Scientific, Technical, Research, Engineering, 

and Modeling Support

(STREAMS)

Sampling and Analysis of Nanomaterials 

in the Environment: A State-Of-TheScience Review

[Final Report]

Prepared for:

U.S. Environmental Protection Agency

National Exposure Research Laboratory

Environmental Sciences Division

944 E. Harmon Ave.

Las Vegas, NV 89119

Prepared by:

Eastern Research Group, Inc.

10200 Alliance Road

Suite 190

Cincinnati, OH 45242

29 August 2008

EPA Contract No. EP-C-05-059

Task Order # 66
ii

Table of Contents

Executive Summary............................................................................................................ 1

List of Acronyms ................................................................................................................ 2

1.0 Introduction and Scope of Review.......................................................................... 3

2.0 Information Search Strategy ................................................................................... 4

2.1 Dialog® Search Strategy and Results................................................................. 4

2.1.1 Dialog® Search Parameters........................................................................ 5

2.1.2 Dialog® Search Procedure and Results...................................................... 5

2.2 Targeted Search of Sources ................................................................................ 9

2.2.1 Nano-specific Journals................................................................................ 9

2.2.2 Conference Proceedings............................................................................ 12

2.2.3 Databases of Nanotechnology Research................................................... 13

2.2.4 Grant Databases........................................................................................ 13

2.3 List of Contacted Researchers .......................................................................... 14

2.4 Results of Literature Search and Potential Future Reviews.............................. 15

3.0 Background........................................................................................................... 23

3.1 Overview of Nanomaterials.............................................................................. 23

3.1.1 Natural Nanomaterials.............................................................................. 23

3.1.2 Anthropogenic Nanomaterials.................................................................. 24

3.2 Overview of Environmental Transport ............................................................. 27

3.2.1 Surface Water Transport........................................................................... 27

3.2.2 Soil Transport............................................................................................ 29

3.2.3 Groundwater Transport............................................................................. 30

4.0 Sampling Techniques............................................................................................ 31

4.1 Sampling Techniques Suited for Surface Waters ............................................. 32

4.2 Sampling Techniques Suited for Sediments..................................................... 32

4.3 Sampling Techniques Suited for Soil ............................................................... 33

4.4 Sampling Techniques Suited for Groundwater................................................. 34

4.5 Comparison of Sampling Techniques............................................................... 34

5.0 Analytical Techniques .......................................................................................... 34

5.1 Analytical Techniques for Size Fractionation................................................... 36

5.2 Analytical Techniques for Size Distribution..................................................... 39

5.3 Analytical Techniques for Surface Area........................................................... 42

5.4 Analytical Techniques for Direct Visualization ............................................... 43

5.5 Analytical Techniques for Phase and Structure ................................................ 44

5.6 Analytical Techniques for Chemical Analysis ................................................. 46

5.7 Comparison of Analytical Techniques.............................................................. 51

6.0 Differentiation of Anthropogenic Nanomaterials................................................. 55

7.0 Summary............................................................................................................... 55

8.0 References............................................................................................................. 57

Appendix A DIALOG® SEARCH OUTPUT
EXECUTIVE SUMMARY

This state-of-the-science review was undertaken to identify and assess currently 

available sampling and analysis methods to identify and quantify the occurrence of 

nanomaterials in the environment. The environmental and human health risks associated 

with nanomaterials are largely unknown, and methods needed to monitor the 

environmental occurrence of nanomaterials are very limited or nonexistent. Because this 

research is current and ongoing, much of the applicable information is found in gray 

literature (e.g., conference proceeding, communications with research scientists and other 

experts). 

The approach to this review included three separate strategies:

 Collection of available published literature using Dialog®;

 Review of information from targeted sources, such as nanospecific journals, conference proceedings, grants databases, and 

research databases; and

 Contacts with industry and academic experts.

This report summarizes the key characteristics that must be considered when collecting 

and analyzing samples in various environmental media. Based on results of the literature 

review, and personal communication with researchers, typical analytical methods and 

techniques that are currently used for nanomaterials are identified and briefly discussed. 

The review also identifies several sources that provided information on analytical 

techniques and equipment for nanomaterials. However, little information was obtained 

for sampling techniques that are specific for analysis of nanomaterials. Information 

obtained indicated that nanomaterial-specific sampling techniques have not yet been 

developed. Another area for which the search results provided little information is for 

differentiating anthropogenic (man-made) nanomaterials from natural nanomaterials. A

number of potential sources that may provide additional information upon a more indepth review were identified. As this report provides a current state-of-the-science 

review of active research topics at the time of writing, this report may require 

modifications as additional research is conducted.
2

LIST OF ACRONYMS

Acronym Definition

AAS Atomic Absorption Spectrometry

AEM Analytical Electron Microscopy

AES Atomic Emission Spectrometry

AFM Atomic Force Microscopy

BET Brunauer-Emmett-Teller method

CBED Convergent Beam Electron Diffraction

CCD Charged Coupled Device

CE Capillary Electrophoresis

DLS Dynamic Light Scattering

EDS Energy Dispersive Spectroscopy

EDX Energy-Dispersive X-ray Spectroscopy

EELS Electron Energy Loss Spectroscopy

EFTEM Energy-Filtered Transmission Electron Microscopy

ESEM Environmental Scanning Electron Microscopy

ETEM Environmental Transmission Electron Microscopy

FFF Field-Flow Fractionation

FLD Fluorescence Detector

FlFFF Flow Field-Flow Fractionation

GF Graphite Furnace

HAADF High-Angle Annular Dark Field

HPLC High-Performance Liquid Chromatography

HR High Resolution

ICP Inductively-Coupled Plasma

LIBD Laser-Induced Breakdown Detection

LC Liquid Chromatography

MALLS Multi-Angle Laser Light Scattering

MS Mass Spectrometry

NMR Nuclear Magnetic Resonance

RTM Resonant Tunneling Model

SAED Selected-Area Electron Diffraction

SAXS Small-Angle X-ray Scattering

SEC Size Exclusion Chromatography

SEM Scanning Electron Microscopy

SIMS Secondary Ion Mass Spectrometry

SPM Scanning Probe Microscopy

STEM Scanning Transmission Electron Microscopy

STM Scanning Tunneling Microscopy

TEM Transmission Electron Microscopy

TFF Tangential-Flow (cross-flow) Ultrafiltration

UV Ultraviolet radiation

XAS X-ray Absorption Spectroscopy

XEDS X-ray Energy-Dispersive Spectroscopy
3

XPS X-ray Photoelectron Spectroscopy

XRD X-ray Diffraction

WAXS Wide-Angle X-ray Scattering

1.0 INTRODUCTION AND SCOPE OF REVIEW

The rapidly advancing field of nanotechnology offers potential benefits to almost 

all industries and products. According to the Woodrow Wilson International Center for 

Scholars’ Project on Emerging Nanotechnology’s Nanotechnology Consumer Product 

Inventory, nanomaterials are currently being used in over 500 consumer products. 

However, the environmental and human health risks associated with these materials are 

largely unknown. Before the environmental and general population risk of these 

materials can be measured or monitored, methods will be needed to collect, separate, 

detect, identify, and quantify the occurrence of nanomaterials in the environment over 

time. The rate of product development has outpaced the rate of methods development, 

and, unfortunately, the methods needed to monitor the environmental occurrence of 

nanomaterials are very limited or nonexistent. Only limited research has been conducted, 

in part due to the immense challenges of sampling nanomaterials in the environment 

(e.g., distinguishing between naturally-occurring nanoparticles and engineered 

nanoparticles). While EPA’s Office of Research and Development (ORD) may 

eventually sponsor research to develop remote, in situ, and continuous monitoring 

devices to detect engineered nanomaterials at very low concentrations, the purpose of this 

initial effort is to identify and assess currently-available sampling and analysis methods. 

This report focuses on soil, sediment, and groundwater environmental sampling. A 

companion research effort is focusing on air sampling and analytical techniques.

Due to the limited data available and the rapid advancements that are being made, 

a traditional literature search (i.e., using an abstract database to search peer-reviewed 

journals) is not expected to effectively capture the cutting-edge information on 

environmental sampling and analysis methods for nanomaterials, particularly those under 

development and those that have not been fully peer-reviewed. Because this research is 

current and ongoing, much of the applicable information is found in gray literature (e.g., 

conference proceeding, communications with research scientists and other experts). 

Additionally, many of the techniques for environmental sampling and analysis of 

nanomaterials may need to be adapted from trace sampling methods and methods used in 

quality assurance or characterization of manufactured nanomaterials; therefore, 

peripheral literature has also been identified and reviewed. Section 2.0 presents the 

technical approach that was used to conduct the information search for this report. 

As this report provides a current state-of-the-science review of active research 

topics at the time of writing, this report may require modifications as additional research 

is conducted.
4

2.0 INFORMATION SEARCH STRATEGY

A detailed information search to support EPA’s review of sampling and analysis 

procedures for detecting and monitoring nanomaterials in complex environmental 

matrices was conducted. The approach to this search included three separate, but parallel,

strategies described in the following subsections:

 Section 2.1 describes the collection of available published 

literature using Dialog® (Search Strategy #1);

 Section 2.2 describes the review of information from targeted 

sources, such as nano-specific journals, conference proceedings, 

grants databases, and research databases (Search Strategy #2); and

 Section 2.3 describes contacts with industry and academic experts 

(Search Strategy #3).

The approach generally included the following steps:

1. Conduct an initial review focused on targeted sources;

2. Evaluate information collected during initial review and identify topic 

areas that require additional information; and

3. Review additional sources to identify articles, presentations, or 

research that could provide the needed information.

Initial efforts focused on reviewing a targeted list of journal articles under Search 

Strategy #2 and contacting industry experts under Search Strategy #3. Additional 

resources were also identified using the Dialog® search results, a list of nano-specific 

journals, conference proceedings, grants databases, and research databases.

2.1 Dialog® Search Strategy and Results

The Dialog® search produced two lists of titles of potentially-relevant articles:

 Fifty-eight titles pertaining to characterization and sampling to 

detect nanomaterials in the environment (Appendix A-1); and

 Sixty-one titles pertaining to the use of nanomaterials for 

environmental remediation (Appendix A-2).

This subsection describes the parameters that were specified for the Dialog® search, the 

search procedure and results, and next steps.
5

2.1.1 Dialog® Search Parameters

The parameters that were specified for the DIALOG search include keywords, 

publication date, languages, and the list of databases included in the search.

Keywords: Keywords were searched in the “title,” “abstract,” and “descriptor” 

fields. 

 Primary Keyword: “nano*”

This was identified as a keyword, assuming it would capture the 

following words of interest: nanomaterial, nanoparticle, nanoscale.

 Secondary Keywords:

 “soil” or “air” or “water” or “sediment” or “environment*” or 

“ground*” or “expos*”

<AND>

 “analy*” or “sampl*” or “remediat*” or “contamina*” or 

“characteriz*” or “anthropogenic*” or “manufactur*” or “fate” or 

“transport” or “separat*” or “detect*” or “monitor*”

Words of interest these secondary keywords were expected to encompass 

include: samples, sampling, analysis, analytical, soil, air, water, sediment, 

remediation, contaminants, contamination, anthropogenic, environment, 

environmental, characterize, characterization, ground, groundwater, 

manufactured, manufacturing, fate, transport, separate, separation, detect, 

detection, monitor, monitoring, exposure, expose.

Publication Dates: The Dialog® search included all articles published in the year 

2000 and later.

Language: Only articles published in English were evaluated.

Databases: Thirty databases were included in the search (see Table 2-1 for the 

list). These were identified by evaluating the Dialog® subject guide in “Science -

Energy & Environment” and “Science - Engineering & Technology.” 

2.1.2 Dialog® Search Procedure and Results

Figure 2-1 shows a decision-making flowchart for the Dialog® literature search. 

This flowchart describes the search procedure and the results of each step:
6

1. Dialog® was run using the specified parameters described in the 

previous section. The Dialog® output produced approximately 585 

unique records.

2. The search was then modified by removing the keywords 

“remediat*,” “air,” and “manufactur*.” However, the Dialog® 

output continued to produce more than 400 records.

3. It was determined that the list of 585 records could be reviewed 

manually within a reasonable timeframe; therefore, a list of titles to 

identify those pertaining to characterization and sampling for 

nanomaterials in the environment was prepared. This initial 

review identified a list of 58 potentially-relevant titles.

4. Abstracts and citations for the 58 potentially-relevant titles (see 

Table A-1 of Appendix A) were obtained. Based on information 

provided in the abstract, unrelated articles and articles of interest

were identified. This review identified 14 articles of interest

(identified in Table A-1), which were obtained and evaluated for 

this report. Articles that are cited in this report are presented in 

Table 2-6 at the end of this section.

5. In addition, it was determined that a list of titles pertaining to the 

use of nanomaterials for environmental remediation may be useful 

(if not for this project, then potentially for future efforts). The use 

of nanomaterials for environmental remediation may be of interest 

to EPA because it is a mechanism by which nanomaterials enter 

the environment. Table A-2 of Appendix A lists 61 titles that were 

identified as potentially pertaining to the use of nanomaterials for 

environmental remediation.

Table 2-1 lists databases that were included in the Dialog® search and the number of hits 

per database for the initial search.
7

Do the specified search 

parameters produce a 

reasonable number of 

records (<200 records)?

Modify search 

parameters

Yes: 

Print list of titles. 

Do the majority of the titles 

seem relevant?

Run DIALOG® and view number of records

No

No

Yes: 

Print list of citations and abstracts.

Identify articles of interest.

Is the full text of the article 

available on DIALOG® and 

less than $10?

Retrieve article from DIALOG®

No Obtain full text of 

article by alternate 

means (library, 

etc.)

Do the specified search 

parameters produce a 

reasonable number of 

records (<200 records)?

Modify search 

parameters

Yes: 

Print list of titles. 

Do the majority of the titles 

seem relevant?

Run DIALOG® and view number of records

No

No

Yes: 

Print list of citations and abstracts.

Identify articles of interest.

Is the full text of the article 

available on DIALOG® and 

less than $10?

Retrieve article from DIALOG®

No Obtain full text of 

article by alternate 

means (library, 

etc.)

Figure 2-1. DIALOG® Literature Search Flow Chart
8

Table 2-1. List of Databases Included for DIALOG® Search and Results

Database

Number Database Name

Number of Hits 

Pertaining to 

Characterization 

and Sampling

Number of 

Hits 

Pertaining to 

Environmental 

Remediation

6 NTIS - National Technical Information Service 0 0

9 Business & IndustryTM 0 0

19 Chemical Industry Notes (CIN) 2 0

31 World Surface Coatings AbstractsTM 1 0

32 METADEX® 0 0

34 SciSearch® - a Cited Reference Science Database - 1990 28 36

35 Dissertation Abstracts Online 5 8

36 MetalBase 0 0

40 Enviroline® 0 3

41 Pollution Abstracts 2 1

57 Electronics and Communications Abstracts 0 0

60 ANTE: Abstracts in New Technologies and Engineering 0 0

64 Environmental Engineering Abstracts 0 0

65 Inside Conferences 8 6

73 EMBASE® (1974-present) 4 0

76 Environmental Sciences 3 1

95 TEME - Technology and Management 1 0

99 Wilson Applied Science & Technology Abstracts 0 0

103 Energy Science and Technology 1 2

110 WasteInfo 0 0

245 WATERNETTM 1 0

293 Engineered Materials Abstracts® 0 1

315 Chemical Engineering and Biotechnology Abstracts 0 1

317 Chemical Safety Newsbase 2 1

322 Polymer Online 0 0

323 RAPRA: Rubber and Plastics 0 0

335 Ceramic Abstracts/World Ceramics Abstracts 0 0

369 New Scientist 0 0

370 Science 0 0

636 Gale Group Newsletter Database 0 1

Total 58 61

For more information on databases, see http://library.dialog.com/bluesheets/.
9

Appendix A-3 lists approximately 470 titles that were not selected for further 

analysis based on their titles and expected content. Examples of common keywords and 

phrases that were found in the unrelated titles include the following:

"nanogram," "nanometer," "nanomolar," "nanofiltration," "nanofilm detectors," 

"nanofiber filters," "nano composite membranes," "nanoemulsion," 

"growth/preparation/synthesis and characterization of nanomaterials," and 

"application of nanomaterials in environmental detection."

2.2 Targeted Search of Sources

This subsection describes the review of targeted sources (Search Strategy #2), 

which includes four groups of targeted sources:

 Nano-specific journals;

 Conference proceedings; 

 Databases of nanotechnology research; and

 Grant databases.

2.2.1 Nano-specific Journals

As a first step, 24 journal articles were acquired and reviewed that were 

recommended by industry and academia experts as good sources of information on 

sampling and analytical techniques for detecting and quantifying nanomaterials in the 

environment. Additional articles were added to this list from personal contacts with 

industry experts (described in Section 2.3) and from the Dialog® literature search 

(described in Section 2.1).

Table 2-6, at the end of this section, presents the entire list of articles reviewed for 

this report and notes the general topics covered by each.

Table 2-2 presents a preliminary list of targeted journals for this review. Articles 

reviewed for this report include 4 of the 16 targeted journals. The remaining 12 journals 

may provide a starting point for future research efforts. 
10

Table 2-2. Preliminary List of Journals to Review for Search Strategy #2

Nano-Specific Journals

Environmental Pollution* Nanorisk Newsletter Nanotechnology NanoNow

Journal of Nano Research Journal of 

Nanobiotechnology

Particle and Fiber 

Toxicology

Nanotoxicology

Journal of Environmental 

Monitoring*

Journal of Nanoparticle 

Research*

Journal of Environmental

Engineering

International Journal of 

Nanoscience (IJN)

Environmental 

Monitoring and 

Assessment

Nano Letters (American 

Chemical Society)*

Journal of Nanoscience and 

Nanotechnology

Fullerenes, Nanotubes 

and Carbon 

Nanostructures

*Journal was included in literature review.

Table 2-3 lists the top 20 nanoscience and nanotechnology journals and the top 20 

environmental sciences journals ranked by their 2006 impact factors. The impact factor 

is the ratio of the number of times journal articles published in the previous two years 

were cited during a particular year to the total number of citable items that the journal 

published in the two previous years; for example:

A = the number of times articles published in 2004 and 

2005 were cited during 2006

B = the number of citable items published by the journal in 

2004 and 2005

Impact Factor = A/B

The impact factor provides a measure of the importance of a journal to its field. This 

literature search has identified articles in the following journals listed in Table 2-3:

 Nano Letters;

 Journal of Nanoparticle Research;

 Environmental Science and Technology; and

 Environmental Pollution.

Future research could focus search efforts on other journals with high impact factors.
11

Table 2-3. List of Top Nanotechnology and Environmental Sciences Journals by 

Impact Factor

Journal Title ISSN

Total 

Citations

Impact 

Factor

Top Nanoscience and Nanotechnology Journals

Nano Letters 1530-6984 19,403 9.960

Small 1613-6810 1,240 6.024

Lab Chip 1473-0197 2,879 5.821

Biosensors Bioelectronics 0956-5663 7,198 4.132

Nanotechnology 0957-4484 6,798 3.037

Micropor. Mesopor. Mat. 1387-1811 6,264 2.796

Microfluid nanofluid 1613-4982 117 2.615

IEEE T. Nanobiosci. 1536-1241 316 2.592

Biomedical Microdevices 1387-2176 620 2.551

J. Micromech. Microeng. 0960-1317 3,839 2.321

Journal of Nanoscience and Nanotechnology 1533-4880 1,755 2.194

Scripta Materiala 1359-6462 8,571 2.161

J. Nanopart. Res. 1388-0764 870 2.156

Current Nanoscience 1573-4137 60 2.080

IEEE T. Nanotechnol. 1536-125X 713 1.909

Journal of Vacuum Science and Technology B 1071-1023 10,633 1.597

Material Science and Engineering, A Structural Materials 0921-5093 18,437 1.490

Microelectornic Engineering 0167-9317 3,817 1.398

Journal of Microlithography, Microfabrication, and Microsystems 1537-1646 304 1.243

Physical E. 1386-9477 2,854 1.084

Top Environmental Science Journals

Environmental Health Perspectives 0091-6765 14,434 5.861

Frontiers in Ecology and the Environment 1540-9295 900 4.842

Global Change Biology 1354-1013 5,729 4.339

Environmental Science and Technology 0013-936X 44,915 4.040

Global Biogeochemical Cycles 0886-6236 5,597 3.796

Conservation Biology 0888-8892 11,192 3.762

Annual Review of Environment and Resources 1543-5938 190 3.080

Remote Sensing of Environment 0034-4257 8,817 3.064

J. Paleolimnol 0921-2728 1,925 3.016

J. Aerosol Science 0021-8502 4,040 2.952

J. Aerosol Science and Technology 0278-6826 3,112 2.905

Conservation Biology 0006-3207 8,759 2.854

Critical Reviews in Environmental Science and Technology 1064-3389 733 2.769

Environmental Pollution 0269-7491 8,569 2.769

Environmental and Molecular Mutagenesis 0893-6692 2,351 2.653

Applied Catalysis A: General 0926-860X 15,023 2.630

Atmospheric Environment 1352-2310 19,210 2.630

Environment International 0160-4120 2,762 2.626

Reviews of Environmental Contamination and Toxicology 0179-5953 701 2.619

International Journal of Hydrogen Energy 0360-3199 3,790 2.612
12

2.2.2 Conference Proceedings

Table 2-4 presents a preliminary list of conferences to review for the targeted 

search. The DIALOG® search identified three additional conferences that may be 

sources of applicable papers/presentations:

 The 4th International Surface Engineering Congress & Exhibition, 

St. Paul, MN (August 2005);

 Institut fur Festkorperforschung (Institute of Solid State Research) 

IFF, Germany (March 2002);

 NSTI Nanotech, the Nanotechnology conference and trade show,

Anaheim, CA (May 2007);

 The 7th International Symposium on Nanocomposites and 

Nanoporus materials (ISNAM7), Gyeongju, Korea (February 

2006); and

 BioMEMS and nanotechnology, Perth, Australia (December 

2003).

Table 2-4. Preliminary List of Conferences to Review for Search Strategy #2

Nano-Specific Conferences

International Symposium on Nanotechnology in 

Environmental Protection and Pollution. Hong Kong. 

June 18 - 21, 2006

Experimental Analysis of Nano and Engineering 

Materials and Structures ICEM 13. Alexandroupolis, 

Greece. July 01 - 06, 2007

"Nanotechnology and Health: Evidence and Impact," 

Ann Arbor, MI. October 25 - 26, 2007

Nanoparticles for European Industry II. London, UK. 

October 24 - 25 2007

11th International Conference Detection Technologies 

2007. San Diego, CA. November 01 - 02, 2007

Material Characterization of Nanoscale Materials Peer 

Consultation. U.S. September 6-7, 2007

3rd International Symposium on Nanotechnology, 

Occupational and Environmental Health. Taipei, 

Taiwan, August 29 - September 1, 2007

International Conference on Nanotechnology 

Occupational and Environmental Health & Safety: 

Research to Practice. December 03 - 08, 2006

Pollution Prevention through Nanotechnology, U.S.

September 25-26, 2007

Nanotechnology - Products and Processes for 

Environmental Benefit. London, UK, May 15-16, 2007

Safer Nano 2006. Beaverton, Ore. March 06 - 07, 2006 Nanoforum 2007. Milan, Italy, September 18 - 19 2007

TMS 2007 Symposium: Towards Functional 

Nanomaterials – Synthesis, Characterization, and 

Applications. Orlando, FL. February 25 - March 1, 2007

3rd International Conference on Humanoid, 

Nanotechnology, Information Technology, 

Communication and Control, Environment, and 

Management. Manila. March 15 - 18, 2007

Aerosol and Particle Measurement Short Course. 

Minneapolis, MN. August 20 - 22, 2007

Nanotechnology and Toxicology in Environment and 

Health. Leipzig, Germany. March 27, 2007

OECD Working Party on Manufactured Nanomaterials. 

Berlin, Germany. April 25 - 27, 2007

Technology, Characterization and Fabrication at the 

Nanoscale. Atlanta, GA. July 24 - 25, 2007
13

This state-of-the-science review does not include information from the above list of 

conferences. Conferences listed in Table 2-4 could provide a starting point for future 

research.

2.2.3 Databases of Nanotechnology Research

The following publicly-available databases listing nanotechnology environmental 

and human health research were identified:

 International Council on Nanotechnology (ICON)’s Environmental 

Health and Safety Database (http://icon.rice.edu/research.cfm); 

 Project on Emerging Nanotechnologies’s Inventory of Current 

Nanotechnology Health and Environmental Implications Research 

(http://www.nanotechproject.com/index.php);

 National Institute for Occupational Safety and Health (NIOSH)’s

Nanoparticle Information Library (NIL)

(http://www2a.cdc.gov/niosh-nil/index.asp); and

 Institute of Occupational Health’s (UK) SAFENANO Publication 

Database Search (http://www.safenano.org/AdvancedSearch.aspx).

This literature review does not include information from the above list of nanoresearch 

databases. These databases could provide a starting point for future research.

2.2.4 Grant Databases

The following is a list of potentially-relevant research projects funded by EPA’s 

Science to Achieve Results (STAR) Grants in 2008: 

 University of Delaware, Newark, DE. - Develop an understanding 

of the fate of manmade nanoparticles released into subsurface 

environments. Project will evaluate mobility of nanomaterials in 

soil and groundwater in a laboratory setting using batch 

experiments. Testing methods include dynamic light scattering and 

confical microscopy experiments. Goal is to evaluate current 

conceptual models. Contacts: Yan Jin and John Xiao. 

 University of Michigan, Ann Arbor, MI - Provide fundamental 

information about the movement, fate and bioavailability of 

manmade, carbon nanotubes under different environmental 

conditions.
14

 Purdue University, West Lafayette, IN - Investigate how manmade 

nanomaterials change or transform under certain environmental 

conditions.

 Arizona State University, AZ - Evaluate biological treatment for 

removal of nanomaterials in wastewater treatment plants. The 

project will examine the fate of nanomaterials in wastewater 

treatment and drinking water treatment plants. The ASU 

researchers hope that this work will lead to methods for 

quantifying nanomaterials in water matrices and biosolids. 

Contact: Paul Westerhoff, Professor (Civil and Environmental 

Engineering). Paul Westerhoff was contacted under Search 

Strategy #3 (see Section 2.3).

Additional contacts may be identified from the above list of STAR grants for future 

research efforts (see Section 2.3). The following additional grant sources were also 

identified and may be reviewed to identify ongoing research in the field of sampling and 

analytical procedures for detecting nanomaterials: 

 EPA’s National Center for Environmental Research (NCER) 

Nanotechnology Research Project (complete list available at 

http://es.epa.gov/ncer/nano/research/index.html); and

 National Nanotechnology Institute (NNI) Research Centers 

(http://www.nano.gov/html/centers/nnicenters.html). 

2.3 List of Contacted Researchers

Table 2-5 lists the contacted researchers.
15

Table 2-5. List of Researchers Contacted

Last Name First Name Title/Office/Department Organization

Denison Richard Senior Scientist Environmental Defense

Murashov Vladimir

Special Assistant to the 

Director

National Institute for 

Occupational Safety and Health

Hochella Michael

Professor, NanoBioEarth, 

Department of Geoscience Virginia Tech

Englert Brian Carl Environmental Scientist EPA Office of Water

Penn R. Lee

Professor, Department of 

Chemistry University of Minnesota

Diallo Mamadou S.

Director of Molecular 

Environmental 

Technology, Materials and 

Process Simulation Center, 

Beckman Institute Caltech

Baer Don

Environmental Molecular 

Science Laboratory

Pacific Northwest National 

Laboratory

Erickson Larry E.

Professor, Department of 

Chemical Engineering Kansas State University

Turco Ron ANE Project Coordinator Purdue University

Westerhoff Paul

Professor, Department of 

Civil and Environmental 

Engineering Arizona State University

2.4 Results of Literature Search and Potential Future Reviews

As a result of the information search strategy described in this section, the 

following information was obtained and evaluated for inclusion in this report:

 More than 500 titles identified by Dialog®; and

 Approximately 60 published articles.

Table 2-6 presents the articles that were selected and reviewed in detail for this report and 

the general topic areas covered by each article. This list of articles includes articles that 

were identified by Dialog® and articles that were identified by the search of targeted 

literature sources and personal contacts. As shown in the table, little to no information 

was found for sediment, soil, and groundwater sampling and for differentiating 
16

anthropogenic nanomaterials from natural nanomaterials. As a state-of-the-science 

review, this document is a “living” document and may benefit from additional research. 

Additional areas for future work include:

 Research additional currently-identified journal articles;

 Research identified journals for additional articles;

 Research identified conference proceedings;

 Contact additional researchers; and

 Focus areas of research on those in which the current review did not find 

substantial information.
Table 2-6. Articles Reviewed for Literature Search

Article Citation

Overview Transport Sampling Analysis Natural Engineered Surface Water Soil Groundwater Surface Water Sediment Soil Groundwater Other Size Fractionation Size Distribution/Surface Area Direct Visualization Mineral Phase/Internal Structure

Chemical Analysis

Differentiation of 

Anthropogenic Nanomaterials

Baer, D.R. et al. Characterization Challenges for Nanomaterials. 

Surface and Interface Analysis. 2008, 40: 529-537 X X X X

Baalousha, M.; et al. Size-Based Speciation of Natural Colloidal 

Particles by Flow Field Flow Fractionation, Inductively Coupled 

Plasma-Mass Spectrometry, and Transmission Electron 

Microscopy/X-ray Energy Dispersive Spectroscopy: ColloidsTrace Element Interaction. Environmental Science & Technology

2006, 40, 2156-2162. X X X X X X

Benoit, G.; Rozan, T. F. The influence of size distribution on the 

particle concentration effect and trace metal partitioning in rivers. 

Geochimica et Cosmochimica Acta 1999, 63, 113-127. X X X X X

Bundshuh et al. Quantification of Aquatic Nano Particles after 

Different Steps of Bodensee Water Purification with Laserinduced Breakdown Detection (LIBD). Acta hydrochimica et 

hydrobiologica 2001, 29 (1), 7-15. X X
Table 2-6. (Continued)

18

Article Citation

Overview Transport Sampling Analysis Natural Engineered Surface Water Soil Groundwater Surface Water Sediment Soil Groundwater Other Size Fractionation Size Distribution/Surface Area Direct Visualization Mineral Phase/Internal Structure

Chemical Analysis

Differentiation of 

Anthropogenic Nanomaterials

Burleson, D. J. et al. On the characterization of environmental 

nanoparticles. Journal of Environmental Science and Health Part 

A - Toxic/Hazardous Substances & Environmental Engineering

2004, 39 (10), 2707-2753. X X X X X X

Chen, Zhou et al.. Quantification of C60 Fullerene Concentrations 

in Water. Environmental Toxicology and Chemistry. 2008, DOI: 

10.1897/07-560.1 X X X

Eggleston, C. Met al. The structure of hematite ([alpha]-Fe2O3) 

(001) surfaces in aqueous media: scanning tunneling microscopy 

and resonant tunneling calculations of coexisting O and Fe 

terminations. Geochimica et Cosmochimica Acta 2003, 67 (5), 

985-1000. X X X X

Essington, M. E. Soil and Water Chemistry: An Integrative 

Approach; CRC Press: Boca Raton, FL, 2004. X

Fortner, J. D. et al. C60 in Water: Nanocrystal Formation and 

Microbial Response. Environmental Science & Technology 2005,

39 (11), 4307-4316. X X X X X

Gilbert, B.et al. Stable cluster formation in aqueous suspensions 

of iron oxyhydroxide nanoparticles. Journal of Colloid and 

Interface Science 2007, 313, 152-159. X X X X X X

Gimbert, L. J.et al. Partitioning and stability of engineered ZnO 

nanoparticles in soil suspensions using flow field-flow X X X X X
Table 2-6. (Continued)

19

Article Citation

Overview Transport Sampling Analysis Natural Engineered Surface Water Soil Groundwater Surface Water Sediment Soil Groundwater Other Size Fractionation Size Distribution/Surface Area Direct Visualization Mineral Phase/Internal Structure

Chemical Analysis

Differentiation of 

Anthropogenic Nanomaterials

fractionation. Environmental Chemistry 2007, 4 (1), 8-10.

Herrmann, A. M.e al.. Nano-scale secondary ion mass 

spectrometry - A new analytical tool in biogeochemistry and soil 

ecology: A review article. Soil Biology & Biochemistry 2007, 39

(8), 1835-1850. X

Heymann, D.et al. Determination of C60 and C70 fullerenes in 

geologic materials by high-performance liquid chromatography. 

Journal of Chromatography A 1995, 689 (1), 157-163. X X X

Hochella, M. F.; Madden, A. S. Earth's nano-compartment for 

toxic metals. Elements 2005, 1 (4), 199-203. X X

Hwang, W. et al. Separation of Nanoparticles in Different Sizes 

and Compositions by Capillary Electrophoresis. Bulletin of the 

Korean Chemical Society 2003, 24 (5), 684-686. X

Lead, J. R.et al. Trace metal sorption by natural particles and 

coarse colloids. Geochimica et Cosmochimica Acta 1999, 63, 

1661-1670. X X X X X

Li, X. Q. et al. Zero-valent iron nanoparticles for abatement of 

environmental pollutants: Materials and engineering aspects. 

Critical Reviews in Solid State and Materials Sciences 2006, 31

(4), 111-122. X X
Table 2-6. (Continued)

20

Article Citation

Overview Transport Sampling Analysis Natural Engineered Surface Water Soil Groundwater Surface Water Sediment Soil Groundwater Other Size Fractionation Size Distribution/Surface Area Direct Visualization Mineral Phase/Internal Structure

Chemical Analysis

Differentiation of 

Anthropogenic Nanomaterials

Lienemann, C. et al. Optimal preparation of water samples for the 

examination of colloidal material by transmission electron 

microscopy. Aquatic Microbial Ecology 1998, 14, 205-213. X X X X

Lyven, B. et al.Competition between iron- and carbon-based 

colloidal carriers for trace metals in a freshwater assessed using 

flow field-flow fractionation coupled to ICPMS. Geochimica et 

Cosmochimica Acta 2003, 67, 3791-3802. X X X X X

Madden, A. S.; Hochella, M. F. A test of geochemical reactivity 

as a function of mineral size: Manganese oxidation promoted by 

hematite nanoparticles. Geochimica et Cosmochimica Acta 2005,

69, 389-398. X X X X X

Novak, J. P. et al. Purification of Molecularly Bridged Metal 

Nanoparticle Arrays by Centrifugation and Size Exclusion 

Chromatography. Analytical Chemistry 2001, 73 (23), 5758-5761. X

Novikov, A. et al. Colloid Transport of Plutonium in the FarField of the Mayak Production Association, Russia. Science 2006,

314, 638-641. X X X X X X

Saleh, N. et al. Adsorbed Triblock Copolymers Deliver Reactive 

Iron Nanoparticles to the Oil/Water Interface. Nano Letters 2005,

5 (12), 2489-2494. X X
Table 2-6. (Continued)

21

Article Citation

Overview Transport Sampling Analysis Natural Engineered Surface Water Soil Groundwater Surface Water Sediment Soil Groundwater Other Size Fractionation Size Distribution/Surface Area Direct Visualization Mineral Phase/Internal Structure

Chemical Analysis

Differentiation of 

Anthropogenic Nanomaterials

Stolpe, B et al. High resolution ICPMS as an on-line detector for 

flow field-flow fractionation; multi-element determination of 

colloidal size distributions in a natural water sample. Analytica 

Chimica Acta 2005, 535, 109-121. X X X X

Tarassov, M. et al. Chemical composition and vibrational spectra 

of tungsten-bearing goethite and hematite from western rhodopes, 

Bulgaria. European Journal of Mineralogy 2002, 14, 977-986. X

USEPA U.S. Environmental Protection Agency Nanotechnology 

White Paper;EPA 100/B-071/100; EPA Science Policy Council: 

Feb 1, 07. X

Waychunas, G. et al. Nanoparticulate oxide minerals in soils and 

sediments: unique properties and contaminant scavenging 

mechanisms. Journal of Nanoparticle Research 2005, 7, 409-433. X X X X X

Wigginton, N. S.; Haus, K. L.; Hochella, M. F. Aquatic 

environmental nanoparticles. Journal of Environmental 

Monitoring 2007, 9 (12), 1306-1316. X X X X X X

Yuan, G. Environmental Nanomaterials: Occurrence, Syntheses, 

Characterization, Health Effect, and Potential Applications. 

Journal of Environmental Science and Health Part A -

Toxic/Hazardous Substances & Environmental Engineering 2004,

A39 (10), 2545-2548. X X
Table 2-6. (Continued)

22

Article Citation

Overview Transport Sampling Analysis Natural Engineered Surface Water Soil Groundwater Surface Water Sediment Soil Groundwater Other Size Fractionation Size Distribution/Surface Area Direct Visualization Mineral Phase/Internal Structure

Chemical Analysis

Differentiation of 

Anthropogenic Nanomaterials

Zhang, Y. et al. Stability and Removal of Water Soluble CdTe 

Quantum Dots in Water. Environ. Sci. Technol. 2008, 42 (1), 321-

325. X X

Total 17 8 7 1 4 6 1 0 1 0 10 15 13 6 16 0
23

3.0 BACKGROUND

This section describes natural and anthropogenic nanomaterials that may be 

present in the environment and the factors that affect their transport in various 

environmental media including surface water, groundwater, and soil. An analysis of 

nanomaterials in air is outside the scope or this review.

3.1 Overview of Nanomaterials

The U.S. National Nanotechnology Initiative defines nanomaterials as materials 

that measure 1 to 100 nanometers in at least one dimension. Nanomaterials exist 

naturally in the environment and also are intentionally and unintentionally produced from

human activities. Section 3.1.1 presents an overview of the nanomaterials that may exist 

naturally in the environment, and Section 3.1.2 describes anthropogenic nanomaterials, 

both intentional and incidental, that are commonly produced.

3.1.1 Natural Nanomaterials

Several types of nanomaterials exist naturally and are produced by natural events 

such as chemical and physical weathering of rocks and minerals, combustion, volcanic 

eruptions, biomineralization, and precipitation reactions.1 For example, volcanic ash 

soils contain a nanodimensional aluminosilicate mineral, called imogolite, that has a 

hollow tubular particle morphology2. Natural inorganic nanoparticles, found in soils and 

geologic systems, can have atmospheric, geogenic or biogenic origin.3 Table 3-1

presents examples of naturally occurring nanomaterials and the mechanism of formation,

and Table 3-2 lists minerals discussed in this report.

Table 3-1. Examples of Formation Processes for Natural Nanomaterials

Formation Process Type of Nanomaterial Examples

Carbon-Containing Nanomaterials

Biogenic Organic colloids Humic, Fulvic acids

Organisms Viruses

Geogenic Soot Fullerenes

Atmospheric Aerosols Organic acids

Pyrogenic Soot Carbon nanotubes, fullerenes

Inorganic Nanomaterials

Biogenic Oxides Magnetite

Metals Silver, Gold

Geogenic Oxides Iron oxide

Clays Allophane

Atmospheric Aerosols Sea salt

Source: Nowack et al.3
24

Table 3-2. List of Minerals Used in Journal Articles Referenced in this Report4

Mineral Name Molecular Formula Description

Hematite -Fe2O3Iron oxide

Goethite -FeOOH Iron oxyhydroxide

Ferrihydrite Fe5HO8•4H2O Iron hydrous oxide

3.1.2 Anthropogenic Nanomaterials

Anthropogenic nanomaterials are nanomaterials that are produced from human 

activity. They include both intentionally and unintentionally produced nanomaterials. 

Examples of unintentionally produced nanomaterials include diesel engine exhaust 

products and combustion process byproducts. The remainder of this subsection describes 

intentionally produced nanomaterials, including their applications and manufacturing 

processes.

Nanotechnology entails manipulating matter through chemical and/or physical 

processes to create materials with specific properties for use in particular applications. 

Size-dependant properties, such as catalytic, electrochemical, melting, magnetic, and 

optical properties, change when materials are reduced to the nanoscale. These unique 

characteristics make nanomaterials highly valuable for applications in commercial, 

medical, military, and environmental sectors.

5

Nanomaterials in their unprocessed form are not marketable to consumers. The 

nanotechnology value chain is often described with three levels of nano-based products:

1. Nanomaterials: The first level includes the unprocessed nanomaterials, 

which serve as the building blocks for other products. 

2. Nanointermediates: The second level includes intermediate products, 

called “nanointermediates” that incorporate nanomaterials or that have 

been designed with nanoscale features. Examples of nanointermediates 

include coatings, fabrics, catalysts, and computer chips. 

3. Nano-enabled products: The third level includes nano-enabled products, 

which are finished goods that use nanomaterials or nanointermediates. 

Examples of nano-enabled products include clothing, sporting goods, 

pharmaceuticals, and medical devices.

As described previously, nanomaterials are materials that are nano-sized in at 

least one dimension. One-dimensional nanomaterials include thin films and surfaces and 

coatings, two-dimensional nanomaterials include nanotubes, nanowires, and nanofibers, 

and three-dimensional nanomaterials include fullerenes, quantum dots, and dendrimers.
25

3.1.2.1 Manufacturing Processes

Manufacturing processes to produce nanomaterials fall into one of two major 

categories:

 “Bottom-up” processes – These processes build nanoscale materials from 

individual atoms or molecules; and

 “Top-down” processes – These processes create nanoscale materials from 

their macro counterparts.

The bottom-up process, also called “molecular nanotechnology,” uses forces of 

nature to assemble nanomaterials atom by atom or molecule by molecule. The process 

can use chemical synthesis, self-assembly, or positional assembly. In general, bottom-up 

processes are less expensive than top-down processes.

The top-down process starts with a bulk material, and uses micro- or nanolithography and etching to cut the bulk material into nanoscale structures. Processes 

include photolithography, electron beam lithography, and dip-pen lithography. The topdown processes are the dominant and most well-established manufacturing methods.

3.1.2.2 Nanomaterial Examples and Applications

Nanomaterial products are often characterized into four major categories:

 Carbon-based materials including carbon nanotubes and fullerenes;

 Metal-based materials including quantum dots, nanogold, nanosilver, and 

metal oxides;

 Dendrimers; and

 Composites.

Below is a more detailed description of these categories.

Carbon-based nanomaterials

Carbon-based nanomaterials include cylindrical shaped carbon nanotubes and 

spherical fullerenes. Carbon nanotubes are essentially graphite sheets that are rolled up 

into a tubular form. Nanotubes may be single-walled or multi-walled. An important 

property of carbon nanotubes is their high strength-to-weight ratio; carbon nanotubes are 

100 times the strength of steel at a fraction of the weight. Carbon nanotubes also have 

unique electrical properties that allow them to be used for displays. Other applications of 

carbon nanotubes include computer chips, nanotools, and energy applications. For 
26

example, carbon nanotubes can be attached to the tips of atomic force microscopes 

(AFM). Research shows that this practice can enhance the resolution for AFM and 

prevent damage to the sample surface and probe. In addition, carbon nanotubes may be 

used as safe hydrogen storage for hydrogen fuel cells.

Fullerenes are spherical cages of carbon atoms. One of the most well known is a 

fullerene composed of 60 carbon atoms, known as C60 fullerene or “buckyball”. 

Fullerenes have applications in drug delivery and in medical imaging as a contrast agent 

for MRIs. In addition, fullerenes have enhanced antioxidant properties that make them 

useful for antiaging cosmetics and pharmaceuticals. Similar to carbon nanotubes, 

fullerenes have unique electrical properties that can be used for power supplies, data 

storage devices, and solar cells. Researchers have also considered using fullerenes for

hydrogen storage for hydrogen fuel cells.

Metal-based nanomaterials

Quantum dots are an example of metal-based nanomaterials. Quantum dots are 

closely packed semiconductor crystals composed of hundreds of thousands of atoms. 

These nanomaterials have unique optical properties that allow them to be used in 

applications such as biomedical imaging. Quantum dots adsorb light energy, which 

causes the energy levels of the electrons in the crystal structure to increase and release 

energy in the form of light. Unique to fluorescent light, quantum dots can emit light at 

different wavelengths depending on the size of the particle.

Materials for manufacturing quantum dots include semiconductors such as 

cadmium selenide, cadmium sulfide, cadmium telluride, lead sulfide, and lead telluride; 

metals such as gold, silver, nickel, and cobalt; and hybrid structures. The two primary 

manufacturing methods for quantum dots include a lithographic process that uses 

pressure to break down a thin semiconductor film into dots and a colloidal synthesis 

process. Quantum dots manufactured using the lithographic process have applications in 

telecommunications, logic circuits, and quantum computing. In the colloidal synthesis

process, materials are dissolved in a polymer solvent. Chemical reaction causes the 

quantum dots to precipitate from solution. Manufacturers can control the size of the 

quantum dots by varying the reaction time. Quantum dots manufactured using the 

colloidal synthesis process can be used for biological and optics applications, such as 

light emitting diodes (LEDs) and tunable lasers.

Dendrimers

Dendrimers are three-dimensional nano-sized polymers composed of an inner 

core and branched units. Manufacturers use two methods to produce dendrimers:
27

 Divergent approach: This approach begins with the inner core and builds 

outward.

 Convergent approach: This approach begins with the outer branches and 

assembles them around the core.

Several modifications can be made to the dendrimer structure to alter its properties for 

specific applications. Modifications include filling the inner voids, modifying the 

dendrimer core, and modifying the dendrimer surface. Surface modifications can alter 

the particle’s charge and solubility, its ability to react with or bind to target entities, and 

its ability to pass through cell boundaries. The primary application of dendrimers is in 

drug delivery. However, because of their spherical shape, viscosity characteristics, and 

catalytic properties, dendrimers also have applications in coatings, additives, and inks.

Composites

Composites combine nanomaterials (such as nano clays) with other nanoparticles 

or bulk-type materials. Nanocomposites can enhance mechanical, thermal, barrier, and 

flame retardant properties for a wide range of products including auto parts and 

packaging materials.

3.2 Overview of Environmental Transport

The transport of nanoparticles in the environment requires extensive additional 

research because the transport mechanisms can depend on the environmental media, 

various environmental parameters, and various nanoparticle parameters. Nanoparticle 

parameters to consider can include particle size and charge, chemical or elemental 

composition, and surface modifications. Environmental media parameters to consider 

can include pH, ionic strength, flow rate, composition, and presence of naturally 

occurring (such as dissolved organic carbon) as well as anthropogenic contaminants and 

their interaction with nanoparticles. The following subsections summarize information 

collected that describes the transport of nanoparticles in surface water, soil, and 

groundwater. Each subsection identifies additional questions that are not addressed by 

the information reviewed to date.

3.2.1 Surface Water Transport

The colloidal stability and extent of aggregation of nanoparticles in water will 

greatly impact the transport potential of the nanoparticles. The colloidal stability can be a 

function of the pH and ionic strength of the water and the particular nanoparticle of 

interest.

With water samples, the dissolved fraction of the water has typically been 

operationally defined using filters. These operational definitions would define any 

material that can pass through the filter (e.g., a 0.2-m filter (particles less than 200 nm) 
28

or a 0.45-m filter (particles less than 450 nm)) as the dissolved fraction, and material 

that does not pass through as the particulate fraction. However, the growing research on 

nanoparticles has shown that this notion will not always hold true3,6,7. The definition of a 

colloid as dispersed particles in the size range of 1 nm to 1 m

3,8

and suspended particles 

as particles greater than 1 m in size can help demonstrate the role of nanoparticles in 

aquatic chemistry 8. Observations of colloidal material in aquatic systems demonstrate 

how nanoparticles may exist as nondissolved particles in water, thereby completely 

changing their transport potential.

Chemical and physical alterations can be applied to nanomaterials to increase 

their water solubility. For example, derivatization of hydrophobic C60 fullerenes with 

hydrophilic functional groups increases the solubility of the C60 nanomaterials. 

Sonicating C60 in organic solvents and water can form stable aqueous suspensions of 

fullerene aggregates denoted as nC60. C60 also has applications in personal care products 

that contain organic ligands. These ligands can affect the aquatic transport of C60

9

.

Molecular solubility alone does not necessarily determine the water-based 

availability of a nanomaterial. Fortner et al.10 show that C60 may form negatively charged 

water-stable colloidal aggregates with diameters from 50 to 500 nm. These colloids can 

have concentrations up to 100 mg/L (100 ppm), which is approximately 11 orders of 

magnitude greater than the estimated molecular solubility of C60. Fortner et al.10 produce 

these aqueous colloidal suspensions by first producing a saturated solution of C60 in 

tetrahydrofuran (THF). The authors then add water to the THF solution under mixing 

and then evaporate the THF to form the aqueous C60 colloidal suspension. The authors 

note that adding an organic solvent, such as toluene, to the aqueous suspension results in 

low partitioning of nano-C60 from the water phase to the organic phase. However, the 

addition of an oxidant drives the nano-C60 to partition from the water phase to the organic 

phase. Therefore, the process of forming the aqueous suspension changes the properties 

of the C60. Fortner et al.10 note that the water-stable nano-C60 aggregates are crystalline 

in nature, and the aggregates’ particle sizes are functions of mixing rate, pH, and ionic 

strength. The authors observe that lower mixing rates increase the particle size. Higher 

pH values produce smaller particles, while lower pH values produce larger particles. 

Higher ionic-strength solutions give rise to larger particles, and ionic strengths similar to

that of seawater (~0.7 I) can cause particles to precipitate. On the other hand, lower ionic 

strengths, such as those similar to groundwater (~0.01 I), can lead to stable particles that 

can remain at concentrations of up to 100 ppm for at least 15 weeks. The researchers 

acknowledge that these fundamental laboratory experiments do not exactly predict what 

will occur if C60 is released into seawater or groundwater, as these experiments do not 

account for additional materials present in natural systems, such as proteins, humic acids, 

organic matter, and soils. This research does demonstrate, however, that important water 

properties can affect the extent of particle aggregation and lead to stable colloids or 

unstable precipitates, which can alter the transport of a nanomaterial.

Researchers at Arizona State University (ASU)11 are currently studying the fate of 

nanomaterials in wastewater treatment plants. The researchers have sampled at eight 

wastewater treatment plants and performed simulations of sequence batch reactors in a 
29

laboratory setting to determine the portion of nanomaterials that partition to biomass. 

Unpublished findings of this research show that the partitioning of nanomaterials from 

water to biosolids ranges from 50 to 90 percent. ASU expects to publish its findings in 

May 200811.

Additional Questions

How do materials present in the natural environment, such as proteins, humic acids, 

organic matter, charged clay particles, and soils, impact the transport of nanomaterials in 

groundwater and seawater?

3.2.2 Soil Transport

Understanding the transport of nanoparticles in soil requires knowledge of the 

nanoparticles’ partitioning between the solid (soil) and liquid (water) phases. In general, 

the tendency for substances to partition from water to soil or sediment depends upon the 

hydrophobic characteristics of the substance and the properties of the solid media to 

which it will adsorb. In addition, partitioning can occur via covalent and ionic bond 

formation as well as through electrostatic adsorption. Surfactants, which are commonly 

used with engineered nanoparticles to aid in dispersions, might also affect the 

partitioning; therefore, the presence of a surfactant should be noted in a study to help 

fully inform the reader. For example, natural organic carbon (NOC) can act as a natural 

surfactant and researchers have found some evidence that NOC coatings can help 

stabilize some aqueous nanomaterial dispersions.

Gimbert et al.7studied the partitioning of engineered ZnO nanoparticles in 

aqueous soil suspensions in the presence of sodium dodecyl sulfate (SDS) surfactant. 

The authors used SDS to ensure the ZnO nanoparticles dispersed in an aqueous solution 

as bare ZnO nanoparticles resisted dispersion in water. The authors first produced

aqueous dispersions of ZnO in the presence of SDS and then used this dispersion to spike 

soil samples to target a final concentration of 1.2 percent mass Zn in soil. This high 

concentration of Zn (as ZnO) in soil was required to simulate a significant environmental 

exposure. They then incubated the soil samples at 60 percent moisture for 0, 7, and 14 

days before analysis. The authors found that this ZnO dispersion quickly equilibrated

between the solid and liquid phases and remained relatively stable for the 14-day period. 

The authors found little dissolution or increase in solid-phase partitioning during the 14-

day period, indicating that the ZnO nanoparticles would persist in the environment. It 

should be noted that these results occurred in the presence of a surfactant.

Wang et al.12 studied the retention of nano-C60 aggregates in water-saturated 

porous media. The authors produce aqueous suspensions of C60 according to the methods 

discussed in Fortner at al.10 and summarized in Section 3.2.1 above: the authors begin 

with a saturated THF solution of C60, add water under mixing, and then remove the THF 

to form the aqueous suspensions of nano-C60. Wang et al.12 study the retention of the 

nano-C60 aggregates in columns packed with either glass beads or Ottawa sand. The 

authors conduct the retention experiments with aqueous C60 suspensions prepared in 
30

deionized water containing 1.0 mM CaCl2 buffered to a pH value of seven with 0.065 

mM NaHCO3 and also with C60 suspensions prepared in deionized water alone. The 

authors find that, when using C60 suspensions with CaCl2 and NaHCO3 (-potential of 

approximately -23.9 mV and ionic strength of approximately 3 mM), the glass beads 

retained from eight to 49 percent of the introduced mass of nano-C60, while the Ottawa 

sand retained up to 77 percent of the introduced mass of nano-C60. Additionally, the 

authors note that the retention of C60 was irreversible as the introduction of nano-C60-free 

deionized water did not elute the retained mass from the column. The Ottawa sand 

column had uniform nano-C60 retention, while the glass bead column had a nano-C60

retention that decreased with distance from the column inlet. This trend suggests that the 

nano-C60 retention in the Ottawa sand approached a limiting capacity. The authors note 

that using aqueous C60 suspensions prepared in deionized water alone (z-potential of 

approximately -64 mV and ionic strength of zero mM) showed no retention in either 

column packing. This observation demonstrates the importance of electrostatic 

interactions on the transport and retention of nano-C60 aggregates in both glass beads and 

Ottawa sand.

Additional Questions

Question 1:

How readily do nanomaterials partition from liquid to solid phases in the absence of a 

surfactant or added surface functionality?

Question 2:

How do soil properties affect transport of nanoparticles?

3.2.3 Groundwater Transport

The transport potential of nanoparticles in subsurface environments can depend 

upon several parameters, such as particle size, solution pH, ionic strength, soil 

composition, and groundwater flow velocity13. Groundwater typically has a higher ionic 

strength than rainfall but may have lower ionic strength than marine and many freshwater 

bodies. Higher ionic strengths can reduce the electrostatic repulsion among nanoparticles 

and increase aggregation. However, research has shown that surface modifications of 

nanoparticles can greatly alter their transport potential in environmental media. For 

example, many researchers are designing supports for zero-valent iron nanoparticles for 

the purpose of groundwater remediation. These supports create negatively charged and 

hydrophilic surfaces to aid electrostatic repulsion among nanoparticles and aquifer 

materials and reduce nanoparticle aggregation and aquifer material filtration13.

Saleh et al.14 design a zero-valent iron nanoparticle core with a protective, 

nonreactive magnetite shell (Fe3O4) to help remediate trichloroethylene from 

groundwater. They find that these nanoparticles rapidly flocculate and settle from 

solution in water. The authors show that modifying the nanoparticle with a novel triblock 

copolymer increases the electrophoretic mobility and suspension stability of the 

nanoparticle. The hydrophilic block of the triblock copolymer promotes electrostatic 
31

repulsion from negatively charged surfaces (such as Fe and Mn oxides and natural 

organic matter) that naturally occur in near-neutral pH subsurfaces. Additionally, the 

triblock copolymer drives the adsorption of the nanoparticle to the nonaqueous phase 

liquid-water (NAPL-water) interface. This example shows how surface modifications of 

nanoparticles can greatly alter their transport potential in environmental media.

Additional Questions

Question 1:

How readily do bare nanomaterials partition from liquid to solid phases in the absence of 

a surfactant or added surface functionality?

Question 2:

How effective are aquifer materials at filtering bare nanomaterials in the absence of an 

added surface functionality?

4.0 SAMPLING TECHNIQUES

This section describes five research projects that involved collecting 

environmental samples for analysis of nanomaterials, including:

 One water sampling project;

 Three sediment sampling projects; and 

 One soil sampling project.

Based on the information obtained, sampling techniques for nanomaterials in 

environmental media currently do not differ from established techniques for sampling 

environmental media. 

Some issues regarding sampling remain whether one is sampling for 

nanomaterials or larger-sized materials. Sample representation is always a concern when 

sampling environmental media. One research scientist interviewed for this report stated 

that one should approach the issue of sample representation by visually inspecting a 

location for heterogeneity within the media. One should scale down the inspection from 

large to small spatial scales to identify areas of heterogeneity where sampling may be 

important15. 

Another important concern with sampling is the risk of contamination. Although 

contamination is a concern for all types of sampling, nanomaterials may be more 

sensitive to contamination as they are likely to be present in very small quantities within 

the environmental media15. 

One should also consider sample preservation and holding time as research shows 

that the structure and reactivity of nanomaterials can be time-dependant and change when 

exposed to different environments. Researchers of the Pacific Northwest National 
32

Laboratory observe that the reactivity of nanomaterials in aqueous solutions changes 

dramatically over the course of one day16. Baer et al.17 describe two case studies that 

demonstrate the effects of time and environment on nanomaterials. In one study, the 

authors demonstrate the influence of particle environments on the nanoparticle chemistry 

by measuring differences in UV-visible transmission results for ceria nanoparticles before 

and after adding an oxidizing agent to the aqueous solution. In the second study, the 

authors demonstrate the time-dependent properties of iron nanoparticles by examining 

iron nanoparticles using transmission electron microscopy (TEM) before and after 

exposing the nanoparticles to deionized water for 24 hours. After 24 hours of exposure to 

deionized water, the oxide shell of the nanoparticle had thickened and was more porous

and less ordered.17

Researchers acknowledge that a need exists for nanomaterial-specific sampling 

techniques. However, to date, developing sampling techniques has not been a high 

priority for nanomaterials research projects. Current priorities include determining how 

nanomaterials behave in the environment, identifying constituents of environmental 

concern, and developing analytical techniques11.

4.1 Sampling Techniques Suited for Surface Waters

One project was identified that involved sampling wastewater for nanomaterials. 

As described in Section 3.2.1, researchers at ASU and the United States Geologic Survey 

(USGS) collected samples at eight wastewater treatment facilities in August 2007. 

Sampling points included the final effluent from treatment and biosolids. The researchers 

analyzed the samples for fullerenes (C60) and micro-sized titanium dioxide (TiO2). The 

researchers hope that the approaches used for detecting micro-sized titanium dioxide can

later be developed for nano-sizes. For analysis of fullerenes, aqueous samples underwent 

a solid-phase extraction, were concentrated into methanol, and were analyzed using 

liquid chromatography coupled with mass spectrometry (LC-MS). The biosolid samples 

were extracted into toluene, concentrated, and analyzed using LC-MS. The detection 

limit for fullerenes analysis was 500 ng/L. The extraction methods for aqueous and 

biosolids samples were validated using matrix spikes. For analysis of titanium dioxide, 

researchers used digression methods to show that TiO2 was present and used SEM to 

identify the microparticles11.

The researchers noted that the samplers in this work did not use any special 

protocols that were specific for nanomaterials. Developing sampling techniques is still in 

the early stages and was not the main focus of the project. Researchers are currently 

evaluating the need for certain protocols, such as “clean hands” sampling, and future 

sampling activities may implement these protocols11.

4.2 Sampling Techniques Suited for Sediments

Three projects were identified that involved sampling sediments for 

nanomaterials. These projects did not use sampling techniques or protocols that were 
33

developed specifically for nanomaterials. The following discussion summarizes the 

sample collection and preparation techniques described for the three sediment sampling 

projects.

Hochella et al.18 demonstrate sampling riverbanks and riverbeds for further

analysis of naturally occurring nanomaterials. The authors obtain samples by digging 

into the side of a riverbank and collecting riverbed mud from beneath a layer of sediment 

under the shallow stream edge.

To prepare samples for TEM analysis, the authors perform the following steps. 

They first air dry their sediment samples before storage. They then lightly grind the dry 

samples to make them more friable, which reduces the larger grain sizes and disperses the 

sample. The authors then use multiple stages of dry sieves at a cut-off size of 65 m and 

then wet sieve in ethanol at 25 m. They perform a final light grinding before preparing 

the TEM ultramicrotomed thin sections.

Hochella et al.19 sample bed sediment from the entrance of a mine for further 

analysis of natural nanoscale particles. The authors obtain the bed sediment from a small 

water channel and a small, shallow pond near the entrances of two mines. The authors 

sieve the wet sediment samples with 63-m sieves using ambient water to prevent 

chemical changes from occurring. The authors note that sieving in this case helps to 

remove detrital material and allows for a uniform comparison between studies. The 

authors bottle and ice pack the samples for transport to the laboratory, where they 

centrifuge and dry the sediment samples. They gently mash the sediment samples to 

separate clots and note the importance of avoiding high-temperature drying to prevent 

mineralogical changes.

Heymann et al.20 obtain samples of geologic materials from the CretaceousTertiary (K-T) boundary in New Zealand for further analysis of fullerenes. The authors 

crush and powder the samples and demineralize a portion of their samples using HCl and 

HF treatments. They then slurry the prepared solid samples with toluene and sonicate for 

several hours to extract fullerenes from the solid materials. The authors recover the 

toluene extraction for analysis of fullerenes.

4.3 Sampling Techniques Suited for Soil

One project was identified that involves the sampling soil for nanomaterials. 

Gimbert et al.7obtain topsoil samples, which they air dry and sieve to 2 mm for 

performing nanomaterial transport studies. The authors did not describe any sampling 

techniques that were applied specifically for nanomaterials.

Additional Questions

Information found to date has been limited in this area. Additional research should be 

conducted in this area.
34

4.4 Sampling Techniques Suited for Groundwater

Information found to date has been limited in this area. Additional research should be 

conducted in this area.

4.5 Comparison of Sampling Techniques

Information regarding techniques for sampling nanomaterials found to date has 

been limited. The current literature search has not revealed well-defined sampling 

techniques specific to nanomaterials with outlined advantages and disadvantages. 

Additional research should be conducted in this area.

5.0 ANALYTICAL TECHNIQUES

This section identifies analytical techniques suited for characterizing naturally 

occurring nanomaterials and anthropogenic nanomaterials in natural media. Wigginton et 

al.21 identify the following characterization parameters applicable to characterizing 

nanomaterials in natural media:

 Size distribution;

 Surface area;

 Direct visualization;

 Phase and structure; and

 Chemical composition.

No single analytical technique provides information to address all five characterization 

parameters. Therefore, it is necessary to use combinations of analytical techniques to 

characterize nanomaterials. Additionally, nanomaterials in natural media may require 

size-fractionation techniques to separate the nanoparticles from larger particles. This 

section presents analytical techniques suited for fractionating and characterizing the five 

parameters of nanomaterials in natural media.

The ASTM Committee E-42 on Surface Analysis guides users of surface 

analytical instruments to produce more reliable results. The scope of the committee is to 

review and coordinate development of standards for all methods of surface analysis by 

photon, electron, and ion emissions or reflection methods, such as x-ray spectroscopy and 

secondary ion mass spectrometry (SIMS). A member of the ASTM Committee E-42 on 

Surface Analysis emphasizes the importance of proper sample handling and use of 

analytical instruments for analyzing nanomaterials. Because analytical instrumentation 

for characterizing nanomaterials are highly sensitive, a greater potential for error exists16.

Burleson et al.1provide a technical review and description of many of the 

analytical techniques listed in Section 5.0. Section 5.7 includes general descriptions and 
35

comparisons of many of the analytical techniques listed below. Below are brief 

descriptions of the major analytical techniques presented in this section.

Transmission Electron Microscopy (TEM)

TEM utilizes an electron beam to probe a sample and images the electrons that 

pass through the sample. TEM can provide a high-resolution direct image of the 

nanoparticles, typically greater than 0.1 nm of spatial resolution. Many TEMs can be 

operated in scanning transmission electron microscopy (STEM) mode1.

Scanning Electron Microscopy (SEM)

Like TEM, SEM also utilizes an electron beam to probe a sample. However, 

SEM primarily measures the secondary electrons (SE) emitted from the sample to 

produce topographical contrast maps. SEM does not provide the same high resolution as 

TEM: its resolution is limited to approximately 1 nm to 1 m

1

.

Energy-Dispersive Spectroscopy (EDS)

X-ray spectroscopy, commonly referred to as energy-dispersive spectroscopy 

(EDS), X-ray energy-dispersive spectroscopy (XEDS), or energy-dispersive X-ray 

spectroscopy (EDX), measures secondary signals from characteristic X-rays produced 

during TEM, STEM, or SEM imaging for detecting and quantifying elements present in 

the sample1.

Electron Energy Loss Spectroscopy (EELS)

EELS measures primary signals from scattered electrons produced during TEM or 

STEM imaging for detecting and quantifying elements present in the sample1.

Atomic Force Microscopy (AFM)

AFM, a type of scanning probe microscopy (SPM), measures the forces between a 

sharp tip and a sample to determine topographic images at a spatial resolution of 

approximately 0.1 nm and provides electrical and mechanical properties of the sample1.

Scanning Tunneling Microscopy (STM)

STM, a type of scanning probe microscopy (SPM), measures a tunneling current 

between a conductive tip and a conductive or semiconductive sample to determine 

topographic images at a spatial resolution of approximately 0.1 nm and is sensitive to the 

chemical identity of surface atoms and molecules1.
36

X-ray Diffraction (XRD)

XRD measures the diffraction of X-ray beams to identify crystalline phases. 

XRD can measure structural properties of crystalline phases and probe atomic 

arrangements of amorphous phases1.

Dynamic Light Scattering (DLS)

DLS shines a light source on a suspension of particles and uses a photoelectric 

detector to measure the intensity of the scattered light. The constant Brownian motion of 

the particles causes time-dependant fluctuations, which are directly related to the 

diffusion coefficients of the particles. The diffusion coefficients allow the estimation of 

the hydrodynamic radius of the particles1.

Laser-Induced Breakdown Detection (LIBD)

LIBD uses an intense, pulsed laser beam to generate plasmas on nanoparticles. 

The generated plasmas emit light that is detected by the tool. The number of light 

emissions per number of laser pulses provides information on the concentration and sizes 

of particles in the sample22.

X-ray Absorption Spectroscopy (XAS)

XAS irradiates a sample with X-rays and measures the amount of X-ray energy 

the sample absorbs. X-ray energies that meet the electron-ejection threshold are absorbed 

and eject an electron. The ejected electrons are backscattered and produce interferences

with the X-rays, which provide information on the average identity, number, and 

arrangement of the nearest neighboring atoms to the absorbing atom. This information 

allows researchers to identify the structure of the atoms in the sample1.

5.1 Analytical Techniques for Size Fractionation

Several fractionation techniques have the potential to separate particle samples 

into various nanoparticle fractions: 

 Centrifugation – Centrifugation is a mechanical method that separates 

particles in a solution based on weight by applying a centrifugal force. 

Heavier particles sink outwardly while lighter particles rise towards the 

center of the vortex.

 Ultrafiltration – Ultrafiltration is a method that separates particles in 

solution based on molecular weight using a membrane barrier. Lower

molecular weight particles permeate through the membrane while higher 

molecular weight particles remain in the retentate. The separation can be 

achieved by either direct-flow (perpendicular to the membrane) 

ultrafiltration or tangential-flow (cross-flow) ultrafiltration (TFF). The 
37

benefit of TFF is the solution flows parallel to the membrane, which 

prevents buildup of particles at the membrane surface.

 Field-flow fractionation (FFF) – FFF separates particles by applying a 

perpendicular gradient or cross flow to a sample solution that is flowing 

through a narrow channel. The perpendicular gradient drives particles of 

different sizes toward the channel wall at different velocities.

 Capillary electrophoresis (CE) – CE separates particles based on their size 

to charge ratios. In this method, a buffer solution carries particles through 

a capillary typically from the anode to the cathode. When an electric 

charge is applied to the sample solution, the positively charged particles 

are attracted to the cathode while negatively charged particles are attracted 

to the anode. In addition to the particle charge, the particle’s size and 

shape determine the frictional forces that affect the particle’s transport 

through the buffer solution23.

 Size exclusion chromatography (SEC) – SEC separates particles based on 

size using the principle that particles of different sizes elute through a 

stationary phase at different velocities. A typical apparatus consists of a 

column packed with porous polymer beads. As the sample solution passes 

through the column, smaller particles will enter the pores. Therefore 

larger particles will elute faster.

These methods can apply for both aquatic colloids3and particles extracted from soil and 

sediment samples7,19. All methods require nanoparticles to be in solution. Therefore,

samples must be extracted into a solvent prior to analysis.

Aquatic Colloids

A typical and widely used method for fractionating colloids is TFF3,24. Benoit 

and Rozan25 use TFF to fractionate colloidal particles from river water samples using 

hollow-fiber filters with a 3,000 molecular weight cutoff. They note that the choice of a 

3,000 molecular weight cutoff is arbitrary and, hence, their “colloidal” and “truly 

dissolved” materials are operationally defined. Lyven et al.24 note that natural aquatic 

colloids may exist in a dynamic state with respect to dissolved phase and particulate 

phase partitioning. Therefore, it is imperative that the fractionation technique involve 

mild and rapid pretreatment. They, therefore, recommend FFF as an appropriate 

fractionation technique for aquatic colloids. They recommend flow FFF (FlFFF) for 

smaller colloidal particles in the size range of 1 to 50 nm. FlFFF is a type of FFF that 

utilizes a cross flow to provide the perpendicular gradient used in the separation24. 

Researchers commonly use FlFFF with on-line detectors to measure particle 

concentrations. These techniques are typically spectral methods such as UV absorbance 

detectors24,26,27, fluorescence detectors (FLD)26, and multi-angle laser light scattering 

(MALLS)26.
38

FlFFF also allows the ease of coupling an on-line detector for chemical analysis, 

such as ICP-MS24,26,27. Stolpe et al.27 note that FlFFF and ICP-MS match well for 

coupling concerning operating flow rates and liquid phases. Additionally, band 

broadening from ICP-MS is not a significant issue as FlFFF peaks are already 

comparatively broad. Stolpe et al.27 also note that preconcentrating the sample may be 

necessary due to low elemental concentrations in natural waters and due to the large 

dilution of the sample during the FlFFF run. They note that preconcentration may 

introduce artifacts and use an on-channel preconcentration technique for their FlFFF 

runs27. Both TFF and FFF necessitate pretreatment to remove larger particles to prevent 

steric interferences and filter overloading24,25.

Several different authors filter their samples through a 0.45-m filter before 

fractionation24-27, although settling is also an option24.

Lead et al.8demonstrate the use of flow-through centrifugation of colloidal and 

suspended particulates from river water samples. They achieve three nominal size 

fractions of greater than 1.0 m, 0.5 to 1.0 m, and 0.05 to 0.5 m. Their nominal size 

fractions are based on Stoke’s law and assume a particle density of 2.5 g/cm3. They note 

that these fractions represent lower limits due to organic matter entrained in the fractions 

and from applying Stoke’s law to generally nonspherical particles.

Lienemann et al.28 describe a method for using ultracentrifugation to deposit 

aquatic colloidal particles directly onto TEM grids for further analysis.

Soils and Sediments

Hochella et al.19 demonstrate the use of centrifugation to remove interstitial water 

from wet sediment samples. After centrifugation, they pour off the supernatant liquid 

leaving the solid sediment behind.

Gimbert et al.7demonstrate a method of fractionating the sub-1.0-m fraction of 

soil suspensions spiked with engineered ZnO nanoparticles using FlFFF. They couple

FlFFF with a UV absorbance detector to characterize the particles and obtain 

fractograms. They find FlFFF to be successful in measuring the particle size distributions 

of the 180-nm nominally sized ZnO nanoparticles.

Engineered Nanoparticle Systems

Additional techniques used to separate engineered nanoparticles within an 

engineered system may prove applicable to separating nanoparticles within 

environmental media.

Hwang et al.23 use capillary electrophoresis (CE) to separate mixtures of gold and 

polystyrene nanoparticles of varying sizes. The authors first demonstrate the application 

of CE in separating gold nanoparticles of varying sizes and then in separating polystyrene 

nanoparticles of varying sizes. Lastly, the authors demonstrate the application of CE in 
39

separating a mixture of gold and polystyrene nanoparticles of equal size. The authors use 

a UV-visible light absorbance detector to detect the separated particles and plot 

electropherograms. The electropherograms show the successful separation of the 

nanoparticles, and the authors note the potential application of CE to mixtures of other 

nanoparticles.

Novak et al.29 demonstrate using centrifugation and size exclusion 

chromatography to purify molecularly bridged gold nanoparticle arrays. The authors 

wish to separate dimers and trimers of the molecularly-bridged gold nanoparticles.

The authors note that centrifugation has the following drawbacks: 1) the 

nanoparticles may aggregate upon concentration, and 2) the nanoparticles may become 

unstable if combined with high ionic strength or nonaqueous solvents. The authors 

overcome aggregation by replacing one of the bridging ligands with another that would 

not cause particle aggregation. The authors perform stepwise g-force density 

centrifugation and collect highly viscous slurries of their modified molecularly-bridged 

gold nanoparticles29.

Novak et al.29 note that SEC has similar drawbacks as centrifugation. 

Additionally, SEC may also lead to the irreversible adsorption of the analytes to the 

stationary phase. The authors overcome this additional drawback by using an aqueous 

mobile phase containing sodium dodecyl sulfate (SDS) buffer. The authors couple SEC 

with a UV-visible light absorbance detector to detect the nanoparticles as a function of 

their column retention time and develop chromatograms. The authors note a high 

resolution of separation when separating pure gold nanoparticles of varying sizes but 

lower resolutions of separation when separating the dimer and trimer molecularly-bridged 

gold nanoparticles. The authors conclude that centrifugation is simpler and less 

expensive than SEC, but SEC has the potential for postcolumn analysis of optical and 

electrochemical properties of the analyzed nanoparticles.

5.2 Analytical Techniques for Size Distribution

Several analytical techniques are suitable for measuring size distribution of 

nanoparticles. The microscopy methods discussed in this section either use point count 

techniques that measure the sizes of individual particles or bulk analyses that measure the 

average and range of particle sizes in a sample, and include the following:

 Transmission Electron Microscopy (TEM) – TEM measures the size of 

individual particles by producing a high resolution (0.1 nm) twodimensional image of the nanomaterial.

 Scanning Electron Microscopy (SEM) – SEM measures the size of 

individual particles by producing a topographical three-dimension image 

of the nanomaterial at resolutions ranging from 1 nm to 1 m.
40

 Scanning Probe Microscopy (SPM) – SPM techniques determine the size 

of individual particles and include atomic force microscopy (AFM), which 

measures forces between a sharp tip and a sample to determine the 

topography of the sample, and scanning tunneling microscopy (STM), 

which measures a tunneling current between a conductive tip and a 

conductive or semiconductive sample to determine the topography of the 

sample.

 Dynamic Light Scattering (DLS) – DLS is a bulk analysis that measures 

the average particle size of dispersions or suspensions.

 Laser-Induced Breakdown Detection (LIBD) – LIBD is a bulk analysis 

that measures the average particle size and concentration of particles in the 

sample.

 Small- and Wide-Angle X-ray Scattering (SAXS/WAXS) – SAXS/WAXS 

is a bulk analysis that determines particle sizes and populations. 

TEM

Many works cited in this report use TEM or a variation of it to obtain size 

distributions of nanoparticles along with shape and dimensional information10,18,19,30-33. 

Variations of TEM can include high-resolution (HR) TEM32,33 and cryogenic (cryo) 

TEM10.

Madden and Hochella30 and Madden et al.31 use TEM images, along with AFM 

images, to determine diameters and heights of synthesized hematite nanoparticles. The 

authors assign the nanoparticles by diameter into histogram bins with each bin assigned 

an average height. This method obtains a size distribution suitable for calculating surface 

area. See Section 5.3 for additional discussion.

Hochella et al.19 use TEM-EDS and EFTEM-EELS to characterize sediment 

samples. The authors are able to characterize 85-90 percent by volume of the TEM 

sections as containing ferrihydrite particles between 10 and 100 nm in diameter. The 

authors note that EFTEM-EELS obtains spatially resolved elemental distributions better 

than TEM-EDS.

SEM

SEM images may also be used to measure nanoparticle size distributions7,8,18,19. 

Lead et al.8demonstrate the use of SEM to verify the discrete size fractionation of aquatic 

nanoparticles from centrifugation. The authors note that most particles sampled are less 

than 1 m in size with some particles as large as 10 m or 100 m in at least one 

dimension.
41

Hochella et al.19 use SEM in conjunction with TEM to gain an additional 

perspective on the sediment samples. The authors note that SEM does not capture the 

complex nature of the particles as well as TEM.

SPM

Madden and Hochella30 and Madden et al.31 use AFM images, along with TEM 

images, to determine diameters and heights of synthesized hematite nanoparticles. The 

authors assign the nanoparticles by diameter into histogram bins with each bin assigned 

an average height. This method obtains a size distribution suitable for calculating surface 

area. See Section 5.3 for additional discussion.

Eggleston et al.34 use STM images of hematite nanoparticles in both air and 

aqueous media to obtain dimensional measurements. They additionally use the resonant 

tunneling model (RTM) to help interpret the STM images. They find RTM to 

qualitatively agree with many features of the STM images.

DLS

Waychunas et al.32, Gilbert et al.33, Fortner et al.10, and Zhang et al.35 demonstrate 

the use of dynamic light scattering (DLS) to measure average size distributions of 

nanoparticle dispersions and suspensions of iron oxyhydroxide32,33, C60 fullerene10, and 

CdTe quantum dots35. Further, Gilbert et al.33 use DLS to measure average size 

distributions as a function of pH, and Waychunas et al.32 use DLS to measure average

size distributions as function of suspension aging. Both of these works use DLS to help

characterize nanoparticle aggregation and understand the factors that can lead to 

aggregation.

LIBD

Bundschuh et al.22 demonstrate the use of LIBD to quantify colloids in the 

effluents of various treatment stages in a drinking water treatment plant. LIBD is a 

sensitive analytical tool capable of quantifying low concentrations (< 1 g/L) 

nanoparticles smaller than 100nm. The method uses an intense, pulsed laser beam to 

generate plasmas on colloidal particles. The generation of plasmas is called a 

“breakdown event.” The plasmas generated by the breakdown event emit light or 

generate shock waves that are detected by the tool. In general, solids require less energy 

to break down than liquids or gases. LIBD is based on the difference in breakdown 

thresholds of liquid and solid matter. The laser beam energy is set to exceed the solid 

breakdown threshold but not the liquid threshold. The number of breakdown events per 

number of laser pulses depends on the concentration and size of the particle.

A charged coupled device (CCD) camera detects the light emissions of single 

plasmas to determine the particle size. Detection of optical spatially resolved plasma 

light emissions results in a spatial distribution of breakdown events within the focal 

volume. Spatial distribution depends on the particle size. The authors compare the 
42

distribution to the distribution width of reference particles to determine the mean particle 

diameter. They then calculate the mean particle diameter and breakdown probability22.

SAXS/WAXS

Waychunas et al.32 demonstrate the use of small- and wide-angle X-ray scattering 

(SAXS/WAXS) to determine the size distribution and population of goethite 

nanoparticles as a function of time. The authors make in situ measurements and note that 

these particular nanoparticles aggregate in solution as they age. The authors additionally 

use SAXS/WAXS to make ex situ measurements on samples they measured using other 

techniques. The authors present graphical processed SAXS results that demonstrate the 

aging particle size distributions over time.

Gilbert et al.33 use SAXS to study the colloidal stability of iron oxyhydroxide 

nanoparticles as a function of pH and ionic strength over time. The authors make in situ

measurements and note slight nanoparticle aggregation after 10 weeks but no 

macroscopic aggregation even after four months at pH values less than 6.6. The authors 

note a greater extent of aggregation at pH values greater than 6.6.

5.3 Analytical Techniques for Surface Area

The average surface area of nanoparticles is a useful characterization parameter. 

Average surface area may be calculated in conjunction with size distribution or may be 

calculated directly using the Brunauer-Emmett-Teller method (BET). The BET method 

utilizes a gas, typically nitrogen, to adsorb to the accessible surface area of a sample. The 

adsorbed gas forms a monolayer of molecules or atoms along the accessible surface area. 

One may then measure the volume of the adsorbed monolayer of gas and, with 

knowledge of the size of the gas molecules or atoms and the mass of the sample, 

calculate the surface area per mass of the sample1.

Madden and Hochella30 and Madden et al.31 discuss methods for calculating the 

surface area of synthesized hematite nanoparticles using measurements from TEM and 

AFM and the particles’ nanocrystalline geometries. The authors use two-dimensional 

TEM images to determine two-dimensional length and width measurements and use 

AFM to determine height measurements. Madden and Hochella30 note that, in this 

particular work, particle diameters measured from AFM are larger than diameters 

measured from TEM due to tip-sample interaction, although heights measured from AFM 

are accurate. Therefore, they use TEM-measured diameters and AFM-measured heights. 

The particles are arranged by diameter into histogram bins with each bin assigned an 

average AFM-measured height. Knowing the nanocrystalline geometry of the particles, 

the authors then calculate the average surface area of the individual particles for each bin. 

The authors calculate the total surface area for all particles by converting the average 

surface area per particle to surface area per mass for each bin and calculate the weighted 

sum of all surface areas.
43

It is important to note that the above method for calculating surface area may not 

be applicable to nanomaterials that do not have a regular or pseudo-regular geometry or 

have significant porosity.

Madden and Hochella30, Madden et al.31, Waychunas et al.32, and Gilbert et al.33

use BET to directly measure the surface area of nanoparticles. Madden and Hochella30

also note that surface areas for ultrafine particles, less than 15 nm in diameter, are

typically lower from BET measurements than those calculated from geometric models as 

described above.

5.4 Analytical Techniques for Direct Visualization

Direct visualization can produce a direct visual representation or image of 

individual nanoparticles from a small sample. Visualization allows one to examine 

geometry and shape characteristics of the observed nanoparticles. Techniques for direct 

visualization include:

 Electron microscopy techniques, such as transmission electron microscopy 

(TEM) and scanning electron microscopy (SEM); and,

 Scanning probe microscopy (SPM), such as atomic force microscopy 

(AFM) and scanning tunneling microscopy (STM).

Electron Microscopy

A widely used electron microscopy technique is TEM, which is an indispensable 

tool and is often a staple for nanomaterial researchers1,36.

A number of cited papers in this report use TEM to obtain images of individual 

nanoparticles10,18,19,28,30,31. Other variations of TEM include high-resolution (HR) 

TEM1,32,33 and scanning transmission electron microscopy (STEM)1,26. Coupling TEM 

with EELS can produce energy-filtered (EF) images with spatial resolutions on the order 

of 0.5 nm1. Hochella et al.19 find better spatially resolved information about elemental 

distributions from EFTEM-EELS images. Fortner et al.10 even use cryogenic (cryo) 

TEM, which uses a cryogenic sample holder to allow the imaging of flash-frozen 

samples. See Section 5.7 for a discussion and comparison of these different variations of 

TEM.

Additionally, HRTEM images may show morphological characteristics of 

nanoparticles. Waychunas et al.32 use HRTEM images to determine morphological 

changes of goethite nanoparticles in suspension from initial oblong shapes to rod-like 

shapes caused by oriented aggregation during aging. The images show rod-shaped 

particles with dimensions of approximately 10 x 100 nm after 33 days of aging.

A number of cited papers in this report additionally use SEM to obtain images of 

individual nanoparticles7,8,18,19. Lead et al.8are even able to visually identify the 

presence of bacteria in their SEM images. Hochella et al.18 additionally capture 
44

backscattered electron (BSE) images to locate grains of sediment samples containing 

heavy metals. Hochella et al.19 use SEM in conjunction with TEM to gain an additional 

perspective on the sediment samples. The authors note that SEM does not capture the 

complex nature of the particles as well as TEM. See Section 5.7 for a discussion and 

comparison of these different variations of SEM.

Scanning Probe Microscopy

A number of cited papers in this report use AFM to image individual 

nanoparticles30,31,34. Madden and Hochella30 and Madden et al.31 mainly use AFM to 

obtain heights of the sampled nanoparticles.

Additionally, Eggleston et al.34 use STM to image hematite nanoparticles in both 

air and aqueous media. They additionally use the resonant tunneling model (RTM) to 

help interpret the STM images. They find RTM to qualitatively agree with many features 

of the STM images.

5.5 Analytical Techniques for Phase and Structure

The structure of nanoparticles may be crystalline or amorphous. Knowledge of 

the structure of naturally occurring crystalline nanoparticles along with chemical 

information may determine the identity of the mineral phase of the nanoparticle. 

Techniques that provide information on nanoparticle structure include electron 

diffraction, X-ray absorption spectroscopy (XAS), X-ray diffraction (XRD), and Raman 

spectroscopy.

Electron Diffraction

When using TEM, one may measure the diffraction of electrons passing through 

the sample to obtain the crystal structure of crystalline materials. Hence, electron 

diffraction can differentiate between amorphous and crystalline materials. Additionally, 

information from electron diffraction and TEM images can determine size and size 

distribution of crystalline nanoparticles. Variations of electron diffraction include 

selected-area electron diffraction (SAED) and convergent beam electron diffraction 

(CBED)1.

Madden and Hochella30 use electron diffraction to confirm the identity of their 

synthesized hematite nanoparticles as judged by the mineral’s structure.

Fortner et al.10 use SAED to confirm the crystalline structure of C60 nanoparticles. 

The SAED diffraction patterns from a single particle show a simple hexagonal unit cell 

structure.
45

X-ray Absorption Spectroscopy

XAS irradiates a sample with X-rays and measures the amount of X-ray energy 

the sample absorbs. X-ray energies that meet the electron-ejection threshold are absorbed 

and eject an electron. The ejected electrons are backscattered and produce interferences 

with the X-rays, which provide information on the average identity, number, and 

arrangement of the nearest neighboring atoms to the absorbing atom. From this 

information, the structure of the atoms in the sample may be obtained1.

Waychunas et al.32 are able to use Extended X-ray Absorption Fine Structure 

(EXAFS) measurements to determine that their goethite nanoparticles increase in 

structural ordering during the aging process of their studies.

X-ray Diffraction

XRD measures the diffraction of X-ray beams to identify crystalline phases. 

When compared to a database of known diffraction patterns, it can quantitatively identify 

mineral composition. For example, Hochella et al.18 use XRD with the computer 

program RockJock to quantitatively determine the mineralogical composition of 

riverbank and riverbed samples. RockJock compares the intensities of the diffraction 

patterns to that of an internal standard: ZnO.

Hochella et al.19 use XRD to determine the presence of mineral phases, such as 

quartz and jarosite, in their acid mine drainage samples.

Madden et al.31 use XRD to confirm the structural characteristics of their 

synthesized nanoparticles are consistent with hematite.

Waychunas et al.32 use XRD to confirm their synthesized iron oxyhydroxide 

nanoparticles are initially goethite and remain as such throughout the aging process of 

their studies.

Gilbert et al.33 use XRD to determine that the crystal phase of their synthesized 

iron oxyhydroxide nanoparticles is consistent with a nanoscale and highly disordered 

goethite phase.

Raman Spectroscopy

Tarassov et al.37 use micro-Raman spectroscopy to study the atomic arrangement 

of hematite and goethite microparticles sampled from the oxidation zone of the 

Grantcharitza scheelite deposit in Bulgaria. The authors compare the Raman spectra of 

their samples against spectra from reference particles. This analysis enables the authors 

to determine that the local atomic structure of the sampled hematite particles deviate from 

reference hematite. The Raman spectra reveal that the sampled hematite has a disordered 

structure.
46

5.6 Analytical Techniques for Chemical Analysis

Chemical analytical techniques either are suitable for a bulk analysis or capable of 

obtaining spatial resolutions. Bulk chemical analytical techniques do not directly identify 

the presence of nanoparticles, nor do they provide appropriate information to characterize 

them. They do, however, directly identify and possibly quantify the presence of atoms, 

functional groups, or molecules. These chemical analytical techniques allow one to 

identify the atomic or molecular components of nanoparticles. Chemical analytical 

techniques capable of obtaining spatial resolutions can identify and spatially map 

elements. These chemical analytical techniques allow for greater surface characterization 

of the sample. This section presents information obtained on sample extraction 

techniques, bulk chemical analyses, and chemical analyses with spatial resolution.

An important step in bulk chemical analysis is sample extraction and preparation. 

Sample extraction techniques directly impact the method detection limit. Chen et al.9

evaluate three techniques for extracting nC60 fullerene from aqueous samples for 

HPLC/MS analysis:

 Technique 1 – Evaporation of aqueous phase followed by partitioning of 

dry fullerenes into toluene

 Technique 2 – Liquid-liquid extraction with addition of salts; and

 Technique 3 – Solid phase extraction (SPE) of aqueous sample using 

preconditioned SPE cartridges followed by toluene extraction to remove 

fullerenes from the cartridges. 

The addition of salts for Technique 2 improved recovery of C60 compared to Technique 

1. However, the authors found Technique 3 to be the most effective of the three methods 

in C60 extraction. The SPE method can be automated and can handle larger volumes of 

sample than Techniques 1 and 2, resulting in less time required for analysis, lower 

detection limits, and reduced potential for error. The authors conclude that SPE is 

applicable for extracting nanoparticles that exist in aqueous environments as discrete or

aggregated forms, and can also be used for analysis of biological or soil samples. The 

sample extraction techniques directly impacted the method detection limit for the analysis

as shown in Table 5-1.

Table 5-1. Determination of Method Detection Limit for the Measurement of Stable 

Aqueous C60 Aggregates in Ultrapure Water9

Technique MDL (g/L)

Technique 1 – Evaporation 2.78

Technique 2 – Liquid-liquid extraction 3.33

Technique 3 – Solid phase extraction 0.30
47

Bulk Chemical Analysis

General analytical techniques suitable for bulk chemical analysis include atomic 

absorption spectrometry (AAS), atomic emission spectrometry (AES), and mass 

spectrometry (MS). These methods are used to identify the elements present in a sample 

and can quantify the average elemental composition of a sample. Excitation sources 

include flame, graphite furnace (GF) and inductively-coupled plasma (ICP). These bulk 

elemental analytical techniques have several advantages: 1) they are relatively easy to 

perform and relatively inexpensive, 2) they have relatively good detection limits, and 3) 

they provide an average composition of a sample of nanoparticles. These methods also 

have several disadvantages: 1) they are destructive techniques (i.e. one may not recover 

the sample after analysis), 2) sample preparation and matrix effects can introduce major 

contaminants, and 3) they are limited to providing only an average composition of the 

sample of nanoparticles and cannot correlate chemical composition to spatial location1.

Benoit and Rozan25 demonstrate a method of extracting particulates from river 

water samples for elemental analysis by GFAAS. They also chelate dissolved metals for 

elemental analysis by GFAAS. The authors use ICP-AES for elements that were at 

higher concentrations. Zhang et al.35 use GFAAS to measure the cadmium concentration 

of water suspensions of CdTe quantum dots. The authors are able to derive the quantum 

dot core concentrations from the cadmium concentrations.

Baalousha et al.26, Lyven et al.24, and Stolpe et al.27 demonstrate coupling ICPMS online with FlFFF. Stolpe et al.27 note that FlFFF and ICP-MS match well for 

coupling concerning operating flow rates and liquid phases. Additionally, band 

broadening from ICP-MS is not a significant issue as FlFFF peaks are already 

comparatively broad.

Stolpe et al.27 additionally note that they choose to use high-resolution ICP-MS 

(HR-ICP-MS) over quadrupole ICP-MS. The authors note that, when compared to 

quadrupole-ICP-MS, HR-ICP-MS offers a higher resolving power, higher sensitivity, and 

lower background noise; hence, it increases the numbers of elements capable of detection 

and lowers the detection limits. However, using a magnetic-sector MS design to obtain 

high resolution images requires a longer time to change magnetic fields; thus, scanning 

large mass ranges of elements may increase the time for analysis27.

Table 5-2 presents results from Lyven et al.24 demonstrating the detection limit 

and actual measured concentration of various elements identified in their aquatic samples

using ICP-MS.

Benoit and Rozan25 and Lyven et al.24 use high temperature catalytic oxidation to 

quantify organic carbon. Lyven et al.24 note they could not reliably quantify the ICP-MS 

carbon signal.

Fortner et al.10 use 13C-NMR to analyze suspensions of nano-C60 in D2O. They 

enrich the C60 with 13C at 25 percent.
48

Heymann et al.20 quantify the naturally occurring C60 and C70 fullerenes in various 

geologic samples. They demonstrate a method for using HPLC to separate C60 and C70

fullerenes from the organic material associated with the geologic samples coupled with 

UV-visible light absorption spectroscopy to quantify the fullerenes at their respective 

retention times. The authors discuss the importance of sample preparation and prior 

knowledge of the nanomaterials sought after. They cite that fullerenes are vulnerable to 

ultraviolet radiation, heating in air, and exposure to ozone and, as such, avoid strong 

irradiation and heating above 60oC of the samples. They note that HPLC is 

nondestructive, which allows the recovery of the sampled fullerenes.

Fortner et al.10 also use HPLC with UV-visible absorption spectroscopy to 

compare the retention time of C60 fullerenes that were recovered from an aqueous phase 

to an organic phase with C60 fullerenes in an organic phase that did not contact an 

aqueous phase initially. Chen et al.9evaluate UV/vis spectroscopy for analyzing aqueous 

nC60 fullerenes. The authors established a linear relationship between UV absorbance 

and the concentration of nC60 in standard water samples. The authors determined that the 

detection limit of 0.3 mg/L was higher than expected environmental concentrations and 

concluded that UV spectrophotometry is not a selective or sensitive method to quantify 

C60 fullerene in aqueous environmental samples.
49

Table 5-2. ICP-MS Detection Limits and Ratio of Measured Concentration to 

Detection Limit from Freshwater Samples as Provided by Lyven et al.24

Element

Isotope 

(m/z)

Detection 

Limit (nmol/L)

Ratio of Measured 

Concentration to 

Detection Limit

C 12 Not Quantified 144a

Mg 26 7.7 21

Al 27 11 47

Ca 44 23 91

Mn 55 0.1 31

Fe 57 14 1000

Co 59 0.02 13

Ni 60 0.2 36

Cu 65 1.5 9

Zn 66 0.9 11

Sr 88 0.005 44

Y 89 10 66

Zr 90 1 3

Mo 95 0.1 7

Sb 121 0.1 5

Ba 137 0.3 28

La 139 0.06 111

Ce 140 0.2 41

Pr 141 0.06 34

Nd 147 0.07 18

Gd 157 0.04 17

Dy 162 0.04 23

Pb 208 0.05 52

Th 232 0.03 26

U 238 0.03 18

a

Estimated using 10 times the standard deviation of the baseline and the fractionated 

creek sample.

Chemical Analysis with Spatial Resolution

X-ray spectroscopy, commonly referred to as energy-dispersive spectroscopy 

(EDS), X-ray energy-dispersive spectroscopy (XEDS), or energy-dispersive X-ray 

spectroscopy (EDX), measures secondary signals from characteristic X-rays produced 

during TEM, STEM, or SEM imaging for detecting and quantifying elements present in 

the sample. EDS is relatively easy to use in conjunction with TEM, STEM, or SEM and 

can obtain a spatial resolution on the order of 0.5 nm for elemental mapping1.

Electron Energy Loss Spectroscopy (EELS) measure primary signals from 

scattered electrons produced during TEM or STEM imaging for detecting and 
50

quantifying elements present in the sample. EELS has an increased energy resolution 

over EDS, which allows it to obtain additional information on chemical bonding, 

oxidation state, and average bond distances. EELS also can achieve a greater spatial 

resolution for elemental mapping, although the resolution is still on the order of 0.5 nm1.

Hochella et al.18 use TEM-EDS and SEM-EDS to analyze riverbank and riverbed 

samples. Hochella et al.19 use TEM-EDS and EFTEM-EELS to characterize acid mine 

drainage sediment samples. The authors note that EFTEM-EELS obtains spatially 

resolved elemental distributions better than TEM-EDS. The authors additionally use 

SEM-EDS, which obtains a poorer spatial resolution of elements than TEM-EDS and 

TEM-EELS. Hochella et al.19 note that TEM-EDS and EFTEM-EELS added significant 

details to the understanding of their acid mine drainage samples that SEM-EDS and XRD 

alone would not have revealed.

Baalousha et al.26 use STEM-EDS to determine surface elemental chemical maps 

of river colloidal particles. The authors use the surface elemental maps to verify the 

chemical compositions determined from FlFFF coupled with ICP-MS. The authors note 

their STEM-EDS results are semiquantitative.

Nanoscale secondary ion mass spectrometry (NanoSIMS) is a high-resolution 

microscopic technique capable of isotopic analysis. A primary ion beam, such as Cs+or 

O

-

, is rastered across the surface of the sample causing it to sputter and eject secondary 

ions from the sample. The ejected secondary ions are separated by their mass-to-charge 

ratios for detection and isotope identification. NanoSIMS may simultaneously identify 

up to five to seven species, depending on the model. The raster-scanning process can 

map the surface isotopes and may achieve a lateral resolution of 50 nm. In addition to 

surface information, NanoSIMS may also provide depth information. Static NanoSIMS 

can provide information within the first nanometer of depth from the sample surface, 

while dynamic NanoSIMS may achieve depths within a few nanometers from the sample 

surface. Herrmann et al. note that time-of-flight secondary ion mass spectrometry (ToFSIMS) may also provide molecular and isotopic surface information, but not while 

simultaneously providing high mass resolution and high spatial resolution with adequate 

signal transmission. NanoSIMS can provide high mass and spatial resolutions with 

excellent signal transmission38.

Herrmann et al.38 provide several considerations for using NanoSIMS. The 

analyzed sample should be dry, stable, conductive, and able to withstand the ultra-high 

vacuum of NanoSIMS. Soil samples should be flat and highly polished to avoid charging 

effects. Additionally, the use of a gold coating and an electron gun may reduce charging 

effects. Aqueous and in vivo samples may not be analyzed with NanoSIMS. Proper 

sample preparation is required. Freeze drying samples may cause ice crystal damage. 

Embedding the sample in an epoxy resin is a suitable sample preparation method. 

Sulphur embedding is also possible, although it is limited to small samples and has a 

short time frame of consistency. Samples should be less than 4 mm thick to avoid 

outgassing issues. Analyzing soil samples may prove semiquantitative and the use of 

standards may prove difficult. NanoSIMS has a field of view ranging from 5 to 50 m. 
51

Precisely aligning the sample where the NanoSIMS analysis is to occur may prove 

challenging due to the restricted field of view. Optical microscopy may assist in 

navigating the sample. Additionally, because NanoSIMS is a destructive technique, one 

may not further analyze the same sample.

Novikov et al.39 use NanoSIMS to analyze the elemental composition, particularly 

plutonium and uranium, of groundwater colloidal samples. NanoSIMS provides 

elemental maps of the colloidal particles.

5.7 Comparison of Analytical Techniques

This section describes the major analytical techniques presented and summarizes 

the advantages and disadvantages of each of the above described analytical techniques for 

each of the covered areas of characterization (e.g., size fractionation, size distribution). 

Advantages and disadvantages of the analytical techniques may include ease of use, 

potential resolution, and data interpretation.

Spectroscopies for Electron Microscopy

X-ray spectroscopy, commonly referred to as energy-dispersive spectroscopy 

(EDS), X-ray energy-dispersive spectroscopy (XEDS), or energy-dispersive X-ray 

spectroscopy (EDX), measures secondary signals from characteristic X-rays produced 

during TEM, STEM, or SEM imaging for detecting and quantifying elements present in 

the sample. EDS is relatively easy to use in conjunction with TEM, STEM, or SEM and 

can obtain a spatial resolution on the order of 0.5 nm for elemental mapping1.

Electron Energy Loss Spectroscopy (EELS) measures primary signals from 

scattered electrons produced during TEM or STEM imaging for detecting and 

quantifying elements present in the sample. EELS has an increased energy resolution 

over EDS, which allows it to obtain additional information on chemical bonding, 

oxidation state, and average bond distances. EELS also can achieve a greater spatial 

resolution for elemental mapping, although the resolution is still on the order of 0.5 nm1.

Transmission Electron Microscopy (TEM)

TEM utilizes an electron beam to probe a sample and images the electrons that 

pass through the sample. TEM offers several advantages for characterizing 

nanoparticles. TEM is typically coupled with EDS or EELS for chemical analysis. TEM 

can provide a high-resolution direct image of the nanoparticles, typically greater than 0.1 

nm of spatial resolution. TEM can also use electron diffraction, such as SAED or CBED, 

to distinguish between crystalline and amorphous phases. Additionally, TEM can 

determine the size and size distribution of crystalline nanoparticles

1

.

However, TEM also carries several disadvantages. Only a small fraction of 

nanoparticles sampled are examined, which makes it difficult to ensure that a 

representative sample is examined1(10,000 images should be examined to ensure 
52

statistical validity1). TEM produces a two-dimensional image of a three-dimensional 

object, which requires proper interpretation of the image. TEM operates near vacuum, 

which requires an ex situ analyzing environment. Sample preparation can introduce 

substantial artifacts, such as aggregate fragmentation, precipitation of salts, or 

nanoparticle aggregation1.

Hochella et al.19 note the difficulty in preparing heterogeneous precipitates, which 

might be sensitive to vacuum and beam exposure, while assuring an unbiased sampling of 

particles. The authors choose a method of embedding the samples in epoxy resin and 

cutting cross-sections using a diamond-knife ultramicrotome. This method allows 

unbiased sampling and uses encapsulation to stabilize delicate phases19.

TEM can be operated at high resolution (HRTEM), which is capable of spatial 

resolutions on the order of 0.1 nm. Energy-filtered TEM (EFTEM), coupled with EELS, 

may produce energy-filtered images with spatial resolutions on the order of 0.5 nm. 

Many TEMs can be operated in scanning transmission electron microscopy (STEM)

mode. STEM provides superior resolution (<0.1 nm spatial resolution) and can still be 

coupled with EDS or EELS. It can also be coupled with high-angle annular dark field 

(HAADF) to produce “Z-contrast” images. A Z-contrast image directly relates image 

contrast with atomic weight of the imaged atoms. Environmental TEM (ETEM) allows 

the characterization of nanoparticles in a controlled atmosphere up to several torr of 

pressure. It can even allow the characterization of nanoparticles while reacting with 

gases to provide more of an in situ characterization1. Despite its disadvantages, TEM still 

remains a staple in characterizing environmental nanoparticles due to its many 

advantages36.

Scanning Electron Microscopy (SEM)

Like TEM, SEM also utilizes an electron beam to probe a sample. However, 

SEM primarily measures the secondary electrons (SE) emitted from the sample to 

produce topographical contrast maps. SEM does not provide the same high resolution 

TEM provides: its resolution is limited to approximately 1 nm to 1m. Like TEM, SEM 

can also be coupled with EDS for chemical analysis. SEM requires less sample 

preparation than TEM, but SEM still maintains the concern for proper sample 

representation. Unlike TEM, SEM does provide reliable three-dimensional topographic 

imaging. SEM can also reduce any hydrocarbons present in the sample, which can 

deposit a layer of carbonaceous material on the imaged area and reduce image contrast. 

The high-vacuum environment can be detrimental to samples with volatile components. 

Inadequately coated samples can lead to charging, which can lead to image distortion, 

artifacts, or sudden discharges. The electron beam itself can damage or alter samples1.

SEM offers the option of capturing backscattered electron (BSE) signals and 

measuring their diffraction through the sample to obtain crystallographic and texture 

information. Additionally, BSE intensities can yield atomic number contrast maps. 

Environmental SEM (ESEM) allows the characterization of nanoparticles in a controlled 
53

atmosphere in the range of 1 to 10 torr. However, ESEM can only provide a maximum 

spatial resolution of three to four nanometers1.

Scanning Probe Microscopy (SPM)

Atomic Force Microscopy (AFM), a type of scanning probe microscopy (SPM), 

measures the forces between a sharp tip and a sample to determine topographic images at 

a spatial resolution of approximately 0.1 nm and provide electrical and mechanical 

properties of the sample. Unlike electron microscopies, AFM offers in situ

characterization and characterization of nonconducting samples, can characterize surfaces 

undergoing reaction, provides sub-nanometer spatial and vertical resolution, and 

possesses an inherent surface sensitivity1.

Disadvantages of AFM include a lack of direct information on chemical 

composition, tip limitations, potential tip and sample damage, potential displacement of 

nanoparticles, and data interpretation1.

Another type of SPM is scanning tunneling microscopy (STM), which measures a 

tunneling current between a conductive tip and a conductive or semiconductive sample. 

STM is capable of achieving molecular- to atomic-scale resolution. STM is also sensitive 

to the chemical identity of the surface atoms and molecules1.

X-ray Diffraction (XRD)

X-ray diffraction (XRD) measures the diffraction of X-ray beams to identify 

crystalline phases. XRD can measure structural properties of crystalline phases and 

probe atomic arrangements of amorphous phases. By comparison to a database of known 

diffraction patterns and use of a computer program such as RockJock, XRD can 

quantitatively identify the mineralogical composition of samples such as quartz or 

feldspar1,18. XRD can determine average particle size of crystalline materials below 

approximately 50 nm. However, XRD cannot directly identify elements present in the 

sample1.

The advantages of XRD include the following: it allows for quick identification of 

crystalline materials, it distinguishes between crystalline and amorphous materials, it 

produces additive patterns, it is quick and relatively inexpensive, it obtains particle size 

and size distribution of crystalline particles, and it can analyze samples in controlled 

atmosphere chambers1.

The disadvantages include the following: trace components (less than 

approximately one mass percent) can be difficult to detect, the technology cannot directly 

identify elements, XRD patterns are an average over all particles in the sample, and peak 

shapes can be difficult to interpret1.
54

Dynamic Light Scattering (DLS)

Dynamic light scattering (DLS) shines a light source on a suspension of particles 

and uses a photoelectric detector to measure the intensity of the scattered light. The 

constant Brownian motion of the particles causes time-dependant fluctuations, which are 

directly related to the diffusion coefficients of the particles. The diffusion coefficients 

allow the estimation of the hydrodynamic radius of the particles1.

DLS allows for in situ and real-time analysis of particle size and aggregation of 

suspensions of nanoparticles. A particle suspension with a concentration that is too high 

or too low or with particles with strong interparticle interactions may lead to inaccurate 

particle size determinations1.

Laser-Induced Breakdown Detection (LIBD)

Laser-Induced Breakdown Detection (LIBD) uses an intense, pulsed laser beam to 

breakdown colloidal particles and generates plasmas. The generated plasmas emit light 

back to the CCD camera. The CCD detects light emissions of single plasmas to 

determine particle size. In addition, detection of optical spatially resolved plasma light 

provides the spatial distribution of breakdown events within the focal volume. LIBD 

allows particles within a sample to be quantified. However, this method does not 

distinguish between or identify individual compounds. The tool can detect colloids as 

small as 2 nm in diameter and at concentrations as low as 1.6 ng/L.

The authors applied this technique in analyzing drinking water samples. The 

ability of this method to apply to environmental samples containing higher concentrations 

of suspended solids is not known based on information reviewed for this report. In 

addition, the method application is specific to analysis of colloids and assumes that 

particle shape is spherical. LIBD uses reference particles to determine the sizes of the 

sample particles. Therefore the method assumes that the particles in the sample have 

comparable properties, adsorption coefficients, dielectric properties, and ionization 

energies to the reference particles22.

X-ray Absorption Spectroscopy (XAS)

X-ray absorption spectroscopy (XAS) irradiates a sample with X-rays and 

measures the amount of X-ray energy the sample absorbs. X-ray energies that meet the 

electron-ejection threshold are absorbed and eject an electron. The ejected electrons are 

backscattered and produce interferences with the X-rays, which provide information on 

the average identity, number, and arrangement of the nearest neighboring atoms to the 

absorbing atom. From this information, the structure of the atoms in the sample may be 

obtained1.

XAS can provide detailed structural information and may be useful for 

semicrystalline and amorphous nanoparticles. This utility of XAS is important when 

compared to XRD, which is suited for primarily for crystalline nanoparticles. XAS 
55

allows for the following advantages: in situ experimentation as high vacuum is not 

required, the possibility of distinguishing between surface and bulk chemical species, the 

identification of elements and their oxidation states, characterization of the degree of 

order of the particles, and determination of atomic arrangement, measurements of surface 

sensitivity. However, XAS has the following disadvantages: the required use of 

synchrotron radiation, complicated data interpretation, and an overall average of all the 

particles for all results1.

6.0 DIFFERENTIATION OF ANTHROPOGENIC NANOMATERIALS

A literature search to date has not revealed peer-reviewed documents concerning 

the differentiation of anthropogenic and natural nanomaterials. Conversations with 

researchers have revealed that differentiating anthropogenic and natural nanomaterials 

can prove difficult, especially when the anthropogenic nanomaterial is released into 

environmental media15. It is helpful to compare the sampled nanomaterial to a known 

sample of an engineered nanomaterial to look for similarities as a control. However, it is 

also important to note that an engineered nanomaterial may undergo changes upon

entering into the environment.

Some anthropogenic nanomaterials do not occur naturally. Therefore, analyzing 

the composition of a sampled nanomaterial from environmental media may provide 

information as to the origin of the nanomaterial. For example, CdSe does not occur 

naturally and, if discovered in the environment, one can assume its original source is 

most likely anthropogenic15.

The current difficulties with differentiating anthropogenic and natural 

nanomaterials have led to the idea of isotopic enrichment of engineered nanomaterials for 

ultimate tracking purposes. Isotopic enrichment could serve as a marker that would 

essentially barcode engineered nanomaterials to identify them with their specific source. 

Researchers have indicated that currently this would prove to be economically infeasible; 

therefore, this technology is not being used15.

7.0 SUMMARY

This state-of-the-science review was undertaken to identify and assess currently 

available sampling and analysis methods to identify and quantify the occurrence of 

nanomaterials in the environment. The environmental and human health risks associated 

with nanomaterials are largely unknown, and methods needed to monitor the 

environmental occurrence of nanomaterials are very limited or nonexistent. Because this 

research is current and ongoing, much of the applicable information is found in gray 

literature (e.g., conference proceeding, communications with research scientists and other 

experts). 

The approach to this review included three separate strategies:
56

 Collection of available published literature using Dialog®;

 Review of information from targeted sources, such as nanospecific journals, conference proceedings, grants databases, and 

research databases; and

 Contacts with industry and academic experts.

This report summarizes the key characteristics that must be considered when collecting 

and analyzing samples in various environmental media. Based on results of the literature 

review, and personal communication with researchers, typical analytical methods and 

techniques that are currently used for nanomaterials are identified and briefly discussed. 

The review also identifies several sources that provided information on analytical 

techniques and equipment for nanomaterials. However, little information was obtained 

for sampling techniques that are specific for analysis of nanomaterials. Information 

obtained indicated that nanomaterial-specific sampling techniques have not yet been 

developed. Another area for which the search results provided little information is for 

differentiating anthropogenic (man-made) nanomaterials from natural nanomaterials. A 

number of potential sources that may provide additional information upon a more indepth review were identified. As this report provides a current state-of-the-science 

review of active research topics at the time of writing, this report may require 

modifications as additional research is conducted.
57

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