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Experimental investigation of tread wear and particle emission from tyres with different treadwear marking
Atmospheric Environment 182 (2018) 200–212
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Experimental investigation of tread wear and particle emission from tyres with different treadwear marking
T
Theodoros Grigoratosa,∗, Mats Gustafssonb, Olle Erikssonb, Giorgio Martinia a European Commission, Joint Research Centre (JRC), Institute for Energy, Transport and Climate (IETC), Sustainable Transport Unit (STU), Via E Fermi 2749, Ispra, 21027, Italy b Swedish National Road and Transport Research Institute (VTI), SE-581 95, Linköping, Sweden
A R T I C LE I N FO
A B S T R A C T
Keywords: Treadwear rating Tyres durability Tread mass loss Tyre particle emissions Tyre wear nanoparticles
The Treadwear Rating (TWR) provided on the sidewall of the tyre is a marking intended to inform the customer about the expected durability of the tyre. The current study explores whether there is a correlation between the TWR and tyres' tread mass loss. Furthermore, it explores the possible correlation between the TWR and tyre wear dust emitted in the form of PM10 and PM2.5. For that reason, two tyres of the same brand (B) but with different TWR and three tyres of different brands (C and D with the same TWR as one of the B tyres and A with a lower TWR) were tested at a constant speed of 70 km/h by means of the Swedish National Road and Transport Research Institute (VTI) road simulator. Tyres of the same TWR but of different brands showed different behaviour in terms of material loss, PM, and PN emissions under the selected testing conditions. This means that it is not feasible to categorize tyres of different brands in terms of their emissions based on their TWR. The test performed on the two tyres of the same brand but with different TWR showed instead a substantial (not statistically significant) difference in both total wear and PM10 emissions. The tyre with the higher TWR (B2) showed less wear and PM10 emissions compared to the B1 tyre having a lower TWR. Since only two tyres of the same brand and with different TWR were tested, this result cannot be generalized and more tests are necessary to confirm the relation within the same brand. In general, the tyre tread mass loss showed no obvious statistical relation to PM10, PM2.5 or PN concentration. In all cases approximately 50% (by mass) of emitted PM10 fall within the size range of fine particles, while PN size distribution is dominated by nanoparticles most often peaking at 20–30 nm.
1. Introduction As exhaust particle emissions continuously decrease due to the introduction of effective emission control technologies, the attention is shifting to other traffic related sources of particle emissions. Among the – so called – non-exhaust traffic related sources there is a growing concern about particles emitted due to brake wear as well as for particles generated as result of the interaction between tyres and the road surface [Amato et al., 2011]. As far as brake wear particle emissions are concerned, numerous comprehensive studies have been published in the last years covering aspects like brake wear PM and PN emission factors [Grigoratos and Martini, 2015], mass and number size distributions [Harrison et al., 2012; Iijima et al., 2007; Wahlström et al., 2010], chemical characterization [Gietl et al., 2010; Kukutschová et al., 2011; Thorpe and Harrison, 2008], and possible adverse health effects [Gasser et al., 2009; Mazzarella et al., 2007; Riediker et al., 2004]. There is a general consensus among the scientific community that a
∗
standardized sampling and measurement methodology for brake wear particles is missing and that is the main reason why sometimes conclusions of available studies are not comparable, if not contrasting. Following this need the UN Particle Measurement Programme (PMP) group has put together a project which aims at developing a suggested test procedure to investigate brake particle emissions [PMP, 2016]. Regarding tyre wear particle emissions the situation appears to be much more complex. While for some aspects available literature data provide adequate answers to open questions, there are many other aspects for which the current knowledge is not sufficient to reach sound conclusions. On one hand, there is a general consensus that more than 90% by mass of the material emitted as a result of tyre wear is particles with diameter bigger than 10 μm [Gualtieri et al., 2008; Kreider et al., 2010]. Studies also agree that mass size distribution of tyre wear particles displays at least one peak at the coarse size fraction [Aatmeeyata et al., 2009; Gustafsson et al., 2008; Kupiainen et al., 2005; Sjödin et al., 2010]. Finally, tyre wear PM10 emission factors of 3.0–13.0 mg/km
Corresponding author. E-mail address: [email protected] (T. Grigoratos).
https://doi.org/10.1016/j.atmosenv.2018.03.049 Received 1 December 2017; Received in revised form 20 March 2018; Accepted 22 March 2018 1352-2310/ © 2018 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/).
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vehicle [Grigoratos and Martini, 2014; Sjödin et al., 2010; Panko et al., 2018; Pant and Harrison, 2013] are considered typical for passenger cars. On the other hand, the composition of tyre wear particles has not been clarified in the sense that it is not clear if pure tyre wear particles exist in the environment, or all particles consist of a mixture of material coming from the tyres, the road, and the material deposited on it [Kreider et al., 2010]. The contribution of tyre wear particles to ambient PM10 and PM2.5 is estimated to vary between 0.8–8.5% and 0.25–3.0% by mass, respectively [Grigoratos and Martini, 2014]. Recently published data from Panko et al., [2018] report contribution to ambient PM10 and PM2.5 between 0.2–10% and 1.0–7.0% by mass, respectively. The European Tyre & Rubber Manufacturers Association (ETRMA) has reported contributions at the lower range of the above intervals [Panko et al., 2013], while other researchers report higher contributions [Gualtieri et al., 2005; Kwak et al., 2013; Sjödin et al., 2010]. Some studies mention that ultrafine particles are not likely to be emitted under “normal” driving conditions [Mathissen et al., 2011], while others have reported nanoparticle emissions under steady state testing [Dahl et al., 2006; Gustafsson et al., 2008]. Finally, inconsistent conclusions arise from the study of literature data regarding possible adverse health effects in human health [Kumar et al., 2013]. On one hand, the Tyre Industry Project (TIP) group has reported that no specific or major threat for human health related to tyre wear particles has been identified [Panko et al., 2013], while on the other hand, toxicology – in-vitro and animal – studies from other researchers have demonstrated negative effects [Dorsey et al., 2006; Gualtieri et al., 2008; Mantecca et al., 2007; Sadiktsis et al., 2012; Stephensen et al., 2005]. Tyres lose roughly 1.0–1.5 kg in weight during their lifespan among which less than 10% falls in the PM10 fraction [Gualtieri et al., 2008; Kreider et al., 2010]. Most of the material is released in the form of particles with sizes bigger than 10 μm, therefore tyre wear particles are present in all environmental compartments including air, water, soils/ sediments, and biota [Wik and Dave, 2009]. In order to fully understand and possibly control total tyre wear emissions, there would be a need to investigate all open aspects listed in the previous paragraph and – at the same time – understand the impact of each size fraction to the environment. As an alternative approach it was decided to investigate if a relation between the declared durability of the tyres and their total mass loss – as well as their PM10, PM2.5 and PN emissions –exists under specific experimental conditions. If this assumption is confirmed particle emissions from tyres could be controlled through their declared durability. Finally, durability could also be used to control the total material released in the environment as a result of tyre wear. The durability of tyres is an important aspect for the customers that at the moment is not regulated in Europe. In the US, the National Highway Traffic Safety Administration (NHTSA) has established the Uniform Tyre Quality Grading Standards (UTQGS) which intends to assist consumers in making informed choices by requiring information be provided on passenger car tyres about their relative performance in the areas of treadwear, traction, and temperature resistance. Based on the UTQGS methodology tyre manufacturers are obliged to give an indication of the expected durability on the sidewall of the tyre by means of the Treadwear Rating (TWR). TWR takes numbers from 100 to about 700. The higher the number, the higher the mileage that the customer can expect to drive before reaching the minimum allowed tread depth. Details regarding the UTQGS methodology can be found in [Legal Information Institute]. The aim of the current study is to explore whether there is a relation between the TWR and tread mass loss. Additionally, the relation between the TWR and the generation of tyre wear dust in the form of PM10, PM2.5 and PN concentration is explored. Finally, some physical properties of tyre wear particles emitted under non extreme driving conditions are investigated.
Fig. 1. The VTI road simulator.
2. Materials 2.1. The VTI circular road simulator The road simulator (Fig. 1) consists of four wheels that run along a circular track with a diameter of 5.3 m. A separate motor drives each wheel. The speed is constant and can be adjusted up to 70 km/h. The wheel axles have different lengths and therefore the wheels are positioned in different distances from the center. Wheels on axles 1 and 3 are at the track edges, while wheels on axles 2 and 4 are running closer to the middle of the track. An internal air cooling system in the hall is able to temperate the simulator hall to below 0 °C. The VTI circular road simulator is described in detail elsewhere [Gustafsson et al., 2009]. 2.2. Pavement A pavement ring including 14 different asphalt pavements of types stone mastic asphalt with different maximum aggregate sizes, SMA6, SMA8 and SMA11 with granodiorite rock was used for the tests. The SMA pavement construction is wear resistant and commonly used in Nordic countries. The current rock quality and the smaller aggregate sizes (6 and 8 mm) are meant for use in Denmark where no studded tyres are used. 2.3. Tyres Five summer tyres (dimension 205/55 R16) were chosen to study variation in wear and particle emission between different TWR (example of TWR marking in Fig. 2). For this, the initial aim was to use the same brand (B) with three different TWR. This proved to be difficult to find, which is why a second brand (A) was used to represent a low TWR (180). The second aim was to study the variation within tyres of the same TWR from different brands. Tyres employed for the study are presented in Table 1. Information regarding the durability of the tyres is provided by the TWR marking stamped by tyre manufacturers on the sidewall of the tyre as a part of the NHTSA uniform tyre-quality grading system. Treadwear rating uses numbers from 100 to about 700. In theory, a tyre rated 200 would have twice as long lifespan as a tyre rated 100 if used in the same conditions — driver, vehicle and roads. The relative performance of tyres depends upon the actual conditions of their use, variations in driving habits, service practices and differences in road characteristics and climate. There are certain limitations when using the TWR. First of all, the TWR is a ratio and not a mileage. This is because multiple factors determine treadwear rates and most of them are a function of driving 201
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Fig. 2. Tread wear rate marking on tyre.
turned off and simulator accelerated to 70 km/h. The selection of this speed has to do with the fact that summer tyres have demonstrated generally low particle emissions which decrease significantly when lower speeds are applied [Gustafsson et al., 2008]. Thus, the selection of a lower constant speed (i.e. 30 km/h) would result in much lower emissions and therefore would render any observations from the current study as very uncertain. There are obvious limitations resulting from the selection of the constant speed profile (i.e. decelerations are important sources of tyre wear), especially when trying to accurately reproduce real world conditions. However, since the current study aims at understanding whether TWR could be used to control tyre wear, the selection of the steady state profile ensures the comparability of the tests and eliminates the possible effect of the driving profile. After 1 h of testing the simulator is stopped and the cooler – along with a large air filtering fan – are started to reduce deposition and lower the PM10 concentration to initial level. Then the next tyre set is mounted and when PM10 concentration reaches initial level the cooler is turned off to start the next test. Tyre inflation pressure is always checked between tests. For all analyses, a 15-min mean value of PM2.5, PM10 and PN concentration at the end of each simulator run was used. PM concentrations were measured by means of a Tapered Element Oscillating Microbalance (TEOM) and two DustTraks. The TEOM is based on gravimetric technique using a microbalance and gives a value of PM10 mass concentration every 5 min. The method is certified for air quality standard monitoring within the EU. As a complement, two optical instruments (DustTraks) were used during the measurements; one measured mass concentration PM2.5 and the other PM10. The time resolution of the sampling was 3 s for both instruments. Particle size distribution was measured using an APS (Aerodynamic Particle Sizer) model 3321 (TSI, USA) measuring mass distribution and an SMPS (Scanning Mobility Particle Sizer) model 3934 (TSI, USA) measuring number distribution. The SMPS was setup to measure and count particles from 7.37 nm to 311 nm. The APS was equipped with a PM10 inlet and hence, measured particles with aerodynamic diameter from 523 nm to 10 μm. Size distributions of particles measured with the SMPS system are presented as number size distributions and particles measured with the APS are presented as mass size distributions. This is because the fine fraction below 1 μm makes up very little of the mass but contain most of the particles while the coarser particles are very few, but dominate the mass concentration. Detailed information regarding particle measurements can be found elsewhere [Gustafsson et al., 2008; Gustafsson et al., 2009].
Table 1 Tyres used in the study. Tyre Number
Manufacturer
TW Rating (TWR)
Codification
1 2 3 4 5
A B C D B
180 300 300 300 400
A0 B1 C1 D1 B2
Table 2 Chosen experimental design for analyses.
Day 1 Day 2 Day 3
Run1
Run2
Run3
Run4
Run5
5 3 4
1 1 2
4 5 3
2 2 1
5 3 4
Table 3 Mean tread mass loss of tested tyres after 3 h runs in 70 km/h. Tyre Number
Tyre
TWR
Mean mass loss per tyre (g)
Loss per km and car (mg)
1 2 3 4 5
A0 B1 C1 D1 B2
180 300 300 300 400
2.9 11.3 3.2 4.6 2.9
55 214 61 87 55
conditions and operating environment. As a result, actual tyre wear is expected to vary within the same tyre line. However, two tyres with exactly the same compound should have a TWR that varies in accordance with tread depth. Secondly, the TWR is provided for summer tyres but not for winter or studded tyres. Finally, the assigning of TWR is done solely by the tyre manufacturer. 3. Test procedures 3.1. Particle test and measurements The conditions in the road simulator hall are drifting during a test day due to frictional heat warming the pavement, tyres and air. To overcome this effect, a test sequence where the same tyre set is run first and last on each test day was used. For three test days the applied sequence is shown in Table 2. Each test sequence starts with tyres being mounted, cooler being 202
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Fig. 3. PM10 concentration (TEOM) during the three tests days. Figures represent tyre numbers.
regarded as “known” to details or what actually consists of. It is only modelled as straight line background behaviour during the day (one line for each day). The tyre effects are not assumed to change between or within days and are modelled as constants. General behaviour and tyre effects are analysed simultaneously with multiple linear regression and general linear models. Depending on the coding scheme for tyres, the tyre effects can be chosen to express differences between pairs of tyres or differences between tyres and an average of all tested tyres. Both these coding schemes have been used in this study. While in the main analysis the tyre effects are modelled only as constants without any lower level structure, in the second analysis they are modelled as a straight-line function of TWR. Multiple linear regression is also used for this analysis. The main analysis treats differences between tyres simply as differences while the second analysis tries to explain the difference between tyres by the fact that they have different TWR. Generally, these two approaches cannot be combined in one analysis. When comparing tyres the environmental effect is not desirable and analyses adjust for such disturbance. Though this may not be of main importance when comparing tyres, it must be shown how this is treated
3.2. Tyre total wear test Tyre wear test requires longer runs for measurable wear amounts. The test tyres’ tread pattern was checked for attached stones in the pattern and blown free from dust using compressed air. The tyre-rim contact surfaces were swiped with a wet cloth and dried using compressed air. Each tyre was weighed on a balance with 0.1 g accuracy. After each test run the cleaning procedure was repeated. Full sets (4 tyres) were run in 70 km/h for 3 h amounting to 210 km per run. Tyre pressure was checked between each test. Two sets of tyres were tested each day. 3.3. Statistical analysis and design of experiment The choice of the experimental design depends on the details of the analysis and vice versa. The analysis procedure and the choice of the experimental design are described in this section. In the main analysis (1st analysis), the model consists of general behaviour, tyre effects and a random component. The general behaviour describes the effect of changes in the environment. It is not 203
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Fig. 4. PM10 concentration (DustTrak) during the three tests days. Figures represent tyre numbers.
4. Results and discussion
and eliminated from the comparison between tyres. Possibly, straight lines are too simple and the analysis should allow a more complicated shape. However, extending with a second order term does not improve the model significantly. Extending with some higher order function has a clear risk of over-adapting to the data. The design was planned to be optimal for pairwise comparisons of tyres in the main analysis. The differences between two tyres are expressed as a regression coefficient. For one design, there are 10 such comparisons that may not have the same standard error. We assume that the best plan is the one that has minimum value of the maximum standard error among all comparisons. The solution was to search for the most efficient design by scanning through a huge set of randomly generated possible designs. The results indicate that it is efficient to use the same tyre on the first and last run each day. Therefore, the search algorithm was tuned to only scan through such designs. The tyres were labelled 1–5 and the chosen design is shown in Table 2.
4.1. Tyre tread mass loss Table 3 shows the averaged tread mass loss for each tested tyre. Mass loss per km and vehicle (mass emission factor) is calculated between 55 and 214 mg/km with 4 out of 5 tyres being within a narrower threshold of 55–87 mg/km. The constant and tight turning in the road simulator might be expected to cause higher than normal wear rates, but the results from the experiments in the current study show that the range between 55 and 214 mg/km is similar to what other researchers classified as normal driving [Boulter et al., 2006; Grigoratos and Martini, 2014]. It seems that there is a substantial (but not statistically) significant difference in the mass loss between the two tyres of the same brand (B) which is in line with the different TWR value provided by the manufacturer. B1 losses almost 4 times more mass than B2, while the TWR ratio of the two tyres is much lower (4/3). This introduces a doubt whether the mass loss can be fully explained by the difference in the TWR. Unfortunately, it was not possible to find a third tyre of the same 204
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Fig. 5. PM2.5 concentration (DustTrak) during the three tests days. Figures represent tyre numbers.
Fig. 6. Mean percentages PM2.5 of PM10 for all runs shown as calculated from APS data (orange bars) and as measured by the used DustTraks (blue bars). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
loss from the TWR value for different brands of tyres, while it may be feasible within the same brand. This is not completely surprising as the assigning of the TWR is done solely by the tyre manufacturer.
brand with different TWR in order to confirm or not the relation. Surprisingly, the tyre with the lower TWR (A0) showed lower mass loss compared to all 3 tyres of 300 TWR (B1, C1, D1). Furthermore, within the 300 TWR there is a significant variation as it spans between 3 g and over 11 g per tyre. Overall, it seems that it is difficult to predict the mass 205
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Fig. 7. Particle number concentrations during all test days.
simulator hall. The distinct peaks at the end of each run results from rinsing tyres and road surface with compressed air after each run, where after the hall air is filtered from particles using a large filter fan before the next run. B1 tyres seem to reach a slightly higher quasi-stable PM10 level compared to B2 following the trend described for the wear tests. This is observed both on testing days 1 and 2 with both TEOM and DustTrak. However, due to the relatively low level of the PM10 emitted as well as the lack of a third tyre of the same brand with a different TWR no solid conclusion can be reached. Once more A0 tyre seems to have low PM10 emissions and in any case not higher than the rest of the tyres, while the tyres of 300 TWR show a variation in their PM10 emissions without an obvious pattern. PM2.5 follows the same pattern at each run as PM10 without
4.2. PM concentrations The PM10 emitted from summer tyre wear is low compared to the emissions caused by winter or studded tyres, which have been the main research area investigated using the road simulator [Gustafsson and Eriksson, 2015]. The PM10 levels reached for different tyres are about 40–50 μg/m3 (TEOM) and 20–30 μg/m3 (DustTrak) and are in comparison with earlier studies with summer tyres in the simulator [Gustafsson et al., 2009]. PM10 background – at least when TEOM is considered – is about 10–20 μg/m3, therefore measured concentrations are relatively low. Due to low concentrations and 1 s time resolution the noise levels are rather high, therefore Figs. 3 and 4 are smoothed using a 1 min running average. In all tests PM10 increases to a quasi-stable level as a result of a balance between particle sources and sinks in the 206
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Fig. 8. Particle mass size distributions from all runs (15 min mean values at end of each 1-h test). In the lower row, the background concentration has been subtracted.
Fig. 9. Particle number size distributions from all runs (15 min mean values at end of each 1-h test). In the lower row, the background concentration has been subtracted.
4.3. PN concentrations
reaching the quasi-equilibrium before the run stops (Fig. 5). The concentration levels at stop are around 10–15 μg/m3. This indicates – based also on the measurement of PM10 – that approximately 50% of the emitted particles (by mass) fall within the size range of PM2.5. This is confirmed in Fig. 6 where the PM2.5/PM10 ratio from both DustTraks and calculated from APS data is shown. The standard deviation is caused by the ongoing increase in concentration during the data outtake. The deviation is higher in the DustTrak data due to higher time resolution (1 s compared to 20 s for APS). DustTrak data are relatively constant around 50–60%, while the APS calculated data are generally slightly lower. Overall, it seems that there is no direct correlation of the PM2.5 concentrations with the TWR marking but due to the relatively low level of emissions it is very difficult to reach solid conclusions.
Particle number concentration measured by means of the SMPS reveals a more complex pattern from day to day. Day 1 shows distinctly growing particle peaks, while on Days 2 and 3 the peaks are sometimes growing, sometimes rapidly growing followed by a slower decrease or sometimes hardly noticeable (Fig. 7). Not knowing the exact nature of these particles (which are likely not to have the same formation process as coarser particles) it is difficult to speculate about the reasons for this behaviour. In any case tyres D1 showed constantly higher PN concentrations compared to the other tyres. On the other hand, tyres B1 showed relatively low PN emissions, which in combination with their relatively high mass emissions show that the higher number of the 207
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Table 4 Results of regression analysis for PM10, PM2.5 and PN concentration. Values for PM10 and PM2.5 are scaled by 103. PM10 TEOM
Level day 1 Slope day 1 Level day 2 Slope day 2 Level day 3 Slope day 3 A0 B1 C1 D1 B2
PM10 DustTrak
PM2.5 DustTrak
Particle Number
Coefficient
Standard Error
Coefficient
Standard Error
Coefficient
Standard Error
Coefficient
Standard Error
42.78 1.32 48.33 −2.72 31.64 2.18 −0.76 3.04 −1.60 2.60 −3.29
2.02 1.37 2.02 1.37 2.02 1.37 2.32 2.32 2.37 2.37 2.37
23.53 0.87 25.83 2 .07 19.37 1.24 0.69 1.27 −1.24 0.68 −1.40
0.82 0.56 0.82 0.56 0.82 0.56 0.94 0.94 0.97 0.97 0.97
11.11 0.54 12.70 1.26 10.54 0.74 0.38 0.52 −1.01 0.61 −0.51
0.62 0.42 0.62 0.42 0.62 0.42 0.71 0.71 0.73 0.73 0.73
7010 751 2031 −413 1309 633 −838 −632 −552 1750 272
279 190 279 190 279 190 321 321 328 328 328
Fig. 10. Observed and fitted PM10 (TEOM) values with tyre labels for all days.
below 1 μm. These findings are in line with previously reported data showing bimodal mass size distributions of tyre wear particles with one peak at the coarser size fraction and another close to 1 μm (Aatmeeyata et al., 2009; Gustafsson et al., 2008; Sjödin et al., 2010). It should be noted that PM10 mass size distributions from tyres are not consistent in literature, but varies greatly depending on the type of tyres tested and testing methods used [Grigoratos and Martini, 2014; Hussein et al., 2008]. It could be concluded that the TWR does not seem to have any kind of effect on the mass size distribution at least in terms of the shape of the distribution. Overall, the variation in the particle mass distribution appears to be dominated by the day-to-day differences, with no differences visually discerned among individual tyres. The concentration levels in the number size distribution in Fig. 9 should be regarded as uncertain, in the light of the complex behaviour
particles emitted from those tyres are of larger sizes. No particular conclusions can be drawn regarding the effect of TWR to PN concentrations as these particles mainly fall in the ultrafine size range and therefore their overall concentrations are low.
4.4. Mass and number size distributions The size distribution over each run measured by means of the APS appears to have similar shapes during each test day. In Fig. 8, the upper row of diagrams shows the actual mass size distributions, while the lower depicts the mass size distributions when the background distributions have been subtracted. The particle contributions from the tyres during day 1 and 3 are wide peaking at 2–7 μm. A coarser peak is noted at 5–6 μm on day 2. All days appear to have a second peak just 208
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Fig. 11. Observed and fitted PM10 (DustTrak) values with tyre labels for all days.
using the main analysis. The vertical distances between circles and bullets are estimates of the random variation. The reference lines represent the general behaviour during the day. The fourth subplot shows the adjusted mean emission for each tyre in comparison to TWR. The adjustment procedure levels out the effect of variation in general behaviour between and within days. The plus-signs show the fitted values for the second analysis. In Fig. 10 the fourth subplot confirms the initial observations described in paragraph 3.2. B1 tyres showed higher PM10 level (not statistically significant) compared to the corresponding of the same brand but with higher TWR (B2). The statistical uncertainty of the difference does not allow for a definite conclusion. A0 seems to be a lower PM10 emitter compared to two of the 300 TWR tyres (B1 and D1), while among the 300 TWR tyres C1 showed a different behaviour in their PM10 emissions compared to the other two brands. When statistically testing the hypothesis that all tyres are equal in PM10 emission against the alternative that there is at least some difference, P = 0.638, meaning that we cannot reject the hypothesis that all tyres emit PM10 equally. When the analysis is performed based on the DustTrak measurements it is estimated that tyre A0 has 0.6889 μg/m3 higher value than the average tyre after adjusting for the difference in general behaviour between and within days. Again B1 tyres are the higher emitter. The fourth subplot (Fig. 11) confirms the observations described in the previous paragraph. However, when statistically testing the hypothesis that all tyres are equal in PM10 emission against the alternative that there is at least some difference, P = 0.349, meaning that we cannot reject the hypothesis that all tyres emit PM10 equally. The data for PM2.5 have different level than PM10 but the assumed structure of the data is the same and the data are collected from the same experimental design. The fourth subplot (Fig. 12) shows that,
of the number concentration during and between days. Nevertheless, all tests conducted by means of the SMPS reveal a distinct peak at 20–30 nm. Numbers decrease rapidly towards coarser sizes and few are over 100 nm in size. During day 2, there seems to be higher numbers in the coarser sizes and day 3 even a tendency for a secondary peak. Again, TWR does not seem to have any kind of effect on the particle number distribution at least in terms of the type and the peak(s) of the distribution. 5. Statistical analyses The main focus of this paragraph is to use the results and initial observations in order to investigate statistical relations between tyres and PM/PN concentrations. Since PM10 is measured using both TEOM and DustTrak, analyses are made on data for both instruments. Also, PM2.5 from DustTrak and PN concentration derived from the SMPS are analysed and presented. The results of the regression analysis for PM10 measured by the TEOM and DustTrak, as well as for PM2.5 measured by the DustTrak are shown in Table 4. Studied tyres are depicted in the subsequent figures based on the following colour codification (A0–Black; B1- Red; C1–Green; D1–Blue; B2–Aqua). 5.1. PM10 and PM2.5 The tyre effects compare each tyre with the mean of all tested tyres. All 5 tyre effects are not estimated in the same analysis. Table 4 combines results from two analyses. The levels estimate the level at the middle of the day (3d out of 5 runs). The slope estimates the difference between two consecutive runs. PM10 data (TEOM) are shown in Fig. 10. The bullets show the observations and the general behaviour. The circles show the fitted values 209
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Fig. 12. Observed and fitted PM2.5 values with tyre labels for all days.
5.4. Tyre tread mass loss and relation to TWR, PM and PN emissions
unlike PM10 measurements, B2 tyre isn't linked to the lowest PM2.5 emissions among all tyres. This is an indication that lower PM10 emissions don't necessarily mean lower PM2.5 emissions. When testing the hypothesis that all tyres are equal in PM2.5 emission against the alternative that there are differences, P = 0.567, meaning that we cannot reject the hypothesis that the tyres emit PM2.5 equally.
The tread mass loss as measured in this study did not show any statistical relation to the TWR marking (Fig. 14a). The variation within the TWR 300 marking is high due to the B1 tyre which wears about three times more than all other tyres. Also, the lower TWR tyre showed very low wear compared to higher TWR tyres. Within the B brand tyres, the order of wear and TWR marking seems to support a relation, but this is uncertain, since only two types are included. A third tyre of the same brand, either of lower (< 200) or higher (> 500) TWR could confirm or not this observation. To study the relation between tread mass loss and PM10, the adjusted mean PM10 from previous statistical analysis was plotted to the mass loss (Fig. 14b). No obvious relation could be found, but the B1 tyres lose most mass and also have a higher PM10 concentration than the other tyres. Further, the TWR 400 tyre showed lowest PM10 and mass loss. Within the same producer a relation between mass loss and PM10 emission that might be related to TWR is present. The A0 tyre with TWR 180 has as low mass loss as the B2, but higher PM10 emission, while the two other TWR 300 tyres diverge. The results for PM2.5 (Fig. 14c) are similar and no statistic correlations are found. Finally, PN concentration (Fig. 14d) shows no correlation with mean tread mass loss.
5.2. Particle number concentration This analysis conducted should be regarded as very uncertain in the light of the complex behaviour of the number concentration during and between days. The same analysis as applied for PM data was performed and it was found that when testing that all tyres are equal against the alternative there are some difference, P = 0.017, meaning that the hypothesis that all tyres are equal can be rejected. Pairwise comparison of tyres shows that there is no significant difference between tyres A0, B1, C1 and B2 but that tyre D1 is significantly different from all of the others (Fig. 13). 5.3. PM and PN in relation to TWR The main analysis compares PM and PN between tyres without focusing on the property of the tyres that cause the possible differences observed. The second analysis tries to compare tyres as if TWR is the underlying property responsible for the differences in the tyres’ properties. No significant results were found when using the second analysis (P = 0.548, 0.186, 0.398 and 0.234 when analysing a relation between TWR and PM10 TEOM, PM10 DustTrak, PM2.5 and PN, respectively). In these comparisons, any difference between brands is part of the error component. This means that the results are not meant to be read as pure within brand comparisons.
6. Conclusions The conclusions can be divided into two categories based on the aim of the current study. The first part focuses on the physical properties of tyre wear particles emitted under the selected testing conditions, while the second part is focused on the effect of the TWR to tyre wear emissions. 210
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Fig. 13. Observed and fitted particle number concentration with tyre labels for all days.
Fig. 14. a. Adjusted mean PM10 as a function of mean tread mass loss; b. Tread mass loss as a function of TWR; c. Adjusted mean PM2.5 as a function of mean tread mass loss; d. Adjusted mean particle number concentration as a function of mean tread mass loss.
• PM •
10 concentrations display a similar pattern at each run with quickly increasing concentrations followed by a quasi-stable level, while PM2.5 concentrations continuously increase without reaching a stable level. PN concentrations behave more randomly than the mass concentration with generally low values. Particle mass size distribution was similar to previously reported
• 211
distributions with summer tyres in the simulator, but magnitude of different mass peaks in the distribution varies in different tests depending on tyres used and ambient conditions chosen. Approximately 50% (by mass) of emitted PM10 fall within the size range of fine particles, while PN size distribution are dominated by ultrafine particles and most often peaking at 20–30 nm.
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• The tread mass loss was between 3 and 11 g/tyre resulting in a
Däck- Och Vägbaneslitage. VTI Rapport 660. VTI, Linköping. Gustafsson, M., Blomqvist, G., Gudmundsson, A., Dahl, A., Swietlicki, E., Bohgard, M., Lindbom, J., Ljungman, A., 2008. Properties and toxicological effects of particles from the interaction between tyres, road pavement and winter traction material. Sci. Total Environ. 393, 226–240. Gustafsson, M., Eriksson, O., 2015. Emission of Inhalable Particles from Studded Tyre Wear of Road Pavements: a Comparative Study. 867A. Statens väg- och transportforskningsinstitut, VTI, Linköping. Harrison, R.M., Jones, A.M., Gietl, J., Yin, J., Green, D.C., 2012. Estimation of the contributions of brake dust, tire wear, and resuspension to non-exhaust traffic particles derived from atmospheric measurements. Environ. Sci. Technol. 46, 6523–6529. Hussein, T., Johansson, C., Karlsson, H., Hansson, H.C., 2008. Factors affecting nontailpipe aerosol particle emissions from paved roads: on-road measurements in Stockholm, Sweden. Atmos. Environ. 42, 688–702. Iijima, A., Sato, K., Yano, K., Kato, M., Tago, H., Kato, M., Kimura, H., Furuta, N., 2007. Particle size and composition distribution analysis of automotive brake abrasion dusts for the evaluation of antimony sources of airborne particulate matter. Atmos. Environ. 41, 4908–4919. Kreider, M.L., Panko, J.M., McAtee, B.L., Sweet, L.I., Finley, B.L., 2010. Physical and chemical characterization of tire-related particles: comparison of particles generated using different methodologies. Sci. Total Environ. 408, 652–659. Kukutschová, J., Moravec, P., Tomášek, V., Matějka, V., Smolík, J., Schwarz, J., Seidlerová, J., Šafářová, K., Filip, P., 2011. On airborne nano/micro-sized wear particles released from low-metallic automotive brakes. Environ. Pollut. 159, 998–1006. Kumar, P., Pirjola, L., Ketzel, M., Harrison, R.M., 2013. Nanoparticle emissions from 11 non-vehicle exhaust sources – a review. Atmos. Environ. 67, 252–277. Kupiainen, K., Tervahattu, H., Raisanen, M., Makela, T., Aurela, M., Hillamo, R., 2005. Size and composition of airborne particles from pavement wear, tyres, and traction sanding. Environ. Sci. Technol. 39, 699–706. Kwak, J.H., Kim, H., Lee, J., Lee, S., 2013. Characterization of non-exhaust coarse and fine particles from on-road driving and laboratory measurements. Sci. Total Environ. 458–460, 273–282. Legal Information Institute. § 575.104 49 CFR 575.104-Uniform tire quality grading standards. https://www.law.cornell.edu/cfr/text/49/575.104#e_2_vi. Mantecca, P., Gualtieri, M., Andrioletti, M., Bacchetta, R., Vismara, C., Vailati, G., Camatini, M., 2007. Tire debris organic extract affects Xenopus development. Environ. Int. 33, 642–648. Mathissen, M., Scheer, V., Vogt, R., Benter, T., 2011. Investigation on the potential generation of ultrafine particles from the tire–road interface. Atmos. Environ. 45, 6172–6179. Mazzarella, G., Ferraraccio, F., Prati, M.V., Annunziata, S., Bianco, A., Mezzogiorno, A., Liguori, G., Angelillo, I.F., Cazzola, M., 2007. Effect of diesel exhaust particles on human lung epithelial cells: an in vitro study. Respir. Med. 101, 1155–1162. Panko, J.M., Chu, J., Kreider, M., Unice, K.M., 2013. Measurement of airborne concentrations of tire and road wear particles in urban and rural areas of France, Japan, and the United States. Atmos. Environ. 72, 192–199. Panko, J.M., Kreider, M., Unice, K.M., 2018. Review of Tire Wear Emissions. A Review of Tire Emission Measurement Studies: Identification of Gaps and Future Needs. Nonexhaust Emissions: an Urban Air Quality Problem for Public Health. Impact and Mitigation Measures 2018 Elsevier Inc. Pant, P., Harrison, R.M., 2013. Estimation of the contribution of road traffic emissions to particulate matter concentrations from field measurements: a review. Atmos. Environ. 77, 78–97. Particle Measurement Programme (PMP) Informal Working Group, 2016. 73rd UNECE GRPE Session - PMP IWG. Progress Report. . https://wiki.unece.org/display/trans/ PMP+41st+session. Riediker, M., Devlin, R.B., Griggs, T.R., Herbst, M.C., Bromberg, P.A., Williams, R.W., Casci, W.E., 2004. Cardiovascular effects in patrol officers are associated with fine particulate matter from brake wear and engine emissions. Part. Fibre Toxicol. 1 (2). Sadiktsis, I., Bergvall, C., Johansson, C., Westerholm, R., 2012. Automobile tyres-A potential source of highly carcinogenic dibenzopyrenes to the environment. Environ. Sci. Technol. 46, 3326–3334. Sjödin, A., Ferm, M., Björk, A., Rahmberg, M., Gudmundsson, A., Swietlicki, E., Johansson, C., Gustafsson, M., Blomqvist, G., 2010. Wear Particles from Road Traffic: a Field, Laboratory and Modelling Study. IVL Swedish Environmental Research Institute Ltd., Göteborg. Stephensen, E., Adolfsson-Erici, M., Hulander, M., Parkkonen, J., Forlin, L., 2005. Rubber additives induce oxidative stress in rainbow trout. Aquat. Toxicol. 75, 136–143. Thorpe, A., Harrison, R.M., 2008. Sources and properties of non-exhaust particulate matter from road traffic: a review. Sci. Total Environ. 400, 270–282. Wahlström, J., Olander, L., Olofsson, U., 2010. Size, shape, and elemental composition of airborne wear particles from disc brake materials. Tribol. Lett. 38, 15–24. Wik, A., Dave, G., 2009. Occurrence and effects of tire wear particles in the environment a critical review and an initial risk assessment. Environ. Pollut. 157, 1–11.
calculated wear rate of between 55 and 212 mg/km.
When the effect of the TWR to tyre wear emissions is examined the main conclusions are:
• There is no general relation between TWR and measured tread mass loss or PM , PM or PN concentration. • It seems that tyres of different brands and same TWR display dif10
• •
2.5
ferent wear as well as PM10 and PM2.5 concentrations, thus not allowing a categorization based on the TWR for different brands. Within the subset of two B tyres, the one with lower TWR has higher tread mass loss and production of PM10. Further research with more tyres of the same brand with different TWR will be required to confirm or not the feasibility of categorization within the same brand. When investigating the relation between tread mass loss and PM10 no obvious statistical relation could be found. However, the B1 tyre loses most mass and also has a higher PM10 concentration while the tyre with the highest TWR has lowest PM10 and mass loss. Further research will be required to confirm or not the relationship between tread mass loss and PM10 emissions. No relation between PM2.5 and PN concentration to tread mass loss was observed.
Acknowledgments The authors are grateful to technicians of the VTI (Swedish national road and transport research institute) Tomas Halldin and Dennis Hydén for skillful operation of the road simulator and assistance with tyre handling. References Aatmeeyata, Kaul, D.S., Sharma, M., 2009. Traffic generated non-exhaust particulate emissions from concrete pavement: a mass and particle size study for two-wheelers and small cars. Atmos. Environ. 43, 5691–5697. Amato, F., Pandolfi, M., Moreno, T., Furger, M., Pey, J., Alastuey, A., Bukowiecki, N., Prevot, A.S.H., Baltensberger, U., Querol, X., 2011. Sources and variability of inhalable road dust particles in three European cities. Atmos. Environ. 45, 6777–6787. Boulter, P.G., Thorpe, A., Harrison, R., Allen, A., 2006. Road Vehicle Non-exhaust Particulate Matter: Final Report on Emission Modelling. Published project report PPR110. TRL limited, Wokingham. Dahl, A., Gharibi, A., Swietlicki, E., Gudmundsson, A., Bohgard, M., Ljungman, A., Blomqvist, G., Gustafsson, M., 2006. Traffic-generated emissions of ultrafine particles from pavement–tire interface. Atmos. Environ. 40, 1314–1323. Dorsey, T.F.J., Lafleur, A.L., Kumata, H., Takada, H., Herrero-Jimenez, P., Thilly, W.G., 2006. Correlations of asthma mortality with traffic-related factors: use of catalytic converters and radial tires. J. Occup. Environ. Med. 48, 1321–1327. Gasser, M., Riediker, M., Mueller, L., Perrenoud, A., Blank, F., Gehr, P., RothenRutishauser, B., 2009. Toxic effects of brake wear particles on epithelial lung cells in vitro. Part. Fibre Toxicol. 6 (30). Gietl, J.K., Lawrence, R., Thorpe, A.J., Harrison, R.M., 2010. Identification of brake wear particles and derivation of a quantitative tracer for brake dust at a major road. Atmos. Environ. 44, 141–146. Grigoratos, T., Martini, G., 2014. Non - Exhaust Traffic Related Emissions. Brake and Tyre Wear PM. Literature Survey. JRC Science and Policy Reports 2014. . Grigoratos, T., Martini, G., 2015. Brake wear particle emissions: a review. Environ. Sci. Pollut. Control Ser. 22, 2491–2504. Gualtieri, M., Mantecca, P., Cetta, F., Camatini, M., 2008. Organic compounds in tire particle induce reactive oxygen species and heat-shock proteins in the human alveolar cell line A549. Environ. Int. 34, 437–442. Gualtieri, M., Rigamonti, L., Galeotti, V., Camatini, M., 2005. Toxicity of tire debris extracts on human lung cell line A549. Toxicol. Vitro 19, 1001–1008. Gustafsson, M., Blomqvist, G., Brorström-Lundén, E., Dahl, A., Gudmundsson, A., Johansson, C., Jonsson, P., Swietlicki, E., 2009. NanoWear - Nanopartiklar Från
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Experimental investigation of tread wear and particle emission from tyres with different treadwear marking
T
Theodoros Grigoratosa,∗, Mats Gustafssonb, Olle Erikssonb, Giorgio Martinia a European Commission, Joint Research Centre (JRC), Institute for Energy, Transport and Climate (IETC), Sustainable Transport Unit (STU), Via E Fermi 2749, Ispra, 21027, Italy b Swedish National Road and Transport Research Institute (VTI), SE-581 95, Linköping, Sweden
A R T I C LE I N FO
A B S T R A C T
Keywords: Treadwear rating Tyres durability Tread mass loss Tyre particle emissions Tyre wear nanoparticles
The Treadwear Rating (TWR) provided on the sidewall of the tyre is a marking intended to inform the customer about the expected durability of the tyre. The current study explores whether there is a correlation between the TWR and tyres' tread mass loss. Furthermore, it explores the possible correlation between the TWR and tyre wear dust emitted in the form of PM10 and PM2.5. For that reason, two tyres of the same brand (B) but with different TWR and three tyres of different brands (C and D with the same TWR as one of the B tyres and A with a lower TWR) were tested at a constant speed of 70 km/h by means of the Swedish National Road and Transport Research Institute (VTI) road simulator. Tyres of the same TWR but of different brands showed different behaviour in terms of material loss, PM, and PN emissions under the selected testing conditions. This means that it is not feasible to categorize tyres of different brands in terms of their emissions based on their TWR. The test performed on the two tyres of the same brand but with different TWR showed instead a substantial (not statistically significant) difference in both total wear and PM10 emissions. The tyre with the higher TWR (B2) showed less wear and PM10 emissions compared to the B1 tyre having a lower TWR. Since only two tyres of the same brand and with different TWR were tested, this result cannot be generalized and more tests are necessary to confirm the relation within the same brand. In general, the tyre tread mass loss showed no obvious statistical relation to PM10, PM2.5 or PN concentration. In all cases approximately 50% (by mass) of emitted PM10 fall within the size range of fine particles, while PN size distribution is dominated by nanoparticles most often peaking at 20–30 nm.
1. Introduction As exhaust particle emissions continuously decrease due to the introduction of effective emission control technologies, the attention is shifting to other traffic related sources of particle emissions. Among the – so called – non-exhaust traffic related sources there is a growing concern about particles emitted due to brake wear as well as for particles generated as result of the interaction between tyres and the road surface [Amato et al., 2011]. As far as brake wear particle emissions are concerned, numerous comprehensive studies have been published in the last years covering aspects like brake wear PM and PN emission factors [Grigoratos and Martini, 2015], mass and number size distributions [Harrison et al., 2012; Iijima et al., 2007; Wahlström et al., 2010], chemical characterization [Gietl et al., 2010; Kukutschová et al., 2011; Thorpe and Harrison, 2008], and possible adverse health effects [Gasser et al., 2009; Mazzarella et al., 2007; Riediker et al., 2004]. There is a general consensus among the scientific community that a
∗
standardized sampling and measurement methodology for brake wear particles is missing and that is the main reason why sometimes conclusions of available studies are not comparable, if not contrasting. Following this need the UN Particle Measurement Programme (PMP) group has put together a project which aims at developing a suggested test procedure to investigate brake particle emissions [PMP, 2016]. Regarding tyre wear particle emissions the situation appears to be much more complex. While for some aspects available literature data provide adequate answers to open questions, there are many other aspects for which the current knowledge is not sufficient to reach sound conclusions. On one hand, there is a general consensus that more than 90% by mass of the material emitted as a result of tyre wear is particles with diameter bigger than 10 μm [Gualtieri et al., 2008; Kreider et al., 2010]. Studies also agree that mass size distribution of tyre wear particles displays at least one peak at the coarse size fraction [Aatmeeyata et al., 2009; Gustafsson et al., 2008; Kupiainen et al., 2005; Sjödin et al., 2010]. Finally, tyre wear PM10 emission factors of 3.0–13.0 mg/km
Corresponding author. E-mail address: [email protected] (T. Grigoratos).
https://doi.org/10.1016/j.atmosenv.2018.03.049 Received 1 December 2017; Received in revised form 20 March 2018; Accepted 22 March 2018 1352-2310/ © 2018 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/).
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vehicle [Grigoratos and Martini, 2014; Sjödin et al., 2010; Panko et al., 2018; Pant and Harrison, 2013] are considered typical for passenger cars. On the other hand, the composition of tyre wear particles has not been clarified in the sense that it is not clear if pure tyre wear particles exist in the environment, or all particles consist of a mixture of material coming from the tyres, the road, and the material deposited on it [Kreider et al., 2010]. The contribution of tyre wear particles to ambient PM10 and PM2.5 is estimated to vary between 0.8–8.5% and 0.25–3.0% by mass, respectively [Grigoratos and Martini, 2014]. Recently published data from Panko et al., [2018] report contribution to ambient PM10 and PM2.5 between 0.2–10% and 1.0–7.0% by mass, respectively. The European Tyre & Rubber Manufacturers Association (ETRMA) has reported contributions at the lower range of the above intervals [Panko et al., 2013], while other researchers report higher contributions [Gualtieri et al., 2005; Kwak et al., 2013; Sjödin et al., 2010]. Some studies mention that ultrafine particles are not likely to be emitted under “normal” driving conditions [Mathissen et al., 2011], while others have reported nanoparticle emissions under steady state testing [Dahl et al., 2006; Gustafsson et al., 2008]. Finally, inconsistent conclusions arise from the study of literature data regarding possible adverse health effects in human health [Kumar et al., 2013]. On one hand, the Tyre Industry Project (TIP) group has reported that no specific or major threat for human health related to tyre wear particles has been identified [Panko et al., 2013], while on the other hand, toxicology – in-vitro and animal – studies from other researchers have demonstrated negative effects [Dorsey et al., 2006; Gualtieri et al., 2008; Mantecca et al., 2007; Sadiktsis et al., 2012; Stephensen et al., 2005]. Tyres lose roughly 1.0–1.5 kg in weight during their lifespan among which less than 10% falls in the PM10 fraction [Gualtieri et al., 2008; Kreider et al., 2010]. Most of the material is released in the form of particles with sizes bigger than 10 μm, therefore tyre wear particles are present in all environmental compartments including air, water, soils/ sediments, and biota [Wik and Dave, 2009]. In order to fully understand and possibly control total tyre wear emissions, there would be a need to investigate all open aspects listed in the previous paragraph and – at the same time – understand the impact of each size fraction to the environment. As an alternative approach it was decided to investigate if a relation between the declared durability of the tyres and their total mass loss – as well as their PM10, PM2.5 and PN emissions –exists under specific experimental conditions. If this assumption is confirmed particle emissions from tyres could be controlled through their declared durability. Finally, durability could also be used to control the total material released in the environment as a result of tyre wear. The durability of tyres is an important aspect for the customers that at the moment is not regulated in Europe. In the US, the National Highway Traffic Safety Administration (NHTSA) has established the Uniform Tyre Quality Grading Standards (UTQGS) which intends to assist consumers in making informed choices by requiring information be provided on passenger car tyres about their relative performance in the areas of treadwear, traction, and temperature resistance. Based on the UTQGS methodology tyre manufacturers are obliged to give an indication of the expected durability on the sidewall of the tyre by means of the Treadwear Rating (TWR). TWR takes numbers from 100 to about 700. The higher the number, the higher the mileage that the customer can expect to drive before reaching the minimum allowed tread depth. Details regarding the UTQGS methodology can be found in [Legal Information Institute]. The aim of the current study is to explore whether there is a relation between the TWR and tread mass loss. Additionally, the relation between the TWR and the generation of tyre wear dust in the form of PM10, PM2.5 and PN concentration is explored. Finally, some physical properties of tyre wear particles emitted under non extreme driving conditions are investigated.
Fig. 1. The VTI road simulator.
2. Materials 2.1. The VTI circular road simulator The road simulator (Fig. 1) consists of four wheels that run along a circular track with a diameter of 5.3 m. A separate motor drives each wheel. The speed is constant and can be adjusted up to 70 km/h. The wheel axles have different lengths and therefore the wheels are positioned in different distances from the center. Wheels on axles 1 and 3 are at the track edges, while wheels on axles 2 and 4 are running closer to the middle of the track. An internal air cooling system in the hall is able to temperate the simulator hall to below 0 °C. The VTI circular road simulator is described in detail elsewhere [Gustafsson et al., 2009]. 2.2. Pavement A pavement ring including 14 different asphalt pavements of types stone mastic asphalt with different maximum aggregate sizes, SMA6, SMA8 and SMA11 with granodiorite rock was used for the tests. The SMA pavement construction is wear resistant and commonly used in Nordic countries. The current rock quality and the smaller aggregate sizes (6 and 8 mm) are meant for use in Denmark where no studded tyres are used. 2.3. Tyres Five summer tyres (dimension 205/55 R16) were chosen to study variation in wear and particle emission between different TWR (example of TWR marking in Fig. 2). For this, the initial aim was to use the same brand (B) with three different TWR. This proved to be difficult to find, which is why a second brand (A) was used to represent a low TWR (180). The second aim was to study the variation within tyres of the same TWR from different brands. Tyres employed for the study are presented in Table 1. Information regarding the durability of the tyres is provided by the TWR marking stamped by tyre manufacturers on the sidewall of the tyre as a part of the NHTSA uniform tyre-quality grading system. Treadwear rating uses numbers from 100 to about 700. In theory, a tyre rated 200 would have twice as long lifespan as a tyre rated 100 if used in the same conditions — driver, vehicle and roads. The relative performance of tyres depends upon the actual conditions of their use, variations in driving habits, service practices and differences in road characteristics and climate. There are certain limitations when using the TWR. First of all, the TWR is a ratio and not a mileage. This is because multiple factors determine treadwear rates and most of them are a function of driving 201
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Fig. 2. Tread wear rate marking on tyre.
turned off and simulator accelerated to 70 km/h. The selection of this speed has to do with the fact that summer tyres have demonstrated generally low particle emissions which decrease significantly when lower speeds are applied [Gustafsson et al., 2008]. Thus, the selection of a lower constant speed (i.e. 30 km/h) would result in much lower emissions and therefore would render any observations from the current study as very uncertain. There are obvious limitations resulting from the selection of the constant speed profile (i.e. decelerations are important sources of tyre wear), especially when trying to accurately reproduce real world conditions. However, since the current study aims at understanding whether TWR could be used to control tyre wear, the selection of the steady state profile ensures the comparability of the tests and eliminates the possible effect of the driving profile. After 1 h of testing the simulator is stopped and the cooler – along with a large air filtering fan – are started to reduce deposition and lower the PM10 concentration to initial level. Then the next tyre set is mounted and when PM10 concentration reaches initial level the cooler is turned off to start the next test. Tyre inflation pressure is always checked between tests. For all analyses, a 15-min mean value of PM2.5, PM10 and PN concentration at the end of each simulator run was used. PM concentrations were measured by means of a Tapered Element Oscillating Microbalance (TEOM) and two DustTraks. The TEOM is based on gravimetric technique using a microbalance and gives a value of PM10 mass concentration every 5 min. The method is certified for air quality standard monitoring within the EU. As a complement, two optical instruments (DustTraks) were used during the measurements; one measured mass concentration PM2.5 and the other PM10. The time resolution of the sampling was 3 s for both instruments. Particle size distribution was measured using an APS (Aerodynamic Particle Sizer) model 3321 (TSI, USA) measuring mass distribution and an SMPS (Scanning Mobility Particle Sizer) model 3934 (TSI, USA) measuring number distribution. The SMPS was setup to measure and count particles from 7.37 nm to 311 nm. The APS was equipped with a PM10 inlet and hence, measured particles with aerodynamic diameter from 523 nm to 10 μm. Size distributions of particles measured with the SMPS system are presented as number size distributions and particles measured with the APS are presented as mass size distributions. This is because the fine fraction below 1 μm makes up very little of the mass but contain most of the particles while the coarser particles are very few, but dominate the mass concentration. Detailed information regarding particle measurements can be found elsewhere [Gustafsson et al., 2008; Gustafsson et al., 2009].
Table 1 Tyres used in the study. Tyre Number
Manufacturer
TW Rating (TWR)
Codification
1 2 3 4 5
A B C D B
180 300 300 300 400
A0 B1 C1 D1 B2
Table 2 Chosen experimental design for analyses.
Day 1 Day 2 Day 3
Run1
Run2
Run3
Run4
Run5
5 3 4
1 1 2
4 5 3
2 2 1
5 3 4
Table 3 Mean tread mass loss of tested tyres after 3 h runs in 70 km/h. Tyre Number
Tyre
TWR
Mean mass loss per tyre (g)
Loss per km and car (mg)
1 2 3 4 5
A0 B1 C1 D1 B2
180 300 300 300 400
2.9 11.3 3.2 4.6 2.9
55 214 61 87 55
conditions and operating environment. As a result, actual tyre wear is expected to vary within the same tyre line. However, two tyres with exactly the same compound should have a TWR that varies in accordance with tread depth. Secondly, the TWR is provided for summer tyres but not for winter or studded tyres. Finally, the assigning of TWR is done solely by the tyre manufacturer. 3. Test procedures 3.1. Particle test and measurements The conditions in the road simulator hall are drifting during a test day due to frictional heat warming the pavement, tyres and air. To overcome this effect, a test sequence where the same tyre set is run first and last on each test day was used. For three test days the applied sequence is shown in Table 2. Each test sequence starts with tyres being mounted, cooler being 202
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Fig. 3. PM10 concentration (TEOM) during the three tests days. Figures represent tyre numbers.
regarded as “known” to details or what actually consists of. It is only modelled as straight line background behaviour during the day (one line for each day). The tyre effects are not assumed to change between or within days and are modelled as constants. General behaviour and tyre effects are analysed simultaneously with multiple linear regression and general linear models. Depending on the coding scheme for tyres, the tyre effects can be chosen to express differences between pairs of tyres or differences between tyres and an average of all tested tyres. Both these coding schemes have been used in this study. While in the main analysis the tyre effects are modelled only as constants without any lower level structure, in the second analysis they are modelled as a straight-line function of TWR. Multiple linear regression is also used for this analysis. The main analysis treats differences between tyres simply as differences while the second analysis tries to explain the difference between tyres by the fact that they have different TWR. Generally, these two approaches cannot be combined in one analysis. When comparing tyres the environmental effect is not desirable and analyses adjust for such disturbance. Though this may not be of main importance when comparing tyres, it must be shown how this is treated
3.2. Tyre total wear test Tyre wear test requires longer runs for measurable wear amounts. The test tyres’ tread pattern was checked for attached stones in the pattern and blown free from dust using compressed air. The tyre-rim contact surfaces were swiped with a wet cloth and dried using compressed air. Each tyre was weighed on a balance with 0.1 g accuracy. After each test run the cleaning procedure was repeated. Full sets (4 tyres) were run in 70 km/h for 3 h amounting to 210 km per run. Tyre pressure was checked between each test. Two sets of tyres were tested each day. 3.3. Statistical analysis and design of experiment The choice of the experimental design depends on the details of the analysis and vice versa. The analysis procedure and the choice of the experimental design are described in this section. In the main analysis (1st analysis), the model consists of general behaviour, tyre effects and a random component. The general behaviour describes the effect of changes in the environment. It is not 203
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Fig. 4. PM10 concentration (DustTrak) during the three tests days. Figures represent tyre numbers.
4. Results and discussion
and eliminated from the comparison between tyres. Possibly, straight lines are too simple and the analysis should allow a more complicated shape. However, extending with a second order term does not improve the model significantly. Extending with some higher order function has a clear risk of over-adapting to the data. The design was planned to be optimal for pairwise comparisons of tyres in the main analysis. The differences between two tyres are expressed as a regression coefficient. For one design, there are 10 such comparisons that may not have the same standard error. We assume that the best plan is the one that has minimum value of the maximum standard error among all comparisons. The solution was to search for the most efficient design by scanning through a huge set of randomly generated possible designs. The results indicate that it is efficient to use the same tyre on the first and last run each day. Therefore, the search algorithm was tuned to only scan through such designs. The tyres were labelled 1–5 and the chosen design is shown in Table 2.
4.1. Tyre tread mass loss Table 3 shows the averaged tread mass loss for each tested tyre. Mass loss per km and vehicle (mass emission factor) is calculated between 55 and 214 mg/km with 4 out of 5 tyres being within a narrower threshold of 55–87 mg/km. The constant and tight turning in the road simulator might be expected to cause higher than normal wear rates, but the results from the experiments in the current study show that the range between 55 and 214 mg/km is similar to what other researchers classified as normal driving [Boulter et al., 2006; Grigoratos and Martini, 2014]. It seems that there is a substantial (but not statistically) significant difference in the mass loss between the two tyres of the same brand (B) which is in line with the different TWR value provided by the manufacturer. B1 losses almost 4 times more mass than B2, while the TWR ratio of the two tyres is much lower (4/3). This introduces a doubt whether the mass loss can be fully explained by the difference in the TWR. Unfortunately, it was not possible to find a third tyre of the same 204
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Fig. 5. PM2.5 concentration (DustTrak) during the three tests days. Figures represent tyre numbers.
Fig. 6. Mean percentages PM2.5 of PM10 for all runs shown as calculated from APS data (orange bars) and as measured by the used DustTraks (blue bars). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
loss from the TWR value for different brands of tyres, while it may be feasible within the same brand. This is not completely surprising as the assigning of the TWR is done solely by the tyre manufacturer.
brand with different TWR in order to confirm or not the relation. Surprisingly, the tyre with the lower TWR (A0) showed lower mass loss compared to all 3 tyres of 300 TWR (B1, C1, D1). Furthermore, within the 300 TWR there is a significant variation as it spans between 3 g and over 11 g per tyre. Overall, it seems that it is difficult to predict the mass 205
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Fig. 7. Particle number concentrations during all test days.
simulator hall. The distinct peaks at the end of each run results from rinsing tyres and road surface with compressed air after each run, where after the hall air is filtered from particles using a large filter fan before the next run. B1 tyres seem to reach a slightly higher quasi-stable PM10 level compared to B2 following the trend described for the wear tests. This is observed both on testing days 1 and 2 with both TEOM and DustTrak. However, due to the relatively low level of the PM10 emitted as well as the lack of a third tyre of the same brand with a different TWR no solid conclusion can be reached. Once more A0 tyre seems to have low PM10 emissions and in any case not higher than the rest of the tyres, while the tyres of 300 TWR show a variation in their PM10 emissions without an obvious pattern. PM2.5 follows the same pattern at each run as PM10 without
4.2. PM concentrations The PM10 emitted from summer tyre wear is low compared to the emissions caused by winter or studded tyres, which have been the main research area investigated using the road simulator [Gustafsson and Eriksson, 2015]. The PM10 levels reached for different tyres are about 40–50 μg/m3 (TEOM) and 20–30 μg/m3 (DustTrak) and are in comparison with earlier studies with summer tyres in the simulator [Gustafsson et al., 2009]. PM10 background – at least when TEOM is considered – is about 10–20 μg/m3, therefore measured concentrations are relatively low. Due to low concentrations and 1 s time resolution the noise levels are rather high, therefore Figs. 3 and 4 are smoothed using a 1 min running average. In all tests PM10 increases to a quasi-stable level as a result of a balance between particle sources and sinks in the 206
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Fig. 8. Particle mass size distributions from all runs (15 min mean values at end of each 1-h test). In the lower row, the background concentration has been subtracted.
Fig. 9. Particle number size distributions from all runs (15 min mean values at end of each 1-h test). In the lower row, the background concentration has been subtracted.
4.3. PN concentrations
reaching the quasi-equilibrium before the run stops (Fig. 5). The concentration levels at stop are around 10–15 μg/m3. This indicates – based also on the measurement of PM10 – that approximately 50% of the emitted particles (by mass) fall within the size range of PM2.5. This is confirmed in Fig. 6 where the PM2.5/PM10 ratio from both DustTraks and calculated from APS data is shown. The standard deviation is caused by the ongoing increase in concentration during the data outtake. The deviation is higher in the DustTrak data due to higher time resolution (1 s compared to 20 s for APS). DustTrak data are relatively constant around 50–60%, while the APS calculated data are generally slightly lower. Overall, it seems that there is no direct correlation of the PM2.5 concentrations with the TWR marking but due to the relatively low level of emissions it is very difficult to reach solid conclusions.
Particle number concentration measured by means of the SMPS reveals a more complex pattern from day to day. Day 1 shows distinctly growing particle peaks, while on Days 2 and 3 the peaks are sometimes growing, sometimes rapidly growing followed by a slower decrease or sometimes hardly noticeable (Fig. 7). Not knowing the exact nature of these particles (which are likely not to have the same formation process as coarser particles) it is difficult to speculate about the reasons for this behaviour. In any case tyres D1 showed constantly higher PN concentrations compared to the other tyres. On the other hand, tyres B1 showed relatively low PN emissions, which in combination with their relatively high mass emissions show that the higher number of the 207
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Table 4 Results of regression analysis for PM10, PM2.5 and PN concentration. Values for PM10 and PM2.5 are scaled by 103. PM10 TEOM
Level day 1 Slope day 1 Level day 2 Slope day 2 Level day 3 Slope day 3 A0 B1 C1 D1 B2
PM10 DustTrak
PM2.5 DustTrak
Particle Number
Coefficient
Standard Error
Coefficient
Standard Error
Coefficient
Standard Error
Coefficient
Standard Error
42.78 1.32 48.33 −2.72 31.64 2.18 −0.76 3.04 −1.60 2.60 −3.29
2.02 1.37 2.02 1.37 2.02 1.37 2.32 2.32 2.37 2.37 2.37
23.53 0.87 25.83 2 .07 19.37 1.24 0.69 1.27 −1.24 0.68 −1.40
0.82 0.56 0.82 0.56 0.82 0.56 0.94 0.94 0.97 0.97 0.97
11.11 0.54 12.70 1.26 10.54 0.74 0.38 0.52 −1.01 0.61 −0.51
0.62 0.42 0.62 0.42 0.62 0.42 0.71 0.71 0.73 0.73 0.73
7010 751 2031 −413 1309 633 −838 −632 −552 1750 272
279 190 279 190 279 190 321 321 328 328 328
Fig. 10. Observed and fitted PM10 (TEOM) values with tyre labels for all days.
below 1 μm. These findings are in line with previously reported data showing bimodal mass size distributions of tyre wear particles with one peak at the coarser size fraction and another close to 1 μm (Aatmeeyata et al., 2009; Gustafsson et al., 2008; Sjödin et al., 2010). It should be noted that PM10 mass size distributions from tyres are not consistent in literature, but varies greatly depending on the type of tyres tested and testing methods used [Grigoratos and Martini, 2014; Hussein et al., 2008]. It could be concluded that the TWR does not seem to have any kind of effect on the mass size distribution at least in terms of the shape of the distribution. Overall, the variation in the particle mass distribution appears to be dominated by the day-to-day differences, with no differences visually discerned among individual tyres. The concentration levels in the number size distribution in Fig. 9 should be regarded as uncertain, in the light of the complex behaviour
particles emitted from those tyres are of larger sizes. No particular conclusions can be drawn regarding the effect of TWR to PN concentrations as these particles mainly fall in the ultrafine size range and therefore their overall concentrations are low.
4.4. Mass and number size distributions The size distribution over each run measured by means of the APS appears to have similar shapes during each test day. In Fig. 8, the upper row of diagrams shows the actual mass size distributions, while the lower depicts the mass size distributions when the background distributions have been subtracted. The particle contributions from the tyres during day 1 and 3 are wide peaking at 2–7 μm. A coarser peak is noted at 5–6 μm on day 2. All days appear to have a second peak just 208
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Fig. 11. Observed and fitted PM10 (DustTrak) values with tyre labels for all days.
using the main analysis. The vertical distances between circles and bullets are estimates of the random variation. The reference lines represent the general behaviour during the day. The fourth subplot shows the adjusted mean emission for each tyre in comparison to TWR. The adjustment procedure levels out the effect of variation in general behaviour between and within days. The plus-signs show the fitted values for the second analysis. In Fig. 10 the fourth subplot confirms the initial observations described in paragraph 3.2. B1 tyres showed higher PM10 level (not statistically significant) compared to the corresponding of the same brand but with higher TWR (B2). The statistical uncertainty of the difference does not allow for a definite conclusion. A0 seems to be a lower PM10 emitter compared to two of the 300 TWR tyres (B1 and D1), while among the 300 TWR tyres C1 showed a different behaviour in their PM10 emissions compared to the other two brands. When statistically testing the hypothesis that all tyres are equal in PM10 emission against the alternative that there is at least some difference, P = 0.638, meaning that we cannot reject the hypothesis that all tyres emit PM10 equally. When the analysis is performed based on the DustTrak measurements it is estimated that tyre A0 has 0.6889 μg/m3 higher value than the average tyre after adjusting for the difference in general behaviour between and within days. Again B1 tyres are the higher emitter. The fourth subplot (Fig. 11) confirms the observations described in the previous paragraph. However, when statistically testing the hypothesis that all tyres are equal in PM10 emission against the alternative that there is at least some difference, P = 0.349, meaning that we cannot reject the hypothesis that all tyres emit PM10 equally. The data for PM2.5 have different level than PM10 but the assumed structure of the data is the same and the data are collected from the same experimental design. The fourth subplot (Fig. 12) shows that,
of the number concentration during and between days. Nevertheless, all tests conducted by means of the SMPS reveal a distinct peak at 20–30 nm. Numbers decrease rapidly towards coarser sizes and few are over 100 nm in size. During day 2, there seems to be higher numbers in the coarser sizes and day 3 even a tendency for a secondary peak. Again, TWR does not seem to have any kind of effect on the particle number distribution at least in terms of the type and the peak(s) of the distribution. 5. Statistical analyses The main focus of this paragraph is to use the results and initial observations in order to investigate statistical relations between tyres and PM/PN concentrations. Since PM10 is measured using both TEOM and DustTrak, analyses are made on data for both instruments. Also, PM2.5 from DustTrak and PN concentration derived from the SMPS are analysed and presented. The results of the regression analysis for PM10 measured by the TEOM and DustTrak, as well as for PM2.5 measured by the DustTrak are shown in Table 4. Studied tyres are depicted in the subsequent figures based on the following colour codification (A0–Black; B1- Red; C1–Green; D1–Blue; B2–Aqua). 5.1. PM10 and PM2.5 The tyre effects compare each tyre with the mean of all tested tyres. All 5 tyre effects are not estimated in the same analysis. Table 4 combines results from two analyses. The levels estimate the level at the middle of the day (3d out of 5 runs). The slope estimates the difference between two consecutive runs. PM10 data (TEOM) are shown in Fig. 10. The bullets show the observations and the general behaviour. The circles show the fitted values 209
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Fig. 12. Observed and fitted PM2.5 values with tyre labels for all days.
5.4. Tyre tread mass loss and relation to TWR, PM and PN emissions
unlike PM10 measurements, B2 tyre isn't linked to the lowest PM2.5 emissions among all tyres. This is an indication that lower PM10 emissions don't necessarily mean lower PM2.5 emissions. When testing the hypothesis that all tyres are equal in PM2.5 emission against the alternative that there are differences, P = 0.567, meaning that we cannot reject the hypothesis that the tyres emit PM2.5 equally.
The tread mass loss as measured in this study did not show any statistical relation to the TWR marking (Fig. 14a). The variation within the TWR 300 marking is high due to the B1 tyre which wears about three times more than all other tyres. Also, the lower TWR tyre showed very low wear compared to higher TWR tyres. Within the B brand tyres, the order of wear and TWR marking seems to support a relation, but this is uncertain, since only two types are included. A third tyre of the same brand, either of lower (< 200) or higher (> 500) TWR could confirm or not this observation. To study the relation between tread mass loss and PM10, the adjusted mean PM10 from previous statistical analysis was plotted to the mass loss (Fig. 14b). No obvious relation could be found, but the B1 tyres lose most mass and also have a higher PM10 concentration than the other tyres. Further, the TWR 400 tyre showed lowest PM10 and mass loss. Within the same producer a relation between mass loss and PM10 emission that might be related to TWR is present. The A0 tyre with TWR 180 has as low mass loss as the B2, but higher PM10 emission, while the two other TWR 300 tyres diverge. The results for PM2.5 (Fig. 14c) are similar and no statistic correlations are found. Finally, PN concentration (Fig. 14d) shows no correlation with mean tread mass loss.
5.2. Particle number concentration This analysis conducted should be regarded as very uncertain in the light of the complex behaviour of the number concentration during and between days. The same analysis as applied for PM data was performed and it was found that when testing that all tyres are equal against the alternative there are some difference, P = 0.017, meaning that the hypothesis that all tyres are equal can be rejected. Pairwise comparison of tyres shows that there is no significant difference between tyres A0, B1, C1 and B2 but that tyre D1 is significantly different from all of the others (Fig. 13). 5.3. PM and PN in relation to TWR The main analysis compares PM and PN between tyres without focusing on the property of the tyres that cause the possible differences observed. The second analysis tries to compare tyres as if TWR is the underlying property responsible for the differences in the tyres’ properties. No significant results were found when using the second analysis (P = 0.548, 0.186, 0.398 and 0.234 when analysing a relation between TWR and PM10 TEOM, PM10 DustTrak, PM2.5 and PN, respectively). In these comparisons, any difference between brands is part of the error component. This means that the results are not meant to be read as pure within brand comparisons.
6. Conclusions The conclusions can be divided into two categories based on the aim of the current study. The first part focuses on the physical properties of tyre wear particles emitted under the selected testing conditions, while the second part is focused on the effect of the TWR to tyre wear emissions. 210
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Fig. 13. Observed and fitted particle number concentration with tyre labels for all days.
Fig. 14. a. Adjusted mean PM10 as a function of mean tread mass loss; b. Tread mass loss as a function of TWR; c. Adjusted mean PM2.5 as a function of mean tread mass loss; d. Adjusted mean particle number concentration as a function of mean tread mass loss.
• PM •
10 concentrations display a similar pattern at each run with quickly increasing concentrations followed by a quasi-stable level, while PM2.5 concentrations continuously increase without reaching a stable level. PN concentrations behave more randomly than the mass concentration with generally low values. Particle mass size distribution was similar to previously reported
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distributions with summer tyres in the simulator, but magnitude of different mass peaks in the distribution varies in different tests depending on tyres used and ambient conditions chosen. Approximately 50% (by mass) of emitted PM10 fall within the size range of fine particles, while PN size distribution are dominated by ultrafine particles and most often peaking at 20–30 nm.
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• The tread mass loss was between 3 and 11 g/tyre resulting in a
Däck- Och Vägbaneslitage. VTI Rapport 660. VTI, Linköping. Gustafsson, M., Blomqvist, G., Gudmundsson, A., Dahl, A., Swietlicki, E., Bohgard, M., Lindbom, J., Ljungman, A., 2008. Properties and toxicological effects of particles from the interaction between tyres, road pavement and winter traction material. Sci. Total Environ. 393, 226–240. Gustafsson, M., Eriksson, O., 2015. Emission of Inhalable Particles from Studded Tyre Wear of Road Pavements: a Comparative Study. 867A. Statens väg- och transportforskningsinstitut, VTI, Linköping. Harrison, R.M., Jones, A.M., Gietl, J., Yin, J., Green, D.C., 2012. Estimation of the contributions of brake dust, tire wear, and resuspension to non-exhaust traffic particles derived from atmospheric measurements. Environ. Sci. Technol. 46, 6523–6529. Hussein, T., Johansson, C., Karlsson, H., Hansson, H.C., 2008. Factors affecting nontailpipe aerosol particle emissions from paved roads: on-road measurements in Stockholm, Sweden. Atmos. Environ. 42, 688–702. Iijima, A., Sato, K., Yano, K., Kato, M., Tago, H., Kato, M., Kimura, H., Furuta, N., 2007. Particle size and composition distribution analysis of automotive brake abrasion dusts for the evaluation of antimony sources of airborne particulate matter. Atmos. Environ. 41, 4908–4919. Kreider, M.L., Panko, J.M., McAtee, B.L., Sweet, L.I., Finley, B.L., 2010. Physical and chemical characterization of tire-related particles: comparison of particles generated using different methodologies. Sci. Total Environ. 408, 652–659. Kukutschová, J., Moravec, P., Tomášek, V., Matějka, V., Smolík, J., Schwarz, J., Seidlerová, J., Šafářová, K., Filip, P., 2011. On airborne nano/micro-sized wear particles released from low-metallic automotive brakes. Environ. Pollut. 159, 998–1006. Kumar, P., Pirjola, L., Ketzel, M., Harrison, R.M., 2013. Nanoparticle emissions from 11 non-vehicle exhaust sources – a review. Atmos. Environ. 67, 252–277. Kupiainen, K., Tervahattu, H., Raisanen, M., Makela, T., Aurela, M., Hillamo, R., 2005. Size and composition of airborne particles from pavement wear, tyres, and traction sanding. Environ. Sci. Technol. 39, 699–706. Kwak, J.H., Kim, H., Lee, J., Lee, S., 2013. Characterization of non-exhaust coarse and fine particles from on-road driving and laboratory measurements. Sci. Total Environ. 458–460, 273–282. Legal Information Institute. § 575.104 49 CFR 575.104-Uniform tire quality grading standards. https://www.law.cornell.edu/cfr/text/49/575.104#e_2_vi. Mantecca, P., Gualtieri, M., Andrioletti, M., Bacchetta, R., Vismara, C., Vailati, G., Camatini, M., 2007. Tire debris organic extract affects Xenopus development. Environ. Int. 33, 642–648. Mathissen, M., Scheer, V., Vogt, R., Benter, T., 2011. Investigation on the potential generation of ultrafine particles from the tire–road interface. Atmos. Environ. 45, 6172–6179. Mazzarella, G., Ferraraccio, F., Prati, M.V., Annunziata, S., Bianco, A., Mezzogiorno, A., Liguori, G., Angelillo, I.F., Cazzola, M., 2007. Effect of diesel exhaust particles on human lung epithelial cells: an in vitro study. Respir. Med. 101, 1155–1162. Panko, J.M., Chu, J., Kreider, M., Unice, K.M., 2013. Measurement of airborne concentrations of tire and road wear particles in urban and rural areas of France, Japan, and the United States. Atmos. Environ. 72, 192–199. Panko, J.M., Kreider, M., Unice, K.M., 2018. Review of Tire Wear Emissions. A Review of Tire Emission Measurement Studies: Identification of Gaps and Future Needs. Nonexhaust Emissions: an Urban Air Quality Problem for Public Health. Impact and Mitigation Measures 2018 Elsevier Inc. Pant, P., Harrison, R.M., 2013. Estimation of the contribution of road traffic emissions to particulate matter concentrations from field measurements: a review. Atmos. Environ. 77, 78–97. Particle Measurement Programme (PMP) Informal Working Group, 2016. 73rd UNECE GRPE Session - PMP IWG. Progress Report. . https://wiki.unece.org/display/trans/ PMP+41st+session. Riediker, M., Devlin, R.B., Griggs, T.R., Herbst, M.C., Bromberg, P.A., Williams, R.W., Casci, W.E., 2004. Cardiovascular effects in patrol officers are associated with fine particulate matter from brake wear and engine emissions. Part. Fibre Toxicol. 1 (2). Sadiktsis, I., Bergvall, C., Johansson, C., Westerholm, R., 2012. Automobile tyres-A potential source of highly carcinogenic dibenzopyrenes to the environment. Environ. Sci. Technol. 46, 3326–3334. Sjödin, A., Ferm, M., Björk, A., Rahmberg, M., Gudmundsson, A., Swietlicki, E., Johansson, C., Gustafsson, M., Blomqvist, G., 2010. Wear Particles from Road Traffic: a Field, Laboratory and Modelling Study. IVL Swedish Environmental Research Institute Ltd., Göteborg. Stephensen, E., Adolfsson-Erici, M., Hulander, M., Parkkonen, J., Forlin, L., 2005. Rubber additives induce oxidative stress in rainbow trout. Aquat. Toxicol. 75, 136–143. Thorpe, A., Harrison, R.M., 2008. Sources and properties of non-exhaust particulate matter from road traffic: a review. Sci. Total Environ. 400, 270–282. Wahlström, J., Olander, L., Olofsson, U., 2010. Size, shape, and elemental composition of airborne wear particles from disc brake materials. Tribol. Lett. 38, 15–24. Wik, A., Dave, G., 2009. Occurrence and effects of tire wear particles in the environment a critical review and an initial risk assessment. Environ. Pollut. 157, 1–11.
calculated wear rate of between 55 and 212 mg/km.
When the effect of the TWR to tyre wear emissions is examined the main conclusions are:
• There is no general relation between TWR and measured tread mass loss or PM , PM or PN concentration. • It seems that tyres of different brands and same TWR display dif10
• •
2.5
ferent wear as well as PM10 and PM2.5 concentrations, thus not allowing a categorization based on the TWR for different brands. Within the subset of two B tyres, the one with lower TWR has higher tread mass loss and production of PM10. Further research with more tyres of the same brand with different TWR will be required to confirm or not the feasibility of categorization within the same brand. When investigating the relation between tread mass loss and PM10 no obvious statistical relation could be found. However, the B1 tyre loses most mass and also has a higher PM10 concentration while the tyre with the highest TWR has lowest PM10 and mass loss. Further research will be required to confirm or not the relationship between tread mass loss and PM10 emissions. No relation between PM2.5 and PN concentration to tread mass loss was observed.
Acknowledgments The authors are grateful to technicians of the VTI (Swedish national road and transport research institute) Tomas Halldin and Dennis Hydén for skillful operation of the road simulator and assistance with tyre handling. References Aatmeeyata, Kaul, D.S., Sharma, M., 2009. Traffic generated non-exhaust particulate emissions from concrete pavement: a mass and particle size study for two-wheelers and small cars. Atmos. Environ. 43, 5691–5697. Amato, F., Pandolfi, M., Moreno, T., Furger, M., Pey, J., Alastuey, A., Bukowiecki, N., Prevot, A.S.H., Baltensberger, U., Querol, X., 2011. Sources and variability of inhalable road dust particles in three European cities. Atmos. Environ. 45, 6777–6787. Boulter, P.G., Thorpe, A., Harrison, R., Allen, A., 2006. Road Vehicle Non-exhaust Particulate Matter: Final Report on Emission Modelling. Published project report PPR110. TRL limited, Wokingham. Dahl, A., Gharibi, A., Swietlicki, E., Gudmundsson, A., Bohgard, M., Ljungman, A., Blomqvist, G., Gustafsson, M., 2006. Traffic-generated emissions of ultrafine particles from pavement–tire interface. Atmos. Environ. 40, 1314–1323. Dorsey, T.F.J., Lafleur, A.L., Kumata, H., Takada, H., Herrero-Jimenez, P., Thilly, W.G., 2006. Correlations of asthma mortality with traffic-related factors: use of catalytic converters and radial tires. J. Occup. Environ. Med. 48, 1321–1327. Gasser, M., Riediker, M., Mueller, L., Perrenoud, A., Blank, F., Gehr, P., RothenRutishauser, B., 2009. Toxic effects of brake wear particles on epithelial lung cells in vitro. Part. Fibre Toxicol. 6 (30). Gietl, J.K., Lawrence, R., Thorpe, A.J., Harrison, R.M., 2010. Identification of brake wear particles and derivation of a quantitative tracer for brake dust at a major road. Atmos. Environ. 44, 141–146. Grigoratos, T., Martini, G., 2014. Non - Exhaust Traffic Related Emissions. Brake and Tyre Wear PM. Literature Survey. JRC Science and Policy Reports 2014. . Grigoratos, T., Martini, G., 2015. Brake wear particle emissions: a review. Environ. Sci. Pollut. Control Ser. 22, 2491–2504. Gualtieri, M., Mantecca, P., Cetta, F., Camatini, M., 2008. Organic compounds in tire particle induce reactive oxygen species and heat-shock proteins in the human alveolar cell line A549. Environ. Int. 34, 437–442. Gualtieri, M., Rigamonti, L., Galeotti, V., Camatini, M., 2005. Toxicity of tire debris extracts on human lung cell line A549. Toxicol. Vitro 19, 1001–1008. Gustafsson, M., Blomqvist, G., Brorström-Lundén, E., Dahl, A., Gudmundsson, A., Johansson, C., Jonsson, P., Swietlicki, E., 2009. NanoWear - Nanopartiklar Från
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