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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

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Environmental Science & Technology

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

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driving conditions

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Gibaek Kim and Seokhwan Lee*

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

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

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*Corresponding author: [email protected]

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

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simulator; ultrafine particles

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ACS Paragon Plus Environment


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Table of Contents (TOC)/Abstract Art.

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ABSTRACT

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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changes in driving condition.

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1. INTRODUCTION

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

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

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

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for air quality legislation and guidelines.5

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

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

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

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

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

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

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

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

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

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reduction of brake wear particles.14

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

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

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

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

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

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

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

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

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

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

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

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

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

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determine the physical and chemical properties of TWPs.

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

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

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

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

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

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

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

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

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environment.23, 26, 27

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

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

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and chemical constituents of particles.28-30

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

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

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

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

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

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

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

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force.

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

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

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

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

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conditions.

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2. MATERIALS AND METHODS

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2.1. Tire material

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

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

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

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

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

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

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

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unit of the tire simulator.

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2.2. Tire simulator

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

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

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

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

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

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

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

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

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

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

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

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conditions on the road.

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2.3. Enclosing chamber

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

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

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

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

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

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

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

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instruments using conductive tubes.

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

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measurement setup.

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

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

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

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wear process was started.

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2.4. Instrumentation

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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

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and time resolution of 6 s.

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

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

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

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

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

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

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

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

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

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

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

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acquisition.

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3. RESULTS AND DISCUSSION

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3.1. Effect of driving speed

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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speed increased (r = 0.9688).

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(a)

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(b)

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

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

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140 km h–1).

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

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

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

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

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



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

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

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

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

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

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limitations or properties inherent to TWPs remains to be investigated.

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

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

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

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

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

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

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

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

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

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

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

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3.2. Effect of load

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

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

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

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


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

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

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

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

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

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

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

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

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(a)

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(b)

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

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

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2,500 N).

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

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

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

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

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

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

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

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

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

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

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

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

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


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

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

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

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

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

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

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

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PM emission was more apparent.

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3.3. Effect of slip speed

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

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

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

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

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

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

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

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

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

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

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shown).

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

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

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

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

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

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

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

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

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

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driving conditions.

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3.4. Effect of harsh braking

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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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

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(a)

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(b)

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

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generated during the harsh braking simulation. 18


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

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

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

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

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

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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

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

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

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

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

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during wear processes.42

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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

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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

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

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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

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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

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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

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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

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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

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

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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

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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

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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


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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


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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


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Characteristics of Tire Wear Particles Generated by ... - ACS Publications

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