Brake and Tire Wear Emissions
from Onroad Vehicles in MOVES3
United States
Environmental Protection
^1 Agency
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Brake and Tire Wear Emissions
from Onroad Vehicles in MOVES3
This technical report does not necessarily represent final EPA decisions or
positions. It is intended to present technical analysis of issues using data
that are currently available. The purpose in the release of such reports is to
facilitate the exchange of technical information and to inform the public of
technical developments.
Assessment and Standards Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
NOTICE
svEPA
United States
Environmental Protection
Agency
EPA-420-R-20-014
November 2020
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Table of Contents
1 List of Acronyms 2
2 Introduction 4
3 Brake Wear 5
3.1 Literature Review 5
3.2 Developing Rates for MOVES 8
3.2.1 Emissions during braking 8
3.2.2 Braking Activity 11
3.2.3 Braking Activity in Idle Mode 16
3.2.4 PM10/PM2.5 Brake Wear Ratio 16
3.2.5 Heavy-Duty and Other Vehicle Types 17
4 Tire Wear 22
4.1 Introduction 22
4.2 Data and Methodology 25
4.3 Analysis 26
4.3.1 PM10/PM2.5 Tire Wear Ratio 30
4.4 Tire Wear Emissions in Project-Scale 30
5 Ongoing and Future Work 31
Appendix A Deceleration from PERE 33
Appendix B Brake and Tire Wear Emission Rates 35
Appendix C Literature Review conducted for MOVES2009 41
References 43
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1 List of Acronyms
AMS Auto Motor Sports magazine
CMB Chemical Mass Balance
CNG Compressed Natural Gas
ELPI Electrical Low Pressure Impactor
EPA U.S. Environmental Protection Agency
ERG Eastern Research Group
FTP Federal Test Procedure
HD Heavy-Duty
HHD Heavy-Heavy-Duty
LD Light-Duty
LDT Light-Duty Trucks
LDV Light-Duty Vehicle
LHD Light-Heavy-Duty
MC Motorcycle
MHD Medium-Heavy-Duty
MOBILE Original Highway Vehicle Emission Factor Model pre-2004
MOVES Motor Vehicle Emission Simulator Model
NAO non-asbestos organic
PART5 computer model (programmed in Fortran) for calculating PMio and
PM2.5 emissions from vehicles
PERE Physical Emission Rate Estimator
PM Particulate Matter
PM2.5 Particulate matter with mean aerodynamic diameter less than 2.5 pm
PM10 Particulate matter with mean aerodynamic diameter less than 10 pm
RWD rear-wheel drive
UDP urban driving program
2
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VMT Vehicle Miles Traveled
VSP vehicle specific power
3
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2 Introduction
The United States Environmental Protection Agency's Motor Vehicle Emission Simulator—
commonly referred to as MOVES—is a set of modeling tools for estimating air pollution
emissions produced by onroad (highway) and nonroad mobile sources. MOVES estimates the
emissions of greenhouse gases (GHGs), criteria pollutants and selected air toxics. The MOVES
model is currently the official model for use for state implementation plan (SIP) submissions to
EPA and for transportation conformity analyses outside of California. The model is also the
primary modeling tool for estimating the impact of mobile source regulations on emission
inventories.
The mobile source particulate matter inventory includes exhaust emissions and non-exhaust
emissions. Exhaust emissions include particulate matter attributable to engine related processes
such as fuel combustion, burnt oil, and other particles that exit the tailpipe. Non-exhaust
processes include brake wear, tire wear, suspension or resuspension of road dust, and other
sources. Particulate matter from brakes and tires is defined as the airborne portion of the "wear"
that can be created by abrasion, corrosion, and turbulence. These wear processes can result in
particles being suspended in the atmosphere. The size, chemical composition, and emission rate
of particles arising from such sources contributes to atmospheric particle concentrations.
However, these particles have different chemical composition and size than exhaust particulate
matter.1
MOVES estimates PM2.5 and PM10 emissions from brake and tire wear from onroad vehicles as
documented in this report. Unlike PM2.5 exhaust emissions, MOVES does not speciate the PM2.5
emissions from brake and tire wear. To provide estimates of speciated PM2.5 emissions for the
national emissions inventory and to provide input for air quality modeling the EPA applies brake
and tire wear SPECIATE profiles outside of MOVES as documented in the MOVES speciation
report.2 MOVES does not estimate emissions from road-dust. EPA estimates of road-dust
emissions are located in AP-42.3
This report was drafted in 2008, based on a literature review conducted in 2006 and 2007. The
algorithms and values discussed here were incorporated into MOVES2009 and carried over into
later versions (MOVES2010a, MOVES2010b, MOVES2014) with little to no changes. The
report was peer reviewed in 2014 as documented in the MOVES2014 report.4
In MOVES3, the brake and tire wear models are essentially the same as in MOVES2014
versions. However, two general updates (among other MOVES3 onroad model changes) are
worth noting with respect to brake wear and tire wear emissions.
1) In MOVES3, we consolidated the MOVES2014 vehicle regulatory classes LHD <=
10k and LHD <=14K into the MOVES3 LHD2b3 regulatory class (as discussed in the
MOVES3 heavy-duty exhaust emission rate report5). We applied the brake and tire wear
emission rates from the MOVES2014b LHD <= 10k regulatory class to represent the
emission rates of the LHD2b3 regulatory class in MOVES3. MOVES3 also added the
glider regulatory class, which are heavy heavy-duty (HHD) trucks with an old powertrain
combined with a new chassis and cab assembly. Because the body of a glider truck is
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assumed to be the same as HHD vehicles, they are modeled with the same brake and tire
wear emission rates. Additional details are discussed in Section 3.2.5.
2) MOVES3 now models "off-network idle," accounting for the additional running
emissions from vehicle idle operation occuring off the road network in areas such as
parking lots, transit/distribution centers, etc. MOVES does not model off-network idle or
extended idle emissions for brake or tire wear because the vehicle is completely stopped
during this non-drive-cycle idle time. Additional details on brake wear during idling are
discussed in Section 3.2.3.
3 Brake Wear
3.1 Literature Review
There are two main types of brakes used in conventional (or non-hybrid electric) vehicles: disc
brakes and drum brakes. In a drum brake, the components are housed in a round drum that
rotates with the wheel. Inside the drum are "shoes" that press against the drum and slow the
wheel. By contrast, disc brakes use an external rotor and caliper to halt wheel movement. Within
the caliper are brake pads on either side of the rotor that clamp together when the brake pedal is
pressed.6 Both types of brakes use frictional processes to resist inertial vehicle motion. The
action of braking results in wear and consequent release of a wide variety of materials
(elemental, organic and inorganic compounds) into the environment.
Brake wear has multiple definitions in the literature. In this paper it refers to the mass of material
lost from the brake pads. A fraction of that wear is airborne particulate matter (PM). MOVES
models only PM <=10 ]im, (PMio). Some studies look at both wear and airborne PM, others look
at one or the other. In brakes, the composition of the brakeliner has an influence on the quantity
and makeup of the released particles. Disc brakes are lined with brake pads while drum brakes
use brake-shoes or friction linings. These materials differ in their rate of wear, the portion of
wear particles that become airborne, and the size as well as composition of those particles.
The overall size or mass of the brake pads also varies with vehicle type. Typically, trucks use
larger brakes than passenger vehicles because their mass is greater. In 2004, most light duty
vehicles used disc brakes in the front and drum brakes in the rear. Disc brakes tend to have
improved braking performance compared to drum brakes and have correspondingly higher cost.
Disc brakes are sometimes used on rear wheels as well for higher performance (sportier)
vehicles.
As a complicating issue, the particulate matter from brakes is dependent on the geometry of the
brakes, wheels and rims. The air flow through the rims to cool the brakes and rotors play a key
role in determining the wear characteristics. The emissions are also sensitive to driver activity
patterns; more aggressive stop and go driving will naturally cause greater wear and emissions.
There are a very limited number of publications on brake wear PM emissions. There are even
fewer publications discussing size distributions and speciation, and none quantifying emissions
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modally on which to directly base a model. This section summarizes the limited literature as of
2006. More details of the literature on brake and tire wear can be found in Appendix C. One of
the earliest studies on brake wear emissions was done in 1983.7 Particulate emissions from
asbestos-based brakes from automobiles were measured under conditions simulating downtown
city driving. The report presented a systematic approach to simulating brake applications and
defining particulate emissions and was used in the development of the EPA PART5 model.8 For
PART5, EPA calculated PMio emission factors for light-duty gasoline vehicles of 12.5 mg/mi for
brake wear. Since 1985, the asbestos in brakes has been replaced by other materials, and newer
studies have been conducted.
Garg et al. (2000)9 conducted a study in which a brake dynamometer was used to generate wear
particles under four wear conditions (much of the background information provided in the
previous paragraphs are from this paper). The study was performed using seven brake pad
formulations that were in high volume use in 1998. Measurements were taken on both front disc
as well as rear drum brakes. The study measured mass, size distribution, elemental composition,
as well as fiber concentration at four temperature intervals. The report also estimated PM2.5 and
PM10 emissions for light-duty vehicles of 3.4 and 4.6 mg/mile, respectively for small vehicles,
and PM2.5 and PM10 emissions of 8.9 and 12.1 mg/mile, respectively for pickup trucks.
Sanders et al (2003)10 looked at three more current (as of -2003) classes of lining materials: low
metallic, semi-metallic and non-asbestos organic (NAO) representing about 90 percent of
automotive brakes at that time. In their dynamometer tests, three lining type/vehicle
combinations (low metallic/mid-size car, semi-metallic/full-size truck, and non-asbestos
organic/full-size car) were subject to two sets of braking conditions: the urban driving program
(UDP) with a set of 24 stops which represent relatively mild braking (< 1.6 m/s2) at relatively
low speed (<90 km/h); and the Auto Motor and Sport magazine (AMS) test representing harsh
braking conditions consisting of 10 consecutive 7.9 m/s2 stops from 96 km/h. In addition to the
dynamometer tests, the authors also reported two other testing scenarios: (a) a wind tunnel test
where a series of 1.8 m/s2 stops from 96 km/s of a full-size car with low metallic brakes were
conducted; (b) test track testing of the same vehicle where stops from 60 mph at 0.15, 0.25 and
0.35 g-forces were conducted with low metallic and NAO brakes. The major findings from those
tests were:
• The mean particle size and the shape of the mass distribution are very similar for each of
the three linings.
• The wear rates are material dependent: the low metallic linings generate 3-4 times the
number of wear particles compared to semi-metallic and NAO linings.
• 50-70 percent of the total wear material was released in the form of airborne particles.
• The wear (and portion of wear that is airborne PM emissions) increased non-linearly with
higher levels of deceleration.
• The most abundant elements in brake wear debris composition were Fe, Cu, Si, Ba, K
and Ti, although the relative composition varied significantly by brake type.
Table 3-1 contains the emission rates derived from the literature review conducted in support of
MOVES2009. While there are emission rates presented from other papers, this paper largely
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relies on the Sanders et al. paper as it includes the widest array of materials in use at the time of
analysis, measurement techniques, and deceleration ranges in a scientifically designed study. It is
the only paper from which modal rates can be derived. It is also the most recent of the papers
listed and improves on the measurement methods introduced in its predecessors. The other
papers results are provided as a source of comparison. Note that the range of rates from Sanders
et al. (2003) largely covers the range presented in the other papers as well. When determining the
MOVES rates, the values from Garg et al. (2000), are also used.
Table 3-1 Non-Exhaust PM Emissions (per vehicle) from mobile sources literature values of emission factors
Literature Source
Vehicle Type
PM2.5
[mg/km]
PM10
[mg/km]
Luhana et al. (2004)
Light Duty
0-79
Heavy Duty
0-610
Sanders et al. (2003)
Light Duty
1.5 -7.0
Abu- Allaban et al.(2003)
Light Duty
0-5
0-80
Heavy Duty
0-15
0-610
Westurland (2001)
Light Duty
6.9
Heavy Duty
41.2
Garg et al(2000)
Passenger Cars*
3.4
4.6
Large Pickup
Trucks
8.9
12.1
Rauterberg-Wulff (1999)
Passenger Cars
1.0
Heavy Duty
Vehicles
24.5
Carbotech (1999)
Light Duty
1.8-4.9
Heavy Duty
3.5
Cha et al. (1983) used in PART5
Cars and Trucks
7.8
* In this table, "passenger cars" are equivalent to light duty cars. "Light Duty" on their own includes all Light-duty
vehicles, including trucks though the studies are not all equivalent in their definitions.
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3.2 Developing Rates for MO VES
3.2.1 Emissions during Braking
The analysis for MOVES braking emission rates was based on the average of:
(1) Composition of brake pad
(2) Number (and type) of brakes
(3) Front vs rear braking
(4) Airborne fraction
and explicitly accounts for:
(1) Particle mass size distribution (PM2.5VS PM10)
(2) Braking intensity
(3) Vehicle class: Light-Duty vs Heavy-Duty
MOVES applies the same tire wear emission rate for all vehicle fuel types (gasoline, diesel, flex-
fuel, CNG or electric) within a MOVES regulatory class.
As discussed in Sanders et al. (2003) which covers brake wear emissions from light-duty
vehicles, most brake pads (at the time of the publication of that paper) are either low-metallic
(mid-size car), semi-metallic (full-size light duty truck), or non-asbestos organic (full-size car).
Using the results from this study, we make the following assumptions which are consistent with
those used in the paper.
• equal mix of the three brake types
• four brakes per light duty vehicle, including two front disc brakes, and two rear drum
brakes
• 2/3 of braking power (and thus emissions) in front brakes (1/3 rear)3
• the fraction of total PM below 2.5 ]im is ~ 10 percent (+/-5 percent)13
• 60 percent of brake wear is airborne PM (+/- 10 percent).
We also do not compensate for the different average weights of the vehicles (though the MOVES
VSP bins scale emissions with mass). We assume there is an equal mix of the three brake types
because the market share penetration is not known.
For each test cycle from Sanders et al. (2003) and Garg et al. (2000), the following figures show
how we went from the measured results to emission rates of g/hour (for deceleration times only)
at various deceleration speeds. Sanders et al. (2003) used three measurement techniques, a filter,
an Electrical Low Pressure Impactor (ELPI), and a Micro-Orifice Uniform Deposition Impactor
(MOUDI). While all three measurement techniques produced similar results, we show all here.
a Based on discussions with Matti Mariq at Ford Motor Company (co-author of Sanders (2003)) and consistent with
the Garg et al. (2000) paper, which used 70%. Some of the other assumptions in this list is also from these
discussions
b More will be discussed below.
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Test results are shown for the UDP and wind tunnel tests from Sanders et al. (2003), as well as
the Garg et al. (2000) analysis. The latter paper adds another deceleration point for comparison.
The Auto Motor and Sport magazine (AMS) results are not presented in the Sanders paper,
however, the authors provided the data for the purposes of this study.
Table 3-2 - Brake Dynamometer (UDP) results0
Test brake lining PMio emiss. (mg/stop/brake)
UDP
filter
ELPI
low metallic
6.9d
7.0
semi-metallic
1.7
1.7
Non-asbestos
1.1
1.5
Average/stop/brake
3.2
3.4
Avg. /veh
9.7
10.2
deceleration = 0.0012 km/s2
avg. brake time in sees = 13.5 sees
avg. emissions in mg/stop = 9.95 Mg/stop
emission rate for the UDP test = 2.65 g/hr
Table 3-3 - Wind Tunnel results
Test brake lining PMio emiss. (mg/stop/brake)
Tunnel
filter
ELPI
MOUDI
low metallic
44
45
40
deceleration=
0.0018
in km/s2
Initial Velocity V(0) =
0.0267
in km/s
avg. brake time in sec =V(0)/dec
14.8
sees
avg. emissions in mg/stop =
129.0
mg/stop
emision rate for the wind tunnel test=
31.4
g/hr
c As these are intermediate values, the number of significant digits may exceed the precision known, however they
are kept in this presentation, and rounded for the final results. The UDP decelerations are the average decelerations
from those measured in the Sanders paper. The average brake times were determined with the assistance of one of
the original authors of the paper (Matti Mariq) who supplied the second by second trace. The filter PM10 were
determined by multiplying the total PM reported in Table 5 of the paper with the PM10 to total PM ratio determined
from the ELPI measurement.
d Sanders et al, reports the total filter PM to be 8.2 mg/brake/stop. In order to get PM10 equivalent, we applied the
ELPI ratio from table 5 in the reference. So 6.9 = 8.2* (7/8.3). The other numbers were calculated in a similar
fashion. Also, the avg per vehicle emissions is the avg stop/veh/brake emissions multiplied by 3. This is based on
the assumption made earlier that 2/3 of braking comes from the front brakes (one was measured) and 1/3 from the
rear brakes.
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Table 3-4 - AMS Test results
Test
brake lining
PM10 emiss.
(mg/stop/brake)
AMS
filter
ELPI
low metallic
800
70
semi-metallic
510
63
Non-asbestos
550
92
Average=
620
75
Avg/veh rate =
1116
135
deceleration =
0.0079
in km/s2
Initial Velocity V(0) =
0.0278
in km/s
avg. brake time in sec =V(0)/dec
3.5
sees
avg. emissions in mg/stop for PM 10=
1116
mg/stop
emision rate for PM10 for the AMS test=
1143
g/hr
avg. emissions in mg/stop for PM2.5=
135.0
mg/stop
emision rate for PM2.5 for the AMS test=
138.2
g/hr
Table 3-5 - Garg et al. (2000) Brake Dynamometer results
Test brake lining PMio emiss.* PM2.5** (mg/stop/brake)
avg. over all
temp.
semi-metallic #1
1.85
1.35
semi-metallic #5
0.82
0.60
NAOS #2
2.14
1.57
NAOS #3
0.89
0.66
NAOS#7
1.41
1.03
Grand Avg. =
1.42 1.04
mg/stop
deceleration =
0.00294
in km/s2
Initial Velocity V(0) =
0.0139
in km/s
avg. brake time in sec =V(0)/dec
4.7
sees
avg. emissions in mg/stop for PM10 =
1.42
mg/stop
emision rate for PM10 for the GM test=
1.08
g/hr
avg. emissions in mg/stop for PM2.5 =
1.04
mg/stop
emision rate for PM2.5 for the test=
0.79
g/hr
We used these four data points to fit an exponential function to determine the emission rate at
different deceleration levels shown in the following Figure 3-1. The AMS test, at higher
decelerations, clearly has a significant influence on results of the curve fit. Additional test data at
higher deceleration levels could be used for future refinement of this data.
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o>
c
d)
4-*
(0
c
o
"7>
U)
E
at
to
c\i
160.0
140.0
120.0
100.0
80.0
60.0
40.0
20.0
0.0
0.0
v = 0.1872.x
3.195
R2 = 0.9995
4.0 6.0 8.0
deceleration in m/s2
10.0
Figure 3-1- Brake wear PM2.5 emission rates in units of grams per hour for light duty vehicles as a function of
deceleration rate based on Sanders et al. (2003) and Garg et al. (2000)
3.2.2 Braking Activity
In the previous section, we determined the rate of particulate matter emissions during braking in
units of grams per hour (per vehicle) as a function of deceleration level for a light-duty vehicle.
MOVES, on the other hand, estimates brake wear from a variety of onroad vehicles over the full
range of driving conditions, but classifies driving into operating modes that are quite different
than the deceleration levels used in brake wear testing. There are four major steps in this
analysis.
1. Estimate the amount of braking (as opposed to coasting to a slower speed) at different
deceleration levels for a light-duty vehicle.
2. Use real-world driving data on the frequency of different deceleration levels to define an
"average" braking deceleration level, and hence an average brake-wear emission rate for
typical braking for a light-duty vehicle.
3. Assign an appropriate amount of this braking to each of the MOVES operating modes.
4. Modify these assignments for other types of vehicles.
Each of these steps is detailed below.
First, we needed to distinguish the deceleration episodes caused by braking from those that were
merely "coasting" to a lower speed. We estimated the fraction of activity that is braking within
each of the "coasting" bins by first determining the coast down curve, then combining that with
the activity fraction as seen in the real-world driving surveys.
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The coastdown curves were generated using the coastdown equations from the Physical
Emission Rate Estimator (PERE)11 and calculating the deceleration at each speed when the
forward tractive power is zero. We assumed all activity below coastdown is braking and all
activity above the curve is low throttle deceleration. Figure 3-2 shows coastdown curves for cars
of a variety of weights (and coastdown coefficients). The dotted curve is a typical coast down
curve for this class of vehicle, where 1.497 kg was defined as the typical mass of a light duty
vehicle (passenger car). More information about the PERE coastdown calculation process is
described in Appendix A.
-1.6 -
-1.8 --
10
20
30
40
50
60
y = -0.0001454x2 j + 0.0000622X - 0.1758
J II' - 1 0
Kilograms
1200
-Poly. 1497)
Speed (mph)
Figure 3-2- Modeled Coastdown curves using the PERE model for a variety of light-duty vehicles masses
Second, we used real-world driving data on the frequency of different deceleration levels to
define an "average" braking deceleration level, and hence an average brake-wear emission rate
for typical braking. For light duty vehicles, the deceleration activity was determined from two
real world instrumented vehicle studies: one from Kansas City and the other in Los Angeles.
The Kansas City study was conducted by EPA and Eastern Research Group (ERG) in 2005 to
study real world driving activity and fuel economy on conventional as well as hybrid electric
vehicles.1' Over 200 vehicles were recruited, though for the current analysis, only the activity
data from the conventional, or non-hybrid, population were examined. The Los Angeles activity
data was conducted by Sierra Research for the California Department of Transportation with
both instrumented vehicles as well as chase car data.13,14'15 The deceleration data was analyzed
for both of these studies.
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Table 3-6 shows the distribution of braking activity across deceleration levels from both the
Kansas City and Los Angeles studies. As expected, the vast majority of braking occurs during
mild decelerations rather than full (high deceleration) stops.
Table 3-6 - Distribution of braking activity in the LA and Kansas City studies for each deceleration bin
Decel (mph/s)
LA
urban
LA
rural
KC
AVG
1
37.1%
27.1%
54.5%
39.5%
2
26.3%
27.9%
26.3%
26.9%
3
17.9%
20.2%
12.8%
17.0%
4
10.2%
12.2%
4.6%
9.0%
5
5.6%
8.2%
1.3%
5.0%
6
1.6%
2.4%
0.30%
1.4%
7
0.64%
0.98%
0.07%
0.6%
8
0.28%
0.41%
0.02%
0.2%
9
0.17%
0.26%
0.02%
0.2%
10
0.10%
0.13%
0.01%
0.08%
11
0.05%
0.09%
0.01%
0.05%
12
0.03%
0.05%
0%
0.03%
13
0.01%
0.01%
0%
0.01%
14
0%
0.01%
0%
0%
sum
100.0%
99.9%
99.9%
100.0%
The emission rate curve from Figure 3-1 was combined with the average activity in Table 3-6
(using a sum of the product) to calculate an average MOVES braking emission rate for light duty
vehicles. This gives an average light-duty vehicle PM2.5 emission rate of 0.557 g/hr for a braking
event.
Third, as mentioned earlier, MOVES models the full range of driving conditions, and thus, we
needed to establish the amount of braking in the MOVES operating modes.
In MOVES braking activity is modelled as a portion of running activity. For light-duty running
emissions, the operating modes are defined in terms of "vehicle-specific power" (VSP). This
parameter represents the tractive power exerted by a vehicle to move itself and its cargo or
passengers11. It is estimated in terms of a vehicle's speed and mass. The MOVES operating
modes for light-duty running exhaust and brake wear emissions are listed in Table 3-7. Similar
operationg modes are available for heavy-duty. More information on these operating modes is
available in the MOVES3 light duty and heavy duty exhaust emission reports.16,5
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Table 3-7 - MOVES Operating Mode Bins by VSP and speed
Operating
Mode
Operating Mode
Description
Vehicle-Specific
Power
(VSP?, kW/Mg)
Vehicle Speed
(w,mi/hr)
Vehicle
Acceleration
including grade
(at, mph/sec)
0
Deceleration/Braking
a, +g sin(Qt) < -2.0
OR
[a, +g sin(0t) < -1.0
AND
a,-i +g-sin(d,.1) < -
1.0 AND
a,-2 +g-sin(6t-z) < -
1.0)
1
Idle
-1.0 < vt< 1.0
11
Coast
VSP,< 0
1 < vt < 25
12
Cruise/Acceleration
0 < VSP,< 3
1 < vt < 25
13
Cruise/Acceleration
3 < VSP , < 6
1 < vt < 25
14
Cruise/Acceleration
6 < VSP,< 9
1 < vt < 25
15
Cruise/Acceleration
9 < VSP, <12
1 < vt < 25
16
Cruise/Acceleration
12 < VSP,
1 < vt < 25
21
Coast
VSP,< 0
25 < vt < 50
22
Cruise/Acceleration
0 < VSP,< 3
25 < vt < 50
23
Cruise/Acceleration
3 < VSP, < 6
25 < vt < 50
24
Cruise/Acceleration
6 < VSP,< 9
25 < vt < 50
25
Cruise/Acceleration
9 < VSP, <12
25 < vt < 50
27
Cruise/Acceleration
12 < VSP < 18
25 < vt < 50
28
Cruise/Acceleration
18 < VSP < 24
25 < vt < 50
29
Cruise/Acceleration
24 < VSP <30
25 < vt < 50
30
Cruise/Acceleration
30 < VSP
25 < vt < 50
33
Cruise/Acceleration
VSP,< 6
50 < vt
35
Cruise/Acceleration
6 < VSP, <12
50 < vt
37
Cruise/Acceleration
12 < VSP <18
50 < vt
38
Cruise/Acceleration
18 < VSP < 24
50 < vt
39
Cruise/Acceleration
24 < VSP <30
50 < vt
40
Cruise/Acceleration
30 < VSP
50 < vt
The MOVES vehicle specific power (VSP) bins are relatively coarse for braking.0 There is a
large "braking" bin (operating mode 0) where all of the activity is assumed to be braking. The
"idle" bin covers speeds from -1 to 1 mph, and includes some braking in the transition
e While this document does not provide a detailed discussion of vehicle specific power, the light duty emission rate
report16 have an extensive discussion
14
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(deceleration) from non-zero speed to zero speed. In addition, however, there are also a number
of "coasting" bins (operating modes 11, 21, 33) that also contain braking events in each speed
category. Each of these operating modes include some braking as well as cruise and coasting
operation (where the throttle is closed or nearly closed, but the brakes are not applied).
Therefore, the emission rate assigned to these bins need to contain the appropriate average rates
including the mix of driving and deceleration, and including decelerations that do not include
braking. Bins 12 and 22 also contain a very small amount of braking, which are ignored - i.e,
the rates in these bins are set to zero.
To estimate the amount of braking activity in modes 1, 11, 21, 33, the brake emission rates in
those bins were multiplied by the amount of braking activity in each bin.f These braking
fractions were derived by combining the amount of average activity from Kansas City and LA
above and the coast down curves from PERE discussed earlier. The resulting fractions in
operating mode 11,21 and 31 for light-duty vehicles are shown in Table 3-8. Additional
information about braking at idle is in Section 3.2.3.
Fourth, the braking fractions in other deceleration operating modes were also calculated using
the PERE and Kansas City and LA driving cycles for other vehicle regulatory classes using the
vehicle weights and road load coefficients as shown in Table 3-8 below. The vehicle weights and
road load coefficients used for these vehicle classes have subsequently been updated in
MOVES2014 and MOVES3. However, as shown in Table 3-8, the braking fractions are fairly
consistent across different regulatory classes, and we have not updated this analysis for
MOVES3. Motorcycle fractions and Urban Bus fractions were not estimated this way.
Motorcycles use the braking fractions from light-duty vehicles (LDV), and Urban Buses use the
same braking fractions as HHD vehicles.
Table 3-8 - Vehicle Weights and Road Load Coefficients By Regulatory Class used to Calculate Braking
Fraction by Operating Mode Class
Light-duty
Vehicles (LDV)
Light-duty
Trucks (LDT)
LHD2b3
LHD45
MHD
HHD
weight (lbs)
3,300
3,968
12,350
20,576
29,800
50,001
mass (kg)
1,497
1,800
5,602
9,333
13,517
22,680
CrO (rolling
resistance)
0.008
0.008
0.008
0.008
0.01
0.01
Cd (drag coeff)
0.32
0.36
0.37
0.44
0.44
0.44
A (frontal area mA2)
2.25
2.5
2.75
6.7
6.7
8.64
OpModelD
Braking Fraction
0
1
1
1
1
1
1
1
0.0437
0.0437
0.0316
0.0316
0.0316
0.016
11
0.978
0.978
0.913
0.906
0.91
1
21
0.641
0.661
0.743
0.685
0.725
0.641
33
0.115
0.122
0.126
0.116
0.121
0.068
f For example, the brake wear PM2.5 emission rate in VSP bin 11 for light-duty vehicles is 0.557 * 0.978 = 0.546
g/hr
15
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3.2.3 Braking Activity in Idle Mode
As discussed above, the braking fraction for idling is estimated from the braking that occurs
during the idle mode within a driving cycle. MOVES uses driving cycles to estimate the
operating mode distribution from on-network driving, including the fraction of idling that occurs
on-network. For off-network idling, MOVES does not estimate brake emissions, because the
vehicle is completely stopped during this non-drive-cycle idle time.
In project-mode, MOVES assigns all operation with speed=0 to operating mode 501 (brake wear;
stopped), and speeds between 0 and 1 mph as operating mode 1 (idle). Operating mode 501
produces zero brake wear emissions, while operating mode 1 produces brake wear emissions (as
shown in Appendix B). In county-scale and national-scale, opMode 1 is used for estimating
brake wear emissions for all speeds < 1 including 0. The difference in project-mode from county-
scale was made so that when project-level users define links with actual speed=0, no brake wear
emission rates are estimated. At county-scale, we use opMode 1 at speed=0, because a
percentage of stopped time was accounted for in the derivation of the opMode 1 brake wear
emission rates from the driving cycles as discussed above. In project-mode, MOVES users have
the option to input their own operating mode distributions, including using operating mode 501
(brake wear; stopped) and operating mode 1 (idle).
3.2.4 PM10/PM2.5 Brake Wear Ratio
MOVES stores PM2.5 brake wear emission rates by operating mode bin, then estimates PM10
emission rates by applying a PM10/PM2.5 ratio. The PM10/PM2.5 ratio is based on the assumptions
that the mass fraction of particles below PM10 is 0.8, and the mass fraction of particles below
PM2.5 is 0.1. More specifically, Sanders et al. (2003), report PM "fractions and cutoffs of 0.8 at
10 pm, 0.6 at 7 pm, 0.35 at 4.7 pm, 0.02 at 1.1 pm, and <0.01 at 0.43 pm for the UDP stops
typical of urban driving". These assumptions result in a PM10/PM2.5 ratio of 8. Where no PM2.5
values were reported, we calculated PM2.5 from PM10 emission rates using this fraction. This
estimate widely varies in the literature. Abu-Allaban et al. (2003) reports that only 5-17 percent
of PM10 is PM2.5, which is consistent with Sanders. Garg et al. (2000), report 72 percent of PM10
is PM2.5, which is disputed by Sanders et al. (2003). The current study does use the PM2.5
measurement reported by Garg et al. (2000), however in reality, this single value has little impact
on the curve fit in Figure 3-1, which is dominated by the more recent data from Sanders et al.
(2003).
The emission rates in g/hr PM2.5 by operating mode and regulatory class are included in
Appendix B. The rates are calculated per the methodology described above and is independent
of model year and environmental conditions. The average PM2.5 and PM10 brake wear emission
rates for passenger cars and trucks (from a national-scale run inventory for calendar year 2017
using MOVES3) are displayed in Table 3-9. MOVES brake wear emission rates by source type
will vary according to the inputs of average speed, and VMT by road type, which impacts the
distribution of operating modes within each source type in MOVES.
16
-------
Table 3-9 Average PM2.5 and PM10 brake wear emission rates (mg/mile) for passenger cars and trucks from a
national-scale run inventory for calendar year 2017 using MOVES3
PM2.5
PM10
Passenger Cars (21)
2.77
22.17
Passenger Trucks (31)
2.88
23.08
The average passenger car MOVES PM10 brake wear emission rates of 22.17 mg/mi (output
from the model) is compared to the previous studies (in the literature) in Table 3-1. Carbotech
(1999), Sanders et al. (2003), Garg et al. (2000), are all laboratory measurements and have
significantly smaller reported emission rates than MOVES. On the other hand Luhana et al.
(2004), Abu-Allaban et al. (2003), Westurland (2001), and Rauteberg-Wulff (1999) are roadside
measurement or tunnel measurements. These studies generally have higher emissions than
laboratory measurements. The MOVES rates are also considerably larger than the publication
cites. This is largely due to the fact that the MOVES primary source, Sanders et al. (2003), cites
results primarily from the UDP braking events which are significantly milder than the AMS
decelerations. Through the modeling described in this paper, the AMS deceleration rates are
weighted in with the milder deceleration emission rates to give higher rates comparable to some
of the results achieved from the tunnel and roadside studies. The light duty rates are thus
calibrated to laboratory measurements adjusted to real-world factors, and "validated" to be
within the range of roadside and tunnel measurements.
3.2.5 Heavy-Duty and Other Vehicle Types
There is very little literature on direct heavy-duty brake emissions measurements. To decelerate,
heavy-duty vehicles employ technologies such as disc and drum as well as other braking
methods including downshifting and engine (or "jake") braking. A scientific study comparing the
emissions and relative activity of each of these methods of braking is beyond the scope of this
report. In order to estimate brake wear emission factors for heavy-duty vehicles an engineering
analysis was combined with results from a top-down study performed by Mahmoud Abu-Allaban
et al. (2003).17 The authors collected particulate matter on filters near roadways and apportioned
them to sources utilizing Chemical Mass Balance, CMB, receptor modeling along with Scanning
Electron Microscopy. The study was performed at roadside locations in Reno, Nevada and
Durham, North Carolina where intensive mass and chemical measurements were taken. The
authors of the paper attempted to collect and differentiate between PM measurements from
tailpipe, tire, road dust, and brake from light- and heavy-duty vehicle types. Compared to the
other papers described in the previous section (on light-duty braking) that include heavy-duty
rates, the Abu-Allaban paper was one of the most recent studies of its kind performed at the time
of the writing of this paper. The results are consistent with the heavy-duty rates measured from
Luhana et al. (2004) as well as Westurland (2001), but it is the only paper to measure PM2.5. The
paper's light-duty rates are also aligned with the rates determined above.
In this study, PM2.5 brake wear emission rates for heavy duty vehicles ranged from 0 to 15
mg/km (0 to 24 mg/mi). For this analysis we have assumed the emission rate was the midpoint of
the range of emission factors, or 12 mg/mi. For the purposes of populating MOVES rates, we do
17
-------
not employ the measured emission rate directly due to the extreme uncertainty and variability of
measurement and locations selected. Rather, we rely on the paper's comparison of light-duty to
heavy-duty emission factors. The emission rates for the exit ramps in Table 5 of the paper, are
reproduced below. Only the exit lanes were included of the many roads where measurements
were collected. The remainder of the roads are represented by the average and the (min to max)
range reported in the table.
Table 3-10 Brake Wear Emission Rates reproduced from Abu-Allaban et al. (2003)
Location
Vehicle Type
PM10 (mg/km)
PM2.5 (mg/km)
J. Motley Exit
Heavy-Duty
610+ 170
0 + 0
Light-Duty
79 + 23
0 + 0
Moana Lane Exit
Heavy-Duty
120 + 33
0 + 0
Light-Duty
10 + 3
0 + 0
Average over all
roads
Heavy-Duty
124 + 71
2 + 2
Light-Duty
12 + 8
1 + 0
Range (min to max)
of measurements on
all roads
Heavy-Duty
0 to 610
Oto 15
Light-Duty
Oto 80
0 to 5
Due to the difficulty of differentiating a small brake emissions signal from the much larger signal
coming from tailpipe, tire wear and road dust combined, there is much uncertainty in these
measurements - yet another reason why adjusted laboratory measurements were favored above.
Clearly PM2.5 was difficult to measure from most sites. Interestingly, the exit lane heavy-duty
measurements were highest for PM10, however (rather inexplicably), the other road types had
higher emissions than for PM2.5. For these reasons, we rely more on averages to determine our
ratio of heavy-duty to light-duty brake emission factors. From these measurements, we can
determine that the average ratio of HD to LD brake emissions is 10 and 2 for PM10 and PM2.5
respectively.8 On average, based on Table 3-10, the ratio is 7.6 for PM10. The following table
compares the ratio for the remaining studies for comparison.
Table 3-11- Ratio of Heavy-Duty to Light-Duty PM from the literature.
Study
PM2.5
PM10
Luhana et al. (2004)
7.7
Abu-Allaban et al. (2003)
3
7.6
Westurland (2001)
6.0
Rauterburg-Wulff (1999)
24.5
Carbotech (1999)
0.7
For the purposes of MOVES, a simpler model requiring a single ratio of HD to LD brake
emissions and another ratio of PM10 to PM2.5 brake emissions is attractive - particularly since the
data to populate the model is sparse. Also the broad range of uncertainties in the literature can
support such simplification. Based on the range in the table, above, the value of the ratio chosen
for development of MOVES emission rates is 7.5, very close to the ratio as measured by Abu-
Alaban et al. (2003), and consistent with the range of studies. Equation 3-1 is used to calculate
8 Though it is not shown in the table here, according to Abu-Alaban, based on the highest sampling sites (maximum
measurements from the table), the ratio of HD to LD brake emissions is 41 and 16 for PM10 and PM2.5 respectively.
18
-------
the brake emission rate for the deceleration/braking mode (OpModelD 0) from the LDV
emission rate.
HHD Emission rate (t~) = 7.5 x LDV Emission rate (-^-) Equation 3-1
\hrj hr
As stated in the Introduction, the brake emission factors for MOVES3 are unchanged from
MOVES2014. The estimated emission factors for all other regulatory classes were derived by
linearly interpolating the rates between the light-duty vehicle (LDV) and heavy heavy-duty
(HHD) vehicle classes by their respective weights as shown in the figure below (or extrapolating
as in the case of motorcycles). This is based on a rather simple engineering (and unproven in this
study) hypothesis that the relative brake emissions are proportional to the weight of the vehicle
classes relative to (and bounded by) light and heavy-duty vehicles. The hypothesis is based on
the assumption that relative mass of the vehicles is proportional to the relative energy required to
stop the vehicles. The resulting HHD emission rates for opModeO is shown in Table 3-12.
Since brake wear emission rates in MOVES are defined by regulatory class, we first estimated
the vehicle weight for each regulatory class. We estimated the actual vehicle weight, including
payload for heavy-duty trucks, not the gross vehicle weight rating (GVWR) which is used to
defined the regulatory class vehicles. The estimated vehicle weight is derived from the source
mass value stored in the MOVES2014 sourceUseTypePhysics table by source type.h The
average vehicle weight of each regulatory class was determined by VMT-weighting the
contribution of each source type to each regulatory class. The resulting estimated vehicle weights
from MOVES2014 are shown in Table 3-12.
Table 3-12 Vehicle Weights and PM2.5 Brake Wear Emission Rates by Regulatory Class for opModelD 0
Regulatory
Class
regClassID
MOVES2014-
estimated vehicle
weight (lbs)
PM2.5 Emission
Rates (g/hr)
MC
10
628
0.355
LDV
20
3,260
0.558
LDT
30
4,197
0.631
LHD2b3
41
4,303
0.639
LHD45
42
18,849
1.76
MHD
46
28,527
2.51
HHD
47
50,285
4.19
Urban Bus
48
36,500
3.12
Gliders
49
50,285
4.19
Figure 3-3 and Table 3-12 shows the linear interpolation between the light-duty and heavy
heavy-duty brake wear emission rates by the MOVES2014-estimated regulatory class weight.
h In MOVES3, the heavy-duty vehicle weight is defined by both source use type and regulatory class18
19
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ro
CC
3.0
c
o
2.5
\n
tn
E
LU
2.0
-------
Table 3-13 contains average brake wear PM2.5 emission rates from a national-scale MOVES3 run
for calendar year 20171 using default activity input, for each source type. Brake emission rates by
source type will vary for local users according to inputs such as road type distribution and speed
distribution that impact the operating mode distribution of vehicle operation.
Table 3-13 Average PM2.5 and PM10 brake wear PM emission rates for the MOVES source types from a
national-scale run inventory for calendar year 2017 using MOVES3
SourceTypelD
Source Type
PM2.5
PM10
mg/veh-mile
mg/veh-km
mg/veh-mile
mg/veh-km
11
Motorcycle
1.58
0.98
12.61
7.83
21
Passenger Car
2.77
1.72
22.17
13.78
31
Passenger Truck
2.88
1.79
23.08
14.34
32
Light Commercial Truck
3.08
1.91
24.64
15.31
41
Intercity Bus
15.50
9.63
123.98
77.04
42
Transit Bus
9.45
5.87
75.62
46.99
43
School Bus
9.94
6.18
79.55
49.43
51
Refuse Truck
13.35
8.29
106.77
66.34
52
Single Unit Short-haul Truck
8.24
5.12
65.89
40.94
53
Single Unit Long-haul Truck
6.88
4.28
55.04
34.20
54
Motor Home
10.66
6.62
85.26
52.98
61
Combination Short-haul
Truck
9.52
5.91
76.13
47.30
62
Combination Long-haul
Truck
7.96
4.94
63.64
39.55
1 Calendar year 2017 run was shown as an example. The rates for other calendar years tested (2006 and 2035) show
little differences.
21
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4 Tire Wear
4.1 Introduction
Tires are an essential part of any vehicle and the number and size of tires increase with the size
of the vehicle. Contact between tires and the road surface causes the tires to wear, with the rate
dependent on a variety of factors.
EPA's previous estimates of tire wear are contained in the PART5 model and are emission rates
of 0.002 grams per mile per wheel. Two LDV studies from the 1970s are the basis for these
emission rates. The PART5 emissions factors are based on tests of older bias-ply tires rather than
more modern radial tire technologies. The National Resource Council report on the MOBILE
model, suggested that the PART5 rates may be out of date.19
Tire wear occurs through frictional contact between the tire and the road surface. Friction causes
small and larger particles to wear from tire, which are then either released as airborne
particulates, deposited onto the road surface or retained in the wheel hub temporarily or
permanently until washed off. The road surface causes friction and abrasion and therefore the
roughness of the surface affects the wear rate by a factor of 2-3.20
In addition to road surface roughness, tires wear is dependent upon a combination of activity
factors such as route and style of driving, and seasonal influences. Heavy braking and
accelerating (including turning and road grade) especially increases tire wear. The route and style
of driving determine the amount of acceleration. Highway geometry is a key factor with rise and
fall in roads also resulting in increased tread wear. The acceleration of the vehicle determines the
forces applied to the tire and includes turning. Tire wear due to tire/road interface is determined
by and is directly proportional to these forces.21 The season results in temperature, humidity and
water contact variations. Wear rates are lower in wet compared to dry conditions.
Finally, vehicle characteristics also influence tire wear. Key factors are the weight, suspension,
steering geometry, and tire material and design. Axle geometry changes result in uneven wear
across the tire width. The type of tire influences the wear significantly. In particular, the physical
characteristics like the shape of the tire (determined by stiffness), the rubber volume (tread
pattern), and the characteristic of the tire (rubber type etc.). As a consequence of different
manufacturing specifications, different brands of tires wear at different rates. Retreads are also
considered to wear more than new tires. Wear rate studies on tire fleets reported in Bennett &
Greenwood (2001) also indicated that retreads had only about 75 percent of the tire tread volume
that new tires had. Cenek et al. (1993) reported that 20 percent of New Zealand passenger tire
sales were retreads and that retreads made up 75 percent of the tire tread in a sample of buses in
the New Zealand fleet.22 However, modeling emissions from retreads was deemed beyond the
scope of the report.
According to the literature, the most straightforward method for determining tire wear is the
periodic measurement of tread depth. However, variations in the extent of wear across the tire
and irregularities in tire shape could lead to inaccurate measurements. Determining tire weight
loss is a more sensitive approach than the measurement of tire depth, though care must be taken
to avoid errors due to damage to tires as a result of their removal from the vehicle and hubs, and
22
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material embedded in the tire. To minimize damage to the tire, Lowne (1970) weighed both the
wheel and tire simultaneously after the wheel was brushed and stones embedded in the tire were
removed.23 Table 4-1 shows a summary of the literature search conducted as of 2006 on the mass
of tire wear.
Wear rates for tires have typically been calculated based on tire lifetime (in kilometers traveled),
initial weight and tread surface depth. Tire wear occurs constantly for moving vehicles, but may
be significantly higher for cars which tend to brake suddenly or accelerate rapidly. Tire wear
rates have been found to vary significantly between a wide range of studies.24
Speed variation is an important factor as well. Carpenter & Cenek (1999) have shown that the
effect of speed variation is highest at low speeds as a result of inertial effects and effective
mass.25 They also examined lateral force effects on tires and assessed tire wear on routes of
different amounts of horizontal curvature and found that there was little variation.
Tire abrasion is difficult to simulate in the laboratory, since the varied nature of the road and
driving conditions influence wear rates in urban environments. Hildemann et al. (1991)
determined the chemical composition of tire wear particles using a rolling resistance testing
machine at a tire testing laboratory over a period of several days.26 Rauterberg-Wulff (1999)
determined particle emission factors for tire wear using modeling in combination with
measurements conducted in the Berlin-Tegel tunnel.27
Tire wear rates have been measured and estimated for a range of vehicles from passenger cars to
light and heavy duty trucks with results reported either as emissions per tire or per vehicle. Most
of the studies report only wear, not airborne PM. The wear rates found in the literature are
summarized in Table 4-1 below and are converted to a per vehicle rate (units are in per vehicle
kilometer). A range of light-duty tire wear rates from 64-360 mg/vehicle/km has been reported in
the literature. Much of the variability in these wear rates can probably be explained by the factors
mentioned above. These studies made no distinction between front and rear tires, even though
they can wear at different rates.28
23
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Table 4-1 - Tire wear rates found in the literature. Rates are per vehicle. Estimated number of tires is
described later.
Source
Remarks
rate in mg/vkm
Kupiainen,K.J. et al(2005)29
Measured tire wear rate
9 mg/km - PM10
2 mg/km -PM2.5
Luhana et al (2003)
Measured tire wear rate
74
Councell.T.B. et al (2004)
Calculated rate based on literature
200
U.S. Geological Survey30
Warner et al. (2002)31
Average tire wear for a vehicle
97
Kolioussis and Pouftis (2000)32
Average estimated tire wear
40
EMPA (2000)33
Light duty vehicle tire wear rate
53
Heavy duty vehicle tire wear rate
798
SENCO (Sustainable Environment
Light duty vehicle tire wear rate
53
Consultants Ltd.) (1999)34
Wear rate for trucks
1403
Estimated rate for light duty vehicles
68
Legret and Pagotto (1999a)
Estimated rate for heavy vehicles (>3.5t)
136
Baumann (1997)35
Passenger car tire wear rate
80
Heavy duty vehicle tire wear rate
189
Articulated lorry tire wear rate
234
Bus tire wear rate
192
Garben (1997)36
Passenger car tire wear rate
64
Light duty vehicle tire wear rate
112
Heavy duty vehicle tire wear rate
768
Motorbike tire wear rate
32
Gebbe (1997)37
Passenger car tire wear rate
53
Light duty vehicle tire wear rate
110
Heavy duty vehicle tire wear rate
539
Motorbike tire wear rate
26.4
Lee et al (1997)38
Estimated tire wear rate
64
Sakai,H (1995)
Measured tire wear rate
184
Baekken (1993)39
Estimated tire wear rate
200
CARB (1993)
Passenger car tire wear rate
120
Muschack (1990)
Estimated tire wear rate
120
Schuring and Clark (1988)40
Estimated tire wear rate
240-360
Pierce,R.N. (1984)
Estimated tire wear rate
120
Malmqvist (1983)41
Estimated tire wear rate
120
Gottle (1979)42
Estimated tire wear rate
120
Cadle et al. (1978)43
Measured tire wear rate
4
Dannis (1974)44
90
While there is significant literature on tear wear, there is relatively little published on airborne
particulate matter from tires. In this report, a model for tire wear rates are first determined, and
then a discussion of the modeling of airborne PM2.5 and PM10 follows building off the wear
model.
24
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4.2 Data and Methodology
This report begins by estimating the tire wear from light-duty vehicles, then, based on the per tire
wear, extrapolates to other vehicle types. Then the emission rates are derived from the wear
rates.
The method primarily depends on the data from work published by Luhana et al. (2004) wherein
wear loss rates for tires have been determined gravimetrically for in-service cars.28 At the time
of this analysis, this paper was both a recent and comprehensive study. The authors weighed car
tires at two-month intervals, and asked drivers to note the details of each trip undertaken. Five
test vehicles (labeled A-E) were selected for the tests. Of these vehicles A (1998 Audi A3), B
(1994 Ford Mondeo), C (1990 Peugeot 205) and E (1992 Vauxhall Cavalier) were front-wheel
drive vehicles (FWD). According to the driver surveys, the predominant road type used by
vehicles A and B were motorways, for vehicle D (1990 Ford Sierra) it was rural roads and
motorways; for vehicle C it was suburban roads, and for vehicle E, it was rural roads. Vehicle D
was excluded from this study since it was a rear-wheel drive (RWD) vehicle. RWD vehicles are
relatively uncommon amongst passenger vehicles in the United States, and the wear from this
particular vehicle was more than double the other FWD vehicles. It is uncertain whether the
discrepancy from this vehicle was because it was a rear-wheel drive or for some other reason.
The selection of vehicles was based primarily on driving conditions, as defined by the main type
of road used by the owner and annual distance driven.
Results from the Luhana et al. (2004) study indicated that the lowest tire wear rates (56 mg/vkm
and 67 mg/vkm respectively-5) were for vehicles A and B that were driven predominantly on
motorways. Vehicles C and E had very similar wear rates (around 85 mg/vkm) although these
vehicles tended to be driven on different roads. Based on the wear rates from the four front-
wheel drive cars alone, the study concluded that the average wear rate is around 74 mg/vkm.
This value is in the lower end of the range of wear rates reported in the literature.
The data presented in Table 4-2 includes calculations for the distances completed by each vehicle
between successive tests, the estimated average trip speeds and predominant road types for the
equivalent periods. It was assumed that the weight of the wheels remained constant during the
tests, and any weight loss was due solely to the loss of tire rubber during driving.
J vkm is "vehicle kilometer" and assumes four times a per tire rate for light-duty vehicles.
25
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Table 4-2: Data from Luhana et al. (2004) with measurements of tire wear for a variety of trips
Avg. trip
speed
Tire Wt. Loss (per axle)
total wt. loss (per
vehicle)
total wt. loss
(per vehicle)
avg. speed
vehicle
tests
km/hr
Front mean (g/km)
Rear Mean
(g/km)
g/km
g/mi
mi/hr
testl-A
90.3
0.0202
0.0092
0.0589
0.0947
56.1
test2-A
90.6
0.0209
0.0126
0.0669
0.1076
56.3
test3-A
93.9
-
0.0069
-
-
58.4
test4-A
92.7
0.0172
0.0086
0.0516
0.083
57.6
testl-B
65.4
0.0298
0.0087
0.077
0.1239
40.6
test2-B
71.9
0.0262
0.0091
0.0705
0.1135
44.7
test3-B
74.4
0.019
0.004
0.0461
0.0742
46.2
test4-B
70.2
0.0297
0.007
0.0735
0.1183
43.6
testl-C
44.5
0.0312
0.0047
0.0718
0.1155
27.7
test2-C
42.9
0.0331
0.0132
0.0925
0.1489
26.7
test3-C
48.8
0.0284
0.0064
0.0697
0.1121
30.3
test4-C
50.4
0.0532
0.0045
0.1153
0.1855
31.3
test3-E
61.3
0.037
0.0104
0.0948
0.1525
38.1
test4-E
65.8
0.0265
0.0109
0.0749
0.1205
40.9
Note: Vehicles A and B were driven mainly on motorways (freeways)
Vehicle C was driven on Suburban Roads and
Vehicle E was driven mostly on Rural roads
4.3 Analysis
Tire wear clearly varies with acceleration as well as speed, and we would like to model it by
VSP bin as we model brake wear. However there is insufficient data to characterize tire wear on
a second-by-second basis to enable binning by operating mode bins. Thus MOVES currently
models tire wear based on average speed as shown in Table 4-3.
26
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Table 4-3: MOVES tire wear operating mode bins based on average speed
opModelD
opModeName
speed lower in mph
speed upper in mph
400
tirewear;idle
401
tirewear;speed < 2.5mph
0
2.5
402
tirewear;2.5mph <= speed < 7.5mph
2.5
7.5
403
tirewear;7.5mph <= speed < 12.5mph
7.5
12.5
404
tirewear;12.5mph <= speed < 17.5mph
12.5
17.5
405
tirewear;17.5mph <= speed <22.5mph
17.5
22.5
406
tirewear;22.5mph <= speed < 27.5mph
22.5
27.5
407
tirewear;27.5mph <= speed < 32.5mph
27.5
32.5
408
tirewear;32.5mph <= speed < 37.5mph
32.5
37.5
409
tirewear;37.5mph <= speed < 42.5mph
37.5
42.5
410
tirewear;42.5mph <= speed < 47.5mph
42.5
47.5
411
tirewear;47.5mph <= speed < 52.5mph
47.5
52.5
412
tirewear;52.5mph <= speed < 57.5mph
52.5
57.5
413
tirewear;57.5mph <= speed < 62.5mph
57.5
62.5
414
tirewear;62.5mph <= speed < 67.5mph
62.5
67.5
415
tirewear;67.5mph <= speed < 72.5mph
67.5
72.5
416
tirewear;72.5mph <= speed
72.5
Using the above data on average speed and total weight loss, an exponential regression curve
was fitted which was characterized by an R2 value of 0.43. The actual and predicted values are
presented in Figure 4-1.
A weak negative correlation is shown between tire wear and average trip speed, with wear being
around 50 percent higher at an average speed of 40 km/h (dominated by urban driving) than at an
average speed of 90 km/h (dominated by motorway driving).
27
-------
0.25 i
Tire weight loss vs mean trip speed (actual)
0.20
0.15
0.10
O)
y = 0.2158e 0015x
R2 = 0.4265
g
0
0.00 -I 1 1 1 1 1 1
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0
mean trip speed in mi/hr
Figure 4-1 Relationship between light-duty tire weight loss (per vehicle) and mean trip speed
The shape of the curve in Figure 4-1 deserves some discussion. It can be seen from the curve that
the wear approaches a maximum at zero speed and goes down as the speed goes up. This is
based on the extrapolation of the fitted curve. It may seem counter-intuitive that emissions are
highest when speed nears zero, however, it is important to note that we do not otherwise account
for acceleration and turning. Much of the tire wear occurs when the magnitude of a vehicle's
acceleration/deceleration is at its greatest, e.g. at low speeds when the vehicle is accelerating
from rest, or when the vehicle is braking hard to stop.
However, for MOVES, the emission rate for average speeds less than 2.5 mph is set to zero at all
scales to avoid anomalous results in project level analyses where increased idling would result in
an over prediction of tire emissions. In addition, MOVES does not model off-network idle or
extended idle emissions for tire wear because the vehicle is completely stopped during this non-
drive-cycle idle time.
The predicted values as determined above are for passenger cars (LDVs). To determine tire wear
loss rates for other regulatory classes it was assumed that total tire wear per vehicle is dependent
upon the number of tires on the vehicle which, in turn, is a function of the number of axles per
vehicle by vehicle class. We did not distinguish between drive axles and other axles. Axle
counts were found in the Vehicle Inventory and Use Survey (VIUS 2002) data base. This data
enabled the calculation of tires per vehicle for each of the six truck classes and thereby tire-wear
losses for the different truck categories (regulatory classes) were determined. The average
number of tires per truck is given in Table 3-3 below.
28
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Table 4-4 - Average Number of Tires per Vehicle - Calculated from 2002 VIUS Survey of axle count.
RegClassID
RegClass name
Average Tires Per
Vehicle
10
MC
2.0
20
LDV
4.0
30
LDT
4.0
41
LHD2b3
5.5
42
LHD45
6.0
46
MHDD
7.0
47
HHDD
14.9
48
Urban Bus
8.0
* Note: Tires per vehicle for LDT is the same as that for LDV
In the future, this analysis could be improved with data on tire wear from heavy-duty trucks.
Once the average tire wear was quantified, it was necessary to determine the fraction of that wear
that becomes airborne PM. The literature indicates that probably less than 10 percent of car tire
wear is emitted as PMio under 'typical' driving conditions but the proportion could be as high as
30 percent (Boulter2005a). According to Luhana et al. (2004), PMio appears to be released from
(all 4) tires at a rate of between 4 and 6 mg/vkm for passenger cars. This suggests that generally
between around 1 percent and 15 percent by mass of passenger car tire wear material is emitted
as PMio (though much higher proportions have been reported in some studies). For this study, it
is assumed that 8 percent of tire wear is emitted as PMio (average of 1 percent and 16 percent.
According to Kupiainen et al (2005), PM2.5 fractions were on average 15 percent of PMio.29
Based on this study, it is assumed that 1.2 percent of the total tire wear is emitted as PM2.5to
develop our tire wear emission rate. The 1.2 percent is derived from assuming that 8 percent of
tire wear to be emitted as PMio and 15 percent of PMio is PM2.5.
We then convert the g/vehicle/mile tire wear emission rates to g/hr by multiplying by the average
speed of each MOVES speed bin. The g/hour tire wear emission rate by speed bin for all
regulatory classes used in MOVES can be found in Appendix B. MOVES applies the same tire
wear emission rate for all vehicle fuel types (gasoline, diesel, flex-fuel, CNG or electric) within a
MOVES regulatory class. The average PM2.5 tire wear emission rates in (mg/mile) for each
regulatory class, across road types and speed bins, from a national-scale run for calendar year
2017 using MOVES3 is shown in Table 4-5.
29
-------
Table 4-5 Average PM2.5 and PM10 tire wear PM emission rates for the MOVES regulatory classes from a
national-scale run inventory for calendar year 2017 using MOVES3
sourceTypelD
sourcetypename
PM2.5
PM10
mg/veh-
mile
mg/veh-
km
mg/veh-
mile
mg/veh-
km
11
Motorcycle
0.64
0.40
4.29
2.66
21
Passenger Car
1.28
0.80
8.55
5.32
31
Passenger Truck
1.28
0.80
8.57
5.32
32
Light Commercial Truck
1.37
0.85
9.16
5.69
41
Intercity Bus
3.87
2.40
25.77
16.01
42
Transit Bus
2.35
1.46
15.68
9.74
43
School Bus
2.30
1.43
15.31
9.51
51
Refuse Truck
3.93
2.44
26.19
16.27
52
Single Unit Short-haul Truck
2.25
1.40
15.03
9.34
53
Single Unit Long-haul Truck
2.17
1.35
14.48
9.00
54
Motor Home
2.21
1.37
14.75
9.16
61
Combination Short-haul Truck
3.81
2.37
25.39
15.78
62
Combination Long-haul Truck
4.13
2.56
27.51
17.10
4.3.1 PM10/PM2.5 Tire Wear Ratio
MOVES stores PM2.5 tire wear emission rates by operating mode bin (in this case, speed bins),
then estimates PM10 emission rates by applying a PM10/PM2.5 ratio. Thus, MOVES applies a
PM10/PM2.5 ratio of 6.667, which is based on the particle size distribution of tire wear measured
by Kupianen et al. (2005)k. Grigoratos et al. (2018)45 reported PM10/PM2.5 ratios between 2 and
2.5 (rather than 6.67). These values will be considered in future tire wear updates in MOVES.
The average PM10 emission rates from the national-scale run inventories using MOVES 3 are
displayed in Table 4-5.
4.4 Tire Wear Emissions in Project-Scale
In project scale, tire-wear emissions are estimated using the link average speed, with one
exception. If the user provides a link-level driving cycle (using the MOVES
driveScheduleSecondLink input table), then MOVES will calculate the average speed from the
input driving schedule, rather than the average speed associated in the link table). As opposed to
brake wear emissions, MOVES users do not have the option to input their own operating mode
k The PM10/PM2.5 ratio is derived from dividing the PM10 fraction of total PM, by the PM2.5 fraction of total PM, :
.08/.012 = 6.667 from values reported by Kupianen et al. (2005)29.
30
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distribution (using the opModeDistribution table)1. Because the tire wear emission rates are
based on average speed over a roadway link, MOVES only uses the most appropriate average
speed over the link.
As stated earlier, the tire wear emission rate at idle is set to zero in the default emission rate table
(Appendix B) used at all scales of analysis.
5 Ongoing and Future Work
As exhaust emissions decrease, brake and tire emissions are projected to contribute an
increasingly larger share of particulate matter emissions from onroad vehicles. The brake and tire
emission rates in MOVES 3 have had only minor revisions since the original
brake and tire analysis was conducted for MOVES2009. While this report notes some minor
updates to the tire and brake wear calculations since then, many inconsistencies remain.
MOVES2014 and MOVES3 included changes to vehicle specifications described in this report.
For example, the default assumptions regarding axle count (and thus number of wheels per
vehicle), average weights, aerodynamics, and rolling resistance have changed for many
regulatory classes. The most significant of these implications may be impact of updated vehicle
weights on brake wear rates.
The MOVES3 emission rates have not been updated to account for more recent studies that
capture improved methods in estimating brake and tire emissions, or that incorporate updated
brake and tire materials and technologies. This analysis looked at front wheel drive brakes,
primarily from vehicles equipped with disc brakes in the front and drum brakes in the rear (the
most common light duty configuration at the time of the literature review). Current light-duty
vehicles are now typically equipped with four disc brakes and hybrid and electric vehicles sold
today use electric regenerative braking. Vehicles with four disc brakes should presumably have
higher emissions, while hybrids and electric vehicles should have lower brake emissions. As
stated in the report, the heavy-duty brake emission data are limited. Moreover, the incident rate
of other forms of decelerating a truck such as downshifting and engine (or jake) braking are also
not considered in this study due to a lack of data.
For tire emissions, it was beyond the scope of this study to quantify the differences in emissions
(per tire) between light duty and various heavy duty tires. It was also beyond the scope of this
study to look at how trends in rolling resistance improvement may increase or decrease tire wear
emissions.
As mentioned in the Introduction, MOVES does not conduct speciation of tire and brake PM
emissions. Some of the references employed did include some of speciated measurements,
however brake material has been known to evolve over time. The current speciation profiles used
for the national emissions inventory and emissions platform for air quality modeling is based on
a study conducted in 2001 with a limited number of samples.46 Updating the speciation profiles
using modern brake configurations and materials is recommended for work.
31
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The EPA has conducted more recent literature review of brake and tire emissions rates.47 In
general, the brake and tire emission rates from MOVES fall within the wide range of the
literature values. The EPA and CARB have recently cooperated on a research program to
measure brake emissions from modern light-duty vehicles.48 We anticipate using this and other
research programs to update the brake emissions in a future update to MOVES.
32
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Appendix A Deceleration from PERE
This appendix briefly describes some of analytical methods used to determine the deceleration
point at which coasting becomes braking. A full description of the PERE model is provided in a
separate EPA report as cited earlier. This section, provides additional information beyond what
can be found in the PERE documentation.
The basis for the tractive load equations in the PERE model are found in the A, B, C coastdown
coefficients described in the report. The author of this report conducted coastdown testing on a
-2001 Nissan Altima on relatively "flat" roads in Southeast Michigan. The A, B, C coefficients
for this vehicle can be found in the EPA database. The A,B,C tractive load equations in PERE
were converted to a coastdown curve and plotted compared to the data below. The area above the
curve is throttle and the area below the curve is braking. The curve itself is "coasting" on neutral
gear.
80
70
60
50
3
Q.
E
CO
30
20
10
0
0 20 40 60 80 100 120 140 160 180 200
Time (seconds)
Figure A-l Coast Down- Modeled and Measured (Altima on 1-94 and Service Drive; Gear: neutral)
Based on these coastdown equations, a series of coastdown curves are generated as a function of
vehicle mass. As in the previous plot, the area under the curve is braking and the area above the
curve is throttling.
Coast Down - Modeled and Measured (altima on 1-94 and service dr; gear:neutral)
X.
~
Data 4
Data 3
Y
VK
Data 2
¦ Datal
modeled
~
irv ~—
33
-------
10
20
40
50
60
70
80
¦0.2
Kilograms
900
¦0.4
1200
1497
¦0.6
1800
Poly. (1497)
Q.
O)
y = -0.0001454x: + 0.0000622X - 0.1758
R! = 1.0
Speed (mph)
Figure A-2. Coast down Curves as a Function of Vehicle Mass
A PERE simulation is run on the FTP cycle and the braking episodes are flagged in the figure
below (for a typical 1497kg LDV).
100 r 1
90
speed
brake
6600 6650 6700 6750 6800 6850 6900 6950 7000
time
Figure A-3 Braking Episodes over the FTP cycle
34
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Appendix B Brake and Tire Wear Emission Rates
This appendix includes the brake and tire emission rates as a function of regulatory class and
operating mode which are stored in the MOVES3 emissionrate table.
Table B-l PM2.5 Brake Emission Rates by Regulatory Class and Operating Mode (g/hr)
regclassID
regClassName
opModelD
opModeName
MeanBaseRate
(g/hr)
10
MC
0
Braking
0.355
10
MC
1
Idling
0.016
10
MC
11
Low Speed Coasting; VSP< 0;
l<=Speed<25
0.348
10
MC
21
Moderate Speed Coasting; VSP< 0;
25<=Speed<50
0.229
10
MC
33
Cruise/Acceleration; VSP< 6;
50<=Speed
0.036
20
LDV
0
Braking
0.558
20
LDV
1
Idling
0.024
20
LDV
11
Low Speed Coasting; VSP< 0;
l<=Speed<25
0.546
20
LDV
21
Moderate Speed Coasting; VSP< 0;
25<=Speed<50
0.359
20
LDV
33
Cruise/Acceleration; VSP< 6;
50<=Speed
0.064
30
LDT
0
Braking
0.631
30
LDT
1
Idling
0.028
30
LDT
11
Low Speed Coasting; VSP< 0;
l<=Speed<25
0.617
30
LDT
21
Moderate Speed Coasting; VSP< 0;
25<=Speed<50
0.418
30
LDT
33
Cruise/Acceleration; VSP< 6;
50<=Speed
0.077
41
LHD2b3
0
Braking
0.639
41
LHD2b3
1
Idling
0.020
41
LHD2b3
11
Low Speed Coasting; VSP< 0;
l<=Speed<25
0.583
41
LHD2b3
21
Moderate Speed Coasting; VSP< 0;
25<=Speed<50
0.475
41
LHD2b3
33
Cruise/Acceleration; VSP< 6;
50<=Speed
0.081
42
LHD45
0
Braking
1.762
42
LHD45
1
Idling
0.056
42
LHD45
11
Low Speed Coasting; VSP< 0;
l<=Speed<25
1.609
42
LHD45
21
Moderate Speed Coasting; VSP< 0;
25<=Speed<50
1.307
42
LHD45
33
Cruise/Acceleration; VSP< 6;
50<=Speed
0.227
35
-------
46
MHD67
0
Braking
2.509
46
MHD67
1
Idling
0.079
46
MHD67
11
Low Speed Coasting; VSP< 0;
l<=Speed<25
2.283
46
MHD67
21
Moderate Speed Coasting; VSP< 0;
25<=Speed<50
1.819
46
MHD67
33
Cruise/Acceleration; VSP< 6;
50<=Speed
0.304
47
HHD8
0
Braking
4.188
47
HHD8
1
Idling
0.067
47
HHD8
11
Low Speed Coasting; VSP< 0;
l<=Speed<25
4.188
47
HHD8
21
Moderate Speed Coasting; VSP< 0;
25<=Speed<50
2.685
47
HHD8
33
Cruise/Acceleration; VSP< 6;
50<=Speed
0.285
48
Urban Bus
0
Braking
3.124
48
Urban Bus
1
Idling
0.050
48
Urban Bus
11
Low Speed Coasting; VSP< 0;
l<=Speed<25
3.124
48
Urban Bus
21
Moderate Speed Coasting; VSP< 0;
25<=Speed<50
2.003
48
Urban Bus
33
Cruise/Acceleration; VSP< 6;
50<=Speed
0.212
49
Gliders
0
Braking
4.188
49
Gliders
1
Idling
0.067
49
Gliders
11
Low Speed Coasting; VSP< 0;
l<=Speed<25
4.188
49
Gliders
21
Moderate Speed Coasting; VSP< 0;
25<=Speed<50
2.685
49
Gliders
33
Cruise/Acceleration; VSP< 6;
50<=Speed
0.285
36
-------
Table B-2 PM2.5 Tire Wear Emission Rates by Regulatory Class and Operating Mode (g/hr) in MOVES3.
regclassID
regClassName
opModelD
opModeName
MeanBaseRate (g/hr)
10
MC
400
idle
0.0000
10
MC
401
speed < 2.5mph
0.0032
10
MC
402
2.5mph <= speed < 7.5mph
0.0060
10
MC
403
7.5mph <= speed < 12.5mph
0.0112
10
MC
404
12.5mph <= speed < 17.5mph
0.0155
10
MC
405
17.5mph <= speed <22.5mph
0.0192
10
MC
406
22.5mph <= speed < 27.5mph
0.0223
10
MC
407
27.5mph <= speed < 32.5mph
0.0248
10
MC
408
32.5mph <= speed < 37.5mph
0.0269
10
MC
409
37.5mph <= speed < 42.5mph
0.0285
10
MC
410
42.5mph <= speed < 47.5mph
0.0298
10
MC
411
47.5mph <= speed < 52.5mph
0.0308
10
MC
412
52.5mph <= speed < 57.5mph
0.0314
10
MC
413
57.5mph <= speed < 62.5mph
0.0318
10
MC
414
62.5mph <= speed < 67.5mph
0.0320
10
MC
415
67.5mph <= speed < 72.5mph
0.0319
10
MC
416
72.5mph <= speed
0.0318
20
LDV
400
idle
0.0000
20
LDV
401
speed < 2.5mph
0.0064
20
LDV
402
2.5mph <= speed < 7.5mph
0.0120
20
LDV
403
7.5mph <= speed < 12.5mph
0.0223
20
LDV
404
12.5mph <= speed < 17.5mph
0.0311
20
LDV
405
17.5mph <= speed <22.5mph
0.0384
20
LDV
406
22.5mph <= speed < 27.5mph
0.0446
20
LDV
407
27.5mph <= speed < 32.5mph
0.0497
20
LDV
408
32.5mph <= speed < 37.5mph
0.0538
20
LDV
409
37.5mph <= speed < 42.5mph
0.0571
20
LDV
410
42.5mph <= speed < 47.5mph
0.0596
20
LDV
411
47.5mph <= speed < 52.5mph
0.0615
20
LDV
412
52.5mph <= speed < 57.5mph
0.0628
20
LDV
413
57.5mph <= speed < 62.5mph
0.0635
20
LDV
414
62.5mph <= speed < 67.5mph
0.0639
20
LDV
415
67.5mph <= speed < 72.5mph
0.0639
20
LDV
416
72.5mph <= speed
0.0635
30
LDT
400
idle
0.0000
30
LDT
401
speed < 2.5mph
0.0064
30
LDT
402
2.5mph <= speed < 7.5mph
0.0120
30
LDT
403
7.5mph <= speed < 12.5mph
0.0223
30
LDT
404
12.5mph <= speed < 17.5mph
0.0311
37
-------
30
LDT
405
17.5mph <= speed <22.5mph
0.0384
30
LDT
406
22.5mph <= speed < 27.5mph
0.0446
30
LDT
407
27.5mph <= speed < 32.5mph
0.0497
30
LDT
408
32.5mph <= speed < 37.5mph
0.0538
30
LDT
409
37.5mph <= speed < 42.5mph
0.0571
30
LDT
410
42.5mph <= speed < 47.5mph
0.0596
30
LDT
411
47.5mph <= speed < 52.5mph
0.0615
30
LDT
412
52.5mph <= speed < 57.5mph
0.0628
30
LDT
413
57.5mph <= speed < 62.5mph
0.0635
30
LDT
414
62.5mph <= speed < 67.5mph
0.0639
30
LDT
415
67.5mph <= speed < 72.5mph
0.0639
30
LDT
416
72.5mph <= speed
0.0635
41
LHD2b3
400
idle
0.0000
41
LHD2b3
401
speed < 2.5mph
0.0088
41
LHD2b3
402
2.5mph <= speed < 7.5mph
0.0166
41
LHD2b3
403
7.5mph <= speed < 12.5mph
0.0308
41
LHD2b3
404
12.5mph <= speed < 17.5mph
0.0429
41
LHD2b3
405
17.5mph <= speed <22.5mph
0.0531
41
LHD2b3
406
22.5mph <= speed < 27.5mph
0.0616
41
LHD2b3
407
27.5mph <= speed < 32.5mph
0.0686
41
LHD2b3
408
32.5mph <= speed < 37.5mph
0.0743
41
LHD2b3
409
37.5mph <= speed < 42.5mph
0.0788
41
LHD2b3
410
42.5mph <= speed < 47.5mph
0.0823
41
LHD2b3
411
47.5mph <= speed < 52.5mph
0.0849
41
LHD2b3
412
52.5mph <= speed < 57.5mph
0.0866
41
LHD2b3
413
57.5mph <= speed < 62.5mph
0.0877
41
LHD2b3
414
62.5mph <= speed < 67.5mph
0.0882
41
LHD2b3
415
67.5mph <= speed < 72.5mph
0.0882
41
LHD2b3
416
72.5mph <= speed
0.0877
42
LHD45
400
idle
0.0000
42
LHD45
401
speed < 2.5mph
0.0095
42
LHD45
402
2.5mph <= speed < 7.5mph
0.0180
42
LHD45
403
7.5mph <= speed < 12.5mph
0.0334
42
LHD45
404
12.5mph <= speed < 17.5mph
0.0464
42
LHD45
405
17.5mph <= speed <22.5mph
0.0575
42
LHD45
406
22.5mph <= speed < 27.5mph
0.0667
42
LHD45
407
27.5mph <= speed < 32.5mph
0.0743
42
LHD45
408
32.5mph <= speed < 37.5mph
0.0804
42
LHD45
409
37.5mph <= speed < 42.5mph
0.0853
42
LHD45
410
42.5mph <= speed < 47.5mph
0.0891
42
LHD45
411
47.5mph <= speed < 52.5mph
0.0919
38
-------
42
LHD45
412
52.5mph <= speed < 57.5mph
0.0938
42
LHD45
413
57.5mph <= speed < 62.5mph
0.0950
42
LHD45
414
62.5mph <= speed < 67.5mph
0.0956
42
LHD45
415
67.5mph <= speed < 72.5mph
0.0955
42
LHD45
416
72.5mph <= speed
0.0950
46
MHD67
400
idle
0.0000
46
MHD67
401
speed < 2.5mph
0.0110
46
MHD67
402
2.5mph <= speed < 7.5mph
0.0209
46
MHD67
403
7.5mph <= speed < 12.5mph
0.0388
46
MHD67
404
12.5mph <= speed < 17.5mph
0.0540
46
MHD67
405
17.5mph <= speed <22.5mph
0.0668
46
MHD67
406
22.5mph <= speed < 27.5mph
0.0775
46
MHD67
407
27.5mph <= speed < 32.5mph
0.0864
46
MHD67
408
32.5mph <= speed < 37.5mph
0.0935
46
MHD67
409
37.5mph <= speed < 42.5mph
0.0992
46
MHD67
410
42.5mph <= speed < 47.5mph
0.1036
46
MHD67
411
47.5mph <= speed < 52.5mph
0.1069
46
MHD67
412
52.5mph <= speed < 57.5mph
0.1091
46
MHD67
413
57.5mph <= speed < 62.5mph
0.1105
46
MHD67
414
62.5mph <= speed < 67.5mph
0.1111
46
MHD67
415
67.5mph <= speed < 72.5mph
0.1110
46
MHD67
416
72.5mph <= speed
0.1104
47
HHD8
400
idle
0.0000
47
HHD8
401
speed < 2.5mph
0.0237
47
HHD8
402
2.5mph <= speed < 7.5mph
0.0447
47
HHD8
403
7.5mph <= speed < 12.5mph
0.0831
47
HHD8
404
12.5mph <= speed < 17.5mph
0.1156
47
HHD8
405
17.5mph <= speed <22.5mph
0.1431
47
HHD8
406
22.5mph <= speed < 27.5mph
0.1661
47
HHD8
407
27.5mph <= speed < 32.5mph
0.1850
47
HHD8
408
32.5mph <= speed < 37.5mph
0.2003
47
HHD8
409
37.5mph <= speed < 42.5mph
0.2125
47
HHD8
410
42.5mph <= speed < 47.5mph
0.2219
47
HHD8
411
47.5mph <= speed < 52.5mph
0.2288
47
HHD8
412
52.5mph <= speed < 57.5mph
0.2336
47
HHD8
413
57.5mph <= speed < 62.5mph
0.2366
47
HHD8
414
62.5mph <= speed < 67.5mph
0.2379
47
HHD8
415
67.5mph <= speed < 72.5mph
0.2378
47
HHD8
416
72.5mph <= speed
0.2365
48
Urban Bus
400
idle
0.0000
48
Urban Bus
401
speed < 2.5mph
0.0127
39
-------
48
Urban Bus
402
2.5mph <= speed < 7.5mph
0.0240
48
Urban Bus
403
7.5mph <= speed < 12.5mph
0.0446
48
Urban Bus
404
12.5mph <= speed < 17.5mph
0.0621
48
Urban Bus
405
17.5mph <= speed <22.5mph
0.0769
48
Urban Bus
406
22.5mph <= speed < 27.5mph
0.0892
48
Urban Bus
407
27.5mph <= speed < 32.5mph
0.0994
48
Urban Bus
408
32.5mph <= speed < 37.5mph
0.1076
48
Urban Bus
409
37.5mph <= speed < 42.5mph
0.1142
48
Urban Bus
410
42.5mph <= speed < 47.5mph
0.1192
48
Urban Bus
411
47.5mph <= speed < 52.5mph
0.1230
48
Urban Bus
412
52.5mph <= speed < 57.5mph
0.1255
48
Urban Bus
413
57.5mph <= speed < 62.5mph
0.1271
48
Urban Bus
414
62.5mph <= speed < 67.5mph
0.1278
48
Urban Bus
415
67.5mph <= speed < 72.5mph
0.1278
48
Urban Bus
416
72.5mph <= speed
0.1271
49
Gliders
400
idle
0.0000
49
Gliders
401
speed < 2.5mph
0.0237
49
Gliders
402
2.5mph <= speed < 7.5mph
0.0447
49
Gliders
403
7.5mph <= speed < 12.5mph
0.0831
49
Gliders
404
12.5mph <= speed < 17.5mph
0.1156
49
Gliders
405
17.5mph <= speed <22.5mph
0.1431
49
Gliders
406
22.5mph <= speed < 27.5mph
0.1661
49
Gliders
407
27.5mph <= speed < 32.5mph
0.1850
49
Gliders
408
32.5mph <= speed < 37.5mph
0.2003
49
Gliders
409
37.5mph <= speed < 42.5mph
0.2125
49
Gliders
410
42.5mph <= speed < 47.5mph
0.2219
49
Gliders
411
47.5mph <= speed < 52.5mph
0.2288
49
Gliders
412
52.5mph <= speed < 57.5mph
0.2336
49
Gliders
413
57.5mph <= speed < 62.5mph
0.2366
49
Gliders
414
62.5mph <= speed < 67.5mph
0.2379
49
Gliders
415
67.5mph <= speed < 72.5mph
0.2378
49
Gliders
416
72.5mph <= speed
0.2365
40
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Appendix C Literature Review conducted for MOVES2009
Table C-l Brief review of literature on brake and tire wear
Luhana,L.;Sokhi,R.; Warner,L.;Mao,H;
Boulter,P;McCrae,I.S.;Wright,J and Osborn,D,"Non-
exhaust particulate measurements:results," Deliverable
8 of the European Commission DC TrEn, 5th
Framework PARTICULA TESproject, Contract No.
2000 -RD.l 1091, Version 2.0 , October 2004.
2004
Non-exhaust particle research was conducted in
the Hatfield road tunnel. Combined tire and brake
wear emissions for PMio from LDVs and HDVs in
the tunnel were found to be 6.9mg/vkm and
49.7mg/vkm respectively. These emission factors
from the Hatfield Tunnel Study appears to be at
the lower end of the range of values reported
elsewhere. The report also includes a literature
review which examines the state of the art in the
field. Tire wear and brake wear rates are listed
below.
Sanders, Paul G.;Xu, Ning ;Dalka, Tom M.; and
Maricq, M. Matti, "Airborne Brake Wear Debris: Size
Distributions, Composition, and a Comparison of
Dynamometer and Vehicle Tests",Environ. Sci.
Techno!, 37,4060-4069,2003
2003
A brake wear study was performed using seven
brake pad formulations that were in high volume
use in 1998. Included were low-metallic, semi-
metallic and non-asbestos organic (NAO) brakes.
The quantity of airborne PM generated by
automotive disk brakes was measured on a brake
dynamometer that simulated : urban driving (low
velocity, low g) and the Auto Motor und Sport
(AMS,high velocity, high g). Airborne fractions
from the low-metallic and semi-metallic linings
were 5 and 1.5 times higher than the NAO lining.
L.R.Warner; R.S. Sokhi;
L.Luhana ; P.G. Boulter; and I. McCrae,"Non-exhaust
particle Emisions from Road Transport", Proceedings
of the 11th International Symposium on Transport and
Air Pollution, Graz, 2002.
2002
The paper presents preliminary results of
gravimetric determination of tire and brake wear
for cars, and chemical analysis of ambient particle
samples for source identification using Inductively
Coupled Plasma (ICP) spectrometry. Results
suggest that the average loss rates of tire and brake
material are 97 and 9 mg/vkm respectively. The
ICP analysis shows a high relative abundance of
Ba, Sb, Zr and Sr for brake and Zn for tire
material. The chemical analysis also suggests that
for tire wear it is much more difficult to use metal
concentrations as tracers.
Abu-Allaban, M.;Gillies, J.A.;Gertler,A.W.;Clayton
,R.; and Proffitt,D., "Tailpipe, re-suspended road dust,
and brake wear emission factors from on-road
vehicles," Atmospheric Environment, 37(1),5283-
5293,2002.
2002
Intensive mass and chemical measurements were
performed at roadside locations to derive brake-
wear emission factors from in-use vehicles. PMio
emission rates for LDSI vehicles ranged from 0 to
80 mg/vkm and for HDVs from 0 to 610 mg/vkm.
The PM2.5 emissions ranged from 0 to 5mg/vkm
for LDSI vehicles and from 0 to 15mg/vkm for
HDVs. Emissions from brake wear were highest
near motorway exits.
Lukewille,A.;Bertok,I.;Amann, M.,
Cofala,J.;Gyarfas,F.;Heyes,C.;Karvosenoja,N.;Klimont
Z.; and Schopp, W., " A framework to estimate the
potential and costs for the control of fine particulate
emissions in Europe",IIASA Interim Report IR-01 -
&?J,Laxenburg, Austria,2001.
Westerlund ,K.G.," Metal emissions from Stockholm
traffic -wear of brake linings ", The Stockholm
2001
Westerlund estimated the amount of material lost
due to brake wear from passenger cars and heavy
goods vehicles. The PMio emission factors were
41
-------
Environment and Health Protection Administration,
100,64,Stockholm,Sweden, 2001.
determined to be 6.9 and 41.2mg/vkm for LDVs
and HDVs respectively.
Garg, B.D.; Cadle, S.H.; Mulawa,P.A.; Groblicki,
P.J.;Laroo,C.; and Parr,G.A., "Brake wear particulate
matter emissions", Environmental Science &
Technology, 34(21),4463,2000b.
2000
A brake wear study was performed using seven
brake pad formulations (non-asbestos) that were in
high volume use in 1998. Brakes were tested on a
brake dynamometer under four wear conditions.
The brake application was designed to simulate
real world events by braking from 50km/h to
Okm/h at a deceleration of 2.94 m/s2. The
estimated range of PM emission rates for small
vehicles to large pickup trucks are 2.9 -7.5
mg/vkm and 2.1 - 5.5 mg/vkm for PMio and PM2.5
respectively.
Annette Rauterberg-Wulff , "Determination of
emission factors for tire wear particles up to lOum by
tunnel measurements", Proceedings of 8th
International Symposium on Transport and Air
Pollution, Graz, 1999.
1999
PMio emission factors were determined for tire
and brake wear using receptor modeling in
combination with measurements conducted in the
Berlin-Tegel tunnel. Tire wear emission factors
for LDVs and HGVs in the tunnel was calculated
to be 6.1 mg/vkm and 31 mg/vkm. For brake wear
it was 1.0 and 24.5 mg/vkm respectively.
Carbotech, "PMio Emissionsfaktoren:Mechanischer
",Arbeitsunterlage, ,17,1999
1999
Cited in Lukewille et al. (2001). The PMio brake
wear emission factor for LDVs was determined to
be 1.8 mg/km and for HDVs it was 3.5 mg/vkm.
Cha,S.; Carter,P.; and Bradow, R.L., "Simulation of
automobile brake wear dynamics and estimation of
emissions,"SAE Transactions Paper,831036, Society
of Automotive Engineers, Warrendale,
Pennsylvania, 1983
1983
Particulate emissions from asbestos-based brakes
from automobiles were measured under conditions
simulating downtown city driving. The report
presents a systematic approach to simulating brake
applications and defining particulate emissions.
Based on the 1.6:1.1 wear ratio between disc and
drum brakes, the estimated airborne particulate
(PMio) emission rate was estimated to be
12.8mg/vmi or 7.9 mg/vkm.
42
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46
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