Generation Characteristics of Nanoparticles Emitted from Subways in Operation

Yongil Lee1,2, Kyomin Choi1,2, Wonseog Jung1,2, Michael E. Versoza2,3, Mona Loraine M. Barabad2,3, Taesung Kim1, Duckshin Park2*

1 SungKyunKwan University, Jangan-gu, Suwon 04763, Korea 2 Korea Railroad Research Institute, Woram-dong, Uiwang 16105, Korea 3 University of Science & Technology, Yuseong, Daejeon 34113, Korea

ABSTRACT

In this study, measurements were carried out to identify the generation characteristics of wear particles emitted under a subway cabin during operation. Along with a fast mobility particle sizer, probes were installed under a subway cabin and in a subway tunnel to measure the size distributions of nanoparticles at 1-s intervals. Based on the particle density measured under the cabin minus that measured in the tunnel, the size distribution of wear particles generated under the cabin during deceleration was estimated to be bimodal at 165.5 nm and 6.98 nm. These particles were most likely generated from wheel-rail contact, as the train utilized electric braking (no mechanical force applied). In addition, a change in the wear mechanism appears to have arisen due to the increased temperature of the wheel-rail contact while nanoparticles were being emitted, leading to an initial generation of 165.5-nm particles followed by 6.98-nm particles 1 s later.

Keywords: Nanoparticle size distribution; Urban railway; Wear particle; Wheel-rail contact.

INTRODUCTION particulate matter were more likely to have cardiovascular diseases (Bigert et al., 2008). Grass determined the level of Metropolitan areas around the world continue to build toxicity for humans posed by metal particulate matter by new subway systems or expand existing ones as a primary looking at New York City subway workers (Grass et al., transportation system to address traffic congestion. Subway 2010). Karlsson compared sampled particles released from vehicles, however, are enclosed and are structurally prone roadside trees and car tires as well as particulate matter to the ingression, generation, and accumulation of dirt and from Stockholm streets and subway platforms in terms of fine dust. Passengers and operators are constantly exposed genotoxicity and inflammatory response, finding that every to contaminants from the inside and outside of the vehicle. particle type induced DNA damage, and those particles Platform screen doors installed in every station in Korea from subway stations did the greatest damage (Karlsson et have helped to reduce fine dust in station buildings (Kim et al., 2006). Active iron (Fe)-induced damage primarily caused al., 2012). Despite this improvement, air quality in subway an oxidation-reduction reaction (Karlsson et al., 2005). A tunnels is problematic, with a mass concentration of particles study on the toxicity level of a metallic oxide using particles 10 µm in diameter almost twice as high as on underground of different diameters found that nanoparticles were much platforms (Park et al., 2009). Recently, the WHO concluded more toxic than larger classes (Karlsson et al., 2009). that fine particulate matter (PM2.5) is carcinogenic to humans Other studies found that fine dust from tunnels mainly (Group 1). Other studies have found that small dust particles consisted of metal components, accounting for 64.7 wt% of are more likely to penetrate deep into lung tissue and PM10 emissions (Guo et al., 2014; Park et al., 2014; Jung et induce disease than larger particles containing the same al., 2010; Midander et al., 2012; Moreno et al., 2015). In elements (von Klot et al., 2005). another study, Park (2014) used a technology acceptance Bigert looked at the effects of fine subway dust on model and found that wear particles arising from subway underground platform workers in Stockholm, Sweden, and vehicle brakes accounted for 67.7% of the PM10 emissions found that those with greater exposure to subway in subway tunnels, with wear particles from brake-wheel- rail contact accounting for 59.6% of pollution under subway cabins. Thus, these were the major pollutants in subway tunnels. Midander (2012) divided the distribution of particles * Corresponding author. from 14–32,000 nm in subway tunnels into four peaks (30 nm, Tel.: +82-31-460-5367; Fax: +82-31-460-5279 90 nm, 3.3 µm, 8 µm). In general, nanoparticles were released E-mail address: [email protected] at high temperatures due to combustion and melting,

Lee et al., Aerosol and Air Quality Research, 18: 2230–2239, 2018 2231 whereas coarse particles were emitted from mechanical wear. Prior to our study, measurement of the nanoparticle size However, nanoparticles were also produced from wear during distribution had not been carried out on running vehicles. wheel-rail contact in another study (Sundh et al., 2009). In this study, we analyzed nanoparticle size distribution as In addition, Fe was found in particles 100 nm or smaller, measured by sampling devices at 1-s intervals under a which could affect the air quality in subway tunnels (Reche subway cabin and in a tunnel. In addition, the size et al., 2017). The generation processes and characteristics distribution characteristics of nano-sized wear particles of wear particles were studied with different disk materials arising from under the cabin were compared with those using a pin-on-disk machine (Olofsson, 2011), which showed collected in the tunnel. a peak that varied from 70 to 80 nm made up of particles emitted from cast iron while another peak was found at 0.3 METHODS OF MEASUREMENT AND ANALYSIS µm, similar to the generation characteristics of wear particles reported by Sundh (2009) in wheel-rail contact. Measurement Subjects and Methodologies Namgung et al. (2016) studied differences in wear Fig. 1 shows the three lines of the Daegu Metro. Line 1 particles depending on train speed and braking force using has a higher passenger load than the other two lines, a dynamometer. They found that higher braking mechanical transporting 191,433 people per day. It spans 31.02 km and force and initial speed led to the generation of more particles consists of only concrete tracks. Each train has six cars and in the 7–100 nm range. Their results showed that 200-nm runs at an average speed of 40.1 km h–1. An end-to-end particles were common, regardless of the two factors noted one-way trip takes about 55 min, and this line runs from above. They also reported mechanism of generation of 5:30 a.m. to midnight at 5-min intervals during rush hour nanoparticle that evaporation occurred with increasing contact and 8-min intervals at other times. For the purpose of this surface temperature after mechanical friction emitted first. study, measurements were carried out on a train heading Abbasi et al. (2011) measured wear particles from brake east at 2:05 p.m. on November 5, 2016. pads and disks to determine the wear particle characteristics, One probe was installed on the window near the using a detection device installed on vehicles during courtesy seats (designated for senior citizens, the disabled, operation. This study found that the emission of wear dust and pregnant women) at first cabin and another on the rear increased as mechanical braking force increased. With side of a wheel under the second cabin of the train, electric braking, no wear particles were emitted from brakes measuring the baseline concentrations in subway tunnels or disks. In other words, many studies have found that and the concentration of nanoparticles generated under the nanoparticles infiltrate into subway cabins from the outside cabin body during deceleration, respectively (Fig. 2). The and are simultaneously generated from vehicle operation. probes were connected to a measurement device with

Fig. 1. Map showing the subway line in Daegu.

2232 Lee et al., Aerosol and Air Quality Research, 18: 2230–2239, 2018

Fig. 2. Side view of the sampling points (A: tunnel, B: under train). conductivity tubes of the same length, avoiding any errors stations varied from 70 to 100 s, depending on the shape of caused by a difference in length. And, we don’t consider the tunnel and the distance between stations. Fig. 4 (Down) isokinetic sampling because of Brownian motion in nanoscale shows train speed and whether the brake was engaged during (Arouca et al., 2010). As the use of electricity on the the measurement process. When the train speed exceeds a subway vehicle was prohibited, an uninterruptible power set limit, Daegu Metro’s braking system automatically supply (UPS) was utilized. A fast mobility particle sizer engages. There are generally two braking systems: electric (FMPS; TSI Model 3091) measured particles ranging from and mechanical. Electric braking is designed to reduce the 5 to 560 nm in size that were generated at 1-s intervals motor-speed (without mechanical force) if the train speed is using electrical mobility by corona discharge in 32 channels. 20 km h–1 or greater, while mechanical and electric braking Before measurement, we conduct calibration of two FMPS are both available once the speed falls below 20 km h–1. and comparison two FMPS (Fig. 3). Operating information, ATC records only whether the braking system was engaged, including subway stops and starts, was recorded by hand in not braking type. As can be seen in Fig. 4 (Down), braking the train to ensure that the FMPS was synchronized with was applied whenever the train decelerated. Also, the the Automatic Train Control (ATC) system. braking system was operated intermittently when the train exceeded the set speed in some constant velocity sections. Information Regarding the Operation of Daegu Metro This figure also shows that the brake was engaged constantly and the Automatic Train Control System when the train passed through the [a] section, in contrast to Modern subway trains are operated automatically. other areas. However, when entering a platform area, they are controlled In Fig. 5, curves show four operational patterns of Daegu manually to ensure that they stop at the correct location. Metro Line 1 trains. In Case 1, the tunnels are straight, and All information is recorded in an ATC system embedded in the train passes through acceleration–constant velocity– the train, which records train speed, whether the brake was deceleration–stopped sections for approximately 80 s. Case engaged, opening and closing of doors, and other information. 2 includes relatively short distances between stations, and Daegu Metro also uses this ATC system to record the train goes through acceleration–deceleration–stopped operational information. For this study, ATC information sections in 70 s. Case 3 involves curved tunnels, in which on train speed and braking provided by Daegu Metro was the train speed is 60 km h–1 or less, with an operating pattern used to identify the operational patterns of the train. Daegu of acceleration–constant velocity–deceleration–stopped. Metro recorded these data while the train made five round Case 4 contains both straight and curved tunnels in an trips. Fig. 4 (Up) shows the overlapping speed distribution acceleration–constant velocity–acceleration–constant velocity curves of the train measured over five trips while it ran –deceleration–stopped pattern. In every case, speed did not from Seolhwa-Myeonggok Station (one end of the line) to exceed 78 km h–1 and the train accelerated for 36 s after Ansim Station (the other end). starting. It also took 36 s for the train to stop after The operational pattern was constant except for the [a] deceleration began. The train’s acceleration and deceleration period, as shown in Fig. 4. This indicates that the operating speed was ± 0.6 m s–2, with similar speeds recorded in other environment for this train did not change during the sections. As can be seen in the results, the key factors that measurement process, and the train ran in a slightly different affect train operational conditions are the distance between manner when a new factor was encountered. Indeed, large- stations and curvature of the track and tunnel. These scale street-level construction was ongoing in the area of [a] operational patterns are assumed to be similar to those in on that day. These data show that the time to travel between other subway systems.

Lee et al., Aerosol and Air Quality Research, 18: 2230–2239, 2018 2233

RESULTS AND DISCUSSION in Daegu Metro Line 1 tunnels and under the train cabin, the ratio of tunnel to under cabin concentrations, and train speed. Particle Number Concentrations in Subway Tunnels and The solid line represents the total number concentration and under the Cabin ratio, while the dotted line represents train speed. The Fig. 6 shows the total number concentration of particles average total number concentration in tunnels was 295,043.1

Fig. 3. Comparison of two FMPS at atmospheric condition.

Fig. 4. Operation information of the subway train at specific measurement times.

2234 Lee et al., Aerosol and Air Quality Research, 18: 2230–2239, 2018

Fig. 5. Operation information of the subway train in each section.

(± 83,005) # m–3. The number concentration was found to emitted during deceleration when the train was running at be nearly constant, except in some sections where the 20 km h–1 or more. This means that electric braking was number varied. Several factors (e.g., vent system and applied. According to Abbasi et al. (2011), electric braking tunnel shape) are assumed to drive this variation (Moreno does not generate wear particles, while mechanical braking et al., 2017). The number concentration under the cabin does. Therefore, the nanoparticle peak shown in Fig. 7 is was 341,209.5 (± 188,027.4) # m–3. When the train traveled assumed to be attributable to wheel-rail contact. We suggest between stations, the number concentration surged instantly, that the resulting constant wear from wheel-rail slip led to a reaching a maximum concentration of 5,055,740 # m–3. series of peaks. Reportedly, the slip speed of wheel-rail These peaks were noted during deceleration in most cases, contact has an impact on the volume of nanoparticles as well as in a few constant velocity sections. These results generated (Sundh and Olofsson, 2011). indicate that trains in operation emit nanoparticles. The bottom image shows the tunnel to under cabin concentration Size Distribution of Nanoparticles from Subway Tunnels ratio. When peaks were present under the cabin, the and under the Cabin concentration was generally higher by 2- to 4-fold, and 19- Fig. 8 shows the average concentration and size distribution fold at most (Fig. 6). The tunnel to under cabin ratio was from subway tunnels and under the cabin in Cases 2 and 3. nearly 1 with these peaks excluded, which was assumed to In all cases, similar size distributions were obtained. The be the baseline concentration. concentration of particles ranging from 29.4–80.6 nm in Fig. 7 shows Cases 1 to 4, described above for Fig. 6, to size was high in tunnels; other sizes were more concentrated clarify why the number concentration of nanoparticles under the cabin, where nanoparticles 165.5 nm in size were spiked under the cabin. Cases 1 and 2, which involved particularly concentrated. The average concentration of straight tunnels, showed similar patterns. In Cases 3 and 4, nano-sized particles with diameter under 10 nm was similar nanoparticles at the sampling port under the cabin were in tunnels and under the cabin, but their standard deviations emitted even when the train was running at a constant were markedly different, showing that single-digit nano-sized velocity. We assume that the tunnels may cause increased particles were being generated. To analyze this phenomenon, particle generation in these cases, rather than the operational Case 2 was expressed in contour graphs as shown in Fig. 9. patterns of the train. In all cases, nanoparticles were Fig. 9 shows the number concentration of nanoparticles by

Lee et al., Aerosol and Air Quality Research, 18: 2230–2239, 2018 2235

Fig. 6. Total number concentration in the subway tunnel and under the train. color. Particles generated under the cabin 8 s after the train The average concentration ratio of 45.3-nm particles was started braking were 165.5 nm in diameter, whereas those negative, which means that the concentration was higher in generated 9 s later were 6.98 nm in diameter. Sundh and the tunnels by at least 2,137 # cm–3. This is not a large Olofsson (2011) found that wear conditions changed as the concentration difference, but provides reasonable suspicion temperature of the contact surface increased, which, in turn, that pollutants in the upper portions of subway tunnels due generated nanoparticles. Namgung et al. (2016, 2017) found to vent systems hanging from the ceiling, pantographs, that 200-nm-sized particles were generated when 12 kN of contact surfaces with trolley lines, and train wind may braking force was applied to a train running at 50 km h–1, cause the observed negative figures. and 7- to 20-nm particles were generated 2 s later. Therefore, In this study, we looked at the size distribution of we assume that, a size change of particles was induced nanoparticles and found that they were emitted due to within 1 s; 165.5-nm-sized nanoparticles were generated by wheel-rail contact. It was difficult to install measurement heat warming the wheel, and then 6.98-nm-sized nanoparticles devices on trains in operation. We could not analyze the were generated later. A slip in wheel-rail contact is similar elements making up the wear particles or their shapes, or to the friction between the pad and disk during braking. As measure the temperature of the contact, and thus it was not a result, all cases showed the same size distributions and possible to determine whether wheel-rail and wheel flange- different total nanoparticle number concentration emitted at gauge corner wear and the resulting temperature increase the wheel-rail contact. induces evaporation of the lubricants applied to the rail resulting in nanoparticle emission. In future studies, it Size Distribution Characteristics of Nanoparticles from would be useful to look at a wider size distribution of under the Cabin particles from 6 to 10,000 nm, and to sample the various Fig. 10 shows the average concentration difference between sizes and analyze their shapes, with the aim of identifying the tunnel and under the cabin in each case. With zero as characteristics of the nanoparticles emitted during wheel- the starting point, the average concentrations in all cases rail contact and the mechanism of wear particle generation. were found to be similar. As mentioned above, 165.5-nm and 6.98-nm particles were emitted at wheel-rail surface CONCLUSIONS due to wear. And the standard deviations at Case 1 and 2 (straight) higher than at the Case 3 and 4 (curved section). We conducted measurements outside a train running on

2236 Lee et al., Aerosol and Air Quality Research, 18: 2230–2239, 2018

Fig. 7. Total concentration in the subway tunnel and under the train in each case.

Fig. 8. Size distribution of the tunnel and under the train for Cases 2 and 3.

Daegu Metro Line 1, travelling from one end of the line to and under the cabin arose from wear particles. We confirmed the other, to figure out the generation characteristics of through measurement that 165.5-nm and 6.98-nm particles wear particles emitted from wheel-rail-brake contact during were emitted under the cabin. As the train is controlled by operation. First, we analyzed ATC recordings and divided electric braking (no mechanical force), nanoparticles were them into four operational condition types and noted emitted due to wheel-rail contact. The increase in temperature whether braking was engaged. Next, an FMPS recorded the during contact resulted in the generation of 165.5-nm wear size distribution of nanoparticles at 1-s intervals. We assumed particles and, 1 s later, 6.98-nm wear particles. The that the difference in particle concentration between tunnels assumption here was that the generation mechanism for

Lee et al., Aerosol and Air Quality Research, 18: 2230–2239, 2018 2237

Fig. 9. Contour plot of the nanoparticle concentration in the tunnel and under the train in Case 2.

25000 Case1 Case3 Case2 Case4 20000

15000 夾

10000

dN/dlogDp(#/ ) 5000

-5000 10 100

particle diameter(nm) Fig. 10. Size distribution difference between the tunnel and under the train in each case.

2238 Lee et al., Aerosol and Air Quality Research, 18: 2230–2239, 2018 nanoparticles from wheel-rail contact was due to mechanical P. and Chillrud, S.N. (2010). Airborne particulate metals friction, which generates heat, resulting in nanoparticles. in the New York City subway: A pilot study to assess The number concentrations and size distributions of the potential for health impacts. Environ. Res. 110: 1–11. wear particles generated during wheel-rail contact vary, Guo, L., Hu, Y.J., Hu, Q.Q., Lin, J., Li, C.L., Chen, J.M., depending on the slip speed, contact surface pressure, and Li, L.N. and Fu, H.B. (2014). Characteristics and state and materials of the rails and wheel surfaces. Lubricants chemical compositions of particulate matter collected at used to prevent the wear of wheels and rails also affect the selected metro stations of Shanghai, China. Sci. Total particle generation (Olofsson et al., 2009; Arias Cuevas et Environ. 496: 443–452. al., 2010; Abbasi et al., 2013). In addition, increases in Jung, H.J., Kim, B., Ryu, J., Maskey, S., Kim, J.C., Sohn, temperature caused by contact wear induce a change in the J. and Ro, C.U. (2010). Source identification of particulate size distribution of nanoparticles (Sundh and Olofsson, 2011; matter collected at underground subway stations in Namgung et al., 2017). The higher the slip speed during Seoul, Korea using quantitative single-particle analysis. wheel-rail contact, the more drastic the temperature increase Atmos. Environ. 44: 2287–2293. (Sundh and Olofsson, 2011). Karlsson, H.L., Nilsson, L. and Moller, L. (2005). Subway As described above, wear may vary according to particles are more genotoxic than street particles and numerous factors. In this study, it was difficult to measure induce oxidative stress in cultured human lung cells. all of these factors, as a limited number of measurement Chem. Res. Toxicol. 18: 19–23. devices could be installed on a train in operation. However, Karlsson, H.L., Ljungman, A.G., Lindbom, J. and Moller, we can assume that temperature is also a very important factor L. (2006). Comparison of genotoxic and inflammatory in changing the mechanism by which nanoparticles are effects of particles generated by wood combustion, a generated. As shown in other studies, wheel-rail contact road simulator and collected from street and subway. generates high temperatures that can emit single-digit Toxicol. Lett. 165: 203–211. nanoparticles. Future studies should focus on determining Karlsson, H.L., Gustafsson, J., Cronholm, P. and Moller, L. the mechanism of generating wear particles and the (2009). Size-dependent toxicity of metal oxide particles contribution of emissions under the cabin through analyzing — A comparison between nano- and micrometer size. the elemental compositions and shapes of particles sampled Toxicol. Lett. 188: 112–118. under the cabin. Kim, K.H., Ho, D.X., Jeon, J.S. and Kim, J.C. (2012). A noticeable shift in particulate matter levels after platform ACKNOWLEDGMENTS screen door installation in a Korean subway station. Atmos. Environ. 49: 219–223. This research was supported by a grant from the Railway Midander, K., Elihn, K., Wallen, A., Belova, L., Karlsson, Technology Research Project of the Ministry of Land A.K.B. and Wallinder, I.O. (2012). Characterisation of Infrastructure and Transport (18RTRP-B082486-05). nano- and micron-sized airborne and collected subway particles, a multi-analytical approach. Sci. Total Environ. REFERENCES 427: 390–400. Moreno, T., Martins, V., Querol, X., Jones, T., BeruBe, K., Abbasi, S., Wahlstrom, J., Olander, L., Larsson, C., Minguillon, M.C., Amato, F., Capdevila, M., de Miguel, Olofsson, U. and Sellgren, U. (2011). A study of E., Centelles, S. and Gibbons, W. (2015). A new look at airborne wear particles generated from organic railway inhalable metalliferous airborne particles on rail subway brake pads and brake discs. Wear 273: 93–99. platforms. Sci. Total Environ. 505: 367–375. Abbasi, S., Olofsson, U., Zhu, Y. and Sellgren, U. (2013). Moreno, T., Reche, C., Minguillon, M.C., Capdevila, M., Pin-on-disc study of the effects of railway friction de Miguel, E. and Querol, X. (2017). The effect of modifiers on airborne wear particles from wheel-rail ventilation protocols on airborne particulate matter in contacts. Tribol. Int. 60: 136–139. subway systems. Sci. Total Environ. 584: 1317–1323. Arias-Cuevas, O., Li, Z., Lewis, R. and Gallardo-Hernandez, Namgung, H.G., Kim, J.B., Woo, S.H., Park, S., Kim, M., E.A. (2010). Rolling-sliding laboratory tests of friction Kim, M.S., Bae, G.N., Park, D. and Kwon, S.B. (2016). modifiers in dry and wet wheel-rail Contacts. Wear 268: Generation of nanoparticles from friction between 543–551. railway brake disks and pads. Environ. Sci. Technol. 50: Arouca, F. O., Feitosa, N.R. and Coury, J.R. (2010). Effect 3453–3461. of sampling in the evaluation of particle size distribution Namgung, H.G., Kim, J.B., Kim, M.S., Kim, M., Park, S., in nanoaerosols. Powder Technol. 200: 52–59. Woo, S.H., Bae, G.N., Park, D. and Kwon, S.B. (2017). Bigert, C., Alderling, M., Svartengren, M., Plato, N., de Size distribution analysis of airborne wear particles Faire, U. and Gustavsson, P. (2008). Blood markers of released by subway brake system. Wear 372: 169–176. inflammation and coagulation and exposure to airborne Olofsson, U., Olander, L. and Jansson, A. (2009). A study particles in employees in the Stockholm underground. of airborne wear particles generated from a sliding Occup. Environ. Med. 65: 655–658. contact. J. Tribol. 131: 044503. Grass, D.S., Ross, J.M., Family, F., Barbour, J., Simpson, Olofsson, U. (2011). A study of airborne wear particles H.J., Coulibaly, D., Hernandez, J., Chen, Y.D., Slavkovich, generated from the train traffic—Block braking simulation V., Li, Y.L., Graziano, J., Santella, R.M., Brandt-Rauf, in a pin-on-disc machine. Wear 271: 86–91.

Lee et al., Aerosol and Air Quality Research, 18: 2230–2239, 2018 2239

Park, D., Lee, T., Hwang, D., Jung, W., Lee, Y., Cho, K., temperature and wear transitions in a wheel-rail contact. Kim, D. and Lee, K. (2014). Identification of the sources Wear 271: 78–85. of PM10 in a Subway tunnel using positive matrix von Klot, S., Peters, A., Aalto, P., Bellander, T., Berglind, factorization. J. Air Waste Manage. Assoc. 64: 1361– N., D'Ippoliti, D., Elosua, R., Hormann, A., Kulmala, 1368. M., Lanki, T., Lowel, H., Pekkanen, J., Picciotto, S., Reche, C., Moreno, T., Martins, V., Minguillon, M.C., Sunyer, J., Forastiere, F. and Grp, H.S. (2005). Ambient Jones, T., de Miguel, E., Capdevila, M., Centelles, S. and air pollution is associated with increased risk of hospital Querol, X. (2017). Factors controlling particle number cardiac readmissions of myocardial infarction survivors concentration and size at metro stations. Atmos. Environ. in five European cities. Circulation 112: 3073–3079. 156: 169–181. Sundh, J., Olofsson, U., Olander, L. and Jansson, A. (2009). Wear rate testing in relation to airborne particles Received for review, December 5, 2017 generated in a wheel-ail contact. Lubr. Sci. 21: 135–150. Revised, April 9, 2018 Sundh, J. and Olofsson, U. (2011). Relating contact Accepted, April 9, 2018