On-road vehicle measurements of brake wear particle emissions

Journal Pre-proof On-road vehicle measurements of brake wear particle emissions Ferdinand H. Farwick zum Hagen, Marcel Mathissen, Tomasz Grabiec, Tim Hennicke, Marc Rettig, Jaroslaw Grochowicz, Rainer Vogt, Thorsten Benter PII:

S1352-2310(19)30582-5

DOI:

https://doi.org/10.1016/j.atmosenv.2019.116943

Reference:

AEA 116943

To appear in:

Atmospheric Environment

Received Date: 4 May 2019 Revised Date:

26 August 2019

Accepted Date: 28 August 2019

Please cite this article as: Farwick zum Hagen, F.H., Mathissen, M., Grabiec, T., Hennicke, T., Rettig, M., Grochowicz, J., Vogt, R., Benter, T., On-road vehicle measurements of brake wear particle emissions, Atmospheric Environment (2019), doi: https://doi.org/10.1016/j.atmosenv.2019.116943. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

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On-Road Vehicle Measurements of Brake

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Wear Particle Emissions

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Ferdinand H. Farwick zum Hagen a,b,*, Marcel Mathissen a,*, Tomasz

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Grabiec c,1 , Tim Hennicke c, Marc Rettig c, Jaroslaw Grochowicz c,

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Rainer Vogt a, Thorsten Benterb

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a

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Germany

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b

Ford Werke GmbH, Research and Innovation Center, Süsterfeldstraße 200, 52072 Aachen,

Bergische Universität Wuppertal, Department of Physical and Theoretical Chemistry, Gauß-

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Straße 20, 42097 Wuppertal, Germany

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c

Ford Werke GmbH, Henry Ford Straße 1, 50735 Köln, Germany

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*Corresponding authors: Ferdinand H. Farwick zum Hagen, e-mail address:

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[email protected]; Marcel Mathissen, e-mail address: [email protected]

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Current address: ILJIN Bearing GmbH, Amsterdam Str. 6a, 97424 Schweinfurt, Germany

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Submitted to: Atmospheric Environment – Elsevier

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Abstract

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Brake wear emissions are investigated during on-road driving with a midsize passenger car on a

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closed test track. A novel sampling system is designed that aims at monitoring the entire aspiration of

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brake wear particles. The wear particles are collected by a cone-shaped sampler, which is attached at

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the outer side of the wheel rim. Thus, the air flow direction penetrating the brake assembly from the

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vehicle underbody to the vehicle outside is preserved. For analysis, the wear aerosol is routed to the

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trunk of the car. In addition to the emission measurements, the setup flow is monitored, which enables

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quantification of the acquired emission data. A 3-hour subsection of the Los Angeles City Traffic

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(LACT), representative for realistic driving behavior, is used as test cycle. For two different brake

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materials, PM10 emission factors are ranging from 1.4 to 2.1 mg km-1 brake-1, while one material is

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found to be 18 % less emissive. Due to high brake disc temperatures exceeding 170°C, high particle

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number emissions occur through ultrafine particle generation. The unrealistic temperatures are

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caused by the limited brake cooling in the semi-closed measurement setup. In contrast, the reference

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brake temperature does not exceed 153°C during the same test, thus ultrafine brake particle

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emissions are not expected during normal driving. Furthermore, well run-in brake material shows

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emission factors near the lower measurement limit at the unrealistic temperatures, suggesting that

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ultrafine particle emissions are characteristic for brand-new materials in combination with high brake

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temperatures observed due to the semi-closed housing of the measurement setup.

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Keywords

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Emission factor

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Brake wear

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PM10

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On-road driving

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Size distribution

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1. Introduction

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Road transport-related particulate matter (PM) contributes approximately 8 % or 11 %, to

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anthropogenic particle emissions for primary PM10 and PM2.5, respectively, measured in Europe (EU-

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33) (Tista et al., 2018). While the exhaust emissions decrease continuously due to improved exhaust

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aftertreatment and filter technologies, the non-exhaust share is increasing because of rising vehicle

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mileage. According to the latest results of the European Environment Agency (EEA), a significant

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fraction of 33.9 % and 26.7 % of the road transport-related PM is assigned to automobile tire and

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brake wear for PM10 and PM2.5, respectively. Further studies consider brake wear separately and

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report contributions of 21 % to the traffic related PM10 in urban areas (Bukowiecki et al., 2010;

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Grigoratos and Martini, 2015). While most of the brake wear deposits either on road or vehicle sites

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(Kumar et al., 2013), about 35-55 % becomes airborne (Garg et al., 2000; Harrison et al., 2012).

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Sanders et al. (2002) even report airborne fractions of 50-70 % escaping the wheel, while about 15-25

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% remains on the wheel.

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Currently, a robust brake particle measurement procedure is developed within the framework of the

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UNECE-GRPE-PM program (PMP-Group, 2019). The most promising approach is the measurement

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of brake wear particles on brake dynamometers. This allows reproducible investigations under

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confined and controlled test conditions, i.e., drive cycles or environmental and vehicle simulation

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settings. The number of dynamometer studies is large and versatile measurement techniques are

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used: With pioneering setup approaches, Garg et al. (2000) and Sanders et al. (2002) established the

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first controlled particle measurements on brake dynamometers. Followed by other studies, the setup

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configurations were modified and ranged from entirely open (Iijima et al., 2008; Sanders et al., 2002)

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over semi-closed (Perricone et al., 2015) to completely brake enclosing arrangements (Garg et al.,

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2000; Hagino et al., 2015; Kukutschova et al., 2011). Further improvements were made regarding

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sampling, i.e., from non-isokinetic to isokinetic sampling, and routing of the brake aerosol in such way

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that particle transport losses are reduced (Farwick zum Hagen et al., 2019). In recent years brake

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wear investigations on dynamometers became more and more robust but the investigation of brake

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wear particles under on-road driving conditions remained unattended. There are only a few studies

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reporting brake wear investigations in on-road driving experiments: Sanders et al. (2003) measured

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brake emissions by sampling in close vicinity to the brake with small probes. Mathissen et al. (2011),

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Kwak et al. (2013), and Wahlström and Olofsson (2014) sampled directly at the friction interface of the

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brake and showed the correlation between braking and emissions. Since the brake dust was sampled

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only partially, a proper emission quantification remained impossible. However, emission quantification

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is crucial for verifying laboratory results through realistic driving investigations.

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The present work introduces a novel sampling approach for brake wear measurements during on-

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road driving. The setup was designed in close relation to dynamometer studies, i.e., the airborne

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brake wear particles should be collected entirely at the brake and transported to the sampling point.

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The wheel remained as enclosure of the brake and only brake wear particles that normally enter the

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environment were sampled. Besides the introduction of the novel sampling approach, the focus of the

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paper is on the following three topics:

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1) Initially, the sampling system was verified by air flow simulations, empirical particle loss

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calculations, and an experimental determination of the aspiration efficiency and background

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contribution through tracer gas experiments.

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2) The novel setup design enabled emission quantification and on-road emission factors (EF)

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could be estimated. Furthermore, ultrafine particle (UF) emissions were studied and its

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relevance for realistic driving was evaluated.

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3) Since the tests were performed in repeatable manner, a test-to-test comparison and material

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ranking became possible. Within the scope of the EU-funded project “LowBraSys” (Low

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environmental impact brake system), the emission behavior of two types of brake materials

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was investigated under realistic driving scenarios.

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2. Material and methods

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2.1 Particle measurement setup

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The measurement concept was based on a constant volume sampling (CVS) system as this setup

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allowed quantification of emission data and improved the reproducibility of experiments (Perricone et

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al., 2016). The brake dust was collected by a sampling apparatus and routed to the measurement

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devices, where the particles were detected. In this process, the sampling procedure was particularly

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challenging because the entire vehicle geometry and dynamics had to be taken into account: On one

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hand the entire brake aerosol had to be collected and particles losses had to be avoided, while on the

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other hand changes to the car geometry – especially near the brake – had to be as little as possible.

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Therefore, a complete enclosure of the brake, where the dust could have been easily sampled or

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even pre-filtered air could have been used, was excluded. The resulting setup would have led to

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modifications that were too far away from real-world conditions. Additionally, the brake cooling was

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expected to be insufficient as well. In order to find a proper way of sampling, the local air flow at the

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brake and inside the wheel house was analyzed by Computational Fluid Dynamics (CFD): During

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driving, the air at the vehicle underbody is compressed and exits to the vehicle sides. This generates

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an air flow inside the wheel rims from the inside to the outside, which cools down the brakes.

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Conserving the flow direction and thus a natural brake cooling, the brake aerosol was sampled at the

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outside of the wheel rim, as shown in figure 1. A cone-shaped collector, which was attached at the

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outside of the wheel rim, fully covered all wheel rim openings (Mathissen et al., 2018b). The geometry

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of the wheel rim itself served as a housing of the brake. Only brake wear that was released to the

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environment was sampled; as it will be shown in section 3.2, the background contribution was

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negligible. Small extensions of the dust shield at the brake and an additional shield inside the wheel

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rim avoided particle loss on vehicle side. An additional shielding at the wheel house reduced

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turbulences on vehicle side.

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Figure 1 – (a) Dust capturing cone at left front wheel (top view). The airflow, indicated by blue (ambient) and red arrows (dust contaminated air), is forced to flow from the inside to the outside of the rim. (b) Test car with measuring setup. Yellow background area shows components that are inside the car. The brake dust is routed from the left front wheel to the trunk (red arrows), where the measuring equipment is located. A fraction of the total aerosol is analyzed by the TSI EEPS, TSI Dusttrak, and TSI APS through a flow splitter. The air flow is monitored by a TSI air velocity transducer. The ambient air is monitored by a second TSI Dusttrak. (c) Image of the test car. The aerosol flow is indicated by red arrows. The yellow crosshairs point to positions, where tracer gas has been released during initial experiments: 1) direct dosing (100 % aspiration), 2) at the brake, closely behind the brake pads (compare (a)) in front of the tire (background investigation). [2-column width, 300dpi]

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The setup was customized for testing at the left front brake of a midsize passenger car. For stable

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flow conditions, the air flow of the system was driven constantly by a blower at the end of the

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transport line. The high negative pressure of the blower (stand-alone specification: 1100 Pa at 250

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m3/h) was roughly estimated in order to properly compensate the pressure drop along the capturing

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cone and the transport line. As sketched in figure 1, ambient air from the vehicle underbody was

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sucked in at the front wheel. The air passed the dust shields before flushing the brake, where it

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intermixed with brake particles. The air was drawn through the rim holes into the capturing cone. The

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shape inside the capturing cone directed the air while reducing dead air spaces that potentially led to

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turbulences. The aerosol was then routed through a swivel joint connecting the rotating cone on one

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side to a stationary hose (dhose,1=38 mm, lhose,1=1.4 m, conductive and grounded) on the other side.

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The hose was routed in a horizontal U-bend and later expanded to a larger diameter hose (dhose,2=100

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mm, lhose,2=5 m) that minimized particle losses. It was further routed over the hood, along the right A-

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pillar onto the vehicle roof, entered the passenger cabin at the right rear window, and was connected

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to the sampling tube (dtube =100 mm, ltube=0.6 m) in the trunk of the car. This tube was positioned in

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front of the blower and was used for sampling and continues monitoring of the air velocity inside (air

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velocity transducer, TSI 8455). The aerosol was sampled in the center of the tube with an

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isokinetically adjusted probe considering an estimated setup flow of 89 m3/h (Baron et al., 2011). The

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probe was connected via a flow splitter to an Aerodynamic Particle Sizer (APS, TSI 3321; sampling

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rate: 1 Hz; particle size range (aerodynamic): 0.5-20 µm; number of channels: 52), Dusttrak (DT, TSI

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8533; sampling rate: 1 Hz) with PM10-impactor upstream, and an Engine Exhaust Particle Sizer

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(EEPS, TSI 3090; sampling rate: 10 Hz; particle size range (electrical mobility): 5.6-560 nm; number

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of channels: 32). Downstream of the blower, the aerosol was routed out of the passenger cabin. For

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PM background monitoring a second DT device was used sampling at the left rear window.

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2.2 Tracer gas measurement setup

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Before studying brake wear particle emissions, a series of measurements were performed to

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characterize the setup. The investigation focused on estimating the aspiration efficiency of the dust

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capturing system and the signal contamination by ambient aerosols. For this purpose, a tracer gas

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study was conducted as described by Mathissen et al. (2011). It is based on assuming similar

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characteristics for particles and tracer gas and allows a mapping of the particle trace. Although this

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assumption is only partially true, it had advantages over studies with artificial test aerosols instead of

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tracer gas: i) The tracer gas allowed mass conservation calculations as it was dosed in a controlled

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way, ii) it was not distorted by the setup geometry (e.g., leading to losses), and iii) it was detected with

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a high sampling sensitivity. Furthermore, the tracer gas was not contaminated with species from other

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sources; in case of using test aerosols, a contamination could not have been excluded, as the

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sampling setup was semi-closed and ambient air aerosols were always present.

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For the investigation, a pressurized tracer gas mixture of NO in N2 (10 % by volume) was used. The

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cylinder was connected to a flow controller (MKS, Mass Flow Controller 200 sccm /min) that switched

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the gas flow on and off every 20 seconds and regulated the flow to 100 sccm/min. The gas was

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routed with a Teflon tube along the outside of the car and was released at three different locations

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into the measurement setup (compare figure 1(c)):

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1) The gas mixture was released directly into the sampling tubing. This served as reference

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measurement, as the full gas volume was transported from this point to the sampling point.

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2) The gas mixture was released at the brake, near the friction interface of disc and pad. The

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Teflon tube was divided into two smaller tubes of equal length and routed to the brake caliper.

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The outlets were positioned at the lower part of the brake pads, one at vehicle side and the

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other one at the outside (compare figure 1(a)).

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3) Estimating the background contribution, the gas mixture was released in front of the tire. The

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gas tube was routed closely to the tire-road interface in order to obtain contributions

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originating from particle resuspension. The gas flow was set to 200 sccm/min.

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For detection, the particle measurement devices in the trunk were replaced with a NO/NO2 analyzer

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(ECO Physics CLD 66). The device was used in NOx-mode compensating potential reactions of the

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tracer gas NO to NO2 (Tsukahara et al., 1999). Simultaneous particle and tracer gas measurements

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were not possible because of limited power capacity inside the test car. The test drives were

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performed with different constant velocities for all measurement configurations. The weather

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conditions during the test drives were sunny and dry with temperatures above 20°C and low wind

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speeds.

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2.3 Brake and test specifications

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2.3.1 Materials

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The investigations were performed on the 15” size left front brake. The disc brake was composed out

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of a floating caliper, which was mounted on the front side of the vehicle axle, a ventilated cast-iron

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rotor, and low-metallic content brake pads (ECE, for material information consider Mathissen et al.

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(2018a)). In addition to the conventional pad material, a new material composition was studied as

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well: the novel cast-iron rotor was coated by an approximately 70 µm thin surface of WC-CoCr using

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high-velocity oxygen fuel (HVOF) coatings (Federici et al., 2016; Wahlström et al., 2017). The lining of

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the novel friction material contained geopolymers that were based on alkaline-activated blast furnace

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slag (Vlcek et al., 2014). Before testing, the friction linings were machined down by 2 mm in order to

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investigate the bulk friction material. It was additionally run-in by a sequence of five 3-hour long Los

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Angeles City Traffic (3h-LACT) cycles according to Mathissen et al. (2018a). The run-in was

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performed on the dynamometer bench avoiding long run-in drives with the test car.

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During the test drives the brake temperatures of both front brakes, i.e., sampling and reference side,

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were recorded using sliding thermocouple sensors (GA4089, Universal Thermosensors LTD) with 1 N

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contact force. Additionally, signals of vehicle velocity, brake pedal use, and brake pressure were

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monitored. The total weight of the instrumented test car was 1719 kg including two drivers. This

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resulted in an inertia of 60.9 kg m2 when assuming a brake power distribution of 71.6/28.4 between

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front and rear brakes.

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2.3.2 Procedures

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The time-controlled 3h-LACT cycle was used as drive cycle because it was classified as realistic

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driving cycle (Mathissen et al., 2018a). It consists out of 217 brake stops with decelerations ranging

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from 0.2 m/s² to 2.88 m/s² and initial vehicle velocities ranging from 16.9 km/h to 154.3 km/h

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(compare cumulated frequency of the cycle velocities in figure 3(b)) (Mathissen and Evans, 2019).

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Due to the setup components outside the vehicle, the speed limit was decreased to 135 km/h. In

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consequence, a single high-speed braking from 154.3 km/h was not reproduced. The test drives were

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conducted by two drivers on an endless track (high speed oval) under exclusive use at Ford Lommel

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Proving Grounds, Belgium. While the driver steered the vehicle, the co-driver slowed down and

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accelerated the vehicle using a second pedal set. The test cycle was reproduced with the help of a

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real-time guidance system. For each material composition, i.e., conventional and novel material, two

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test runs were performed. Since short rain showers occurred during the first runs, the tests were

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repeated and performed under dry and sunny weather conditions with ambient temperatures of

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around 20°C. For comparison, another set of the conventional brake material was investigated.

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Instead of the rather new conventional material, this set was used under normal driving for more than

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6.000 km before. For the emission investigation, the material was tested several times by using a 20-

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min section of the 3h-LACT cycle. This section contained 30 brake stops in a critical test section, as it

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comprised moderate as well as high brake temperatures and a wide range of decelerations (compare

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figure 4(a)). The initial brake temperature before testing was set to 100±10°C.

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3 Setup characterization

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3.1 System air flow

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The system air flow was measured downstream of the sampling probe of the particle measurement

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devices and upstream of the blower. During several measurements when the car was at standstill, an

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average setup flow of

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velocity within the setup decreased with increasing vehicle velocity. The behavior of the

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corresponding setup flow is shown in figure 2.

=76.3 m3/h was calculated. However, when the car was in motion, the air

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Figure 2 – Setup flow depending on vehicle velocity estimated through NOx-mass conservation (yellow, data from direct NO-dosing) and TSI air velocity transducer (blue). Error bars refer to measurement uncertainty and the connecting lines result from interpolation. [1-column width, 300dpi]

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Without going into detail, for comparison, the flow measurements were validated by mass

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conservation during the tracer gas experiments. The signals of both measurement techniques are in

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very good agreement. Beginning at about 76 m3/h at standstill, the air flow was reduced to 50% at

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vehicle speeds of around 100 km/h and dropped even further with increasing speed. Although the air

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flow drop appeared to be constant, a linear fit for the data was not appropriate. Instead, the data was

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interpolated using the Matlab software “Piecewise Cubic Hermite Interpolating Polynomial” (pchip)

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method. The decreasing setup flow was accompanied by an increased pressure drop over the entire

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sampling system. Either the absolute pressure at the vehicle underbody was reduced during driving or

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the rotating wheel and especially the spokes of the wheel rim created turbulences that prevented

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smooth air flows. Since the suction capacity of the blower was constant, both cases would have led to

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a reduced system air flow. However, the latter effect was observed within the CFD calculations but its

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consequences were unpredictable in the design stage of the experiments.

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3.2 Sampling Efficiencies

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The tracer gas experiments were performed at different constant vehicle velocities ranging from 0 to

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130 km/h. For every dosing position and every constant speed, the tracer gas was dosed four times

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for 20 seconds followed by a 10-sec pause, during which no test gas was released. Since the tests

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were performed on oval and straight tracks, where cross winds could have affected the

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measurements, the order of driven velocities was randomly chosen and the tests were repeated on

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different days.

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The NOx mixing ratio increase was clearly detected and was reproducible for constant testing

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conditions. Potential influences due to cross winds were not observed. During the dosing pause the

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mixing ratios returned swiftly to background. Since the flow controller sometimes overshot after

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turning it on, the mixing ratio data were averaged over the last 2/3 of the NOx signal peaks excluding

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the overshoot region. In figure 3, the averaged data points are binned and plotted against the average

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driving velocity.

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Figure 3 – (a) NOx mixing ratios measured during NO dosing at brake (blue, pos. #2) and direct dosing (black, pos. #1). Each data point is showing the averaged mixing ratios at each constant velocity section. The error bars indicate standard deviation of the binned measured data. The line represents the data interpolation (Matlab pchip-method). (b) Calculated aspiration efficiency (blue) and tire/road contribution (red) from tracer gas experiment. The estimated error area is based on the highest error during the NOx-measurement. For comparison, the cumulated frequencies of velocities during the 3h-LACT cycle are presented. [1-column width, 300dpi]

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The detected NOx mixing ratios of the reference measurement, where the tracer gas was released

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inside the sampling tube, is almost linearly increasing with increasing driving velocity. Since the entire

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tracer sample was transported to the sampling point and the dosing rate was always kept constant, as

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consequence, the dilution ratio between the tracer gas and setup flow must have changed. Thus, the

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setup flow (

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mixing ratio is c NO , the measured mixing ratio is

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results are presented in figure 2 and are in good agreement with the flow values of the air velocity

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transducer.

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In case of releasing the tracer gas at the brake, the detected NOx mixing ratios were comparable to

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that of the reference position for vehicle velocities up to 50 km/h. For higher velocities, however, the

) was calculated through mass-conservation: NO , and

=



. The tracer gas

is the released gas flow. The

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mixing ratios deviated and were almost constant at around 12 ppmv. From 80 km/h to 130 km/h, the

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mixing ratio decreased to about 10 ppmv.

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In order to estimate the aspiration efficiency, the data points of both measurement series were

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interpolated (Matlab pchip method). The ratio of both series, i.e., the aspiration efficiency, is shown in

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figure 3(b). Up to vehicle velocities of 50 km/h, the aspiration model was 1, meaning that all particles

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at the brake were captured by the setup. For higher speeds the aspiration efficiency was constantly

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decreasing to about 0.5 at 130 km/h. Although in the worst case only 50 % of particles were expected

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to be captured at 130 km/h, it was noted that the majority of vehicle velocities during the 3h-LACT

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cycle are in the range where the aspiration efficiency was above 0.8. This is indicated by the

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cumulative frequency plot of the vehicle velocities. The average aspiration efficiency during the cycle

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was even higher and reached approximately 0.93. In analogy to the estimation of the aspiration

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efficiency, the background contribution from the tire/road interface was modelled. At low velocities, a

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contribution of tire and road particles of less than 8 % was found. For velocities in the excess of 30

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km/h, this contribution vanished. Thus, the influence of tire and road wear particles was assessed to

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be negligible.

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The setup transport efficiency η

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during a 3h-LACT cycle. Considering internal, diffusional, and gravitational deposition effects (Baron

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et al., 2011), models for deposition in tubes and bends (McFarland et al., 1997; Pui et al., 1987) were

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applied, while the setup was separated into a straight tube section of 3 m total length and five 90°-

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bends with radii rbend=0.3 m. The resulting efficiency depended strongly on the particle size (dP). For

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dP<1 µm, η

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because of stronger diffusional deposition. Particles with dP>1 µm were also assumed to be

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transported less efficiently and η

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found at a particle size of around 7-8 µm. Furthermore, a significant amount of particles was expected

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to deposit on the rotating wheel (Sanders et al., 2003). This effect is inevitable for the present

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measurement approach. Overall, significant losses of coarse particles were expected when assessing

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brake PM10 concentrations both due to the “artificial” losses of the sampling approach and “naturally”

!

!

was roughly estimated for an average setup flow of 54 m3/h

was closely around 1 and only for particles smaller than 0.02 µm, it dropped slightly

!

decreased to 0.9 for 3 µm sized particles. The 50 % cut-off was

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occurring losses in the wheel. PM2.5 and particle number (PN) concentrations were less affected by

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losses of the sampling approach and thus expected to be more accurate.

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4. Results and discussion

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4.1 Time resolved emissions

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All test drives were performed in a reproducible manner as the driving distance in table 1 shows.

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Compared with the driving distance of 146.2 km for the ideal 3h-LACT cycle, the driven distances

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were marginally shorter by about 200 m. Small deviations were acceptable because they mainly

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resulted from softer accelerations, which were not relevant for the study of brake wear emissions. In

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figure 4, the velocity profile and a temporal overview of all measurement signals is given exemplary

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for the second run of the 3h-LACT with conventional break pad material.

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Figure 4 – Temporal overview plot of 3h-LACT cycle, second run, conventional brake pad material. (a) Velocity profile (black, left axis; blue area, driving distance, here: 146.1 km), disc temperature curves (right axis; red, TC at setup side; yellow, TC on reference side). (b) PM10 concentration of TSI Dusttrak. For reasons of clarity the raw data signal is shown only. (c) PM10 per dissipated energy ∆Ekin per brake stop. (d) Particle number concentration (dN/dlogdp) of TSI APS depending on aerodynamic diameter, dP,aero. (e) Indicator for Tbrake,setup > Tbrake,ref,max (black) and particle number concentration (dN/dlogdp) of TSI EEPS depending on electric mobility diameter, dP,mob. [2-column width, 300dpi]

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The rapid increase of the brake temperatures clearly identified active brake events. While at the

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beginning both temperatures, i.e., on sampling and reference side, were similar, they were diverging

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with time. This was caused by the different brake cooling: on the sampling side, the cooling air flow

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was limited by the blower and decreased with increasing driving velocity (figure 2). On reference side,

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the brake cooling behaved vice versa and increased with increasing driving velocity. This led to higher

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brake temperatures on the sampling side with a maximum difference of about 63°C during the test.

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Since the brake temperature is most influential for ultrafine particle generation of brakes (Alemani et

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al., 2018; Farwick zum Hagen et al., 2019; Mathissen et al., 2018a; Nosko and Olofsson, 2017) and

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realistic measurements were in focus of this study, an indicator for brake temperatures above the

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maximum reference temperature (Tsetup > Tref,max=162°C) was integrated in the temporal overview

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adjacent to the EEPS signal. This allowed a simple judgement whether realistic brake temperatures

336

were present. UF emission modes were observed by the EEPS similar to Farwick zum Hagen et al.

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(2019) and were nearly present during all Tsetup > Tref,max phases. According to Namgung et al. (2016),

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the UF modes originate from condensed vapor followed by coagulation and agglomeration processes.

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Thus, it is expected that these particles are volatile. Fine particles modes (PM2.5-0.1) however, with

340

peaks at particle diameters dP of around 0.3 µm were also present and seemingly independent from

341

the brake temperature. These modes were consistent with the APS signal, which indicated the same

342

origin of the particles, i.e., abrasion (Gietl et al., 2010). In the APS, the modes appeared much

343

broader with peaks in the range of dP,aero =0.7-2 µm and extented into the coarse particle size range

344

(PM10-2.5). The amount of particles measured with larger dP,aero became smaller and vanished at

345

around dP,aero =4-6 µm. Obviously, particles with large diameter were lost not only by transport within

346

the tubing but also on vehicle components such as parts of the brake and the wheel rim.

347 348 349

Table 1 – List of characteristic parameters during all test drives of the 3h-LACT cycle. The extrapolated filter load is calculated using the average setup flow. The percentages show the reduction compared to conventional a b material. Considering actual flow and aspiration correction. Considering Dusttak calibration factor. Material

3h-LACT cycle

Driving distance [km]

DT filter PM10 ∆mextrapol [mg]

DT drag ratio

a

DT calibration factor

Mean PM10 / ∆Ekin -1 a,b

[mg kJ ] st

Serial

1 run

Serial

2

nd

run

146.1 (99.9%)

316.9

55 %

2.14

0.012±0.008

146.1 (99.9%)

276.2

51 %

2.16

0.011±0.007

st

Novel

1 run

Novel

2

nd

run

145.8 (99.7%)

249.9 (78.8 %)

38 %

2.64

0.016±0.010

144.5 (98.8%)

210.5 (76.2 %)

41 %

2.45

0.010±0.010

350 351

The time-resolved particle mass (PM10) concentration measured by DT ranged from 0.1-36 mg/m3.

352

Small PM10 concentrations occurred during driving periods and were still higher than the constant

353

ambient air concentration that was around 0.01 mg/m3. The PM concentrations during driving were

354

attributed to brake drag, which is generated brake dust during cruising conditions without braking

355

(Farwick zum Hagen et al., 2019; Hagino et al., 2016). The calculated amount of brake drag ranged

356

from 38-55 % depending of the test and brake material that was used. High PM10 peaks resulting from

357

brake events were readily recognizable. In figure 4 (c) the amount of PM10 was related to the

358

dissipated energy upon braking (∆Ekin) and will be discussed later in more detail.

359

Due to the semi-open setup design, an overall background signal contribution was present and may

360

overlapped with minor emission peaks. However, since most of the prominent emission peaks were

361

clearly discernible, the measured data were reliable.

362

4.2 Emission factor

363

A simple material ranking was obtained by mass analysis: airborne PM10 was collected through filters

364

(Pallflex TX40) for each cycle. In order to obtain total values, the cumulated filter load ∆mfilter was

365

extrapolated using the average setup flow. As shown in table 1, the total airborne PM10 ranged from

366

about 210 mg cycle-1 to 316 mg cycle-1 and decreased by about 14 % through repetition. While this

367

behavior was similar for both material compositions, the entire airborne PM10 of the novel material

368

was about 22.5 % less than that of the conventional material.

369

A more detailed analysis was performed with the EF analysis. Considering the actual setup air flow

370 371

and an aspiration efficiency "

,$ ,

which was modelled depending on the vehicle velocity (see

section 3.2), the EFs were calculated as follows: %& =

'

$+#- . /

$

∙

,$

∙"

)

,$ ∙

*

)

is the total concentration of the 0 1 -data point in time and * is the driven distance during each

372

where

373

cycle. Due to the particle residence time within the setup, the signal acquisition of the instruments was

374

delayed towards the dust aspiration at the front brake. Since the particle residence time was varying,

375

a precise correction remained unknown and thus,

376

simultaneously. However, the variation of the calculated EFs was estimated by taking into account

377

incremental time shifts of the values: "

378

with the maximum respond time during the tracer gas experiments (worst case assumption). The

379

mean particle residence time, however, was expected to be smaller. Thus, the total concentrations

380

were shifted by ±3 s, compensating potential misalignment between setup airflow and particle

381

detection. For all variations, the maximum and minimum EFs were chosen (worst case assumption)

382

and expressed by error bars in the respective diagrams.

$

,$

$ ,

,$ ,

and "

,$

were assumed to occur

was shifted stepwise forward up to 12 s, which complied

383 384 385 386 387 388 389 390

Figure 5 – Emission factors from two 3h-LACT drives with conventional (blue, dashed) and novel (orange, dotted) material compositions. Conventional material with a higher mileage (>6.000 km) is shown for the critical 20-min test section. In (a) the PM10-EFs (TSI Dusttrak) and the background estimations are shown, the error bars refer to worst case assumptions when applying corrections regarding aspiration and setup flow. The PNEF (TSI EEPS) are shown in (b) and the signal background estimation is shown on grey background. Note: PN-EFs include volatile particles and should not be compared to regulated exhaust particles PN. [1.5-column width, 300dpi]

391

Two types of EFs regarding the particle mass (PMEF) and particle number (PNEF) were calculated. In

392

case of PMEF, the DT sensor signal was used and calibrated with the corresponding filter values:

393

since the DT sensor underestimates the PM of brake aerosols (Hagino et al., 2015), the raw signal

394

data were multiplied with the calibration factors listed in table 1. As shown in figure 5 (a), the PMEF

395

was in the range of 1.8-2.1 mg km-1 brake-1 for the conventional material. For the novel material

396

composition, the PMEF was about 18 % smaller and around 1.4-1.7 mg km-1 brake-1. The decreasing

397

PMEF-trend with repetition indicated smaller PM10 emissions the longer the material was in use.

398

However, when testing the same material composition with a much higher mileage (>6.000 km real-

399

world driving) during several runs of the 20-min LACT cycle, the PMEF was still of the same quantity.

400

The slightly higher PMEF during the first 3h-LACT runs is attributed to running-in aging since the tests

401

were performed directly after mounting the material on the vehicle. Compared to dynamometer

402

studies the present PMEF were smaller than most of the published values (Farwick zum Hagen et al.,

403

2019; Garg et al., 2000; Perricone et al., 2016; Sanders et al., 2003). Possible explanations are the

404

high particle losses in the transport tubing for coarse particles and particle deposition on the wheel

405

rim.

406

For the PNEF the APS and EEPS signals were used. When a data set was partially incomplete, the

407

driven distance was adjusted and sections with missing data were ignored. Since the PNEF was

408

dominated by UF particle emissions, only the EEPS data were plotted in figure 5 (b). The calculated

409

variation of the PNEF was not considered because it showed only very small differences. Note that

410

PNEF includes volatile particles and should not be compared to regulated exhaust PN, which is

411

defined to count solid particles. Further, as pointed out in more detail in the next chapter, the brake

412

temperature is very critical and it was artificially increased due to the housing of the sampling system.

413

At the observed temperatures of the reference brake PN emissions would not exceed 1E10 km-1

414

brake-1. Neglecting the artificially elevated brake temperature, for the conventional material, the PNEF

415

started at 1.3E13 km-1 brake-1 during the first run and decreased to 4.5E12 km-1 brake-1 by about 66

416

% during the second run. The novel material behaved similar but with about 60 % smaller absolute

417

values. Thus, during the second run a PNEF of about 1.8E12 km-1 brake-1 was found. The PNEF was

418

about 2-3 order of magnitudes higher than their corresponding background values, which was in the

419

range of 6E9-2E10 km-1 brake-1 and close to the detection limit of the instrument. The EFs were

420

dominated by UF particles that were emitted during high brake temperature sections. Interestingly, for

421

the conventional material with more than 6.000 km mileage, a PNEF close to background level was

422

found. Although the material was tested several times during the test section, where the highest brake

423

temperatures occurred, no UF emission mode was found. This suggests a strong influence of the

424

brake material history. The falling PNEF during the first two 3h-LACT runs already indicated a

425

reduction of UF particle emissions. Following the explanation of UF brake particle formation by

426

Namgung et al. (2016), either the initial degassing of brake material is assumed to be final or it begins

427

at different temperatures depending on the material history. In contrast, the APS PNEF was constantly

428

around 1.2E9 km-1 brake-1 and 6.9E8 km-1 brake-1 for conventional and novel material, respectively.

429

The values were slightly higher during the first test run, which is consistent with the PM10 emission

430

results.

431

4.3 Emission of PN and PM per brake stop

432

Total particle emission values were calculated similar to the EF calculations above (section 4.2) but,

433

instead of using the full cycle, only the data during the brake events were considered. All brake events

434

were clearly identified by the recorded brake pedal use signal and emission peaks were temporally

435

aligned. An extension of the brake intervals by 4 s ensured a complete determination of the emission

436

modes. In figure 6 the total PN per stop is plotted versus the mean brake temperature.

437 438 439 440 441 442 443 444 445

Figure 6 – Particle number emission values for each brake event of the second run of the 3h-LACT cycle. In (a) conventional (blue) and novel material compositions (orange) are compared. The mean brake temperature range of the non-enclosed reference brake is indicated by the yellow bar and is not exceeding 153°C. Temperatures do not reach the critical temperature and no ultrafine particles would be formed. In (b) the conventional material (blue) is compared with the serial material of significantly longer driving history (magenta) during a 20-min LACT section. PN emission increase is highlighted. The blue and orange shading indicate the critical temperatures at which PN increase is occurring. [1.5-column width, 300dpi]

446

For most of the brake events the total PN was close to the background level, which was about 4E9

447

stop-1 brake-1. With increasing brake temperature, the total PN remained unchanged. However, at a

448

certain temperature, also known as critical temperature, a steep increase of the total PN was

449

observed. Critical temperatures were assumed to be material specific and values of about 168°C and

450

178°C were found for the conventional and novel material compositions, respectively. Beyond the

451

critical temperature, the total PN was around 1E13 stop-1 brake-1 and the concentrations were

452

reaching the upper detection limit of the instrument. The higher critical temperature of the novel

453

material led to less brake stops with high PN emissions and consequently to lower PNEF during the full

454

cycle. Indicated by the yellow bar, the range of mean temperatures of the reference brake is shown.

455

The average brake temperatures did not exceed 153°C during the 3h-LACT, showing that normally

456

under these driving conditions UF particle emission are not to be expected. In case of the material

457

with high mileage, the total PN remained at background level. Although higher temperatures were

458

reached the critical temperature remained unclear. In contrast, the PM10 emissions were not

459

temperature dependent.

460 461 462 463

Figure 7 – PM10 per dissipated energy ∆Ekin for each brake stop (conventional material, second 3h-LACT run). The DT data are calibrated and corrected regarding actual setup flow and aspiration efficiency. [1-column width, 300dpi]

464

Figure 7 shows the total PM per brake stop in dependency to the dissipated brake energy ∆Ekin, which

465

was calculated by the initial and final vehicle velocities during braking and assuming a wheel load of

466

615.8 kg at the front axis (71.6 % of total mass). The results varied widely from 0.0024 mg kJ-1 to

467

0.0725 mg kJ-1 per brake. However, as the histogram in figure 7 shows, the majority of data points

468

was found next to the mean value of around 0.01 mg kJ-1 per brake. The average value was nearly

469

identical for both materials (compare table 1) with slightly higher results during the initial runs.

470

Compared to dynamometer instigations (Farwick zum Hagen et al., 2019), where DT values of 0.026

471

mg kJ-1 per brake were found on average, the present values were lower by about 60 %. The

472

differences were caused by higher particle losses in the on-road driving setup. Furthermore, it is

473

assumed that the actual dissipated brake energy was smaller compared to the calculated ∆Ekin values

474

because the parasitic drag of the vehicle (e.g., rolling and wind resistance) was not included in the

475

calculation. Thus, the realistic emission values are expected to be higher.

476

5. Conclusion

477

For on-road investigations of brake wear particles, a novel particle measurement setup was

478

developed, integrated into a midsize passenger vehicle, and tested on road. Conserving the natural

479

air flow at the brake, the brake wear was collected at the outside of the wheel rim. A semi-closed

480

housing of the brake aimed the collection of the entire brake aerosol, which was transported to the

481

measurement devices located in the trunk of the car. By means of tracer gas experiments, the

482

aspiration efficiency was characterized as velocity dependent with decreasing aspiration at vehicle

483

speeds above 50 km/h. Similarly, the setup air flow depended on the vehicle velocity. For increasing

484

vehicle velocities, the air flow decreased and led to a decreased brake cooling. Two brake materials

485

were tested during a realistic drive cycle (3h-LACT) with the following results:

486

•

The measured particle signal was of high accuracy although compromises regarding

487

aspiration, setup flow, and brake temperature were made. The small tire/road and background

488

particle contribution was estimated to be negligible.

489

•

while the novel material composition showed about 18 % lower PM10 emissions.

490 491

For the conventional brake pad material, the PMEF was in the range of 1.4-2.1 mg km-1 brake-1,

•

Regarding PN, the EF reached total numbers of 2E12-1.3E13 km-1 brake-1, which was

492

dominated by UF particle emissions during high brake temperature sections and included

493

volatile particles. The novel material produced about 60% less particles. However, the PN

494

emissions were obtained during unrealistic high temperature sections and were not

495

representative for realistic driving. For temperatures observed at the reference brake, the PNEF

496

would not exceed 1E10 km-1 brake-1.

497

•

The critical brake temperature at which UF emission occurred, was found at 168°C and 178 °C

498

for the conventional and novel material, respectively. The temperature of the reference brake

499

did not exceed 153°C during the same test, thus UF brake emissions are not expected during

500

normal driving.

501

•

Since UF particle emissions were not observed during tests with brake material with higher

502

mileage (> 6.000 km), they are assumed to depend on the material history. It is believed that

503

brake lining ingredients, which form UF particles, start evaporating at different brake

504

temperatures.

505

Compared to literature results of dynamometer studies, the obtained PM10 emission results were

506

generally smaller but of similar magnitude. This was decisively affected by the high losses for coarse

507

particles due to the rather complex setup geometry. The UF particle formation was favored, due to

508

higher brake temperatures compared to the reference brake originating from the manipulated brake

509

cooling through the setup. Additionally, the varying setup flow complicated the data analysis. A more

510

realistic brake cooling and a stable setup flow could have been achieved only by a more powerful

511

blower. On the other hand, this would have led to power supply problems on the vehicle. As

512

recommendation, brake wear particle investigations should be carried out at dynamometer benches

513

because of less technical restrictions, higher test-to-test reproducibility and robustness, and better

514

cost efficiency. Dynamometers provide more options for setup optimization regarding particle losses,

515

the use of advanced measurement techniques and devices. Furthermore, comparable test conditions,

516

i.e. drive cycle and environmental parameters, can be selected. Attention should be paid to

517

performing tests with realistic operational parameters, which – in particular the brake temperature –

518

should be continuously verified through on-road investigations. This study proposes one feasible

519

approach for on-road investigations of brake wear particle emissions; it may be used as verification

520

setup for dynamometer investigations and serve as orientation for future work.

521

Acknowledgements

522

This work was supported by the EU through the Horizon 2020 project “LowBraSys” [grant number

523

636592, 2015-2019]. We thank all project partners for keen discussions. We acknowledge technical

524

support from Mr. F. De Corte and the staff at Ford Lommel Proving Grounds, Belgium.

525

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•

On-road driving investigation of brake wear particles in a semi-closed vehicle setup

•

Known aspiration and setup flow enable quantification of emission data

•

Robust setup design and repeatable tests allow material comparisons

Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: