Evaluation of Exposure Concentrations Used in ... - ACS Publications

Subscriber access provided by University of Idaho Library

Critical Review

Evaluation of Exposure Concentrations Used in Assessing Manufactured Nanomaterial Environmental Hazards: Are They Relevant? Patricia Ann Holden, Fred Klaessig, Ronald F Turco, John Priester, Cyren M. Rico, Helena Avila Arias, Monika Mortimer, Kathleen Pacpaco, and Jorge L Gardea-Torresdey Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/es502440s • Publication Date (Web): 26 Aug 2014 Downloaded from http://pubs.acs.org on August 31, 2014

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Environmental Science & Technology is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 39

Environmental Science & Technology

1

Evaluation of Exposure Concentrations Used in Assessing Manufactured

2

Nanomaterial Environmental Hazards: Are They Relevant?

3 4

Patricia A. Holden a,e, Frederick Klaessig c,e, Ronald F. Turco b, John H. Priester a,e, Cyren M. Rico d,e,

5

Helena Avila-Arias b, Monika Mortimera,e, Kathleen Pacpaco a,e, Jorge L. Gardea-Torresdey d,e

6 7

a Bren

8

Barbara, Santa Barbara, California 93106-5131, USA

School of Environmental Science & Management, University of California Santa

9 10

b

11

Lafayette, Indiana 47907, USA

College of Agriculture − Laboratory for Soil Microbiology, Purdue University, West

12 13

c

Pennsylvania Bio Nano Systems, Doylestown, Pennsylvania 18901, USA

14 15

d Department

16

University of Texas at El Paso, El Paso, TX

of Chemistry and Environmental Science & Engineering PhD Program, The

17 18

e University

19

CEIN)

of California Center for Environmental Implications of Nanotechnology (UC

20 21

Corresponding author: Holden, PA Email: [email protected]. Tel: 805-893-3195

22 23

ACS Paragon Plus Environment

1


Page 2 of 39

24

Abstract

25

Manufactured nanomaterials (MNMs) are increasingly produced and used in consumer

26

goods, yet our knowledge regarding their environmental risks is limited. Environmental

27

risks are assessed by characterizing exposure levels and biological receptor effects. As

28

MNMs have rarely been quantified in environmental samples, our understanding of

29

exposure level is limited. Absent direct measurements, environmental MNM

30

concentrations are estimated from exposure modeling. Hazard, the potential for effects on

31

biological receptors, is measured in the laboratory using a range of administered MNM

32

concentrations. Yet concerns have been raised regarding the “relevancy” of hazard

33

assessments, particularly when the administered MNM concentrations exceed those

34

predicted to occur in the environment. What MNM concentrations are administered in

35

hazard assessments, and which are “environmentally relevant”? This review regards MNM

36

concentrations in hazard assessments, from over 600 peer-reviewed articles published

37

between 2008 and 2013. Some administered MNM concentrations overlap with, but many

38

diverge from, predicted environmental concentrations. Other uncertainties influence the

39

environmental relevance of current hazard assessments and exposure models, including

40

test conditions, bioavailable concentrations, mode of action, MNM production volumes, and

41

model validation. Therefore, it may be premature for MNM risk research to sanction

42

information on the basis of concentration “environmental relevance”.

43


2

Page 3 of 39

44 45


Introduction For over a decade, there have been concerns regarding the potential for

46

manufactured nanomaterials (MNMs) to cause environmental impacts.1 To inform MNM

47

use and disposal,2 and to guide industry towards innovating safer MNMs,3, 4 hazards are

48

assessed for a range of biological receptors. However, the relevance of hazard assessment

49

research is questioned, including how it facilitates understanding real risks of MNMs

50

released into the environment.5 Similar issues arise with human health hazard assessment,

51

including what constitutes “realistic exposure scenarios”6 and how to improve toxicity

52

testing relevancy.7 For critically evaluating in vitro MNM dosing in human health risk

53

assessment, airborne occupational MNM exposures, plus deposition and retention in the

54

lung environment, have been modeled.8 This forms a strong basis for evaluating how

55

relevant in vitro hazard tests have been to date, and what MNM concentrations should be

56

tested in the future for assessing human health risk.8 A critical examination of MNM dosing

57

regimes, juxtaposed against expected concentrations at receptors, would also be useful for

58

guiding MNM environmental risk assessment.

59

Environmental risk assessment requires understanding hazards to environmental

60

receptors, but also exposure magnitudes.5 Yet, relatively little research has been conducted

61

on exposure assessment, including few reports of MNMs measured in environmental

62

samples.9 Detecting and quantifying MNMs in complex environmental matrices remains

63

challenging.10 Without directly knowing MNM concentrations in the environment, most

64

exposure assessments have been developed from model predictions, including material

65

flow analysis (MFA).9, 11 Models are used to estimate MNM concentrations in various

66

environmental compartments,9, 12, 13 and such models are increasingly validated against


3


67

measurements, when available.9, 14, 15 Meanwhile, MNM hazard assessment research—

68

typically planned and performed independently of exposure modeling—involves testing

69

MNM toxicity magnitudes and mechanisms, using various organisms and conditions,

70

including various MNM concentrations.16, 17 Even when ecology drives MNM hazard

71

assessments,18 are study designs meaningful for environmental risk assessment? What

72

chemical concentrations are used in MNM hazard assessments? Are such concentrations

73

“environmentally relevant”?

74

To address these questions, MNM exposure modeling and measurement results can

75

be co-evaluated alongside MNM hazard assessment exposure conditions. Such co-

76

evaluation would be useful for several reasons. First, co-evaluation could assist with

77

defining “environmental relevance” and thereby inform future nanotoxicology to better

78

support environmental risk assessment. Relatedly, without carefully defining

79

“environmental relevance”, risk estimates may arbitrarily disregard hazard assessments

80

performed at MNM concentrations exceeding model estimates.5 High environmental MNM

81

concentrations (“hot spots”) could occur, and risks should be understood. Further, even

82

peer reviewing for publication is affected, since some journals recommend scoring for

83

“environmental relevance”. Since “environmental relevance” is not defined, such criteria

84

could bias peer reviews.

85

Page 4 of 39

Herein, we illustrate MNM concentrations administered in environmental hazard

86

research, juxtaposed against those measured and modeled. We ask: what MNM

87

concentrations have been used in hazard assessments, and are they “environmentally

88

relevant”? Related to conventional pollution risk assessment: what constitutes

89

“environmental relevance”, and is there precedence for confining hazard assessment


4

Page 5 of 39


90

regimes to modeled environmental concentrations? If the MNM hazard assessment

91

enterprise self-sanctions, i.e. discounting studies that utilize greater than predicted

92

exposure concentrations, could planning for long-term environmental protection be

93

constrained? We conclude with a synthetic perspective, towards stimulating dialog across

94

the nascent endeavors of MNM exposure and hazard assessments.

95 96

Methods Used in Data Collection and Interpretation

97

MNM Exposure Concentrations Used in Environmental Hazard Assessments

98

To evaluate MNM exposures in experimental hazard assessments, we extracted

99

concentration values from peer-reviewed articles, mostly from 2008 through 2013 (SI

100

Table S1). Over 600 articles were identified via the Web of Science (WOS) for several

101

environmental receptors or compartments: aquatic organisms (algae and macro-

102

organisms); microorganisms (bacteria, protozoa and fungi); soil, sediments, and

103

wastewater; terrestrial plants. We also noted food web studies. Details are in the

104

Supporting Information. Although articles regard many MNM types, they were classified

105

into the following MNM categories: metal oxides (e.g. nano-ZnO, -TiO2, -CeO2, SiO2, etc.);

106

metals (nano-Ag, -Au, -Fe, and other); carbonaceous (multi- or single-walled carbon

107

nanotubes or CNTs, graphene, fullerenes, and carbon black); quantum dots (e.g. CdSe or

108

CdTe). Articles were not categorized further, e.g. by MNM characteristics (e.g. primary

109

particle size or coating chemistry), aqueous media type, MNM physicochemical properties

110

such as charge or agglomeration state, endpoint metrics, toxicity, mode of action, and

111

toxicant concentration at the damage site(s). Other exposure variables were recognized

112

(e.g. temperature or oxygenation), but mainly concentration data were extracted. While


5


Page 6 of 39

113

other issues are also important, such as the toxicant concentration and form at the site of

114

effects in organisms, the most relevant comparison—based on the in-common spatial scale

115

of simulation versus MNM administration—is between modeled exposure concentration

116

and the nominal concentration employed in toxicity tests.

117

Extracted concentration data were organized into spreadsheets according to

118

receptor or compartment, and MNM category. Toxicity results were not tabulated, mainly

119

because of the disparate measurement and interpretation methods used across the studies,

120

making their results comparisons difficult or incredible. Mostly, each article generated one

121

entry that regarded one receptor or compartment type, and one MNM category. However,

122

some articles regarded multiple MNM categories or receptor types; in such cases, one entry

123

was created for each combination of MNM category and environmental receptor or

124

compartment. Because we sought to understand how frequently MNM concentrations

125

were researched across MNM categories and various environmental receptors or

126

compartments, this approach mostly resulted in one table entry per article (i.e. individual

127

research study). Still, 693 entries resulted from 615 articles (Table S1, Supporting

128

Information) because some articles regarded more than one biological receptor or

129

compartment, or MNM category.

130

For each entry, concentration units were converted to parts per million (ppm) for

131

comparing across aqueous, versus solid (e.g. soil or sediment), exposures. The mode,

132

median and mean exposure concentrations were calculated—across all MNM categories.

133

Concentration data were then used to score (1 or 0, for presence or absence, respectively)

134

range “bins” spanning ≤0.001 to >1000 ppm at order of magnitude intervals. This

135

classification enabled examining which concentration ranges had been more studied for


6

Page 7 of 39


136

each receptor or compartment and MNM category. For each receptor or compartment and

137

MNM category, the numbers of publications reporting exposure concentrations within the

138

bin levels were graphed as histograms.

139 140 141

Estimated or Measured Environmental MNM Concentrations The binning process was also applied to modeled or measured environmental

142

concentrations. Environmental concentration sources included a comprehensive

143

compilation9 of modeling results that were graphed alongside direct environmental

144

measurements19, 20 for water, soil, sediments, and biosolids. Two other recent modeling

145

studies13, 21 were additional sources. During the revision of this manuscript, another

146

modeling study was published,15 but the predicted concentrations were very similar to

147

prior studies and thus the comparisons herein were unchanged.

148

All three sources regarded the MNM categories: metal oxide, metals, and

149

carbonaceous; none regarded quantum dots. Compartment categories were similar to

150

those in hazard assessments: water, wastewater treatment plant (WWTP) effluent, WWTP

151

biosolids, soils, and sediments. After tabulating the modeled and measured MNM

152

environmental concentrations, then binning the concentration values using the same

153

approach that was used for classifying hazard assessment MNM concentrations, we

154

annotated the hazard assessment MNM concentration histograms to co-display, for the

155

aquatic and also the soil/ sediment/ wastewater receptors, the predicted MNM

156

environmental concentration ranges.

157 158


7


159

Results

160

Estimated or Measured Environmental MNM Concentrations

161

Page 8 of 39

Measured or modeled MNM environmental concentrations ranged from a low of

162

≤0.001 ppm to a high of >1000 ppm, i.e. spanning all concentration “bins” used for

163

classifying hazard assessment concentrations (Table 1). Across environmental

164

compartments of water (surface water or WWTP effluent), and solid media (soil,

165

sediments, and biosolids), the lowest MNM concentration estimates are ≤0.001 ppm. The

166

highest for water are in WWTP effluent (0.11 to 1 ppm) and the highest overall are for

167

biosolids (>1000 ppm; Table 1). However, many of the estimated surface water

168

concentrations are orders of magnitude lower than the lowest concentration bin used

169

herein, i.e. sub parts per trillion (ppt). Other reported environmental measurements, i.e.

170

that were either more recent or not included in Gottschalk et al.9, either overlap22, 23 or, in

171

one case (sediments), greatly exceed24 the compiled ranges. Still, given the currency and

172

comprehensiveness of the consulted review,9 and the consistency across the main three

173

consulted articles,9, 13, 21 the summarized modeled or measured MNM concentration ranges

174

represent current available information (Table 1).

175 176

Exposure Concentrations Used in MNM Hazard Assessments

177

Aquatic, including Benthic, Organisms

178

Across all MNM categories and for all aquatic, terrestrial plant or microbial

179

receptors, or receptors in soils, sediment, or wastewater, there were 1692 concentration

180

data points evaluated (Table 2) from the 615 surveyed articles (Table S1). The numbers of

181

studies regarding aquatic organisms (271 total) were, by organism (Table S1, Supporting


8

Page 9 of 39


182

Information): algae (13), daphnia (76), fish (119 total, including 20 medaka, 64 zebrafish,

183

12 carp, 18 trout, and 5 minnow), mollusc (42, including 7 gastropod, 20 mussel, 5 oyster, 5

184

clam, 1 scallop, 2 bivalve, 2 abalone), echinoderm (5, all urchin), crustacean (14, including 4

185

shrimp or mysid, 3 crab, 1 copepod, and 6 amphipod), and polychaete (2). Since studies

186

used multiple doses, the number of concentration data points exceeded the number of

187

studies, i.e. totaling 733 (Table 2).

188

Across aquatic organism and MNM categories, the mean MNM concentration, and

189

the concentration most frequently administered (mode), were 71 ppm and 5 ppm,

190

respectively (Table 2). Thus, across the receptor categories, the lowest overall MNM

191

concentrations were for aquatic organisms (Table 2). The administered MNM

192

concentrations spanned the concentration range from ≤0.001 to >1000 ppm (Fig. 1a).

193

While a more detailed analysis by MNM was not warranted—mainly because of the uneven

194

study count per MNM—concentrations appeared to be similar across MNM categories, as

195

indicated by similarly shaped histograms (Fig. 1a, Fig. S1). Administered MNM

196

concentration ranges differed by organism: except for echinoderms, crustaceans and

197

polychaetes, most aquatic organisms were tested at MNM concentrations up to 1000 ppm

198

(Fig. S2); MNM concentrations >1000 ppm were administered for only two receptor types

199

(Daphnia sp. and fish, Fig. S2b and c, respectively); the highest administered MNM

200

concentration range for echinoderm studies (1.1 to 10 ppm) was lower than the highest

201

concentration for the other aquatic receptors, except for polychaetes (Fig. S2); studies of

202

molluscs appeared to use mostly lower MNM concentrations, as indicated by the left-

203

skewed histogram (Fig. S2d).


9


204

Page 10 of 39

In comparing modeled or measured environmental MNM concentration ranges

205

(Table 1, and blue shaded regions of Fig. 1a and Fig. S1) to the ranges (all of Fig. 1a and Fig.

206

S1) and to the median (0.6 ppm, Table 2) of administered concentrations, half of the

207

aquatic hazard studies reported using administered concentrations that were greater than

208

predicted environmental concentrations. This comparison does not differentiate surface

209

waters from the slightly more MNM-concentrated WWTP effluents (Table 1, and Fig. 1a),

210

because WWTP effluent receiving streams can be “effluent-dominated”.25 On face value, the

211

range of MNM concentrations administered in hazard assessments would seem ideal, i.e.

212

that half are above, and half are within, predicted environmental MNM concentrations.

213

However, one might be concerned if many publications only report toxicity testing over

214

high concentration ranges.

215

To assess the latter, the spreadsheet of aquatic entries (Excel document, Supporting

216

Information) can be sorted, finding that 229 of the 271 hazard studies administered

217

concentrations only above the lowest concentration bin. In other words, nearly 85 percent

218

of all aquatic studies excluded testing in the sub-ppb concentration range. Further, 66%

219

(180 studies) only tested concentration ranges exceeding 0.01 ppm. Nearly half (43%, or

220

116 studies) only tested MNMs at concentrations exceeding 0.1 ppm, and 22% (50 studies)

221

only tested MNMs at concentrations exceeding the median test concentration (i.e. at ranges

222

at or above 1.1 to 10 ppm). Nearly 6% of the studies only tested aquatic toxicity at

223

concentrations exceeding 10.1 ppm, and 2% of studies excluded test concentrations below

224

100 ppm. These statistics would suggest that there is, at the level of the individual study, a

225

large disparity between predicted environmental, versus tested, MNM concentrations.

226

While there is general overlap (Fig. 1a and Fig. S1), individual study concentration ranges


10

Page 11 of 39


227

mostly exceed those predicted. It would seem that this situation could be rectified if future

228

toxicity studies routinely tested low concentrations.

229 230 231

Microorganisms Hazard assessments were classified into the “microorganism” category if they

232

regarded MNM effects on bacteria, protozoa, or fungi. The few articles concerning MNM

233

effects on viruses were not evaluated as they were clinically, not environmentally, oriented.

234

The numbers of entries were: 220 (bacteria), 14 (protozoa), 9 (fungi). Most environmental

235

nanotoxicology publications regarded bacteria. For 2013, the topics “bacter* and

236

nanomaterial*” yielded 174 publications (Table S2), but the topics “plant* and

237

nanomaterial*” and “fish* and nanomaterial*” yielded only 111 and 31 publications,

238

respectively (ISI Web of Science Search, January 1, 2014). However, many MNM-bacterial

239

studies are clinically-oriented: out of over 600 identified publications from 2008-2013, ca.

240

62% are oriented towards antibacterial or disinfection applications (235 of 623, Table S2),

241

with others regarding the environment. Of the 220 bacterial studies recovered, 75 were

242

regarding testing MNMs for antibacterial or disinfection properties, and 145 regarded

243

environmental toxicity. Thus, the total entries related to bacterial environmental toxicology

244

(as above, 145) is significant and, given the lack of bias in recovering sources (Supporting

245

Information), representative. All of the entries for protozoa regarded environmental

246

toxicity, as did five out of nine studies with fungi.

247

While not a comprehensive test of the hypothesis, we examined administered MNM

248

concentration ranges for antibacterial (e.g. disinfection) versus environmental hazard

249

assessments to determine if the former tended to be higher. Not surprisingly, studies


11


250

targeting MNM antibacterial, including disinfection, properties used relatively higher

251

exposure concentrations, particularly for carbonaceous, metal (including nano-Ag) and

252

metal oxide MNMs (Fig. S3). Further analysis only regarded the environmental bacterial

253

nanotoxicology studies.

254

Page 12 of 39

The distributions of administered MNM concentrations for microorganisms appear

255

similar to those for aquatic organisms (Fig. 1b versus 1a), and similar between MNM

256

categories, across all microorganisms (Fig. S4). As expected, given the greater number of

257

entries for bacteria relative to other microorganisms, the distribution of administered

258

MNM concentrations for all microbes (Fig. 1b) appears very similar to that for bacteria (Fig.

259

S5a). Still, protozoan and fungal testing apparently involved higher MNM concentrations,

260

relative to bacterial testing (Fig. S5).

261

The reported toxicity magnitudes are not summarized or interpreted here, as there

262

are many reviews regarding bacterial-nanomaterial interactions, including across several

263

MNMs,26 for nano-Ag27-30 and quantum dots,31, 32 and regarding effects mechanisms33, 34 and

264

sensitivities compared to higher organisms.35 Further, based on our literature survey, a

265

different analysis would be required to compare across bacterial studies, owing to

266

disparate MNM preparations, toxicity endpoints, and experimental methods, including use

267

of positive and negative controls. This point also applies to the other compartments and

268

organisms, i.e. aquatic, soil/sediment/wastewater, and terrestrial plants. For evaluating the

269

realism of administered MNM concentrations, frequency distributions are informative.

270

Because microbial nanotoxicity studies were conducted in aqueous media, the

271

environmental relevance of tested MNM concentrations should be compared to the MNM

272

concentration ranges predicted, or measured, for surface water or WWTP effluent (Table 1,


12

Page 13 of 39


273

and blue shaded bars in Fig. 1a). One can readily see, comparing Fig. 1a and 1b, that the

274

concentrations of MNMs used in microorganism toxicity testing are at ranges exceeding

275

those used in aquatic organism toxicity testing, and so the microbial test ranges well exceed

276

those predicted for water. The descriptive statistics (Table 2) confirm: the mean, and most

277

frequently studied (mode) concentrations across all microbes and MNMs were

278

approximately 362 and 55 ppm, respectively. Half of the entries are for concentrations

279

exceeding approximately 6 ppm (Table 2), i.e. not even within range of predicted

280

environmental concentrations in water (Fig. 1a and 1b). Thus, it would appear that most

281

environmental microorganism nanotoxicology studies have utilized overly high MNM

282

concentrations. Because the publication pace in microbial nanotoxicology appears to be

283

accelerating (Table S2), it would be important to include low MNM concentrations in future

284

studies, so that the growing field addresses a full range of possibly relevant concentrations.

285 286 287

Soils, Sediments and Wastewater After landfills, soils are predicted to be significant destinations for MNMs released

288

into the environment.12 For soils, there are concerns that MNMs could disrupt nutrient

289

cycling, a high value ecosystem service,36 via impacts on the microbial community. Nutrient

290

cycling is substantially carried out by diverse microbial communities whose interacting

291

populations and biogeochemical functions are practically inseparable from the physical

292

matrix with its environmental factors (e.g. water potential, pH, redox, etc.). That, coupled

293

with the possibility that soil sorption reactions will lower MNM bioavailability,37

294

necessitates studying soils—and, similarly, sediments—in microcosms where MNMs are

295

amended to the matrix with its intact microbial communities. Similarly, wastewater is


13


Page 14 of 39

296

comprised of complex microbial communities whose biogeochemical functions, whether

297

specialized or broad, are best studied within the matrix, i.e. activated or anaerobic sludges.

298

Therefore, we distinctly categorized articles that addressed nanotoxicology for soils,

299

sediments or wastewater, with the latter including various biological unit processes in

300

WWTPs.

301

Of the 84 studies sourced, 57, 21, and 6 regarded soils, wastewater, and sediments,

302

respectively. As per the histogram (Fig. 1c), most tested MNM concentrations were in the

303

high ranges, with none in the sub-ppb range. Few studies regarded quantum dots, and

304

most regarded metal MNMs (Fig. 1c, Fig. S6). No studies of sediments regarded metal

305

oxides (Fig. S7b). The administered MNM concentrations were not normally distributed,

306

but rather were skewed to the right: more studies utilized higher than lower

307

concentrations (Fig. 1c, Fig. S6). This was particularly the case for soil studies (Fig. S7a).

308

Overall, across the three media types, the mean and most frequently studied

309

concentrations were approximately 1200 and 550 ppm, respectively (Table 2).

310

Neither activated sludge nor anaerobic digester sludge MNM concentrations were

311

specifically predicted by exposure modeling. Still, MNM concentrations in sludge studies

312

can be compared to the concentration ranges predicted, or measured, for soils, sediments,

313

and biosolids (Table 1), particularly because both sludge types are converted to biosolids

314

in WWTPs. While many of the exposure modeling outcomes predict sub-ppb levels (Table

315

1), it is notable that none of the sourced toxicity studies employed such low MNM

316

concentrations (Fig. 1c). Further, only three studies employed concentrations below 100

317

ppb, and many employed MNM concentrations exceeding 1000 ppm (Fig. 1c). Based on the

318

median MNM concentration across soils, sediments or wastewater (55 ppm, Table 2), half


14

Page 15 of 39


319

of the studies administered MNM concentrations within the highest ranges of predicted, or

320

measured, environmental MNM concentrations (100.1-1000 and >1000 ppm, Table 1 and

321

Fig. 1c). Thus, there is a large disparity when comparing exposure modeling results to

322

experimental nanotoxicity test conditions: models often predict very low MNM

323

concentrations in soils, sediments, and biosolids (Table 1), yet microcosm exposures

324

employ concentrations that are orders of magnitude higher (Fig. 1). One measurement of

325

nano-TiO2 in sediments near a WWTP effluent outfall would support the realism of high-

326

end MNM concentration testing,24 yet there is only one such report. Further, it is unknown

327

if the reported Ti nanomaterial was manufactured or natural, i.e. indigenous to that

328

environment.9

329 330

Terrestrial Plants

331

There is great concern regarding the possible entry of MNMs into the food chain, via

332

agricultural crops grown, for example, in soils fertilized with MNM-containing biosolids.38,

333

39

334

biomass40 in the WWTP activated sludge precursors to biosolids, and thus land application

335

of biosolids is a certain route by which MNMs can enter soils. MNMs can genetically

336

damage food crops,41 affect food crop nutrient content,42 and interfere with nutrient cycling

337

including nitrogen fixation in root nodule symbioses.43 Further, many vegetables are grown

338

hydroponically, and thus MNM uptake via aqueous plant growth media is of concern.38

339

Not all biosolids are land-applied to agriculture. However, MNMs sorb to microbial

Overall, 134 studies were examined regarding MNM concentrations used in plant

340

nanotoxicity testing. Because more than one MNM concentration was often tested, this

341

resulted in 294 data points (i.e. an MNM concentration for a given plant, within an


15


Page 16 of 39

342

individual study, Table 2). One can observe that, across the range of administered MNM

343

concentrations, the tendency with plant exposures is to use higher MNM concentrations

344

(Fig, 1d, Fig. S8). As such, the mean actual concentration was approximately 860 ppm, and

345

the most frequently studied concentration (mode) was 55 ppm. Similarly to the

346

publications regarding aquatic organisms (Fig. 1a) and microorganisms (Fig. 1b), the

347

frequencies of tested concentrations did not appear to vary significantly by MNM category

348

(Fig. 1d) except that there were few studies using quantum dots (Fig. S8). Across the lower

349

end concentration ranges, only one study reported using MNMs at sub-ppb (≤0.001 ppm)

350

levels, and eight studies tested MNMs at the next highest range (0.0011 – 0.01 ppm, Fig.

351

1d). Over 90% of the sourced studies did not test MNMs across the lowest three

352

concentration ranges (i.e. below 0.10 ppm), and over 80% did not test MNMs at

353

concentrations below 1.1 ppm.

354 355 356

Food Webs As summarized in the Supporting Information, there are few studies of food webs,

357

i.e. using mesocosms, and all ten sourced were published since 2011. While one might

358

assume that food web studies would employ the lowest MNM concentrations, the studies

359

report a wide range of administered concentrations (Fig. S9). No studies used MNM

360

concentrations exceeding 1000 ppm, and most studies—which were mainly aquatic

361

mesocosms—appeared to use MNM concentrations below 1 ppm. Thus, there is a tendency

362

with food web studies to employ MNM concentrations more reflecting those measured or

363

predicted in water (as in Fig. 1a).

364


16

Page 17 of 39

365


Summary of Modeled or Measured, vs. Administered, Exposure Concentrations

366

In summary, across the major compartments of water (surface water and WWTP

367

effluent) and solid media (soil, sediments, and biosolids), and across major receptors of

368

aquatic organisms, microorganisms, complex communities (in soils, sediments or

369

wastewater) and terrestrial plants, there are some overlaps in modeled and measured

370

MNM concentrations, versus those administered in toxicity studies. However, there are also

371

large disparities, with much higher MNM concentrations being routinely tested as

372

compared to what are predicted for, or measured in, the environment. There are few

373

patterns that differ across MNMs, but there are some differences across receptors. Future

374

hazard assessment studies would be improved by strategically incorporating concentration

375

ranges that overlap with those modeled or predicted (Table 1, Fig. 1). In the following

376

sections, we discuss uncertainties in hazard assessment that transcend MNM

377

concentration, and some major uncertainties currently inherent to exposure modeling.

378 379 380

Uncertainties When Defining Environmental Relevance of MNM Hazard Assessments Ideally, hazard assessment research would be performed under conditions that

381

mimic the environments in which biological receptors are exposed. Therefore, how to

382

define and incorporate “realism” into MNM hazard assessment studies is an important

383

issue. As above, on the basis of administered MNM concentrations, there appears to be a

384

broad lack of environmental realism in MNM hazard assessment research to date—that is,

385

if one assumes that the modeled and measured MNM environmental concentrations are

386

themselves “realistic”. What other factors, besides administered MNM concentrations, may


17


387

influence hazard assessment “environmental relevance”? Further, what are the key

388

uncertainties in predicted MNM environmental concentrations?

Page 18 of 39

389 390 391

Uncertainties regarding environmental relevance in MNM hazard assessment There are many factors, besides MNM test concentration, that influence hazard

392

assessment “environmental relevance”. On one hand, to be most environmentally-relevant,

393

instead of only testing standard organisms studied out of an ecological context, hazard

394

assessment research should regard MNM impacts in systems that are sufficiently complex

395

to include all relevant ecological interactions.18, 44 This is particularly true for ecosystem

396

processes that require multiple populations interacting as communities, as is the case for

397

biological N2 fixation within plant root-bacterial symbioses.43 However, assessing MNM

398

hazards by only using mesocosms is impractical and slow, and alternative test strategies

399

proposed for accelerating human health hazard assessments45 could also have a role in

400

environmental nanotoxicology if such alternative tests employ “environmentally relevant”

401

receptors.18, 46 Regardless of the receptor, a wide range of MNM exposure concentrations

402

may be required to allow for resolving MNM bioavailability mechanisms, uptake,

403

bioaccumulation, and organismal internal concentrations at sites of toxicity.

404

Media choice would also be an important consideration, since aqueous chemistry

405

significantly affects biological population responses to MNMs,47 and since defined media

406

could conceivably be formulated to closely represent nutrient-depleted soil or water

407

environments. Further, depending on the media, MNM dissolution, speciation and

408

complexation can interfere with differentiating particle versus ion toxicity, e.g. in the case


18

Page 19 of 39


409

of Ag ions dissolved from Ag MNMs but then complexing with chloride, leading to an

410

underestimate of dissolution-mediated Ag MNM toxicity.48

411

In addition to receptor type and media, “environmental realism” is also affected by

412

MNM delivery choice, e.g. whether to administer and study as-produced, “neat” MNM

413

particles, versus “aged” MNMs. On one hand, MNMs that are relatively stable may exert

414

similar toxicities over prolonged exposure, including MNM “aging” periods,49 while other

415

MNMs may acquire a mitigating cap, as in Ag MNMs becoming sulfidated.50 Still, how fast

416

aging occurs, relative to hazard assessment study periods, is an important consideration.

417

For example, nano-ZnO can dissolve quickly in environmental waters,51 including the soil

418

solution.38 If plants grow slowly in soils43 relative to MNMs dissolving in the soil solution,

419

then administering neat MNMs may be reasonably “environmentally relevant”. Fully

420

exploring how fast MNMs physicochemically transform in situ, relative to how fast

421

biological receptors respond, would assist resolving when it is “environmentally relevant”

422

to administer “neat”, as-produced, MNM powders during environmental hazard

423

assessment. For MNMs that are embedded in composites with polymers, conducting hazard

424

assessments using neat MNMs may still be “relevant”, if MNMs can release from

425

composites.52

426

Thus, in addition to MNM concentrations, other factors affecting “environmental

427

realism” during MNM hazard assessment include: choice of biological receptors, choice of

428

test conditions including media chemistry and ecological complexity, and what MNM forms

429

should be used, including aged or neat. Given these multiple factors, it is uncertain if the

430

choice of MNM concentration overwhelmingly determines MNM hazard assessment

431

“environmental relevance”.


19


432 433

Page 20 of 39

Uncertainties regarding predicted environmental MNM concentrations Uncertainties associated with modeling environmental MNM concentrations also

434

contribute to the ambiguity in what comprises “environmentally relevant” MNM

435

concentrations for MNM hazard assessment. For example, modeling requires

436

understanding the source magnitude, i.e. MNM production volumes. Yet, accurate

437

quantifications of production volumes are not readily available. At industry trade

438

association meetings, colleagues are reminded of antitrust law requirements such as,

439

“Don’t, in fact or appearance, discuss or exchange information on:… company data on costs,

440

production, capacity inventories, sales, etc….”.53 Not complying can lead to allegations of

441

price-signaling, as in the pigment TiO2 suit recently settled for $163.5 million.54, 55 Industry

442

insiders understand that consolidated nanomaterial production volumes are difficult to

443

obtain or that intermediaries, such as market research firms, provide only estimates. This

444

is because market research relies on information gained via interviews, financial reports,

445

trade show handouts, and other sources.

446

However, academic researchers have used market research estimates of production

447

volumes as starting points for modeling environmental MNM concentrations. These, along

448

with other sources, can result in a wide variety of production volume estimates. For

449

example, silver production volume estimates vary greatly (Table S3), i.e. 500 t/a stemming

450

from personal communication;11 1230 t/a via trade association analysis;11 55 t/a, and a

451

range of 5.5 to 550 t/a from a survey of experts;56 2.8 to 20 t/a in the U.S., using “creative

452

approaches” combining order inquiries with proxy parameters.57 Keller, et al.12 and the

453

European Commission’s (EC’s) staff58 cite market research reports for 450 t/a and 22 t/a,

454

respectively. Given that production volume estimates can vary by two to three orders of


20

Page 21 of 39


455

magnitude (Table S3), estimates of MNM environmental concentrations are rather

456

uncertain (Table 1).

457

What MNM production information is most reliable? Market research practitioners

458

utilize superior access to supply chain resources and their detailed knowledge of end use

459

markets to arrive at self-consistent findings. (For a discussion of financial reporters

460

operating in the nanotechnology environment, see Ebeling et al.59) However, industry

461

insiders temper market research report findings with their own market knowledge. In

462

proposing production volumes herein (Table S3), weight has been given to market

463

estimates having some level of government review, i.e., an imprimatur of relevance to

464

nanomaterial environmental health and safety. However, the EC’s definition is relatively

465

recent and may be a surprise to some market segments. For those material suppliers,

466

reported volumes will reflect an increasing awareness of definitions rather than a market

467

growth.

468

We illustrate the challenge with a compilation of global production estimates for

469

eleven nanomaterials (Fig. 2). Details on sources, volumes and interpretations are found

470

with Table S3 in the Supporting Information. Major marketplace segments are identified, as

471

are their alignments with specific nanomaterials. Symbols () indicate uncertainties in

472

volume and likely growth trends. As shown in the following discussion, the definition of

473

“nanoscale”, and a knowledge covering the many market segments, can significantly affect

474

the reliability of market research estimates, which influence estimates of environmental

475

concentration through the modeling of likely release scenarios.

476 477

Volume ranking highlights the older, passive fillers that often have mineralogical counterparts (Fig 2, Table S3). Carbon black, carbon nanofibers and carbon nanotubes


21


Page 22 of 39

478

share markets for reinforcement, electrical conductivity and thermal conductivity. 60

479

Silicon dioxide has sub-categories (and CAS-numbers61)—diatomaceous earth, synthetic

480

amorphous silica, silica fume, and quartz—that also span descriptors such as natural,

481

incidental and engineered. All are “manufactured” when processed into commercial

482

products leading to a combined volume (Fig. 2). Adjusting the upper boundary of nanoscale

483

to above 100 nm would affect TiO2 estimates greatly, due to the 5 million t/a of pigment

484

grade TiO2 for which the mean primary particle size found in aggregates is between 250

485

and 300 nm.62, 63 Carbon black (CB), SiO2, Al2O3 and TiO2 describe a class of “large volume,

486

long-term-use” materials relative to the remaining particles including future novel

487

compositions, and such “large volume, long-term-use” nanomaterials are used in several

488

markets. For example, the tire industry, known for CB, is also a significant market for

489

precipitated silica. The paper industry utilizes process additives (antifoams, retention aids)

490

and paper fillers (alumina, silica, calcium carbonate) that can be nanoscale, and is also a

491

source of nanocellulose, which may displace carbon nanotubes and nanofibers in

492

reinforcement. Elastomer and polymer compounders, and the paint and coatings

493

industries, use fillers extensively. For some markets, e.g. optical fiber ferrules for zirconia

494

or catalyst carriers for TiO2, nanomaterials are converted into much larger objects, and

495

there are others, such as chemical mechanical planarization (CMP), where MNM

496

consumption occurs within a closed-loop industrial context (workplace and waste

497

treatment). Other MNM uses, such as pesticides in an agricultural setting, and in food,

498

personal and household care products, offer considerable opportunity for widely dispersed

499

environmental exposure.


22

Page 23 of 39

500


Several authors and organizations utilize patent claims and product formulations to

501

suggest environmental concentrations.64, 65 In many respects, these efforts responded to

502

the public’s early questions about consumer and environmental exposures. Silver

503

illustrates a pitfall in that many authors mistook prominence for large production volumes

504

when using the Project on Emerging Nanotechnologies (PEN) listing, even though verifying

505

the products’ commercial status was difficult.66 Yet, formulated household products lead to

506

immediate human exposure and, for silver, there is past medical experience to consider.67

507

Lorenz, et al.68 and the Magic Nano incident69 demonstrate the very real exposure potential

508

with aerosol sprays.

509

Life cycle analyses track a material from production through to disposal,11, 12 and

510

production volumes allow for calculating general background exposure levels. Specific

511

production site knowledge is useful for estimating localized environmental exposure such

512

as along a river system, and there are also generic scenarios for point sources.70 Total

513

production volumes also act as surrogates for the frequency of everyday incidents such as

514

spills, broken bags, accidental exposures and their locations. However, anticipated

515

environmental background levels are distinct from the frequency and duration of acute

516

exposures.71

517

Therefore, the investigator interested in establishing a “realistic” or

518

“environmentally relevant” exposure level for nanomaterial testing faces several

519

challenges. There are distinctions to draw among environmental concentration, exposure

520

level, and dose; there are several assessment methods with accompanying nuances: risk

521

assessment, life cycle analysis (and its sub-category of life cycle impact assessment),

522

comprehensive environmental assessments and multi-criteria decision analysis.72 Whether


23


523

as narratives used to set research priorities73 or as computer models calculating a

524

predicted environmental concentration,11 these methods establish material (mass) flows

525

passing from production-to-use-to-disposal.

526

Page 24 of 39

Practitioners utilize mapping to identify life cycle stages or ”hot spots”, allowing

527

scenario-specific information to be applied to material flows to estimate releases and

528

concentrations. However, estimating environmental exposure for a nanomaterial is more

529

challenging due to the definition. Nanoscale materials are defined by size and not by

530

property.74 Without recognized properties or known effects, it becomes difficult to verify

531

life cycle models, leading to over- or underestimates of exposure.9 Recent articles20, 24, 75

532

report on nanoscale TiO2 content in biosolids exceeding nearby production or consumption

533

with paint as an apparent source, i.e., non-nano-pigment grade TiO2.9, 20 which does have a

534

nanoscale component.76 Additionally, particles respond to environmental conditions, which

535

for silver can entail repeated dissolution and re-precipitation, as well as sulfide

536

formation.77-79 While silver sulfide does not readily re-oxidize, other metals and metal

537

sulfides do.79 Effectively, non-nano sources, sinks, changes in surface chemistry and

538

chemical transformations, all meeting the definition of nanomaterial, are possible at each

539

environmentally relevant stage of the life cycle, and they are not necessarily included in the

540

mass balance assumptions of many life cycle models.

541

Thus, major uncertainties in MNM environmental concentration modeling include

542

understanding production volumes of actual nanoscale materials that can be released into

543

the environment and, as above, accounting for transformations that would affect not only

544

toxicity but also integrity and retention of properties conferring nano-specific reactivity

545

and hazard.


24

Page 25 of 39

546 547


Conclusions Herein, upon reviewing administered concentrations reported in more than 600

548

articles concerning MNM environmental hazards, we show that there is some overlap, but

549

also disparity, as compared with modeled or measured environmental MNM

550

concentrations (Fig. 1 vs. Table 1). There are uncertainties in modeling environmental

551

MNM concentrations, mainly stemming from limited production volume information, but

552

also in accounting for MNM release and environmental transformation. Further, there are

553

great uncertainties regarding MNM bioavailability, and the effective concentrations that

554

cause toxicity by a particular mode of action within a receptor. This limits defining with any

555

degree of detail, the MNM doses that are most realistic for the myriad environmental

556

receptors and their exposure conditions. Although human occupational exposure by

557

inhalation and MNM deposition into the lung have been modeled for improving in vitro

558

hazard assessment,8 MNM environmental exposure and hazard assessment endeavors do

559

not yet account for bioavailability, bioaccumulation, biotransformation, and mode of action.

560

Actual concentrations in, and around, biological receptors may be much higher than

561

average ambient concentrations of toxicants that are modeled or measured in bulk.

562

However, even if the concentrations near receptors are not high, it may be necessary to

563

default to administering higher MNM exposure concentrations in bioaccumulation studies,

564

since many common methods for quantifying MNMs in tissues or similarly complex

565

matrices have relatively high detection limits.10 For all of these reasons, it is premature to

566

discount MNM hazard assessment research on the basis of “environmental relevance”.

567

Further, while modeling results are compared and comparable to the limited

568

measurements of MNM environmental concentrations, it is important to validate models,


25


Page 26 of 39

569

perhaps even for their abilities to predict conventional pollutant concentrations. This could

570

serve as a good “check” on model performance when reapplied to predicting future MNM

571

environmental concentrations.

572

To maximize environmental realism, hazard assessment should, as closely as

573

possible, be conducted to include ecologically relevant receptors and exposure conditions.

574

Extremely low to rather high MNM concentrations could be routinely administered in

575

toxicity assessments. What MNM exposure conditions, including concentrations, are

576

“environmentally relevant”, especially given that predicted concentrations are averages

577

and thus do not capture “hot spots”, i.e. environmental locations where MNMs may hyper-

578

concentrate? By comparison, pharmaceutical pollutants are expected to occur at low

579

concentrations in the environment,80 yet pharmaceutical aquatic toxicity is studied under

580

acute (high concentration) exposure conditions expected with spills or highly unregulated

581

situations.80, 81. The MNM hazard and exposure assessment communities are prudent to

582

design their studies carefully, particularly since the nanotechnology industry with its many

583

anticipated societal and environmental benefits could be unduly thwarted if great risks are

584

inaccurately predicted or perceived82. Yet, in the absence of careful consideration of such

585

questions, conservatism within the MNM hazard and exposure assessment communities

586

may lead to “self-sanctioning” that itself could constrain research and thereby prevent

587

necessary and full discovery.

588 589

Acknowledgements

590

This work was supported by the National Science Foundation and the

591

Environmental Protection Agency under Cooperative Agreement DBI-1266377 and


26

Page 27 of 39


592

Purdue-Colciencias agreement under Colombia-Purdue Institute for Advanced Scientific

593

Research – (CPIASR). Any opinions, findings, and conclusions are those of the authors and

594

do not necessarily reflect the views of the National Science Foundation or the

595

Environmental Protection Agency. This work has not been subjected to EPA review and no

596

official endorsement should be inferred.

597 598

Supporting Information Available

599

There are two Supporting Information files: an Excel workbook containing binned

600

concentration data for each MNM hazard assessment study that was sourced, and a Word

601

document containing additional methods, results, and a table plus references of the Excel

602

spreadsheet entries. This information is available free of charge via the Internet at

603

http://pubs.acs.org/.

604 605


27


606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651

Page 28 of 39

References

1. The Royal Society Nanoscience and nanotechnologies: opportunities and uncertainties; The Royal Society and The Royal Academy of Engineering: London, 2004; p 116. 2. National Research Council, Research Progress on Environmental, Health, and Safety Aspects of Engineered Nanomaterials. The National Academies Press: Washington, D.C., 2013; p 150. 3. Wang, X.; Xia, T.; Duch, M. C.; Ji, Z. X.; Zhang, H. Y.; Li, R. B.; Sun, B. B.; Lin, S. J.; Meng, H.; Liao, Y. P.; Wang, M. Y.; Song, T. B.; Yang, Y.; Hersam, M. C.; Nel, A. E., Pluronic F108 coating decreases the lung fibrosis potential of multiwall carbon nanotubes by reducing lysosomal injury. Nano Letters 2012, 12, (6), 3050-3061. 4. Xia, T. A.; Zhao, Y.; Sager, T.; George, S.; Pokhrel, S.; Li, N.; Schoenfeld, D.; Meng, H. A.; Lin, S. J.; Wang, X.; Wang, M. Y.; Ji, Z. X.; Zink, J. I.; Madler, L.; Castranova, V.; Lin, S.; Nel, A. E., Decreased dissolution of ZnO by iron doping yields nanoparticles with reduced toxicity in the rodent lung and zebrafish embryos. ACS Nano 2011, 5, (2), 1223-1235. 5. Gottschalk, F.; Kost, E.; Nowack, B., Engineered nanomaterials in water and soils: A risk quantification based on probabilistic exposure and effect modeling. Environmental Toxicology and Chemistry 2013, 32, (6), 1278-1287. 6. Schrurs, F.; Lison, D., Focusing the research effort. Nature Nanotechnology 2012, 7, (9), 546-548. 7. Oberdörster, G., Nanotoxicology: in vitro—in vivo dosimetry. Environ Health Perspect 2012, 120, (1). 8. Gangwal, S.; Brown, J. S.; Wang, A.; Houck, K. A.; Dix, D. J.; Kavlock, R. J.; Hubal, E. A. C., Informing selection of nanomaterial concentrations for ToxCast in vitro testing based on occupational exposure potential. Environ. Health Perspect. 2011, 119, (11). 9. Gottschalk, F.; Sun, T. Y.; Nowack, B., Environmental concentrations of engineered nanomaterials: review of modeling and analytical studies. Environmental Pollution 2013, 181, 287-300. 10. Von Der Kammer, F.; Ferguson, P. L.; Holden, P. A.; Masion, A.; Rogers, K. R.; Klaine, S. J.; Koelmans, A. A.; Horne, N.; Unrine, J. M., Analysis of engineered nanomaterials in complex matrices (environment and biota): general considerations and conceptual case studies. Environmental Toxicology and Chemistry 2012, 31, (1), 32-49. 11. Mueller, N. C.; Nowack, B., Exposure modeling of engineered nanoparticles in the environment. Environmental Science & Technology 2008, 42, (12), 4447-4453. 12. Keller, A. A.; McFerran, S.; Lazareva, A.; Suh, S., Global life cycle releases of engineered nanomaterials. Journal of Nanoparticle Research 2013, 15, (6), 1-17. 13. Liu, H. H.; Cohen, Y., Multimedia environmental distribution of engineered nanomaterials. Environmental Science & Technology 2014, 48, (6), 3281-3292. 14. Lazareva, A.; Keller, A. A., Estimating potential life cycle releases of engineered nanomaterials from wastewater treatment plants. ACS Sustainable Chemistry & Engineering 2014, 2, (7), 1656–1665. 15. Sun, T. Y.; Gottschalk, F.; Hungerbuhler, K.; Nowack, B., Comprehensive probabilistic modelling of environmental emissions of engineered nanomaterials. Environmental Pollution 2014, 185, 69-76.


28

Page 29 of 39

652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696


16. Handy, R. D.; Cornelis, G.; Fernandes, T.; Tsyusko, O.; Decho, A.; Sabo-Attwood, T.; Metcalfe, C.; Steevens, J. A.; Klaine, S. J.; Koelmans, A. A.; Horne, N., Ecotoxicity test methods for engineered nanomaterials: practical experiences and recommendations from the bench. Environmental Toxicology and Chemistry 2012, 31, (1), 15-31. 17. Handy, R. D.; van den Brink, N.; Chappell, M.; Muhling, M.; Behra, R.; Dusinska, M.; Simpson, P.; Ahtiainen, J.; Jha, A. N.; Seiter, J.; Bednar, A.; Kennedy, A.; Fernandes, T. F.; Riediker, M., Practical considerations for conducting ecotoxicity test methods with manufactured nanomaterials: what have we learnt so far? Ecotoxicology 2012, 21, (4), 933972. 18. Holden, P. A.; Nisbet, R. M.; Lenihan, H. S.; Miller, R. J.; Cherr, G. N.; Schimel, J. P.; Gardea-Torresdey, J. L., Ecological nanotoxicology: integrating nanomaterial hazard considerations across the subcellular, population, community, and ecosystems levels. Accounts of Chemical Research 2013, 46, (3), 813–822. 19. Kaegi, R.; Sinnet, B.; Zuleeg, S.; Hagendorfer, H.; Mueller, E.; Vonbank, R.; Boller, M.; Burkhardt, M., Release of silver nanoparticles from outdoor facades. Environmental Pollution 2010, 158, (9), 2900-2905. 20. Kaegi, R.; Ulrich, A.; Sinnet, B.; Vonbank, R.; Wichser, A.; Zuleeg, S.; Simmler, H.; Brunner, S.; Vonmont, H.; Burkhardt, M.; Boller, M., Synthetic TiO2 nanoparticle emission from exterior facades into the aquatic environment. Environmental Pollution 2008, 156, (2), 233-239. 21. Keller, A. A.; Lazareva, A., Predicted releases of engineered nanomaterials: from global to regional to local. Environmental Science & Technology Letters 2014, 1, (1), 65-70. 22. Johnson, A. C.; Park, B., Predicting contamination by the fuel additive cerium oxide engineered nanoparticles within the United Kingdom and the associated risks. Environmental Toxicology and Chemistry 2012, 31, (11), 2582-2587. 23. Gondikas, A. P.; Kammer, F. v. d.; Reed, R. B.; Wagner, S.; Ranville, J. F.; Hofmann, T., Release of TiO2 nanoparticles from sunscreens into surface waters: a one-year survey at the old Danube recreational lake. Environmental Science & Technology 2014, 48, (10), 54155422. 24. Luo, Z. X.; Wang, Z. H.; Li, Q. Z.; Pan, Q. K.; Yan, C. Z.; Liu, F., Spatial distribution, electron microscopy analysis of titanium and its correlation to heavy metals: occurrence and sources of titanium nanomaterials in surface sediments from Xiamen Bay, China. Journal of Environmental Monitoring 2011, 13, (4), 1046-1052. 25. National Research Council, Water Reuse: Potential for Expanding the Nation's Water Supply Through Reuse of Municipal Wastewater. The National Academies Press: Washington, D.C., 2012; p 262. 26. Navarro, E.; Baun, A.; Behra, R.; Hartmann, N. B.; Filser, J.; Miao, A. J.; Quigg, A.; Santschi, P. H.; Sigg, L., Environmental behavior and ecotoxicity of engineered nanoparticles to algae, plants, and fungi. Ecotoxicology 2008, 17, (5), 372-386. 27. Volker, C.; Oetken, M.; Oehlmann, J., The biological effects and possible modes of action of nanosilver. In Reviews of Environmental Contamination and Toxicology, Vol 223, Whitacre, D. M., Ed. Springer: New York, 2013; Vol. 223, pp 81-106. 28. Lara, H. H.; Garza-Trevino, E. N.; Ixtepan-Turrent, L.; Singh, D. K., Silver nanoparticles are broad-spectrum bactericidal and virucidal compounds. Journal of Nanobiotechnology 2011, 9, (30), 1-8.


29


697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742

Page 30 of 39

29. Marambio-Jones, C.; Hoek, E. M. V., A review of the antibacterial effects of silver nanomaterials and potential implications for human health and the environment. Journal of Nanoparticle Research 2010, 12, (5), 1531-1551. 30. Duran, N.; Marcato, P. D.; De Conti, R.; Alves, O. L.; Costa, F. T. M.; Brocchi, M., Potential use of silver nanoparticles on pathogenic bacteria, their toxicity and possible mechanisms of action. Journal of the Brazilian Chemical Society 2010, 21, (6), 949-959. 31. Nadeau, J. L.; Priester, J. H.; Stucky, G. D.; Holden, P. A., Bacterial Interactions with CdSe quantum dots and environmental implications. In Nanoscience and Nanotechnology, Grassian, V. H., Ed. John Wiley & Sons, Inc.: New York, 2008; pp 195-229. 32. Gomes, S. A. O.; Vieira, C. S.; Almeida, D. B.; Santos-Mallet, J. R.; Menna-Barreto, R. F. S.; Cesar, C. L.; Feder, D., CdTe and CdSe quantum dots cytotoxicity: a comparative study on microorganisms. Sensors 2011, 11, (12), 11664-11678. 33. Suresh, A. K.; Pelletier, D. A.; Doktycz, M. J., Relating nanomaterial properties and microbial toxicity. Nanoscale 2013, 5, (2), 463-474. 34. Hajipour, M. J.; Fromm, K. M.; Ashkarran, A. A.; de Aberasturi, D. J.; de Larramendi, I. R.; Rojo, T.; Serpooshan, V.; Parak, W. J.; Mahmoudi, M., Antibacterial properties of nanoparticles. Trends in Biotechnology 2012, 30, (10), 499-511. 35. Bondarenko, O.; Juganson, K.; Ivask, A.; Kasemets, K.; Mortimer, M.; Kahru, A., Toxicity of Ag, CuO and ZnO nanoparticles to selected environmentally relevant test organisms and mammalian cells in vitro: a critical review. Archives of Toxicology 2013, 87, (7), 1181-1200. 36. Costanza, R.; dArge, R.; deGroot, R.; Farber, S.; Grasso, M.; Hannon, B.; Limburg, K.; Naeem, S.; Oneill, R. V.; Paruelo, J.; Raskin, R. G.; Sutton, P.; vandenBelt, M., The value of the world's ecosystem services and natural capital. Nature 1997, 387, (6630), 253-260. 37. Tong, Z. H.; Bischoff, M.; Nies, L.; Applegate, B.; Turco, R. F., Impact of fullerene (C60) on a soil microbial community. Environmental Science & Technology 2007, 41, (8), 29852991. 38. Gardea-Torresdey, J. L.; Rico, C. M.; White, J. C., Trophic transfer, transformation, and impact of engineered nanomaterials in terrestrial environments. Environmental Science & Technology 2014, 48, (5), 2526-2540. 39. Servin, A. D.; Morales, M. I.; Castillo-Michel, H.; Hemandez-Viezcas, J. A.; Munoz, B.; Zhao, L. J.; Nunez, J. E.; Peralta-Videa, J. R.; Gardea-Torresdey, J. L., Synchrotron verification of TiO2 accumulation in cucumber fruit: a possible pathway of TiO2 nanoparticle transfer from soil into the food chain. Environmental Science & Technology 2013, 47, (20), 1159211598. 40. Westerhoff, P. K.; Kiser, A.; Hristovski, K., Nanomaterial removal and transformation during biological wastewater treatment. Environmental Engineering Science 2013, 30, (3), 109-117. 41. Lopez-Moreno, M. L.; de la Rosa, G.; Hernandez-Viezcas, J. A.; Castillo-Michel, H.; Botez, C. E.; Peralta-Videa, J. R.; Gardea-Torresdey, J. L., Evidence of the differential biotransformation and genotoxicity of ZnO and CeO2 nanoparticles on soybean (Glycine max) plants. Environmental Science & Technology 2010, 44, (19), 7315-7320. 42. Peralta-Videa, J. R.; Hernandez-Viezcas, J. A.; Zhao, L.; Diaz, B. C.; Ge, Y.; Priester, J. H.; Holden, P. A.; Gardea-Torresdey, J. L., Cerium dioxide and zinc oxide nanoparticles alter the nutritional value of soil cultivated soybean plants. Plant Physiology and Biochemistry 2014, 80, (0), 128-135.


30

Page 31 of 39

743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787


43. Priester, J. H.; Ge, Y.; Mielke, R. E.; Horst, A. M.; Moritz, S. C.; Espinosa, K.; Gelb, J.; Walker, S. L.; Nisbet, R. M.; An, Y. J.; Schimel, J. P.; Palmer, R. G.; Hernandez-Viezcas, J. A.; Zhao, L. J.; Gardea-Torresdey, J. L.; Holden, P. A., Soybean susceptibility to manufactured nanomaterials with evidence for food quality and soil fertility interruption. P. Natl. Acad. Sci. USA 2012, 109, (37), E2451-E2456. 44. Bernhardt, E. S.; Colman, B. P.; Hochella, M. F.; Cardinale, B. J.; Nisbet, R. M.; Richardson, C. J.; Yin, L. Y., An ecological perspective on nanomaterial impacts in the environment. J. Environ. Qual. 2010, 39, (6), 1954-1965. 45. Nel, A. E.; Nasser, E.; Godwin, H.; Avery, D.; Bahadori, T.; Bergeson, L.; Beryt, E.; Bonner, J. C.; Boverhof, D.; Carter, J.; Castranova, V.; DeShazo, J. R.; Hussain, S. M.; Kane, A. B.; Klaessig, F.; Kuempel, E.; Lafranconi, M.; Landsiedel, R.; Malloy, T.; Miller, M. B.; Morris, J.; Moss, K.; Oberdorster, G.; Pinkerton, K.; Pleus, R. C.; Shatkin, J. A.; Thomas, R.; Tolaymat, T.; Wang, A.; Wong, J., A multi-stakeholder perspective on the use of alternative test strategies for nanomaterial safety assessment. ACS Nano 2013, 7, (8), 6422-6433. 46. Holden, P. A.; Schimel, J. P.; Godwin, H. A., Five reasons to use bacteria when assessing manufactured nanomaterial environmental hazards and fates. Current Opinion in Biotechnology 2014, 27, 73-78. 47. Pelletier, D. A.; Suresh, A. K.; Holton, G. A.; McKeown, C. K.; Wang, W.; Gu, B. H.; Mortensen, N. P.; Allison, D. P.; Joy, D. C.; Allison, M. R.; Brown, S. D.; Phelps, T. J.; Doktycz, M. J., Effects of engineered cerium oxide nanoparticles on bacterial growth and viability. Applied and Environmental Microbiology 2010, 76, (24), 7981-7989. 48. Groh, K. J.; Dalkvist, T.; Piccapietra, F.; Behra, R.; Suter, M. J.-F.; Schirmer, K., Critical influence of chloride ions on silver ion-mediated acute toxicity of silver nanoparticles to zebrafish embryos. Nanotoxicology 2014, 0, (0), 1-11. 49. Velzeboer, I.; Peeters, E.; Koelmans, A. A., Multiwalled carbon nanotubes at environmentally relevant concentrations affect the composition of benthic communities. Environmental Science & Technology 2013, 47, (13), 7475-7482. 50. Reinsch, B. C.; Levard, C.; Li, Z.; Ma, R.; Wise, A.; Gregory, K. B.; Brown, G. E.; Lowry, G. V., Sulfidation of silver nanoparticles decreases Escherichia coli growth inhibition. Environmental Science & Technology 2012, 46, (13), 6992-7000. 51. Fairbairn, E. A.; Keller, A. A.; Maedler, L.; Zhou, D.; Pokhrel, S.; Cherr, G. N., Metal oxide nanomaterials in seawater: linking physicochemical characteristics with biological response in sea urchin development. Journal of Hazardous Materials 2011, 192, (3), 15651571. 52. Hirth, S.; Cena, L.; Cox, G.; Tomovic, Z.; Peters, T.; Wohlleben, W., Scenarios and methods that induce protruding or released CNTs after degradation of nanocomposite materials. Journal of Nanoparticle Research 2013, 15, (4). 53. American Chemistry Council Antitrust checklist for American Chemistry Council Meetings. http://chemitc.americanchemistry.com/News-Events/Past-Events/PDFAntitrust-Review.pdf (May 20, 2014), 54. United States District Court Titanium dioxide antitrust litigation; Report Number; Institution: City, Date, 2013; p 6. http://www.tio2antitrustlitigation.com/, accessed May 2014 55. Reisch, M. S., Titanium dioxide makers settle suit. Chemical & Engineering News 2013, 91, (37), 16.


31


788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833

Page 32 of 39

56. Piccinno, F.; Gottschalk, F.; Seeger, S.; Nowack, B., Industrial production quantities and uses of ten engineered nanomaterials in Europe and the world. Journal of Nanoparticle Research 2012, 14, (9). 57. Hendren, C. O.; Mesnard, X.; Droge, J.; Wiesner, M. R., Estimating production data for five engineered nanomaterials as a basis for exposure assessment. Environmental Science & Technology 2011, 45, (7), 2562-2569. 58. European Commission Commission Staff Working Paper. Types and uses of nanomaterials, including safety aspects, Accompanying the Communication from the Commission to the European Parliament, the Council and the European Economic and Social Committee on the Second Regulatory Review on Nanomaterials; SWD(2012) 288 final; European Commission: Brussels, 3.10.2012, 2012; p 111. http://ec.europa.eu/nanotechnology/pdf/second_regulatory_review_on_nanomaterials__staff_working_paper_accompanying_com(2012)_572.pdf (August 15, 2014). 59. Ebeling, M. F. E., Mediating uncertainty - Communicating the financial risks of nanotechnologies. Science Communication 2008, 29, (3), 335-361. 60. U.S. Environmental Protection Agency Final Rule: Significant New Use Rules on Certain Chemical Substances; Report Number; Institution: City, Date, 2013; pp 3821038223. http://www.gpo.gov/fdsys/pkg/FR-2013-06-26/pdf/2013-15032.pdf (August 14, 2014). 61. Waddell, W. H., Silica, Amorphous. In Kirk-Othmer Encyclopedia of Chemical Technology, John Wiley & Sons, Inc.: online, 2006; p 33. 62. Dupont, Titanium dioxide: a brief overview of TiO2 pigments compared with TiO2 nanomaterials. In Dupont: 2010. http://www.dtsc.ca.gov/TechnologyDevelopment/Nanotechnology/upload/Whiting_TiO2_Uses.pdf (August 15, 2014). 63. Eastern Research Group Scientific, Technical, Research, Engineering and Modeling Support (STREAMS) Final Report. Contract No. EP-C-05-059, Task Order No. 94. State of the science literature review: nano titanium dioxide environmental matters; EPA/600/R-1/089; Institution: Washington, D. C., Date, 2010; p 486. http://www.epa.gov/nanoscience/files/NanoPaper2.pdf (August 14, 2014). 64. Boxall, A.; Chaudhry, Q.; Sinclair, C.; Jones, A.; Aitken, R.; Jefferson, B.; Watts, C. Current and future predicted environmental exposure to engineered nanoparticles; Central Science Laboratory: York, UK, 2007. http://randd.defra.gov.uk/Document.aspx?Document=CB01098_6270_FRP.pdf (August 14, 2014). 65. Project on Emerging Nanotechnology A Nanotechnology Consumer Product Inventory. http://www.nanotechproject.org/inventories/ (August 14, 2014), 66. Berube, D. M.; Searson, E. M.; Morton, T. S.; Cummings, C. L., Project on Emerging Nanotechnologies - Consumer Product Inventory Evaluated. Nanotechnology Law & Business 2010, 7, (2), 152-163. 67. Nowack, B.; Krug, H. F.; Height, M., 120 Years of Nanosilver History: Implications for Policy Makers. Environmental Science & Technology 2011, 45, (4), 1177-1183. 68. Lorenz, C.; Hagendorfer, H.; von Goetz, N.; Kaegi, R.; Gehrig, R.; Ulrich, A.; Scheringer, M.; Hungerbuhler, K., Nanosized aerosols from consumer sprays: experimental analysis and exposure modeling for four commercial products. Journal of Nanoparticle Research 2011, 13, (8), 3377-3391.


32

Page 33 of 39

834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877


69. Norgaard, A. W.; Larsen, S. T.; Hammer, M.; Poulsen, S. S.; Jensen, K. A.; Nielsen, G. D.; Wolkoff, P., Lung Damage in Mice after Inhalation of Nanofilm Spray Products: The Role of Perfluorination and Free Hydroxyl Groups. Toxicological Sciences 2010, 116, (1), 216-224. 70. European Commission Technical Guidance Document on Risk Assessment in support of Commission Directive 93/67/EEC on Risk Assessment for new notified substances Commission Regulation (EC) No 1488/94 on Risk Assessment for existing substances Directive 98/8/EC of the European Parliament and of the Council concerning the placing of biocidal products on the market; EUR 20418 EN/4; Institution: Luxembourg, Date, 2003. http://ihcp.jrc.ec.europa.eu/our_activities/publichealth/risk_assessment_of_Biocides/doc/tgd (August 14, 2014). 71. Krug, H.; Wick, P.; Nowack, B.; Mü ller, N. Human and Ecotoxicity of Synthetic Nanomaterials: Initial Insights for Major Accident Prevention; UW-1301-E Federal Office for the Environment FOEN Bern, 2013; p 44. http://www.bafu.admin.ch/publikationen/publikation/01697/index.html?lang=en (August 14, 2014). 72. Grieger, K. D.; Laurent, A.; Miseljic, M.; Christensen, F.; Baun, A.; Olsen, S. I., Analysis of current research addressing complementary use of life-cycle assessment and risk assessment for engineered nanomaterials: have lessons been learned from previous experience with chemicals? Journal of Nanoparticle Research 2012, 14, (7), 1-23. 73. U.S. Environmental Protection Agency Nanomaterial Case Studies: Nanoscale Titanium Dioxide in Water Treatment and in Topical Sunscreen (Final); EPA/600/R09/057F; U.S. Environmental Protection Agency: Research Triangle Park, NC, November, 2010, 2010; p 204. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=230972 (August 14, 2014). 74. Klaessig, F.; Marrapese, M.; Abe, S., Current Perspectives in Nanotechnology Terminology and Nomenclature. Nanostructure Science and TechnologyNanotechnology Standards 2011, (2), 22-52. 75. Kim, B.; Murayama, M.; Colman, B. P.; Hochella, M. F., Characterization and environmental implications of nano- and larger TiO2 particles in sewage sludge, and soils amended with sewage sludge. Journal of Environmental Monitoring 2012, 14, (4), 11291137. 76. Weir, A.; Westerhoff, P.; Fabricius, L.; Hristovski, K.; von Goetz, N., Titanium dioxide nanoparticles in food and personal care products. Environmental Science & Technology 2012, 46, (4), 2242-2250. 77. Liu, J. Y.; Hurt, R. H., Ion release kinetics and particle persistence in aqueous nanosilver colloids. Environmental Science & Technology 2010, 44, (6), 2169-2175. 78. Akaighe, N.; MacCuspie, R. I.; Navarro, D. A.; Aga, D. S.; Banerjee, S.; Sohn, M.; Sharma, V. K., Humic acid-induced silver nanoparticle formation under environmentally relevant conditions. Environmental Science & Technology 2011, 45, (9), 3895-3901. 79. Lombi, E.; Donner, E.; Tavakkoli, E.; Turney, T. W.; Naidu, R.; Miller, B. W.; Scheckel, K. G., Fate of zinc oxide nanoparticles during anaerobic digestion of wastewater and posttreatment processing of sewage sludge. Environmental Science & Technology 2012, 46, (16), 9089-9096.


33


878 879 880 881 882 883 884 885 886 887 888 889

Page 34 of 39

80. Santos, L.; Araujo, A. N.; Fachini, A.; Pena, A.; Delerue-Matos, C.; Montenegro, M., Ecotoxicological aspects related to the presence of pharmaceuticals in the aquatic environment. Journal of Hazardous Materials 2010, 175, (1-3), 45-95. 81. Brausch, J. M.; Connors, K. A.; Brooks, B. W.; Rand, G. M., Human Pharmaceuticals in the Aquatic Environment: A Review of Recent Toxicological Studies and Considerations for Toxicity Testing. Reviews of Environmental Contamination and Toxicology, Vol 218 2012, 218, 1-99. 82. Pidgeon, N.; Harthorn, B. H.; Bryant, K.; Rogers-Hayden, T., Deliberating the risks of nanotechnologies for energy and health applications in the United States and United Kingdom. Nature Nanotechnology 2009, 4, (2), 95-98.


34

Page 35 of 39

890 891 892 893 894 895


Table 1. Modeled or measured MNM concentration magnitudes by MNM category for two environmental compartments (separated by a bold line): water (surface water or WWTP effluent), and solid media (biosolids, soil, sediments). Concentration ranges (bins) span ≤0.001 to >1000 ppm, with intervening 10-fold ranges. These match the hazard assessment MNM concentration data categorization described in the Methods, and in Table S1. Modeled versus measured concentrations are not distinguished where “both” are indicated (2nd column from left). WWTP= wastewater treatment plant. The lowest and highest bin magnitudes for each compartment, across MNM categories, appear in “bold” font. Bins in brackets were gaps in the source data. Modeled Modeled or Measured MNM Environmental Concentration Ranges According to Compartment or MNM Category (ppm) Source measured Metal oxides Metals Carbonaceous ≤0.001; 0.0011-0.01 ≤0.001 ≤0.001 water: surface both Gottschalk water et al.9 ≤0.001 ≤0.001 ≤0.001 modeled Liu and water: WWTP effluent

≤0.001; [0.0011-0.01]; 0.0110.10; 0.11-1 ≤0.001; 0.0011-0.01; 0.0110.10

≤0.001; [0.0011-0.01]; 0.011-0.10 ≤0.001; 0.0011-0.01; 0.0110.10

≤0.001; 0.0011-0.01; 0.011-0.10 ≤0.001

≤0.001; [0.0011-0.01]; 0.0110.1; 0.11-1; 1.1-10; 10.1100; 100.1-1000; >1000 1.1-10; 10.1-100; 100.1-1000

0.0011-0.01; 0.0110.1

modeled

≤0.001; [0.0011-0.01]; [0.011-0.10]; 0.11-1; 1.1-10 ≤0.001

≤0.001; 0.0011- 0.01; 0.011-0.1; 0.11-1; 1.1-10; 10.1-100 0.0011-0.01; 0.011-0.1; 0.11-1; 1.1-10; 10.1-100; 100.1-1000 ≤0.001; 0.0011-0.01; 0.0110.10 ≤0.001

both

0.011-1; 1.1-10; 10.1-100

0.0011-0.01; 0.011-0.10

modeled

0.0011-0.01; 0.011-0.10; 0.11-1; 1.1-10

≤0.001

≤0.001; 0.0011-0.01; 0.011-0.10; 0.11-1; 1.1-10 ≤0.001; 0.0011-0.01; 0.011-0.1

both modeled

solid media: biosolids

both

modeled

solid media: soil

solid media: sediments

both


Cohen13 Gottschalk et al.9 Keller and Lazareva21 Gottschalk et al.9

0.11-1; 1.1-10

Keller and Lazareva21

≤0.001; 0.0011- 0.01

Gottschalk et al.9 Liu and Cohen13 Gottschalk et al.9

≤0.001

Liu and Cohen13

35


896 897 898 899 900

Page 36 of 39

Table 2. Mode, median and mean exposure values (ppm), by receptor or compartment and across all MNMs, calculated from administered MNM concentrations used in published nanotoxicology hazard assessments (Table S1). The number of individual concentrations excerpted across the surveyed 615 published articles is indicated by “n”. Receptor or compartment

n

Aquatic organisms Microorganisms Soil/Sediment/Wastewater Terrestrial plants

733 575 90 294

Calculated MNM concentration statistic (ppm) mode Median mean 5.1 0.6 71.0 55.1 5.6 361.6 550.1 55.1 1183.5 55.1 55.1 860.2

901 902


36

Page 37 of 39

903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948


Figure 1. Histograms of the number of nanotoxicology hazard assessment publications over the period 2008-2013 that report administering MNMs at various MNM concentrations, binned by orders of magnitude from ≤0.001 to >1000 ppm. Distributions are for: aquatic organisms (a), microorganisms (b), soil/sediment/wastewater (c) and terrestrial plants (d). Bar shading denotes MNM material category: dark solid = metal oxide; light solid = metal; diagonal lines = carbonaceous; and unfilled = quantum dots. Blue coloring of bars in parts a) and c) denote ranges for which MNM environmental concentrations have been modeled or measured for waters (surface water and WWTP effluent) and solid media (soils, sediments, and biosolids), respectively (Table 1). These ranges are not overlain in b) or d), since modeled water concentrations (Table 1) can more readily be compared to aquatic organisms exposure levels in toxicity testing (a); similarly, modeled solid media concentrations (i.e. soils, sediments and biosolids, Table 1) can be more readily compared to the soil/sediment/wastewater exposure levels in toxicity assessments (c).


37


Page 38 of 39

949 950

951 952 953 954 955 956 957 958 959

Figure 2. Global production volumes (tons per year), growth expectations (relative to gross domestic product or GDP), and primary uses for selected nanomaterials (left and right, colored arrows with sector or product labels). Arrows are differently colored for readability; otherwise, the colors have no specific meaning. The development of volume data is discussed in more detail in the Supporting Information and in Table S3.


38

Page 39 of 39


960 961

962 963 964 965 966 967

TOC Art

968 969 970 971 972 973 974


39

Evaluation of Exposure Concentrations Used in ... - ACS Publications

Recommend Documents