Characteristics of Tire Wear Particles Generated by a Tire Simulator

Subscriber access provided by UNIV TEXAS SW MEDICAL CENTER

Characterization of Natural and Affected Environments

Characteristics of tire wear particles generated by a tire simulator under various driving conditions Gibaek Kim, and Seokhwan Lee Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b03459 • Publication Date (Web): 02 Oct 2018 Downloaded from http://pubs.acs.org on October 9, 2018

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 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 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.

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 30

Environmental Science & Technology

1

Characteristics of tire wear particles generated by a tire simulator under various

2

driving conditions

3 4

Gibaek Kim and Seokhwan Lee*

5

Department of Engine Research, Korea Institute of Machinery and Materials, 156,

6

Gajeongbuk-ro, Yuseong-gu, Daejeon 34103, Republic of Korea

7 8 9

*Corresponding author: [email protected]

10 11 12 13 14 15 16 17 18 19 20 21

KEYWORDS: Enclosing chamber; particulate matter; tire wear particles (TWPs); tire

22

simulator; ultrafine particles

23

1

ACS Paragon Plus Environment


24

Table of Contents (TOC)/Abstract Art.

25 26

2


Page 2 of 30

Page 3 of 30


27

ABSTRACT

28

Physicochemical properties of pure tire wear particles (TWPs) were investigated in a

29

laboratory. A tire simulator installed in an enclosing chamber was employed to eliminate

30

artifacts caused by interfering particles during the generation and measurement of TWPs.

31

TWP particulate matter (PM2.5 and PM10) was correlated with tire speed (r > 0.94) and load (r

32

> 0.99). Their mass size distributions showed that TWP mode diameters ranged between 3

33

and 4 µm (unimodal). Tire wear caused by slip events resulted in an increase in the number

34

concentration (ca. 8.4 × 105 cm–3) of particles (mainly ultrafine particles (UFPs)) at low

35

PM2.5 and PM10 values (1 and 2 µg m–3, respectively). During braking events, UFPs were

36

emitted at an early stage, with an increase in number concentration (up to 1.1 × 107 cm–3); a

37

high mass concentration (3.6 mg m–3) was observed at a later stage via the coagulation of

38

early emitted UFPs and condensation. On the basis of morphology and elemental

39

composition, TWPs generally had elongated (micron-scale) and round/irregular (submicron-

40

scale) shapes and they were classified into C/Si-rich, heavy metal-containing, S-containing,

41

and mineral-containing particles. This study determined that TWP emissions can vary with

42

changes in driving condition.

43 44

3



45

1. INTRODUCTION

46

Airborne particulate matter (PM) can cause adverse health effects,1 visibility

47

impairment,2 and climate change.3 PM consists of particles of varying sizes and chemical

48

compositions4 and PM level (i.e., mass concentration) is currently being used as a barometer

49

for air quality legislation and guidelines.5

50

Atmospheric particles have a variety of natural and anthropogenic sources6 and road

51

traffic is known to be an important contributor to PM in urban areas.7 Traffic-related particles

52

typically originate from exhaust and non-exhaust emission sources.8 In particular, the

53

emission of exhaust particles can be caused by incomplete fuel combustion and lubricant

54

volatilization,9 whereas non-exhaust particles can be generated through tire, braking, and road

55

wear processes, as well as through road dust re-suspension.10, 11 Since stringent emissions

56

regulations and the adoption of cleaner fuels can lead to substantial reductions in exhaust

57

emissions,12 the relative contribution of tire and road wear particles to PM is expected to

58

gradually increase.13 Note that it has been reported that regenerative braking can lead to

59

reduction of brake wear particles.14

60

Several efforts have been made toward characterizing the properties of non-exhaust

61

particles in the laboratory15-19 and on-road13, 20, 21 measurements. However, studies focusing

62

on tire wear particles (TWPs) are relatively rare and TWPs have been less well characterized

63

than other non-exhaust particles. Moreover, the reliability of the reported physical properties

64

of TWPs might be in question because they varied widely among early studies, denoting

65

significant uncertainties.22 The primary reasons for such discrepancies in the literature might

66

be differences in experimental methods (i.e., the absence of a standard protocol)22 and

67

difficulty in excluding background and other unwanted particles from TWP measurements.19

4


Page 4 of 30

Page 5 of 30


68

In particular, the elimination of artifacts caused by the presence of interfering particles (e.g.,

69

road dust, brake wear, and other particles) could be of key importance for accurate TWP

70

analysis.23 Nevertheless, particle measurements in most previous studies of non-exhaust

71

particles have been conducted without attempting to segregate TWPs, instead examining a

72

complex mixture of diverse particles. Therefore, it has remained difficult to accurately

73

determine the physical and chemical properties of TWPs.

74

It has been reported that the physical and chemical properties of TWPs can be

75

influenced by a variety of factors, such as the characteristics of vehicles, tires, road surfaces,

76

and driving conditions.10 Contact between tires and the road surface can lead to shear force

77

and evaporation of tires. Shear force can trigger the release of relatively large, coarsely

78

distributed particles, whereas evaporation can induce the emission of comparatively fine

79

particles.22 Once emitted, TWPs can be found in all environmental compartments, including

80

the atmosphere, soil, and water.24, 25 In addition, tire wear can be considered as one of the

81

most important global contributors to the releases of microplastics (MPs) in the

82

environment.23, 26, 27

83

Accurate measurement of TWPs is essential for determining their exact role in

84

human health and the ecosystem, because their impact depends on the size, concentration,

85

and chemical constituents of particles.28-30

86

It is difficult to avoid mixing TWP with other non-negligible particles under realistic

87

on-road driving conditions.31 In this study, TWPs were generated by a tire simulator that can

88

mimic various driving conditions in the laboratory, and that allows precise control and

89

determination of other factors affecting the generation of TWPs. This lambourn-like wear

90

simulator has been often employed in the laboratory studies and this setup might be useful to

5



91

estimate tire wear based on Schallamach’s theory31 describing that the abrasion quantity is

92

proportional to the abrasion per unit energy dissipation, the sliding distance, and the normal

93

force.

94

The physical properties of TWPs were then measured in real time in an enclosing

95

chamber, which excluded background and contamination particles. In addition, we conducted

96

off-line morphological and elemental analyses of the particles. To our knowledge, this is the

97

first report of the physical properties of pure TWPs generated under various driving

98

conditions.

99 100

2. MATERIALS AND METHODS

101

2.1. Tire material

102

The effects of driving conditions on the physical properties of TWPs were

103

investigated using a single type of tire, because tire wear is dependent on both the driving

104

conditions and physical characteristics of the tire. We selected a commercial non-studded tire

105

that is widely used in Korea as the test tire (Ecowing, Kumho, Korea). According to uniform

106

tire quality grading (UTQG),33 the specifications of this tire (code: 205/55R16 94V) include

107

440 treadwear; the tire is rated grade A in terms of both traction and temperature. The tire

108

pressure was set to 36 psi and the tire was tightly connected to the shaft of the driving control

109

unit of the tire simulator.

110 111

2.2. Tire simulator

112

The tire simulator (NEOPLUS Inc., Daejeon, Korea) consisted of a rotating drum, a

113

test tire, and a control system (Figure 1). The tire simulator can control lateral load (100–

6


Page 6 of 30

Page 7 of 30


114

8,000 N), drum speed (20–180 km h–1), tire speed (20–180 km h–1), and slip speed (–20 to 20

115

km h–1). These parameters were controlled and recorded every second. Driving speed was

116

controlled by the rotating speed of the drum. The diameter of the rotating drum was 1.2 m

117

and the drum surface was coated with 80-grit sandpaper to simulate the roughness of asphalt

118

pavement.34 The sandpaper used in this study also has a wear-resistant surface option, such

119

that the influence of track abrasion can be eliminated or at least minimized during TWP

120

measurements.19 It is important to announce that our tire simulator might not provide real-

121

world conditions since the road material, the tire contact stress, direction of the load transfer

122

(vertical vs. horizontal), and aerodynamics in the chamber differ from those of real-driving

123

conditions on the road.

124 125

2.3. Enclosing chamber

126

The tire simulator was operated within an enclosing chamber (length: 3.5 m × width:

127

2.4 m × height: 2.2 m) equipped with a series of sampling ports. The first blower (left)

128

supplied particle-free air through high-efficiency particulate air (HEPA) filters and the second

129

blower (light) ensured that backward flow into the chamber was prevented. The flow rate

130

(110 ± 9 L min–1) was monitored by an anemometer (TA 460; TSI Instruments, Shoreview,

131

MN, USA) installed in the sampling port and was maintained during the measurement period.

132

To reduce particle loss, stainless steel sampling ports were connected to measurement

133

instruments using conductive tubes.

7



134 135

Figure 1. Schematic of the tire simulator operated within the enclosing chamber and the

136

measurement setup.

137

Because the two blowers were activated simultaneously, number concentration in the

138

chamber, which was measured using a condensation particle counter (CPC) (3010D; TSI)

139

was close to 0 cm–3 (Figure S1) and the chamber was kept in a clean condition until the tire

140

wear process was started.

141 142

2.4. Instrumentation

143

Several particle instruments were installed downstream of the chamber. As TWPs

144

were generated, real-time measurements of number concentrations, number and mass size

145

distribution, and PM concentration were implemented simultaneously. We also conducted

146

particle collection for off-line morphological and elemental TWP analyses.

147

A Fast Mobility Particle Sizer (FMPS) spectrometer (3091; TSI) equipped with a

148

cyclone (50% cut-off diameter of 1 µm), which has an aerosol flow rate of 10 L min–1, sheath

149

air flow rate of 40 L min–1, and time resolution of 1 s, was used to measure particle number

150

concentrations and number size distributions (5.6–560 nm).

151

An aerodynamic particle sizer (APS) (3321; TSI) was used to determine the mass

152

size distributions of particles ranging from 0.5 to 20 µm in aerodynamic diameter (52 8


Page 8 of 30

Page 9 of 30


153

channels) at a sample flow rate of 1 L min–1.

154

PM can be divided into PM2.5 and PM10, i.e., particles with aerodynamic diameters

155

smaller than 2.5 µm and 10 µm, respectively. PM is often measured using two different

156

methods: gravimetric analysis of particles collected on the filter or substrate, and real-time

157

PM estimation via a light-scattering method. In this study, we used the latter method because

158

a real-time technique is more appropriate to monitor rapid changes in PM levels. An optical

159

particle counter (OPC) (GRIMM 180; GRIMM, Ainring, Germany) was used to determine

160

the PM concentrations (PM2.5, PM10, and PM2.5/PM10) of TWPs at a flow rate of 1.2 L min–1

161

and time resolution of 6 s.

162

To examine their morphology and elemental composition, TWPs were collected and

163

then analyzed by transmission electron microscopy (TEM) (Tecnai F20; Philips, Andover,

164

MA, USA) with energy dispersive spectroscopy (EDS) (R-TEM, CM200-UT; Philips,

165

Ventura, CA, USA), as well as scanning electron microscopy (SEM) (SU-70; Hitachi, Tokyo,

166

Japan) with EDS (EDAX; Ametek Inc., Mahwah, NJ, USA). TWPs were collected for TEM

167

sampling on a carbon film-coated 200 mesh copper grid (CF200-Cu; Electron Microscopy

168

Sciences, Hatfield, PA, USA) using a mini particle sampler (MPS) (Ecomesure, Janvry,

169

France). For SEM sampling, TWPs were collected on a membrane filter with a diameter of

170

47 mm and pore size of 0.4 µm (Nuclepore Track-Etch Membrane; Whatman Inc., Maidstone,

171

UK) using a PM10 cyclone (URG-2000; URG Corp., Chapel Hill, NC, USA) with a flow rate

172

of 16.7 L min–1. The SEM samples were treated with platinum sputtering for clear image

173

acquisition.

174 175

9



176

3. RESULTS AND DISCUSSION

177

3.1. Effect of driving speed

178

Under a steady lateral load of 1,000 N, the tire simulator was run to generate TWPS

179

at driving speeds of 50, 80, 110, and 140 km h–1. The resulting TWPs were measured to

180

investigate the effect of driving speed on TWP emissions. Figure 2a shows the average PM2.5,

181

PM10, and PM2.5/PM10 ratio values; error bars indicate standard deviation (i.e., standard

182

deviation obtained from 98 measurements for each error bar). The PM concentrations and

183

PM2.5/PM10 ratio tended to increase as the driving speed increased. The measured PM2.5,

184

PM10, and PM2.5/PM10 ratio had linear relationships with driving speed, with correlation

185

coefficients (r) of 0.9840, 0.9355, and 0.9911, respectively. The PM2.5/PM10 ratio, which

186

indicates the relative contribution of PM2.5 to PM10,35 ranged from 0.24 to 0.32. Figure 2b

187

shows the average TWP mass size distribution; error bars indicate standard deviation. Overall

188

TWP mass concentrations (µg m–3) increased at higher driving speeds. The TWP mass size

189

distributions obtained in this study demonstrated that particles were mainly 3–4 µm in

190

aerodynamic diameter, with a unimodal distribution within the speed ranges investigated. The

191

mode concentration of mass size distribution (i.e., concentration in the peak bin) increased as

192

speed increased (r = 0.9688).

193

(a)

10


Page 10 of 30

Page 11 of 30


194 195

(b)

196 197

Figure 2. (a) Average particulate (PM)2.5 and PM10 concentrations, PM2.5/PM10 ratio, and (b)

198

mass size distributions by mode concentration under constant driving speeds (50, 80, 110,

199

140 km h–1).

200

PM levels (PM2.5, PM10, and PM2.5/PM10 ratio) and mass size distributions of TWPs

201

were positively correlated with driving speed. PM2.5 and the PM2.5/PM10 ratio continuously

202

increased as driving speed increased (from 50 to 140 km h–1), and PM10 tended to level off at

203

speeds between 110 and 140 km h–1. TWPs are known to be generated by shearing forces36

204

and through volatilization.13 The former mechanism predominantly results in coarse particles, 11



205

whereas the latter generates smaller fine particles through the evaporation of volatile content.

206

Thus, we believe that shear stress acting on the tire surface was limited, and that the

207

volatilization process became relatively dominant at the high speeds produced in our

208

laboratory experiments. As a result, fewer PM10 particles were generated, leading to PM10

209

saturation, unlike PM2.5 and the PM2.5/PM10 ratio. Whether this result was due to instrumental

210

limitations or properties inherent to TWPs remains to be investigated.

211

Driving speed appeared not to significantly affect the TWP mass size distribution,

212

whereas its concentration tended to increase with elevated driving speed. It is worth

213

mentioning that Grigoratos et al.18 reported that the treadwear rating (TWR) also appeared

214

not to affect the shape of mass size distributions of TWPs measured by APS. Hussein et al.37

215

and Kwak et al.20 reported unimodal TWP mass size distributions with mode diameters of 2–

216

3 µm and 3–5 µm, respectively; our results show reasonable agreement with these previously

217

reported values. However, the TWP mass concentrations observed in this study were

218

relatively low, possibly due to the effects of background particles or differences in

219

experimental methods (i.e., on-road vs. laboratory measurements). Note that our laboratory

220

facility may not have been capable of perfectly simulating real driving conditions. However,

221

we can rule out the presence of contaminating particles as an influencing factor.

222 223

3.2. Effect of load

224

Under a consistent speed of 110 km h–1, the tire simulator was operated with lateral

225

loads of 500, 1,000, 1,500, 2,000, and 2,500 N. The TWPs emitted were then measured to

226

investigate the effect of load on TWP emission. Figure 3a shows the average PM

227

concentrations and PM2.5/PM10 ratios of TWPs; error bars indicate standard deviation. Both 12


Page 12 of 30

Page 13 of 30


228

PM2.5 and PM10 proportionally increased as the load increased. As a result, there were linear

229

correlations between the lateral load and PM concentration (PM2.5: r = 0.9937, PM10: r =

230

0.9922). However, the PM2.5/PM10 ratio decreased as the load increased (0.77 at 500 N, 0.31

231

at 2,500 N). Figure 3b shows the average mass size distributions of TWPs generated with

232

increased loads; TWP mass concentrations (µg m–3) increased as load increased, with a

233

unimodal distribution (mode diameter: 3–4 µm). The mass size distribution mode

234

concentration exhibited a higher correlation coefficient (0.9921) than that observed under

235

constant driving speeds (50, 80, 110, and 140 km h–1).

236

(a)

237 238

(b)

13



239 240

Figure 3. (a) Average PM2.5 and PM10 concentrations, PM2.5/PM10 ratio, and (b) mass size

241

distributions by mode concentration under consistent loads (500, 1,000, 1,500, 2,000, and

242

2,500 N).

243

Despite insufficient direct research, it has been speculated that tire wear might be

244

affected by vehicle weight,14 and that higher PM concentrations could be emitted by heavier

245

vehicles.38 The current study demonstrated that TWP emissions can be quantitatively affected

246

by the load applied on the tire surface. Additionally, load was found to have a more

247

pronounced effect than driving speed on PM2.5 and PM10 concentrations, as shown by the

248

higher correlation coefficients. In contrast, the PM2.5/PM10 ratio decreased as load increased.

249

This decaying tendency can be explained by enhanced shear force due to the increased load

250

on the tire surface. As mentioned earlier, coarse particles emitted from the tire have been

251

associated with shear force. The emission of particles greater than 2.5 µm typically increases

252

with increases in load. Consequently, the fraction of particles corresponding to PM10

253

dominated that of particles smaller than 2.5 µm (PM2.5) in the current study, leading to a

254

decrease in the ratio of PM2.5 to PM10. Moreover, PM10 concentration was 3.8 times more

255

sensitive than PM2.5 concentration, based on the relationship between PM concentration and 14


Page 14 of 30

Page 15 of 30


256

load, suggesting a greater influence of load on PM10; e.g., the PM10 concentration was 2.1

257

times more sensitive than the PM2.5 concentration to changes in driving speed. In terms of

258

mass size distribution, a tendency toward a more linear mode concentration of TWPs

259

generated under increased load was seen compared to that obtained under the constant

260

driving speed conditions, because saturation behavior of PM concentration was not observed

261

within the load ranges tested. This result indicates that the shear stress driven by load was

262

proportionally transferred to the tire surface. As a result, the relationship between load and

263

PM emission was more apparent.

264 265

3.3. Effect of slip speed

266

Under a constant driving speed and lateral load (80 km h–1 and 100 N), tire wear

267

(caused by a difference in speed between the tire and drum of the tire simulator) occurred at

268

slip speeds of 0, –2, –4, –6, –8, and –10 km h–1. Figure 4 shows a contour plot of size

269

distributions and the total number concentration of TWPs as a function of slip speed. As the

270

slip speed reached –10 km h–1, significant particle generation occurred, lasting until the slip

271

event ended. The total TWP number concentration measured by the FMPS (5.6–560 nm)

272

dramatically increased, to 8.4 × 105 cm–3. TWPs generated by the slip event were dominated

273

by particles smaller than 100 nm in diameter (i.e., ultrafine particles (UFPs)). However, the

274

slip events produced very low PM2.5 and PM10 concentrations (1 and 2 µg m–3, respectively).

275

There were no significant correlations between PM concentration and slip speed (data not

276

shown).

15



277

278

Figure 4. Number size distribution and total number concentration of tire wear particles

279

(TWPs) emitted under a constant slip speed (0, –2, –4, –6, –8, and –10 km h–1).

280

It has been reported that UFPs can be produced by gas-to-particle conversion of

281

evaporated compounds emitted from the tire surface,13 and that once slip speed exceeds a

282

certain tolerance limit, significant emission of UFPs can begin. UFPs contribute little to mass

283

concentration and they are not currently regulated. However, they are believed to have a

284

greater impact on health than PM2.5 and PM10.39 In fact, the critical point at which significant

285

UFP generation from tires begins might vary among tire types and experimental conditions.

286

Thus, further studies are required to relate UFP emissions from tires with tire type and

287

driving conditions.

288 289

3.4. Effect of harsh braking

16


Page 16 of 30

Page 17 of 30


290

We simulated harsh braking conditions in the laboratory, defining a harsh braking

291

event as a full stop of the tire from high speed (ca. 130 km h–1). In more detail, harsh braking

292

events consisted of the following steps: acceleration (2.3 km h–1 s–1), deceleration (–12.5 km

293

h–1 s–1), and full stop. Deceleration was performed 5.3 times faster than acceleration; however,

294

more severe braking conditions were not achievable due to instrument limitations. This harsh

295

braking simulation was conducted within 1 min. Figure 5a illustrates the number size

296

distribution and total number concentration of TWPs generated during harsh braking events.

297

An exponential increase in number particle concentration was observed, leading to

298

exceedingly high concentrations (ca. 1.1 × 107 cm–3); the mode diameters of number size

299

distributions ranged between 40 and 60 nm during harsh braking events. Following the

300

exponential increase in the number of particles, TWP mass concentration also started to

301

increase significantly. As shown in Figure 5b, increases in PM concentration were observed

302

twice, during and after each harsh braking event. The first peaks were observed at the

303

beginning of the harsh braking event (PM2.5 = 80 and PM10 = 348 µg m–3) and the largest

304

peaks were observed during the later stage (PM2.5 = 717 and PM10 = 3,585 µg m–3). The

305

mode diameters of mass size distribution were determined by APS to be ca. 4–7 µm. Particle

306

number size distributions measured by APS were converted to mass size distributions and PM

307

concentrations under the assumption that TWPs are spherical, with a density of 1.2 g cm–3.40

308

(a)

17



309 310

(b)

311 312

Figure 5. (a) Particle number size distribution and (b) mass size distribution of TWPs

313

generated during the harsh braking simulation. 18


Page 18 of 30

Page 19 of 30


314

To obtain mass data based on the number of particles, it is necessary to determine the

315

particle density. In TWP research, it has often been assumed that TWPs are spherical, with a

316

density of 2.8 g cm–3.15, 34, 37 However, TWP density might be closer to that of road dust. For

317

example, soil particle density is in the range of 2.6–2.7 g cm–3.41 Previous studies may have

318

focused on non-exhaust particles in a mixture state (i.e., tire wear and road wear particles

319

including road dust) rather than on pure TWPs. Since rubber is the main component of tire

320

material, we assumed that TWPs are spherical particles with a density of 1.2 g cm–3,40 to

321

convert number size distribution measured by APS to mass size distribution and PM

322

concentration. Although we considered TWP density to reflect the main tire composition,

323

TWP density may differ from our assumption because the tread surface might experience

324

thermal decomposition, leading to changes in the physical and chemical properties of TWPs

325

during wear processes.42

326

It has been reported that a small proportion of tire wear materials (< 10%) can be

327

emitted as PM10 under typical driving conditions.43 However, in this study, TWPs generated

328

during the harsh braking experiment led to significant increases in both number and mass

329

concentrations. The first PM concentration peak occurred at the moment when the harsh

330

braking event occurred, followed by even higher PM concentrations (9–10 times) as a result

331

of coagulation and condensation after the harsh braking event had ended. It has been reported

332

that particles can be emitted from tires at temperatures exceeding 180°C.42 Although

333

temperature was not measured directly in the current study, a high tire surface temperature

334

can be inferred from the formation of visible smoke close to the contact surface between the

335

tire and drum during harsh braking. Accordingly, volatile material from the tire clearly

336

evaporated as the tire cooled down. The particle size distribution subsequently shifted

19



337

towards larger particles through particle coagulation and condensation, resulting in a high

338

number concentration followed by a high mass concentration (Figure 5).

339 340

3.5. Morphological and elemental properties

341

The morphology and elemental composition of TWPs were analyzed by TEM/EDS

342

(Figure 6) and SEM/EDS (Figure 7), respectively. TWPs were classified into three groups,

343

based on their morphological properties: elongated, round, and irregular particles. Micron-

344

size TWPs were often elongated in shape, whereas submicron-sized TWPs tended to be round

345

or irregular. As a result of EDS analysis, TWPs were found to have wide-ranging elemental

346

compositions (Al, Ba, C, Ca, Cl, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, O, S, Si, Ti, and Zn),

347

agreeing well with the results of previous studies.44, 45 Note that the presence of Pt detected

348

by SEM/EDS (Figure 7) was due to sputter deposition. Based on their elemental properties,

349

TWPs were categorized into four main groups: C/Si-rich, heavy metal-containing, S-

350

containing, and mineral-containing particles. C/Si-rich particles were by far the most

351

frequently observed particles in EDS analysis among all TWP elemental composition

352

categories.

353

A previous study36 reported TWP morphological properties, including an elongated

354

shape, that are consistent with our findings. The number of particles (131) analyzed in this

355

study was insufficient to reach a clear conclusion. Nevertheless, data on morphological and

356

elemental properties can still provide useful information on the types of TWPs. TWPs can be

357

generated mechanically, producing coarse particles with elongated shapes. They can also be

358

formed through gas-to-particle conversion processes, leading to smaller particles with a

359

round/irregular morphology. TWPs that are sufficiently large (i.e., micron-sized) to efficiently

20


Page 20 of 30

Page 21 of 30


360

contribute to mass concentration are often not spherical, informing the likelihood of non-

361

TWP artifacts being present among the particles, since traditional techniques assume that the

362

particles are spherical. Our morphological findings highlight the challenging task of

363

determining the PM2.5 and PM10 of TWPs using current methods.

364

C, Si, and Zn are abundant elements used in tire manufacturing. In particular, C is the

365

main component of tire treads and carbon black (CB), and SiO2 is commonly used as a

366

reinforcing filler.46 Zn can be found in the form of ZnO, which is added to strengthen the

367

tire,47 and S is used to prevent tire deformation at high temperatures.48 Although the Zn found

368

in TWPs can be also found on paved surfaces,49 Zn has often been used as a TWP indicator

369

because it is present in tire treads at relatively high quantities (ca. 1 wt %).50 In addition,

370

fillers in tread compounds can contain mineral elements (i.e., mineral fillers).51 Elements

371

commonly used in tire manufacturing were detected using our off-line technique. Our

372

morphological and chemical data suggest that the particles analyzed in the current study were

373

mainly TWPs, and not contamination particles from other sources.

374 375

3.6. Emission behavior of tire wear particles under various driving conditions

376

Table 1 provides an overview of the tire wear and emission behaviors of TWPs under

377

the various driving conditions simulated in this study. Four different data sets (A–D) are

378

summarized in terms of tire speed, load, slip speed, and harsh braking. PM2.5 and PM10 data

379

in Table 1 were determined by APS and OPC, generally showing 2–4 fold variation. Tests A

380

and B (i.e., normal driving conditions) exhibited similar wear rates and PM2.5 and PM10

381

emissions. Tire tread losses were ca. 100–150 times higher in Tests C and D (i.e., harsh

382

driving conditions) than in Tests A and B. Large increases in tire tread loss and PM emission

21



383

were observed in Test D. However, Test C showed the lowest PM emission results, despite

384

having the second largest tire tread loss.

385

As shown in Table 1, data obtained from two instruments (APS and OPC) showed

386

significant uncertainty, which created difficulty in interpreting TWP emission behavior.

387

Unfortunately, there is no clear reason for the disagreement in results between these

388

commercial instruments; the discrepancy may have been due to the non-spherical but

389

complicated shapes of TWPs at varying densities resulting from complex physicochemical

390

degradation processes occurring at the tire surface during wear. However, the data showed

391

that the TWP emission pattern was a function of driving conditions, which appeared to cause

392

tire wear and TWP emission behavior to vary greatly. Despite the remarkable tire tread loss

393

observed in Test C (slip event), the lowest PM emission was observed in that test because

394

TWPs generated by the slip event did not effectively increase the mass concentration of

395

airborne particles (i.e., release of either UFPs or particles > 10 µm). Since wear rate and PM

396

emission can vary greatly depending on the tire types and testing method,22,37 further study is

397

required.

398

Our results demonstrated that the physical properties of TWPs can vary with driving

399

conditions including tire speed, load, slip speed, and harsh braking. It has been found that tire

400

wear can cause substantial particle emissions with respect to number and/or mass

401

concentration. Thus, TWPs could be significant contributors to particle emissions in urban

402

areas. This study represents the first step in characterizing TWPs in a recently constructed

403

facility, and describes the challenges that remain to be overcome in TWP analysis. Further

404

studies using various tire types and driving conditions should be conducted to definitively

405

determine the effects of TWPs on human health and ecosystems.

22


Page 22 of 30

Page 23 of 30

406


(a)

(b)

(c)

(d)

(e)

(f)

Figure 6. Transmission electron microscopy/energy dispersive spectroscopy (TEM/EDS) data for TWPs generated by the tire simulator. 23



407

(a)

(b)

(c)

(d)

(e)

(f)

Figure 7. Scanning electron microscopy (SEM)/EDS data for TWPs generated by the tire simulator.

408 24


Page 24 of 30

Page 25 of 30

409 410


Table 1. Effects of driving conditions on emissions of tire wear particles (TWPs). APS, aerodynamic particle sizer; OPC, optical particle counter; PM, particulate matter. Driving condition simulated in laboratory Tire Slip Distance Test Load (N) speed speed (km) (km h–1) (km h–1) 50 80 A 1000 63.3 0 110 140 500 1000 B 110 91.7 0 1500 2000 2500 0 -2 -4 C 100 80 80.0 -6 -8 -10 D

100–150

0–130

3.4

-

PM2.5 emission per tire tread loss (%)d

PM10 emission per tire tread loss (%)e

0.33 (APS) 0.29 (OPC)

0.04 (APS) 0.12 (OPC)

0.12 (APS) 0.40 (OPC)

5.24 (APS) 12.01 (OPC)

0.16 (APS) 0.28 (OPC)

0.03 (APS) 0.10 (OPC)

0.16 (APS) 0.37 (OPC)

380.0

0.14 (APS) 1.14 (OPC)

0.27 (APS) 2.41 (OPC)

0.52 (APS) 0.47 (OPC)

0.00004 (APS) 0.0003 (OPC)

0.00007 (APS) 0.0006 (OPC)

8918.1

15,572 (APS) 36,837 (OPC)

66,432 (APS) 36,857 (OPC)

0.23 (APS) 1.00 (OPC)

0.17 (APS) 0.41 (OPC)

0.74 (APS) 0.41 (OPC)

Tire tread loss (mg)

Wear rate (mg/km)

PM2.5 emission per km (µg km–1)a

PM10 emission per km (µg km–1)b

PM2.5/PM10

200

3.2

1.29 (APS) 3.72 (OPC)

3.69 (APS) 12.65 (OPC)

300

3.3

0.84 (APS) 3.38 (OPC)

30400

30500

c

411

a

Mass of TWPs smaller than 2.5 µm divided by distance (µg km–1)

412

b

Mass of TWPs smaller than 10 µm divided by distance (µg km–1)

413

c

Ratio of mass of TWPs smaller than 2.5 µm divided by distance to mass of particles smaller than 10 µm divided by distance (a/b)

414

d

Mass of TWPs smaller than 2.5 µm divided by tire tread loss (%)

415

e

Mass of TWPs smaller than 10 µm divided by tire tread loss (%) 25



416

Acknowledgments

417

This research was supported by the Center for Environmentally Friendly Vehicles as

418

a Global-Top Project of the Ministry of Environment of Korea, and was partially funded by

419

the Basic Research Fund (NK212E) of the Korea Institute of Machinery and Materials

420

(KIMM).

421 422

Supporting Information

423 424

The Supporting Information is available free of charge on the ACS Publications website.

425

26


Page 26 of 30

Page 27 of 30


426

References

427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470

1. Valavanidis, A.; Fiotakis, K.; Vlachogianni, T., Airborne particulate matter and hu man health: Toxicological assessment and importance of size and composition of particles for oxidative damage and carcinogenic mechanisms. J. Environ. Sci. Heal th C Environ. Carcinog. Ecotoxicol. Rev. 2008, 26, (4), 339-362. 2. Noll, K. E.; Mueller, P. K.; Imada, M., Visibility and aerosol concentration in urb an air. Atmos. Environ. (1967) 1968, 2, (5), 465-475. 3. Pilinis, C.; Pandis, S. N.; Seinfeld, J. H., Sensitivity of direct climate forcing by atmospheric aerosols to aerosol size and composition. J. Geophys. Res. 1995, 100, (D9), 18,739-18,754. 4. Harrison, R. M.; Yin, J., Particulate matter in the atmosphere: Which particle prop erties are important for its effects on health? Sci. Total. Environ. 2000, 249, (1-3) , 85-101. 5. Kim, K. H.; Kabir, E.; Kabir, S., A review on the human health impact of airbor ne particulate matter. Environ. Int. 2015, 74, 136-143. 6. Bellouin, N.; Boucher, O.; Haywood, J.; Reddy, M. S., Global estimate of aerosol direct radiative forcing from satellite measurements. Nature 2005, 438, (7071), 11 38-1141. 7. Karagulian, F.; Belis, C. A.; Dora, C. F. C.; Prüss-Ustün, A. M.; Bonjour, S.; Ad air-Rohani, H.; Amann, M., Contributions to cities' ambient particulate matter (PM ): A systematic review of local source contributions at global level. Atmos. Environ. 2015, 120, (Supplement C), 475-483. 8. Hagino, H.; Oyama, M.; Sasaki, S., Laboratory testing of airborne brake wear part icle emissions using a dynamometer system under urban city driving cycles. Atmos. Environ. 2016, 131, 269-278. 9. Vouitsis, E.; Ntziachristos, L.; Pistikopoulos, P.; Samaras, Z.; Chrysikou, L.; Sama ra, C.; Papadimitriou, C.; Samaras, P.; Sakellaropoulos, G., An investigation on th e physical, chemical and ecotoxicological characteristics of particulate matter emitt ed from light-duty vehicles. Environ. Pollut. 2009, 157, (8-9), 2320-2327. 10. Thorpe, A.; Harrison, R. M., Sources and properties of non-exhaust particulate ma tter from road traffic: A review. Sci. Total. Environ. 2008, 400, (1-3), 270-282. 11. Abu-Allaban, M.; Gillies, J. A.; Gertler, A. W.; Clayton, R.; Proffitt, D., Tailpipe, resuspended road dust, and brake-wear emission factors from on-road vehicles. Atmos. Environ. 2003, 37, (37), 5283-5293. 12. Kumar, P.; Pirjola, L.; Ketzel, M.; Harrison, R. M., Nanoparticle emissions from 11 non-vehicle exhaust sources - A review. Atmos. Environ. 2013, 67, 252-277. 13. Mathissen, M.; Scheer, V.; Vogt, R.; Benter, T., Investigation on the potential gen eration of ultrafine particles from the tire-road interface. Atmos. Environ. 2011, 45, (34), 6172-6179. 14. Barlow, T., Briefing Paper on Non-exhaust Particulate Emissions from Road Trans port 2014. 15. Gustafsson, M.; Blomqvist, G.; Gudmundsson, A.; Dahl, A.; Swietlicki, E.; Bohgar d, M.; Lindbom, J.; Ljungman, A., Properties and toxicological effects of particles from the interaction between tyres, road pavement and winter traction material. S ci. Total. Environ. 2008, 393, (2-3), 226-240. 27



471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516

16. Kupiainen, K. J.; Tervahattu, H.; Räisänen, M.; Mäkelä, T.; Aurela, M.; Hillamo, R., Size and composition of airborne particles from pavement wear, tires, and trac tion sanding. Environ. Sci. Technol. 2005, 39, (3), 699-706. 17. Dahl, A.; Gharibi, A.; Swietlicki, E.; Gudmundsson, A.; Bohgard, M.; Ljungman, A.; Blomqvist, G.; Gustafsson, M., Traffic-generated emissions of ultrafine particle s from pavement-tire interface. Atmos. Environ. 2006, 40, (7), 1314-1323. 18. Grigoratos, T.; Gustafsson, M.; Eriksson, O.; Martini, G., Experimental investigatio n of tread wear and particle emission from tyres with different treadwear marking. Atmos. Environ. 2018, 182, 200-212. 19. Foitzik, M. J.; Unrau, H. J.; Gauterin, F.; Dörnhöfer, J.; Koch, T., Investigation o f ultra fine particulate matter emission of rubber tires. Wear 2018, 394-395, 87-95 . 20. Kwak, J. H.; Kim, H.; Lee, J.; Lee, S., Characterization of non-exhaust coarse an d fine particles from on-road driving and laboratory measurements. Sci. Total. E nviron. 2013, 458-460, 273-282. 21. Harrison, R. M.; Jones, A. M.; Gietl, J.; Yin, J.; Green, D. C., Estimation of the contributions of brake dust, tire wear, and resuspension to nonexhaust traffic part icles derived from atmospheric measurements. Environ. Sci. Technol. 2012, 46, (12 ), 6523-6529. 22. Grigoratos, T.; Martini, G., Non-Exhaust Traffic Related Emissions. Brake and Tyr e Wear PM Literature Review 2014. 23. Jan Kole, P.; Löhr, A. J.; Van Belleghem, F. G. A. J.; Ragas, A. M. J., Wear an d tear of tyres: A stealthy source of microplastics in the environment. Int. J. Env. Res. Pub. He. 2017, 14, (10), 1-31. 24. Wik, A.; Dave, G., Occurrence and effects of tire wear particles in the environme nt - A critical review and an initial risk assessment. Environ. Pollut. 2009, 157, ( 1), 1-11. 25. Turner, A.; Rice, L., Toxicity of tire wear particle leachate to the marine macroal ga, Ulva lactuca. Environ. Pollut. 2010, 158, (12), 3650-3654. 26. Magnusson, K.; Eliasson, K.; Fråne, A.; Haikonen, K.; Hultén, M., Swedish sourc es and pathways for microplastics to the marine environment - a review of existin g data. IVL Swedish Environmental Research Institute Report 2016, C183, 1-87. 27. Nizzetto, L.; Futter, M.; Langaas, S., Are Agricultural Soils Dumps for Microplast ics of Urban Origin? Environ. Sci. Technol. 2016, 50, (20), 10777-10779. 28. Natusch, D. F. S.; Wallace, J. R., Urban aerosol toxicity: The influence of particl e size. Science 1974, 186, (4165), 695-699. 29. Jickells, T. D.; An, Z. S.; Andersen, K. K.; Baker, A. R.; Bergametti, C.; Brooks, N.; Cao, J. J.; Boyd, P. W.; Duce, R. A.; Hunter, K. A.; Kawahata, H.; Kubilay , N.; LaRoche, J.; Liss, P. S.; Mahowald, N.; Prospero, J. M.; Ridgwell, A. J.; T egen, I.; Torres, R., Global iron connections between desert dust, ocean biogeoche mistry, and climate. Science 2005, 308, (5718), 67-71. 30. Lighty, J. S.; Veranth, J. M.; Sarofim, A. F., Combustion aerosols: Factors govern ing their size and composition and implications to human health. J. Air. Waste. M anage. 2000, 50, (9), 1565-1618. 31. Schallamach, A.; Turner, D. M., The wear of slipping wheels. Wear 1960, 3, (1), 1-25. 32. Sanders, P. G.; Xu, N.; Dalka, T. M.; Maricq, M. M., Airborne brake wear debri 28


Page 28 of 30

Page 29 of 30

517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562


33. 34.

35.

36.

37.

38. 39. 40.

41.

42.

43. 44.

45.

46. 47.

48.

s: Size distributions, composition, and a comparison of dynamometer and vehicle t ests. Environ. Sci. Technol. 2003, 37, (18), 4060-4069. Lindenmuth, B. E., An overview of tire technology. The Pneumatic Tire 2006, 227. Kwak, J.; Lee, S.; Lee, S., On-road and laboratory investigations on non-exhaust ultrafine particles from the interaction between the tire and road pavement under braking conditions. Atmos. Environ. 2014, 97, 195-205. Han, S.; Youn, J. S.; Jung, Y. W., Characterization of PM10 and PM2.5 source p rofiles for resuspended road dust collected using mobile sampling methodology. Atmos. Environ. 2011, 45, (20), 3343-3351. Kreider, M. L.; Panko, J. M.; McAtee, B. L.; Sweet, L. I.; Finley, B. L., Physica l and chemical characterization of tire-related particles: Comparison of particles ge nerated using different methodologies. Sci. Total. Environ. 2010, 408, (3), 652-659 . Hussein, T.; Johansson, C.; Karlsson, H.; Hansson, H. C., Factors affecting non-tai lpipe aerosol particle emissions from paved roads: On-road measurements in Stock holm, Sweden. Atmos. Environ. 2008, 42, (4), 688-702. Timmers, V. R. J. H.; Achten, P. A. J., Non-exhaust PM emissions from electric vehicles. Atmos. Environ. 2016, 134, 10-17. Howard, C. V., Statement of Evidence: Particulate Emissions and Health. Proposed Ringaskiddy Waste-to-Energy Facility 2009. Murakami, M.; Nakajima, F.; Furumai, H., Size- and density-distributions and sour ces of polycyclic aromatic hydrocarbons in urban road dust. Chemosphere 2005, 6 1, (6), 783-791. Yu, C.; Kamboj, S.; Wang, C.; Cheng, J. J., Data Collection Handbook to Suppor t Modelling Impacts of Radioactive Material in Soil and Building Structures. 2015 . Cadle, S. H.; Williams, R. L., Gas and particle emissions from automobile tires i n laboratory and field studies. J. Air. Pollut. Control. Assoc. 1978, 28, (5), 502-5 07. Boulter, P. G., A review of emission factors and models for road vehicle non-exh aust particulate matter. 2005. Hildemann, L. M.; Markowski, G. R.; Cass, G. R., Chemical Composition of Emi ssions from Urban Sources of Fine Organic Aerosol. Environ. Sci. Technol. 1991, 25, (4), 744-759. McKenzie, E. R.; Money, J. E.; Green, P. G.; Young, T. M., Metals associated w ith stormwater-relevant brake and tire samples. Sci. Total. Environ. 2009, 407, (22 ), 5855-5860. Rattanasom, N.; Saowapark, T.; Deeprasertkul, C., Reinforcement of natural rubber with silica/carbon black hybrid filler. Polym. Test. 2007, 26, (3), 369-377. Councell, T. B.; Duckenfield, K. U.; Landa, E. R.; Callender, E., Tire-wear particl es as a source of zinc to the environment. Environ. Sci. Technol. 2004, 38, (15), 4206-4214. Mastral, A. M.; Murillo, R.; Callén, M. S.; García, T.; Snape, C. E., Influence of process variables on oils from tire pyrolysis and hydropyrolysis in a swept fixed bed reactor. Energ. Fuel. 2000, 14, (4), 739-744. 29



563 564 565 566 567 568 569 570

49. Legret, M.; Odie, L.; Demare, D.; Jullien, A., Leaching of heavy metals and poly cyclic aromatic hydrocarbons from reclaimed asphalt pavement. Water Res. 2005, 39, (15), 3675-3685. 50. Davis, A. P.; Shokouhian, M.; Ni, S., Loading estimates of lead, copper, cadmium , and zinc in urban runoff from specific sources. Chemosphere 2001, 44, (5), 997 -1009. 51. Zhang, Y.; Hwang, J. Y.; Peng, Z.; Andriese, M.; Li, B.; Huang, X.; Wang, X. Microwave absorption characteristics of tire. TMS Annual Meeting 2015, 235-243.

571

30


Page 30 of 30

Characteristics of Tire Wear Particles Generated by a Tire Simulator

Recommend Documents