There have been several studies of changi ng size distributions of metal-containing nanoparticles as produced by changes in matr ix (Kapoor, Lawless et al. 1994; Peukert, Schwarzer et al. 2005; Shim and Gupta 2007; Baalous ha 2009). Increased ionic strength is one factor that often induces greater degree of aggregation, usually at tributed to a collapse of the double layer and a decrease of the associated el ectrostatic repulsion (Dom ingos, Tufenkji et al. 2009; Gilbert, Ono et al. 2009). SP-ICPMS is a potentially powerful tool for studying nanoparticle transformation pro cesses. Because of the speed of SP-ICPMS analyses, fast transformation processes can be followed. The sensitivity of SP-ICPMS could allow the first

studies of transformations at enviro nmentally relevant concentrations.

SP-ICPMS was used to analyze suspension of 60 nm silver over several minutes after the ionic strength was increased by addition of CaCl 2 to a final concentra tion of 200 mM. The original nanoparticle concentration was similar to those used in most transformation studies to date (4.5 x 10 8 mL -1 or 500 ng/mL). The resulting CDFs at 0 (unspiked), 8, and 14 minutes after

CaCl 2 addition shift progressively to the right (higher ion counts per pulse) with time (Figure 6). This reflects the expected aggregation to larger particle clusters.

A similar experiment was conducted at a concen tration of silver na noparticles that might be found in a wastewater effluent (2.2 x 10 5 mL -1 or 0.25 ng/mL) (Benn and Westerhoff 2008). The transformation was followed over two days, reflecting the slow transformation kinetics expected at low concentration. The CDFs at 0, 1, and 49 hours indicate that at least 85% of the dwell times containing any ion signal produced only 1 or 2 ion counts (Figure 7). This result indicates either dissolved silver or silver nanopar ticles of less than about 30 nm diameter. Silver nanoparticles in this experiment appear to dissolv e at environmentally rele vant concentrations.

11The portion of the CDFs with par ticle mass rank >0.85 shift progressi vely to the left over time, indicating that the dominant proc ess is a continued dissolution, ra ther than aggregation. The small number of large nanoparticles (ion coun ts >200 per particle) does increase over time, indicating slight competing aggregation. This very preliminary study is the first of silver nanoparticle size transformations at environmentally relevant concen trations. It is made possible by the high particle concentra tion sensitivity of SP-ICPMS.



### Screening urban runoff using SP-ICPMS

SP-ICPMS was applied to a small screening-level assessment of metal-containing nanoparticles in a surface water consisting of urban runoff (Las Vegas Wash). Water samples were to be filtered for two reasons. First, it was hoped that a size cuto ff of about 0.45 μm could be achieved that would produce data that reflect ed true nanoparticle c ontent. Second, unfiltered water could contain larger partic les (>5 μm) that could potentially clog the nebulizer. The effect of filtration on nanoparticle recovery was studied.

A reagent water suspension of 50 nm diameter gold nanoparticles (1 x 10 4 mL -1 ) before and after filtration through a 0.45 μm nylon filter (Figure 8a and 8b, respectively) was analyzed by SP-ICPMS. Although the nominal cut-off of th e filter is 10 times the diameter of the nanoparticles, the filter retains vi rtually all the nanopartic les. The CDFs of the unfiltered (Figure 8c) and filtered (Figure 8d) suspensions show that only a few smaller nanoparticles (< 30% of the original mean particle mass) were recovered in the filtrate. The poor filtrate recovery may indicate adsorption of the nanopar ticles on the membrane material.

Recovery studies with reagent water suspensi ons of 50 nm gold and 60 nm silver showed that nearly 100% recovery was obtained in the filtrate using 5.0 μm cut-off nylon filters, so Las Vegas Wash water samples were filtered in the field with these filters. One sample was spiked before filtration with 50 nm gold and 60 nm silv er nanoparticle suspensions. Even accounting for a 10:1 dilution of silver nanopa rticles in the spiked sample, th e silver SP-ICPMS analysis of the spiking suspension (5 x 10 4 mL -1 – Figure 9a) and the 5.0-μm filtered spiked Las Vegas Wash water sample (5 x 10 3 mL -1 – Figure 9b) demonstrate poor recovery. In addition, the CDFs of the spiking suspension (Figure 9c) and the 5.0-μm filtered spiked sample (Figure 9d) show a large bias toward small nanoparticles in the filtered sample. The poor recovery in the real water samples could be due to either adso rption of nanoparticles on larger suspended solids in the spiked sample or a layer of solids on the filter membrane blocking the passage of nanoparticles. An investigation of the mechan ism of the poor nanoparticle recovery and of possible approaches to ameliorate the problem is needed. For the preliminary demonstration study reported here, 5.0-μm filtered samples were analyzed to protect the nebulizer, despite the poor recovery. No attempt at correcting results for recovery was made.

Silver–bearing particles are pr esent in the Las Vegas Wash water (Figure 10). The pulse heights indicate a Ag mass equiva lent to about 50-nm diameter metallic Ag particles. The particle concentration is approximately 200 mL -1 , not correcting for the low recovery. By

12contrast, the recovered gold-b earing particle concentration may be on the order of 10 mL -1
(Figure 10).

Approximately 400 particles per mL of titani um-bearing particles above an equivalent

TiO 2 diameter of about 60 nm are present in La s Vegas Wash water samples (Figure 11). The largest particle is equiva lent to about 400 nm TiO 2

.

The SP-ICPMS analysis of Las Vegas Wash water for the lanthanoid elements and yttrium (Figure 12) show the presence of cerium-beari ng particles. It is likely that the source is natural, given the presence of the other lanthanoids and yttrium which tend to occur with cerium

in minerals.

SP-ICPMS analysis of Las Vegas Wash wate r at m/z 57, which is the isotope commonly used for iron determination, was conducted at a 10 ms dwell time (Figure 13, upper trace). The continuous signal is largely due to ArOH + plasma background. Signi ficant pulses above the background are hard to distinguish. SP-ICPMS anal ysis with a 3 ms dwell time demonstrates the improved signal-to-noise in SP-ICPMS as dwell tim e decreases (Figure 13, lower trace). In SPICPMS, background is proportional to dwell time, wh ile signal is independ ent of dwell time, as long as the latter is much longer th an the plume pulse transit time, τ p (Heithmar 2009a). The background signal in Figure 13 is decreased prop ortionally to the 3/10 dwell time ratio. The background is apparently dominated by flicker noise rather than shot noise, because the background fluctuation appears to decrease nearly as much as the mean background, rather than the square-root relationship produced by shot noise. Significant pulses above the 3 ms background are obvious, indicati ng iron-bearing particles.



### Coupling SP-ICPMS with separation methods

A preliminary investigation of the coup ling of SP-ICPMS with HDC separations was

conducted. Initial results indi cated significant background inte rference in the SP-ICPMS of gold. SP-ICPMS analysis of SDS eluent from the Agilent reciprocating piston pump (no HDC column) detected numerous background pulses that precluded analysis of HDC chromatograms (Figure 14). It was considered unlikely that the background pulses were due to gold. Tantalum, with a single isotope at m/ z 181, is known to form oxide polyatomic ions (m/z 197). The presence of tantalum-containing particles in the SDS eluent was confirmed by the SP-ICPMS analysis at m/z 181 (Figure 14 b). The intens ities of the m/z 197 background peaks to the m/z 181 peaks indicate a roughly 1-2% TaO + formation relative to the Ta + . This is consistent with expected values. Because the tantalum a ppeared to come from the HPLC pump, the reciprocating piston pump was replaced with a syri nge pump. It was hoped that the much slower moving parts of the latter would produce fewer tantalum-bearing particles. The resulting m/z 197 and m/z 181 SP-ICPMS backgrounds revealed only two background peaks greater than 5 ions appear at m/z 197 over a 12 minute period (Figure 15). This level of background is acceptable. Interestingly, the two peaks observed are likely gold, since none of the peaks at m/z 181 are large enough to have produced a pulse of these magnitudes, assuming 2% TiO + /Ti +

.

13A suspension of 60 nm gold nanoparticles (50 pg/mL – 2.3 x 10 4 mL -1 ) was analyzed by HDC coupled to the ICPMS. The m/z 197 chromat ogram with 1 s integration time typical for conventional hyphenated analysis includes a poo rly defined peak around 760 s, indicating the elution of 60 nm gold (Figure 16a). The small p eak at about 830 s is near the elution volume of dissolved gold. The chromatogram of an identi cal sample at the SP-ICPMS dwell time of 10 ms (Figure 16b) exhibited a group of individual pulses with a mean ion count of about 40-50 at 760 s, consistent with a SP-ICPMS particle gold mass equivalent to 60 nm gold. Thus, the retention time of the HDC peak provides information that th e particle diameter is about 60 nm, while the SP-ICPMS signal confirms that th e individual particles contain a high fraction of gold. This complementary information would eliminate the possibi lity in a real analysis that the signal at a 60 nm retention is due to nanopart icles with adsorbed gold or mi nerals with low gold content.

The HDC-ICPMS chromatogram (conventional 1 s integration windows) of a mixture of 60 nm gold nanoparticles (50 pg/mL – 2.3 x 10 4 mL -1 ) and 30 nm gold nanoparticles (25 pg/mL

–

9.2 x 10 4 mL -1 ) contains peaks around 770 s (50 nm gold) and 785 s (30 nm gold) (Figure 17a). There is no complementary information in the ch romatogram to confirm that composition. The HDC-SP-ICPMS chromatogram (10 ms dwell ti me) includes individual pulses around 770 s producing about 40-50 ions each, while those ar ound 785 s produce about 6-7 ions (Figure 17b). This is in excellent agreement with the ratio pr edicted by their nominal diameters of about 8:1.

One issue with HDC-ICPMS in eith er the conventional mode or th e SP mode is the presence of occasional spurious single particles (see fo r example the peaks at about 820, 840, and 850 seconds). The cause of these peaks is currently un clear. However, we suspect that they result from contamination from earlier chromatographic runs using larger Au nanoparticles at much higher concentrations ( μ g/mL).

A preliminary experiment coupling CE w ith SP-ICPMS was conducted with a suspension of 30 nm gold (4 x 10 8 mL -1 ; retention time ca. 13 minutes) and 50 nm gold (9 x 10 7 mL -1 ; retention time ca. 15 minutes). The 30 nm particle concentration in this experiment resulted in a substantial fraction of dwell times with multiple nanoparticles, so the pulse ion-count ratio was less than the expected 5:1 (Figure 18). Neverthe less, the 30 nm and 50 nm particles appear to be nearly completely resolved.



## Conclusions and Future Work

The experiments described in this report indi cate the promise of SP-ICPMS as a viable metrology tool for metal-containing ENMs. The theory of the technique is valid for gold nanoparticles up to at least 200 nm diameter ( 83 femtogram mass). Particle element mass and particle concentration measurem ents are precise and unaffected by large excesses of non-analyte particles.

SP-ICPMS allows the study of nanoparticle size transformati on at an environmentally relevant concentration. The part icle concentration sensitivity of other methods have previously

limited transformation studies to concentrations se veral orders of magnitude higher. The results presented in this report indicat e that, while aggregation is si gnificant at high nanoparticle

14concentration (2.2 x 10 5 mL -1 ), dissolution is the dominant tr ansformation process at a more environmentally relevant concentration (4.5 x 10 8 mL -1 ).

SP-ICPMS is a convenient stand-alone method for screening urban runoff water for particles containing substantial mass of a sel ected analyte element. The method does not respond to high concentrations of particles with low element ma ss per particle, which complicate analyses by hyphenated methods.

Sample handling artifacts, such as low recoveries of filtered samples, must be addressed to allow reliable screening-level assessments of water containing suspended solids. Alternative methods for removing large particles will be inve stigated. These methods include filtering with large-area metal sieves and centrifugation.

The coupling of separation methods such as HDC or CE with SP-ICPMS provides more selective analysis than either the separation technique with conventional ICPMS or SP-ICPMS alone. Additional coupled tech niques will be investigated. Coupling flow-FFF with SP-ICPMS is particularly promising, given the high resolu tion of that method compared to HDC. Other emerging techniques such as microfluidic oscilla ting electric field-FFF may be investigated in

collaboration with others.

The main limitation of the SP-ICPMS is its limited nanoparticle concentration dynamic range using commercial ICPMS in struments. This limitation may be largely overcome using a commercial instrument introduced this year that greatly reduces the dead time between individual dwell times, allowing shorter dwell ti mes that increase the upper limit of the dynamic range. Implementation of SP-ICPMS on that instrument is planned soon.

15

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21

## Tables

Table 1 Engineered nanomaterials uses in consumer products.

Nanomaterial Number of products Common uses (with selected examples)

Silver 121 Nutritional supplements; personal care products (tooth brus hes, tooth paste); biocide coating on membranes (gloves, masks, condoms); cothing (socks, underwear, baby apparel); toys and pacifiers; dispersed biocide (washing machines)

Titanium dioxide 32 Resin coat ings; personal care products (skin cream, hair dryers); nutritional supplements; catalysts (self-cleaning coatings)

Zinc oxide 30 Sun block

Carbon nanotubes 19 Material construction (sporting goods, automobile and aircraft parts)

Gold 15 Nutritional supplements, personal care products (skin cream); catalysts.

Fullerenes 7 Cosmetics

Cerium oxide 1 Fuel additive

22Table 2 Common ENM characterization metric s and selected charac terization methods.

Characterization metric Measurement methods

Size distribution - diameter SEM, TEM, AFM, DLS, SLS, NTA, flowFFF, sed-FFF, CE, HDC

Size distribution - mass Sed-FFF Specific surface area adsorption isotherm Surface charge ζ potential by DLS Shape SEM, TEM, AFM, SLS with DLS or FFF

23Table 3 Comparison of SP-ICPMS with hyphenated ensemble methods.

SP-ICPMS Hyphenated ensemble methods Measures elemental mass of nanoparticles, not nanoparticle size distribution. Separate nanoparticles into size fractions diameter, and determine total metal concentration associated with each particle size

fraction.

Provides concentration of metal-based nanoparticles, and mass of metal in each particle. Cannot differentiate large concentration of particles containing litt le analyte from low

concentration with hi gh analyte content. Therefore, no information is provided on

number or characteristics of metal-based particles. Fast analysis (e.g., ≤ 60 seconds) Lengthy analys is (e.g., 20 – 30 minutes)

24Table 4. Statistics of replicate SP-ICPMS analyses of 50 nm gold nanoparticles (4 x 10 3 mL -1 ).

Replicate Mean number of ions p er particle Number of particles

1 25.6 94

2 25 105

3 26.4 87

4 1 26.3 101

5 1 25.9 115

Grand mean 25.8 101

% RSD 2.2 2 11

1 Replicates 4 and 5 were analyzed in pres ence of 60 nm silver particles at 5 x 10 7 mL -1

. 2 Corresponds to < 0.8% RSD in mean particle diameter.

25

## Figure Captions

Figure 1. Number of environmenta l health and safety (EHS) research projects initiated since

1998.

Figure 2. Time resolved ICPMS signal for disso lved gold (30 pg/mL) at (a) 10 ms dwell time and (b) 2 s dwell time.

Figure 3. Time resolved ICPMS signal for 50 nm gold nanoparticle suspension (30 pg/mL) at (a) 2 s dwell time and (b) 10 ms dwell time.

Figure 4. Correlation of calculated gold nanopartic le diameter from the particle elemental mass determined by SP-ICPMS vs. the nominal diameter reported by the manufacturer.

Figure 5. CDF of five replicat e SP-ICPMS analyses of 50 nm gol d nanoparticle suspensions at 4

x 10 3 mL -1 . Replicates 4 and 5 also containe d 60 nm silver nanoparticles at 5 x 10 3 mL -1

.

Figure 6. Change in CDF of 60 nm silver nanopa rticles (500 ng/mL) over time after spiking with

200 mM CaCl 2

.

Figure 7. Change in CDF of 60 nm silver nanoparticles (0.25 ng/mL) over time after spiking

with 200 mM CaCl 2

.

Figure 8. SP-ICPMS of 50 nm gold nanoparticles (1.0 x 10 4 mL-1) - (a) time-resolved signal of unfiltered suspension, (b) signal of filtrate suspension - 0.45 μ m Nylon filter, (c) CDF of unfiltered suspension, (b) CDF of filtrate suspension - 0.45 μ m Nylon filter.

Figure 9. SP-ICPMS of 60 nm silver ENMs - (a) time-resolved signal of 5x10 4 mL -1 spiking solution, (b) signal of Las Vegas Wash water spiked to 5x10 3 mL -1 and then passed through 5.0 μm filter, (c) CDF of 5x10 4 mL -1 spiking solution, (d) CDF of spiked and filtered Las Vegas Wash sample.

Figure 10. Time resolved SP-ICPMS signal of silver and gold in 5.0-μm filtered Las Vegas

Wash water.

Figure 11. Time resolved SP-ICPMS signal of titanium in 5.0-μm filtered Las Vegas Wash

water.

Figure 12. Time resolved SP-ICPMS signal of lanthanoid elements and yttrium in 5.0-μm filtered Las Vegas Wash water.

Figure 13. Time resolved SP-ICPMS signal of m/ z 57 in 5.0-μm filtered Las Vegas Wash water

at two dwell times.

26Figure 14. Time resolved SP-ICPMS signal of el uent from liquid chromatograph reciprocating pump – (a) m/z 197 and (b) m/z 181.

Figure 15. Time resolved SP-ICPMS signal of eluent from piston pump – (a) m/z 197 and (b)

m/z 181.

Figure 16. HDC-ICPMS chromatograms of 60 nm gold nanoparticles (50 pg/mL) – (a) 1 s dwell time and (b) 10 ms dwell time.

Figure 17. HDC-ICPMS chromatograms of 60 nm gold nanoparticles (50 pg/mL) and 30 nm gold nanoparticles (25 pg/mL) mixture – (a) 1 s dwell time and (b) 10 ms dwell time.

Figure 18. CE-SP-ICPMS electropherogram of 30 nm and 50 nm gold nanoparticles.

27r Number of p ojects60050040030020010001998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010Year initiatedbICPMS (dissolved)ICPMS(dissolved)2 s dwell timetime (s) time (s)

Io n s detected1401201008060402000 10 20 30 40 50 60 70aICPMS (dissolved)10 ms dwell time Ions de t ected353025201510500 5101520 25 30time (s)0 5101520 25 3045b4035ICPMS (nanoparticles)ICPMS(nanoparticles)10 ms dwell time Ions detected353025201510500 5 10 15 20 25time (s)time(s)30250aICPMS (nanoparticles)2002 s dwell time010 20 30 4050 60 70

Ion s detected150100500010 20 30 4050 60 70time (s)Diameter from element a l mass (SP-IC P MS; nm)25020015010050030.448.684201050100150200Nominal diameter (nm)pa rticle mass ran k1.210.80.60.40.200 10 20 30 40 50 60 70 80ions detectedionsdetectedRep. 1Rep. 2Rep. 3Rep. 4Rep. 50 min.8 min.14 minutes0.910.50.60.70.8

mass rank010.20.30.4

particle00.10 100 200 300 400 500 600ions detectedParticle mass rank10.80.60.40.200 100 200 300 400 500 600Ions detected0 hr1 hr49 hr506070

i ons detected/dwe ll i o ns detected/dwell(c)90(a)10.9800 8.403020 particle mass ra n k particle mass rank0.70.60.50.40.30.2100.1000 5 10 15 20 25 30 35 40 45 500 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0ions detectedtime (s)(d)90(b)8010.970605040300 8.0.70.60.50.40.30.2200.101000 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 00 5 10 15 20 25 30 35 40 45 50ions detectedtime (s)4060200(a)1(c)1800.91600.80.7

e ions det e cted/dwell ions detected/dw ll140120100140120100 particl e mass rank particle mass ran k0.60.50.40.30.28060400.120000 50 100 150 200 250 3000 50 100 150 200 250time (s)ions detected(d)(b)12000.91800.81600.70.60.50 4.0.3800.20.1200050 100 150 200 250 3000 50 100 150 200 2500time (s)time(s)ions detectedionsdetected

eions d e tected/dwellAg107 Au1979080706050403020100050100150200250300time (s)Ions de t ected per dwell16001400120010008006004002000050 100 150 200 250 300 350time (s)400Ions d e tected per dwell350300250200150100500050100Ce140150time (s)La139Nd142200Y89250300600040005000

ll20003000

o ns detected/dwe01000

io0100200300400ti ( )mes10 ms dwell time3 ms dwell timea120m/z 19710080

counts60402000 100 200 300 400 500 600 700 800time (s)b25000m/z 18120000

counts1500010000500000 100 200 300 400time (s)500 600 700 800120am/z 1971008060402000 100 200 300 400 500 600 700 800time (s)120bm/z 1811008060402000 100 200 300 400 500 600 700 800time (s)

counts countsa4003501 s300750 770 790 810 830 850 870 890time (s)

counts250200150100500time(s)b1009010 ms8070

counts6050403020100750 770 790 810 830 850 870 890time (s)a14001s12001000

counts8006004002000600650700750800850900time (s)200b18010 ms160140

counts120100806040200600650700750800850900time (s)30 & 50 nm Au @ 10-ms integration time1406080100120

u ndance0204060

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