Brake and Tire Wear Emissions from Onroad Vehicles in MOVES5


Brake and Tire Wear Emissions
from Onroad Vehicles in MOVES5



£%	United States

Environmental Protect
Agency

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Brake and Tire Wear Emissions
from Onroad Vehicles in MOVES5

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

4>EPA

United States
Environmental Protection
Agency

EPA-420-R-24-012
November 2024

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Table of Contents

1	Introduction	4

2	Brake Wear	5

2.1	Literature Review (2006-2007)	6

2.2	Developing Rates for MOVES	9

2.2.1	Emission Rates for Light-Duty Vehicles for Model Years Prior to 2011	9

2.2.2	Emission Rates for Light-Duty Vehicles for Model Years 2011 and Later	17

2.2.3	Emission Rates for Heavy-Duty Vehicles for Model Years Prior to 2011	27

2.2.4	Emission Rates for Heavy-Duty Vehicles for Model Years 2011 and Later	33

2.2.5	Braking Activity	38

2.3	PM10/PM2.5 Brake Wear Ratio	44

2.4	Summary of MOVES Brake Wear Rates	44

3	Tire Wear	49

3.1	Introduction	49

3.2	Data and Methodology	52

3.3	Analysis	54

3.3.1 PM10/PM2.5 Tire Wear Ratio	58

3.4	Tire Wear Emissions in Project-Scale	59

Appendix A Deceleration from PERE	60

Appendix B Literature Review conducted for MOVES2009	62

4	References	65

1

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List of Acronyms	AMS

Auto Motor Sports magazine

CARB

California Air Resources Board

CBDC

California Brake Dynamometer Cycle

CMB

Chemical Mass Balance

CNG

Compressed Natural Gas

ELPI

Electrical Low Pressure Impactor

EMFAC

California Air Resources Board (CARB)'s on-road vehicle emissions model

EPA

U.S. Environmental Protection Agency

ERG

Eastern Research Group

ETW

Equivalent Test Weight

EV

Electric Vehicle

FTP

Federal Test Procedure

GHG

Greenhouse Gas

HD

Heavy-Duty

HHD

Heavy-Heavy-Duty

HDIUT

Heavy-Duty In-Use Testing

HLW

Heavily Loaded Weight

ICE

Internal Combustion Engine

LD

Light-Duty

LDT

Light-Duty Trucks

LDV

Light-Duty Vehicle

LHD

Light-Heavy-Duty

LM

Low-Metallic

MC

Motorcycle

MHD

Medium-Heavy-Duty

MOBILE

MOVES precursor

MOUDI

Micro-Orifice Uniform Deposition Impactor

MOVES

Motor Vehicle Emission Simulator Model

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MY	Model Year

NAO	Non-Asbestos Organic

PART5	MOVES precursor for PMio and PM2.5 emissions

PERE	Physical Emission Rate Estimator

PM	Particulate Matter

PM2.5	Particulate matter with mean aerodynamic diameter less than 2.5 pim

PM 10	Particulate matter with mean aerodynamic diameter less than 10 |j.m

RWD	Rear-wheel drive

SIP	State Implementation Plan

STP	Scaled Tractive Power

UDP	Urban Driving Program

VMT	Vehicle Miles Traveled

VSP	Vehicle Specific Power

3

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1 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 PMio emissions from brake and tire wear from onroad vehicles as
documented in this report. 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 in AP-42.3

This report was first 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 remained essentially the same as MOVES2014 and earlier
versions. However, there were two general updates 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 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
2.2.3.

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2) M0VES3 also introduced modeling of "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 2.2.5.3.

No updates were made for MOVES4, but in MOVES5, we have updated the brake wear emission rates for
both light and heavy-duty vehicles for model years 2011 and later. The new rates are developed using
measurements from brake dynamometer emissions testing of brake systems representative of modern
vehicles. The pre-2011 base rates remain unchanged, as they represent older generations of braking
technology.

2 Brake Wear

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 nm, (PMio). Some studies look at both wear and airborne PM, others look at one or the other. In
brakes, the composition of the brake lining 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.

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.

In MOVES, brake wear rates are stored in the EmissionRate table. As such, we assume that brake wear
emissions do not change with vehicle age. In the EmissionRate table, brake wear is indicated by
polProcessID = 11609 which refers to the Pollutant ID 116 (Primary PM2.5 - Brakewear Particulate) and
the process ID 9 (Brakewear). In the EmissionRate table, the meanBaseRate specifies the average mass-
rate of emissions that are released per unit time in each operating mode (as explained in Section 2.2.5).

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For brake wear, the meanBaseRatelM value is the same as meanBaseRate since l/M programs do not
include brake wear. In MOVES, PMio emissions are derived from PM2.5 using the PM10PM25ratio value
stored in the PMlOEmissionRatio table.

2.1 Literature Review (2006-2007)

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 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 B. 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 section
introduction 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 PMio emissions for
light-duty vehicles of 3.4 and 4.6 mg/mile, respectively for small vehicles, and PM2.5 and PMio 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.

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• 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 2-1 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 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.

7

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Table 2-1 Non-Exhaust PM Emissions (per vehicle) from mobile sources literature values of emission
factors from brake lining wear (largely cited in Luhana et al. (2004)'s literature review)

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 its own
includes all light-duty vehicles, including trucks though the studies are not all equivalent in
their definitions.

8

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2.2 Developing Rates for MOVES

Prior to M0VES5, brake wear rates for all MOVES regulatory classes did not vary by model year. MOVES
now estimates brake wear emission rates for two ranges of model years. For model years up to and
including 2010, the base brake wear rates remain the same as those used in MOVES4. The analysis for
these braking emission rates accounts for:

(1)	Composition of brake pads

(2)	Number (and type) of brakes

(3)	Front vs rear braking

(4)	Airborne fraction

(5)	Particle mass size distribution (PM2.5VS PMio)

(6)	Braking intensity

(7)	Vehicle class: Light-Duty vs Heavy-Duty

For model years 2011 and later, a separate set of rates has been developed for MOVES5 based on testing
of brake configurations representing a more modern fleet. Because the rates for the two model year
ranges were developed using different methodologies, some underlying assumptions used to derive
emission rates differ as well. In addition to the seven parameters listed above, the base emission rates
for model years 2011 and later account for differences by fuel type to account for electric vehicles (EVs)
that occupy an increasing share of the vehicle fleet and use regenerative braking.

Finally, because the new data sets do not cover motorcycle brakes, the base motorcycle brake wear
emission rates in MOVES remain unchanged for all model years.

2.2.1 Emission Rates for Light-Duty Vehicles for Model Years Prior to 2011

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 pim is ~ 10 percent (+/-5 percent)b

•	60 percent of brake wear is airborne PM (+/-10 percent).

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.

9

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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.

2.2.1.1 Base Rates by Braking Intensity

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. In Table 2-2 through Table
2-5, 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.

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Table 2-2 - 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

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

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 PMio were determined by multiplying the total PM reported in
Table 5 of the paper with the PMi0 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 PMio 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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Test

Table 2-3 - Wind Tunnel results

brake lining PMi0emiss. (mg/stop/brake)

Tunnel

filter

ELPI

MOUDI

low metallic

44

45

40

deceleration=



0.0018

km/s2

Initial Velocity V(0) =



0.0267

km/s

avg. brake time in sec =V(0)/dec



14.8

s

avg. emissions in mg/stop =



129.0

mg/stop

emision

rate for the wind tunnel test=

31.4 g/hr





Table 2-4-

AMS Test results

Test

brake lining

PMio 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

km/s2

Initial Velocity V(0) =

0.0278

km/s

avg. brake time in sec =V(0)/dec

3.5

s

avg. emissions in mg/stop for PM i0=

1116

mg/stop

emision rate for PMio 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

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Table 2-5 - Garg et al. (2000) Brake Dynamometer results

Test	brake lining	PMi0emiss.* 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

km/s2

Initial Velocity V(0) =

0.0139

km/s

avg. brake time in sec =V(0)/dec

4.7

s

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 as shown in Figure 2-1. 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)

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of a variety of weights and coastdown coefficients. The dotted curve is a typical coastdown 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.

Figure 2-2 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
of conventional and hybrid electric vehicles.12 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
(Caltrans) with both instrumented vehicles as well as chase car data.1314 15 The deceleration data was
analyzed for both studies.

Table 2-6 shows the distribution of braking activity across deceleration levels from the Kansas City and
Los Angeles studies. As expected, the majority of braking occurs during mild decelerations rather than
full, high-deceleration stops.

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Table 2-6 Distribution of braking activity in the LA and Kansas City studies for each deceleration bin

Decel

(mph/s)

urban

LA rural

AVG

37.1%

27.1%

54.5%

39.5%

26.3%

27.9%

26.3%

26.9%

17.9%

20.2%

12.8%

17.0%

10.2%

12.2%

4.6%

9.0%

5.6%

8.2%

1.3%

5.0%

1.6%

2.4%

0.30%

1.4%

0.64%

0.98%

0.07%

0.6%

0.28%

0.41%

0.02%

0.2%

0.17%

0.26%

0.02%

0.2%

0.10%

0.13%

0.01%

0.08%

0.05%

0.09%

0.01%

0.05%

0.03%

0.05%

0.03%

0.01%

sum

100.0%

99.9%

100.0%

The emission rate curve from Figure 2-1 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 PM25 emission rate of 0.557 g/hr for a braking event.

2.2.1.3 MOVES Rates

The MOVES pre-2011 light-duty brake wear PM2.5 base emission rates (operating mode 0) in g/hr are
shown in Table 2-7. The rates are calculated per the methodology described above. They are the same
for all pre-2011 model years and are independent of fuel type. Brake wear rates for operating modes 11,
21, and 33 are ratioed from these base rates using the braking fractions derived in Section 2.2.5.1. A
summary of effective g/mile emission rates is given in Section 2.4

Table 2-7 Pre-2011 light-duty brake wear PM2.5 base emission rates (operating mode 0) in g/hr

Regulatory class

PM2.5 (g.hr)

Passenger Cars (20)

0.557

Passenger Trucks (30)

0.627

The average passenger car PM10 brake wear emission rates of 24.84 mg/mi (output from MOVES5) is
compared to the previous studies (in the literature) in Table 2-1. Carbotech (1999), Sanders et al. (2003),
Garg et al. (2000), are all laboratory measurements and have significantly lower 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 measurements or tunnel measurements. These studies generally

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have higher emissions than laboratory measurements. The MOVES rates are also considerably higher
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.

2.2.2 Emission Rates for Light-Duty Vehicles for Model Years 2011 and
Later

The data from this analysis comes from a light-duty brake dynamometer test campaign jointly led by EPA
and the California Air Resources Board (CARB), along with a companion data set from a study led by the
California Department of Transportation (Caltrans).16,17 The studies covered a range of common vehicle
and brake configurations, including different brake pad materials, and employed a variety of instruments
to characterize brake wear PM, including measurements of particle mass, number, and size distribution.

Because brake wear emissions in MOVES are modeled in terms of PM2.5 and PMio mass, this analysis
uses the mass measurements captured by a TSI 100S4 MOUDI, with 10, 2.5 and 1 pim cut points.

2.2.2.1 Brake Dynamometer Drive Cycle

Both studies used a new test cycle, the California Brake Dynamometer Cycle (CBDC), which was
developed as part of the EPA-CARB study to represent average real-world braking activity for light-duty
vehicles.16 The CBDC is based on micro-trip braking events sampled from the 2010-2012 California
Household Travel Survey and contains segments with a range of braking intensities that together are
intended to be representative of real world driving.18 The test cycle development also accounted for
brake heating and cooling during braking operation to ensure that the cycle's brake temperature profiles
would also be representative of real-world driving. However, the addition of these cooling segments
means that the total distance of the CBDC exceeds the summed distance of the representative micro-
trips it is composed of.

MOVES has only one primary braking operating mode (opModelD 0) and therefore, cannot differentiate
braking by intensity. The opMode 0 rate in MOVES represents a fleetwide average emission rate for
braking across all conditions. Therefore, brake wear emission rates derived from the entire CBDC are
suitable for use in MOVES because they provide an approximation for average braking behavior. Because
of the greater total distance in the CBDC relative to its component micro-trips, distance-based emission
rates (g/mile) use the summed distance of the selected micro-trips. Time-based emission rates (g/hr),
like those used in MOVES, use the total time during the CBDC where the brakes are applied as opposed
to the full drive cycle duration, which includes periods of acceleration and steady-state speed operation.
For this analysis, the break wear rates for each test were calculated as the total measured PM emissions
for the test cycle divided by the total braking time of the CBDC.

-------
2.2.2.2

Brake Dynamometer and PM Measurement

The PM sampling was conducted on a brake dynamometer test bench enclosed within a constant
volume sampling system. High efficiency particulate air (HEPA) filtered air was directed through the front
of the brake enclosure, passed through and around the braking system, and ducted out towards a set of
isokinetic sampling probes. Figure 2-3 shows a schematic of the sampling system.17 The four sampling
probes were situated at a 90-degree elbow in the ducting system at least eight diameters from the brake
enclosure to ensure isokinetic sampling from a laminar flow. Figure 2-4 shows a velocity contour map
from a computational fluid dynamics (CFD) simulation of the sampling system from the air inlet to the
sampling probes.16 The sampling probes fed a variety of instruments used to characterize PM emissions.
Because brake wear emissions in MOVES are modeled in terms of PM2 5 and PM!0 mass, this analysis
uses the mass measurements captured by a TSI 100S4 MOUDI, with 10, 2.5 and 1 [im cut points. Because
the sampling system was fully enclosed and samples were collected continuously through the CBDC, any
condensed particle emissions during the test cycle were measured, including fugitive emissions from
heating and cooling of the braking system, and particulates released between braking events.

HEPA 13 filters

M6330 LINK system

Incoming air

airspeed sensor

air temperature sensor

Elect ropolished
brake test enclosure

air temp and

humidity

sensor

lsokinetic& electropolished

CVS tunnel
pirn

Climate control unit
20 °C & 50% RH

TSI Instrumentcluster6 nm- 18

Figure 2-3 Schematic of brake wear PM testing system

-------
A-,rf\o\N direction

Velocity [m/s]
0 5 10 15 20

Figure 2-4 Velocity contour of cooling air resulting from CFD simulation

New brake components undergo a "bedding in" process when they are first exposed to braking forces
and temperatures. During this process, the surfaces of the friction components are altered and
eventually reach an equilibrium state. In this transition period, particulate emissions may change and not
be representative of normal braking emissions. For this reason, each brake configuration was run
through a burnishing cycle prior to sampling on the CBDC.16

2.2.2.3 Test Configurations and Vehicle-Level Results

The studies included testing of both front and rear brake configurations for several popular light-duty
vehicle models. The vehicles were selected to be a representative sample of typical vehicles in the
national fleet, and to include a representative range of brake technologies. They also included a variety
of brake pads including both original equipment supplier (OES) and aftermarket brake pads. In the study,
all OES pad materials were non-asbestos organic (NAO). The aftermarket pads included both NAO and
low-metallic (LM) pad compositions. The joint EPA and CARB study included six vehicles, including one
hybrid. Three of the vehicles in the study were tested for both an equivalent test weight (ETW) and a
heavily loaded weight (HLW). For this analysis, we have also included testing results from one electric
vehicle (EV), the Tesla Model 3, that comes from the Caltrans study. Two replicate tests were conducted
for each configuration. The full scope of the combined data sets used in this analysis is summarized in
Table 2-8 below.

-------
Table 2-8 Light-duty brake dyno test configurations

Vehicle

Model
Year

Front/Rear
Type

Regenerative
Braking

Pad Materials

Wheel Load

Toyota Camry

2011

disk/disk

OES-NAO, Aftermarket-NAO,
Aftermarket-LM

ETW

Honda Civic

2013

disk/drum

OES-NAO, After-NAO

ETW

Ford F-150

2015

disk/disk

OES-NAO, Aftermarket-NAO,
Aftermarket-LM

ETW, HLW

Toyota Sienna

2013

disk/disk

OES-NAO, Aftermarket-NAO

ETW, HLW

Toyota Prius

2016

disk/disk

yes

OES-NAO, Aftermarket-NAO

ETW

Nissan Rogue

2016

disk/disk

OES-NAO, Aftermarket-NAO

ETW, HLW

Tesla Model 3

2019

disk/disk

yes

OES-NAO

ETW

2.2.2.4 Brake Wear Rates by Vehicle Mass and Technology

The raw measured brake wear rates from the dynamometer testing were combined for each vehicle
configuration to generate per-vehicle brake wear emission rates in units used by MOVES (grams per
braking hour). The per-vehicle weights were determined by adding the average of the measured rates for
the front wheel to the average of the measured weights for the rear wheel and multiplying the result by
two. The resulting rates are summarized in Figure 2-5. Generally, for each vehicle, all NAO pads produced
similar emissions. The low-metallic pads produced the highest emission rates. Because the OES and
aftermarket NAO pads produce similar emissions, and because the testing report did not include relative
population fractions for OES NAO vs aftermarket NAO pads, we have combined the results for all NAO
pads for the rest of this analysis.

In addition to using a variety of brake pad materials, the current light-duty vehicles fleet includes a mix of
onboard deceleration technologies. Most notably, some electric and hybrid-electric vehicles use
regenerative braking to decelerate, which significantly reduces friction brake usage. Particulate emissions
from brakes are generated by the force of friction used to dissipate vehicle energy at the brake surface.
However, when a vehicle is using regenerative brakes, some of the kinetic energy from slowing the
vehicle is used to recharge the battery instead of being dissipated entirely by the friction applied by the
brakes. Thus, there is less material wear via friction and less particulate emissions.19

As seen in Figure 2-5, the two vehicles equipped with regenerative braking systems (the 2016 Toyota
Prius and the 2019 Tesla Model 3) have much lower brake wear emission rates than comparable vehicles
without regenerative braking systems. This is consistent with other studies on the topic. For example, a
study on non-exhaust emissions from electric vehicles found that regenerative braking reduced brake
wear emissions by 68%.20

-------
c 4-

^gaESm

Lffl

Pad Type

AfterMkt-LM
AfterMkt-NAO
OES-NAO

•V

/
£>

-------
2.0-

1.5-

1.0-

0.5-

o.o-

NAO

r2=c

).99

r2=c

).93

o ,
my

_y
o

o
o

^ ^ -

fcr"*

Vehicle

2011 Toyota Camry LE
2013 Honda Civic LX
2013 Toyota Sienna LE

2015 Ford F-150

2016 Nissan Rogue
O 2016 Toyota Prius
A 2019 Tesla Model 3

O
O

1000

2000 3000 0 1000

Vehicle mass (kg)

2000

3000

Figure 2-6 Vehicle-level brake wear PM2.5 emission rates by vehicle mass and brake pad material

FT = 0.98

NAO

FT = 0.91

Vehicle

O 2011 Toyota Camry LE

O 2013 Honda Civic LX

O 2013 Toyota Sienna LE

O 2015 Ford F-150

O 2016 Nissan Rogue

O 2016 Toyota Prius

A 2019 Tesla Model 3

1000

2000 3000 0 1000

Vehicle mass (kg)

2000

3000

Figure 2-7 Vehicle-level brake wear PMi0 emission rates by vehicle mass and brake pad material

The EPA report includes estimated proportions of NAO and LM pads in the national fleet for each of the
tested vehicle models. Because the test vehicles were selected to represent common vehicles in the
national fleet, and because the pad material fractions are similar across the range of vehicle models, we
used the average of the pad fractions from these vehicles to represent the national fleet in MOVES.

Table 2-9 summarizes the estimated pad fractions reported for each vehicle model.16 The table also
includes the average of these values. Assuming that the test vehicles are representative, of the national
fleet, 82 percent of the fleet is equipped with NAO pads. This is a higher rate of NAO usage than used for

-------
the pre-2011 rates, which, lacking additional data, assumed that a third of pads were organic, and two-
thirds were either low-metallic or semi-metallic. Population fractions of pad materials were not reported
for the Tesla which is equipped with NAO brake pads from the factory. Lacking additional data on EV pad
fractions, in MOVES, we have assumed that 100 percent of EV pads are NAO for the purposes of defining
base brake wear emission rates.

Table 2-9 Estimated fleet-level pad material fractions for each vehicle model

Vehicle

NAO Fraction

LM Fraction

2013 Honda Civic LX

0.77

0.23

2016 Toyota Prius

0.82

0.18

2016 Nissan Rogue

0.88

0.12

2011 Toyota Camry LE

0.82

0.18

2013 Toyota Sienna LE

0.77

0.23

2015 Ford F-150

0.87

0.13

Average

0.82

0.18

The brake wear PM rates discussed above represent rates measured on a brake dynamometer under
optimized sampling conditions. The measurements did not account for particle deposition on the surface
of the wheel, the undercarriage of the vehicle, or the roadway. Sanders et al estimated that deposition
onto these surfaces reduces the emitted brake wear PM by about a third.10 To account for this, we
multiply the slopes of the fit lines illustrated in Figure 2-6 and Figure 2-7 by 0.66 to get an estimated
brake wear airborne emission rate as a function of vehicle mass: E=0.66am, where a is the fitted slope,
and m is the vehicle mass.

Figure 2-8 shows the final weighted PM2.5 emission to mass relationship alongside the NAO and LM pad
regressions. For reference, the pre-2011 brake wear rates for light-duty cars (source type 21) and light-
duty trucks (source types 31, and 32) are plotted against their source type masses from the MOVES
sourceUseTypePhysics table. Given the pre-2011 assumption that there was an equal mix of brake pad
materials between low-metallic semi-metallic, and NAO pads, the older rates agree very well with these
more recent testing results.

Table 2-10 lists the inputs used to generate the lines plotted in Figure 2-8, as well as the equivalent
values for EV brake wear rates based on the results of the Tesla.

-------
1.00-

Source type

~ 21

~ 31

~ 32

Pad material

/// Average pad

LM
/' NAO

1000 2000

Vehicle mass (kg)

Figure 2-8 Airborne PM2.5 g/h regressions for MY 2011 and later plotted against pre-2011 MOVES brake

wear rates for source types 21, 31, and 32

Table 2-10 Airborne emission rate regression slopes by pad material and vehicle engine type corrected

for airborne fraction

Engine

NAO

NAO Slope

LM Slope

Average Slope

Type

Size

Fraction

(g/hr kg)

ICE

PM2.5

0.82

0.18

1.74xl0"4

3.78xl0"5

2.48xl0"4

ICE

PM10

0.82

0.18

4.20xl0"4

9.12xl0"5

6.47xl0"4

PM2.5

1.00

0.00

5.96x10 s

PM10

1.00

0.00

8.50x10 s

-------
2.2.2.5 Vehicle Masses by MOVES Fuel Type

With a relationship that defines an estimated emission rate based on a vehicle's weight, the final step to
developing MOVES base rates is to identify the appropriate vehicle masses to use for the rate calculation.
MOVES uses the source mass field from the sourceUseTypePhysics table to calculate VSP and operating
modes. However, this mass is not split out by fuel type. This is a specific concern in the case of brake
wear from electric vehicles because they tend to be heavier than their conventional ICE counterparts.

Therefore, instead of relying on the source mass in MOVES sourceUseTypePhysics table, we consulted
the 2021 EPA Automotive Trends Report, to assess the state of light-duty vehicle masses.22 Figure 2-9
shows trends in vehicle mass for model years 2011-2021 by fuel type. The fuel types reported by the
trends report are grouped to match the MOVES fuel types as follows: gasoline, hybrid, and PHEV vehicles
are assigned to the MOVES gasoline fuel type (fuel type 1); diesel is assigned to the MOVES diesel fuel
type (fuel type 2), and electric and fuel cell vehicles are assigned to the MOVES electricity fuel type (fuel
type 9). We assume that vehicles that use E85 (fuel type 5) weigh the same as regular gasoline vehicles.

fuelType

- Diesel
EV
FCV
Gas
Hybrid
PHEV

^ ntf-0 otf"0 ^ ^ ^

rfi, rjO rjO rfi rfi rfi rfi rfi ^ rfi rfi rfi rfi rfi'

Model Year

-------
Figure 2-9 Average vehicle mass vs. model year by fuel type ID and regulatory class. The columns are
grouped by MOVES fuel type, and the rows are MOVES regulatory classes. The dashed lines show

averaged values for 2011-2021.

It is worth noting that not only do EVs have a larger vehicle mass than gasoline vehicles, but that diesel
light-duty trucks also tend to be heavier than their gasoline counterparts.® Table 2-11 shows the average
vehicle weight values by fuel type and regulatory class.

Table 2-11 Production-weighted average vehicle weight by MOVES regulatory class and fuel type for

model years 2011-2021

Regulatory class

regClassID

fuelTypelD

Vehicle Weight (kg)

Car

1,5

1,615

Car

1,645

Car

1,930

Truck

1,5

2,132

Truck

2,538

Truck

2,634

Combining the vehicle masses from Table 2-11 with the PM vehicle mass relationship summarized in
Table 2-10 (which accounts for regenerative braking for electric vehicles) yields a final set of brake wear
PM base emission rates for MOVES. Figure 2-10 shows the PM2.5 rates by model year with separate rates
by fuel type after model year 2011. The final set of 2011 and later PM2.5 rates are summarized in Table
2-12 along with the accompanying PM10 emission ratios derived at the end of Section 2.2.2.4.

e The difference likely suggests that the larger light-duty trucks are more frequently equipped with diesel
engines, rather than that diesel trucks are heavier than their gasoline counterparts of similar size.

-------
LD-Trucks

Fuel Type

— Gasoline

— Diesel
Electric

Model Year

Figure 2-10 MOVES light-duty PM2.5 base rates by model year and fuel type

Table 2-12 MOVES light-duty PM2.5 base rates, and PM10 emission ratio by regulatory class and fuel

type for MY 2011 and later

Regulatory Class

RegClassID

FuelTypelD

PM2.5 Rate
(g/h)

PM10 Emission
Ratio

Car

1,5

0.400

2.61

Car

0.408

2.61

Car

0.115

1.42

Truck

1,5

0.529

2.61

Truck

0.629

2.61

Truck

0.157

1.42

2.2.3 Emission Rates for Heavy-Duty Vehicles for Model Years Prior to
2011

As noted in the Introduction, the pre-2011 brake wear emission factors in MOVES are unchanged from
MOVES2014. 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. In order to estimate brake wear emission
factors for pre-2011 heavy-duty vehicles an engineering analysis was combined with results from a top-
down study performed by Mahmoud Abu-Allaban et al. (2003).23 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 wear, road dust, and brake wear 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 available
at the time of this analysis. The results are consistent with the heavy-duty rates measured from Luhana
et al. (2004) as well as Westurland (2001), but it was the only paper to measure PM2.5- The paper's light-
duty rates are also aligned with the rates determined above.

In the Abu-Allaban study, PM2.5 brake wear emission rates for heavy duty vehicles ranged from 0 to 15
mg/km (0 to 24 mg/mi). For our 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 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. Because Abu-Allaban
et al. did not report HHD brake wear at all sites, we also computed the average brake wear just for the
sites with both HD and LD measurements.

-------
Table 2-13 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

Average over all
matching sites

Heavy-Duty

124±71

2 ± 2

Light-Duty

15.50

0.67

Range (min to
max) of
measurements on
all roads

Heavy-Duty

0 to 610

Oto 15

Light-Duty

0 to 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 sites with both HD and LD measurements, we determined that the average ratios of HD to
LD brake emissions are 8 and 3 for PM10 and PM2.5 respectively/

f Though it is not shown in the table here, according to Abu-Allaban, 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.

-------
Table 2-14 Ratio of Heavy-Duty to Light-Duty PM from the literature.

Study

PM2.s

PM10

Luhana et al. (2004)

7.7

Abu-Allaban et al. (2003)

8.0

Westurland (2001)

6.0

Rauterburg-Wulff (1999)

24.5

Carbotech (1999)

0.7

For the purposes of MOVES, a simple model requiring a single ratio of HD to LD brake emissions and
another ratio of PMi0 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 HD to LD ratio chosen for development of
MOVES emission rates is 7.5, close to the ratio as measured by Abu-Allaban et al. (2003), and consistent
with the range of studies. While this HD to LD ratio was derived for PM10, we apply it for PM2.5- Equation
2-1 is used to calculate the PM2.5 brake emission rate for the deceleration/braking mode (OpModelD 0)
from the LDV emission rate.

/ g \ g

HHD Emission rate —) = 7.5 x LDV Emission rate (—) Equation 2-1

\farj

The resulting HHD emission rates for opMode 0 are shown in Table 2-15.

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.

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 define the regulatory class. The
estimated vehicle weight was derived from the source mass value stored in the MOVES2014

-------
sourceUseTypePhysics table by source type.g 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 2-15.

Table 2-15 Vehicle Weights and PM2.5 Brake Wear Emission Rates by Regulatory Class for opModelD 0

(Deceleration/Braking Mode)

Regulatory
Class

regClassID

MOVES2014-
estimated
vehicle weight
(lbs)

PM2.5
Emission
Rates (g/hr)

628

0.355

LDV

3,260

0.558

LDT

4,197

0.631

LHD2b3

4,303

0.639

LHD45

18,849

1.76

MHD

28,527

2.51

HHD

50,285

4.19

Urban Bus

36,500

3.12

Gliders

50,285

4.19

Figure 2-11 and Table 2-15 shows the linear interpolation between the light-duty and heavy heavy-duty
brake wear emission rates by the MOVES2014-estimated regulatory class weight.

3 In MOVES3 and later, the heavy-duty vehicle weight is defined by both source use type and regulatory
class24

-------
cc 3.0
"i 2.5

£ 2.0

ra 1.5

in 1.0
oi

| 0.5

0.0

0 10000 20000 30000 40000 50000 60000

Regulatory Class Weight

Figure 2-11 Interpolated Brake Wear PM2.5 Emission Rates by MOVES2014-estimated Regulatory Class
Weight. Passenger Cars and Combination Heavy duty Trucks define the slope.

In MOVES3, the vehicle weights for heavy-duty vehicles were updated with more current data sources.
Additionally, the heavy-duty vehicle weights in MOVES vary according to regulatory class and source type
as documented in the Population and Activity Report.24 For MHD, HHD, and Urban Bus, the weights are
generally within 10% of the weights used to derive the brake emission rates. For LHD2b3 and LHD45, the
differences in weights are more significant. The average LHD2b3 weights for light-trucks and single-unit
trucks in MOVES3 and later versions are estimated to be between 7,500 lbs to 7,879 lbs, compared to
4,303 lbs in MOVES2014b. The average LHD45 weight for single-unit trucks in MOVES3 and later versions
is 12,716 lbs compared to 18,849 in MOVES2014b. One reason for the difference in weights for LHD2b3
is because MOVES2014b modeled Class 2b and 3 trucks in two regulatory classes (LHD <= 10k and LHD
<=14K) and MOVES now models all Class 2b and 3 trucks in one regulatory class (LHD2b3). We applied
the brake and tire emission rates from the MOVES2014b LHD <= 10k regulatory class to represent the
emission rates of the LHD2b3 regulatory class in MOVES. This weight discrepancy is no longer relevant
for the MY 2011 and later trucks (see Section 2.2.4) but suggests MOVES may be underestimating brake
wear from 2010 and earlier LHD2b3 trucks and overestimating brake wear from 2010 and earlier LHD45
trucks.

In addition to the updated rates for LHD2b3, we added the glider regulatory class in MOVES3. In MOVES,
gliders are defined as heavy heavy-duty (HHD) trucks with an old powertrain combined with a new
chassis and cab assembly, as such they have the same vehicle weight and brake emissions as HHD
vehicles.

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2.2.4 Emission Rates for Heavy-Duty Vehicles for Model Years 2011 and
Later

In M0VES5, the emission rates for heavy-duty vehicles were updated using the data from a heavy-duty
brake test program conducted by CARB and Caltrans17. The testing was performed using a LINK heavy-
duty brake dynamometer for various configurations to consider the impacts of different vehicle
categories and other parameters such as axle types, brake types, vehicle loading conditions and
vocational cycles. The raw test data was further analyzed and processed to develop full vehicle level
MOVES emission rates using the process described below.

2.2.4.1 Individual Wheel Test Configurations

The heavy-duty dynamometer test bench in the CARB/Caltrans test program was largely the same as the
one used for the light-duty testing as described in Section 2.2.2.2. For the heavy-duty testing, two Teflon
filters were used to measure PM2.5 and PM10.

A set of individual wheel tests were performed for various configurations as summarized in Table 2-16
for the heavy-duty vehicle categories considered. As part of the HD test program, some tests were done
with original friction material and then repeated with aftermarket fraction material. No statistically
meaningful emission differences were observed since the material formulation do not vary significantly
between original and aftermarket.h For MOVES modeling, we used the emission test data with original
friction material.

h According to the HD testing report, the majority of commercial vehicle brake components in the U.S.
are supplied by only a few companies, who provide both original and aftermarket parts.

-------
Table 2-16 Individual wheel test configurations in CARB/Caltrans HD test program

Vehicle Category

Axle Type

Brake Type

Vehicle Weight (lbs)

Vocational Cycle

Heavy-heavy duty
(Class 8)

• Steer1

• Drive

• Trailer*

• Drum

• Air disc

• Loaded: 81,011

• Unloaded: 28,759

• Drayage
(Northern
California)

• Cement

• Long-haul out-
of-state (OOS)

Medium-heavy
duty

(Delivery truck)

• Steer

• Drive

• Hydraulic disc

• 27,785

• Beverage

• Local moving

Urban bus

• Steer

• Drive

• Air disc

• 36,299

• Urban bus

Refuse

• Steer

• Drive

• Air disc

• 44,701

• Refuse

In Table 2-17, the speed traces of selected vocational cycles are shown for comparison.

1 Loaded condition tested only.
J Drum brake type tested only.
34

-------
Table 2-17 Vocational cycle speed traces

Vehicle
Category

Vocational cycle speed traces

Heavy-heavy
duty (ClassS)

— Drayage —Cement —Long-haul OOS

—, - ,

rv .

r\ fa A

EE \

O 100 200 300 400 500 600 700 800 900 1,000 1,100 1,200 1,300 1,400 1,500 1,600

Cycle Time [s]

Medium-
heavy duty

(Delivery
truck)

Urban Bus

—Beverage —Local Moving —Urban Bus

0 100 200 300 400 500 600 700 800 900 1,000 1,100 1,200 1,300 1,400 1,500 1,600 1,700

Cycle Time [s]

Each individual wheel test provided filtered PM2.5 and PM10 gravimetric mass measurement data, cycle
distance, braking event history and other information. In MOVES, emission rates are expressed in the
unit of "grams per hour" by regulatory class. For brake wear base rates, the PM2.5 "filter mass" (reported
from the testing) is divided by the "total cumulative cycle braking time" to estimate PM2.5 base rate for
each test configuration.

2.2.4.2 Full Vehicle Rate Development Process

To develop full vehicle level emission rates starting from the individual wheel test data, additional
processing steps are necessary to apply fleet-average weighting factors for each vehicle category that
include:

• the number of wheels per axle

• the mix of loaded and unloaded operation (for HHD only)

• the mix of drum and disc brake types (for HHD only)

• the mix of vocational cycles (for HHD and MHD)

We used the estimates in Table 2-18 from the CARB/Caltrans HD brake wear test report where the CA-
Vehicle inventory and Use Survey (VIUS) database was used to estimate the wheels per axle and
load/unloaded weighting. The drum/disc type weighting was based on a market survey; vocational cycle
weighting was estimated using EMFAC speed distribution data.

-------
Table 2-18 Estimates of the number of wheels per axle and fleet-average weighting factors

Test vehicle
category

Individual
wheel test
configurations

Wheels per axle

Vehicle load
weighting

Brake type
weighting

Vocational cycle
weighting

Heavy-heavy
duty (Class 8)

• Drum/Steer

• Drum/Drive

• Drum/Trailer

• Disc/Steer

• Disc/Drive

• Steer axle: 2

• Drive axle: 4

• Trailer: 4.16

• Loaded:
73%

• Unloaded:
27%

• Drum:
85%

• Disc:
15%

• Drayage:
18%

• Cement:
24%

• Long-haul
OOS: 58%

Medium-
heavy duty
(Delivery
truck)

• Hydraulic
disc/Steer

• Hydraulic
disc/Drive

• Steer axle: 2

• Drive axle:
2.21

N/A

• Beverage:
27%

• Local
moving: 73%

Urban bus

• Air disc/
Steer

• Air disc/
Drive

• Steer axle: 2

• Drive axle: 2

N/A

2.2.4.3 MOVES Heavy-Duty Brake Wear Base Rates

The full vehicle emission rates by test vehicle category are transformed into MOVES emission rates by
regulatory class. Table 2-19 shows the mapping between test vehicle categories and MOVES regulatory
classes.

Table 2-19 Mapping between test vehicle categories and MOVES regulatory classes

MOVES regulatory
class (regClassID)

Classification

Test data source for mapping

HHD (47), Gliders (49)

Class 8 trucks
(GVWR>33,000 lbs)

Heavy-heavy duty (Class 8) test data

MHD (46)

Class 6 & 7 trucks

(19,500
-------
The CARB/Caltrans HD brake test program did not include the LHD2b3 (41) and LHD45 (42) regulatory
class vehicles. To fill the data gaps, we developed the MOVES rates for those regulatory classes by
adjusting the diesel light-duty truck rate shown in Table 2-12 by the class average weights in Table 2-20
for LHD2b3 and LHD45, respectively.

For MOVES, the emission rates were adjusted based on the weight ratios between the test vehicle
weights (listed inTable 2-16) and the corresponding MOVES regulatory class average weights (Table
2-20).

Table 2-20 MOVES class average weights by regulatory class

MOVES HD regulatory
class (regClassID)

Class average weights
(Tons)

Class average weights (lbs)

LHD2b3 (41)

3.456

7,619

LHD45 (42)

5.870

12,942

MHD (46)

13.374

29,484

HHD (47)

24.032

52,982

Urban Bus (48)

15.603

34,398

Gliders (49)

24.664

54,374

MOVES5 has the added capability to model electric vehicles (EVs) as part of heavy-vehicle fleet
population25 and it is desirable to consider the effect of regenerative braking on brake wear emissions.
The CARB/Caltrans HD brake test program, however, did not consider any heavy-duty electric vehicles
and there is little data available in the literature. As an approximation, we used the ratio of the light-duty
ICE vehicle rate vs. the EV (based on Tesla) rate in Table 2-10 to calculate the HD EV rates for each
regulatory class by scaling down the HD ICE PM2.s emission rates proportionally. This approach assumes
implicitly that the electric heavy-duty fleet has the same vehicle characteristics (weight, wheel
configuration, number of axles, etc.) as its non-EV counterpart. This approach differs from the approach
for light-duty because we lacked data on the weight of HD EVs and assume that heavy-duty truck weights
depend less on powertrain weight and more on payload and GVWR.

The updated PM2.s base rates for MY2011+ heavy-duty vehicles are summarized in Table 2-21. The ICE
rates are used for gasoline, diesel and CNG-powered vehicles.

-------
Table 2-21 Updated PM2.5 base rates for MY2011+ heavy-duty vehicles

MOVES HD regulatory
class (regClassID)

PM2.5 base rates [g/h] for
ICE vehicles

PM2.5 base rates [g/h] for
electric vehicles

LHD2b3 (41)

0.86

0.21

LHD45 (42)

1.46

0.35

MHD (46)

3.60

0.87

HHD (47)

16.69

4.01

Urban Bus (48)

1.71

0.41

Gliders (49)

16.69

N/A

2.2.5 Braking Activity

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)k. This parameter represents
the tractive power exerted by a vehicle to move itself and its cargo or passengers. The VSP equation used
in MOVES is given as:

Av + Bv2 + Cv3 + mv(a + gsin(0))
m

Where v is the vehicle's speed, a is the vehicle's acceleration m is the vehicle's mass, and i? is the road
grade. The coefficients A, B, and C are known as the road load coefficients and represent rolling
resistance, rotational resistance, and aerodynamic drag of the vehicle respectively. When VSP equals 0 it
indicates that the vehicle does not not need to apply any power to achieve its current speed and
acelleration. When VSP is positive, it means that power is required to achieve the speed and
acelleration. Finally, when VSP is negative, it means that the vehicle needs to provide braking power to
achieve the associated speed and acceleration.

The MOVES operating modes for running exhaust and brake wear emissions are listed in Table 2-22.

More information on these operating modes is available in the MOVES light-duty and heavy-duty exhaust
emission reports.26,5 The MOVES vehicle specific power (VSP) bins are coarsely defined for braking.1
There is a large "braking" bin (operating mode 0) where deceleration is large or sustained. The "idle" bin
covers speeds from -1 to 1 mph and includes some braking in the transition (deceleration) from non-zero
speed to zero speed. In addition, there are three "coasting" bins (operating modes 11, 21, 33) where VSP
can be less than zero and, as such, also contain braking events. Therefore, the emission rates assigned to

k For heavy-duty vehicles, the MOVES operating modes are the same, but use Scaled Tractive Power (STP) instead of VSP.

-------
these bins need to contain the appropriate average rates including the mix of driving and deceleration,
including decelerations that do not include braking. When deceleration is between -1 mph/s and -2
mph/s, the operating mode is assigned by the duration of the deceleration. If the vehicle has been
decelerating for the two consecutive seconds prior to the current second, it is assigned to be operating
Mode 0. Otherwise, it is assigned to one of the "coasting" bins.

Table 2-22 - MOVES Operating Mode Bins by VSP and speed

Operatin
g Mode

Operating Mode
Description

Vehicle-Specific
Power

(VSP, kW/Mg)

Vehicle Speed
(i/,mi/hr)

Vehicle
Acceleration
including grade
(at, mph/sec)

Deceleration/Brakin
g

at +g-sin(0t) < -2.0
OR

[ot +g-sin(dt) < -
1.0 AND

ot-1 +g-sin(dt l) < -
1.0 AND

at-2 +g-sin(0t-2) < -
1.0)

Idle

-1.0
-------
To estimate the amount of braking activity in modes 1, 11, 21, and 33, the brake emission rates in those
bins were multiplied by the proportion of activity with VSP < 0 in each bin. These braking fractions were
derived separately for light and heavy-duty vehicles and applied for all model years.

2.2.5.1 Braking Fractions for Light-Duty Vehicles

To estimate the amount of time light duty vehicles spend braking in each of the braking-associated
opModes, we analyzed drive traces from the 2010-2012 California Household Travel Survey.27 The
dataset contains data for 2,910 light-duty vehicles which were split into groups of passenger cars
(regClass 20), and passenger trucks (regClass 30) for analysis. The dataset contained 1.875x10s hours,
and 9.049xl04 hours of second-by-second driving activity, for cars and trucks, respectively. The drive
traces were processed to calculate VSP and MOVES opMode for each second of driving activity. The
dataset did not include the road load coefficients for the vehicles, so the MOVES defaults were used to
represent each regulatory class. Braking time was assigned to all time intervals where VSP was less than
zero. Figure 2-12 and Table 2-23 show the results of the drive cycle analysis.

6e+06~
4e+06 -

^ 2e+06_

0e+00 -

0
>

^2 3e+06 -

2e+06 -
1e+06 -
0e+00 -

Figure 2-12 MOVES opMode distributions with associated braking activity. Note: idle activity (which
has negligible braking) was omitted for scale purposes

I..J

ll L.J IIIiIhmh'IIIhb

0 11 12 13 14 15 16 21 22 23 24 25 27 28 29 30 33 35 37 38 39 40

MOVES opModes

Time Braking Total Time in Mode

-------
Table 2-23 Braking fractions by MOVES opMode and regClass

opMode

regClass 20

regClass 30

0 (braking)

0.9979621

0.9948194

1 (idle)

0.0000018

0.0000014

11 (coasting/decel)

1.0

21 (coasting/decel)

1.0

33 (coasting/decel)

0.3320758

0.2908599

As the figure and table show, opModes 11 and 21 are entirely made up of braking activity. This makes
intuitive sense because, by definition, these operating modes only contain activity with negative VSP.
OpMode 33 was shown to be roughly a third braking activity for both cars and trucks. Interestingly, the
braking opMode (opMode 0) contained a very small but quantifiable amount of non-braking
deceleration. Likewise, the idle opMode (opMode 1) only contained a tiny fraction of braking activity.
Figure 2-13 helps to interpret these results. It depicts a mapping of the light-duty car opModes onto a
speed and acceleration space. The line separating opModes 11 and 12, and opModes 21 and 22
represents the line of VSP = 0 and is continued as a dotted line through opMode 33. The lighter grey
hatched rectangle overlapping op modes 11, 21, and 33 is the low-deceleration (e.g., acceleration
between -1.0 and -2.0 mph/sec) portion of opMode 0 that is defined based on the number of seconds
spent decelerating. At high driving speeds, this low deceleration braking space crosses into the area of
positive VSP values, which accounts for the small fraction of non-braking activity observed in the braking
opMode.

-------
OpModelD

Speed (MpH)

Figure 2-13 MOVES opModes mapped in speed and acceleration space

2.2.5.2 Braking Fractions for Heavy-Duty Vehicles

To estimate the amount of time heavy-duty vehicles spend braking in each of the braking associated
opModes, we analyzed the drive traces from the Heavy-Duty Diesel In-Use Testing (HDIUT) data for
MY2010+ vehicles. This HDIUT dataset was extensively used in MOVES to develop exhaust emission
rates. Exhaust Emission Rates for Heavy-Duty Onroad Vehicles in MOVES528 provides detailed
descriptions of the HDIUT program and the methodology to calculate MOVES opMode distributions for
heavy-duty vehicles.

As explained in that report, the HDIUT data includes second-by-second information about engine speed,
torque, axle power, vehicle speed, and acceleration, from which we calculated scaled tractive power
(STP) and MOVES opMode. For braking faction estimates, we count time intervals with STP < 0 (while
excluding a subset of those records where either the vehicle speed is 0 or the acceleration is greater
than 0) as "braking time" in each of the braking associated opModes.

-------
The braking factions based on the HDIUTm data are summarized in Table 2-24 and applied to all model
years".

Table 2-24 Braking factions by MOVES opMode and regClass for heavy-duty vehicles

LHD2b3(=LDT)

LHD45

MHD

HHD

Urban
Bus

OpModelD

Braking Fraction

0 (braking)

0.994819

0.87996

0.877744

0.786902

0.97811

1 (idle)

1.44E-06

0.001594

0.016118

0.004802

0.003346

(coasting/decel)

0.652373

0.710629

0.70482

0.679883

(coasting/decel)

0.743501

0.874805

0.797833

0.690515

(coasting/decel)

0.29086

0.312656

0.262391

0.274519

0.179825

2.2.5.3 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
such as during passenger pick-up and drop-off, MOVES does not estimate brake emissions, because the
vehicle is completely stopped during this non-drive-cycle idle time.

At County Scale and Default Scale, opMode 1 is used for estimating brake wear emissions for all speeds
less than 1 including zero 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. However, when
estimating brake wear at Project Scale, MOVES assigns all operation with speed equal to zero to
operating mode 501 (brake wear; stopped), and with 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. This approach allows Project Scale modelers to define links with sustained idling and no
brake wear. At Project Scale, MOVES users also have the option to input their own operating mode
distributions, including using operating mode 501 (brake wear; stopped) and operating mode 1 (idle).

m Since HDIUT program doesn't include LHD2b3, we set the LHD2b3 braking fraction equal to the LDT
values in Table 2-23.

n The heavy-duty braking fractions in pre-MOVES5 versions were estimated based on light-duty vehicle
activity data.

-------
2.3 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.

For model years 2010 and earlier, 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) reports PM "fractions and cutoffs of 0.8 at 10 pim, 0.6 at 7 pim, 0.35 at
4.7 pirn, 0.02 at 1.1 pim, and <0.01 at 0.43 pim for the UDP stops typical of urban driving". These
assumptions result in a PM10/PM2.5 ratio of 8. This ratio is used for all source types and model years prior
to 2011. 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) reports 72 percent of PM10
is PM2.5, which is disputed by Sanders et al. (2003). Our calculation 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 2-1, which is dominated by the more recent data from Sanders et al. (2003).

For model years 2011 and later, the PM10 ratio for light-duty vehicles is taken as the ratio of the average
slopes for PM10 and PM2.5 rates in Table 2-10. We get a PM10 to PM2 5 ratio of 2.61 for light-duty ICE
vehicles, and 1.42 for light-duty EVs. For MY 2011 and later, we set the ratio to 2.857 for all MY2011+
heavy-duty vehicles. This estimate is based on the ratio of the aggregated PM2.5 and PM10 emission rates
across the heavy-duty vehicle categories in the CARB/Caltrans HD brake test program.17

2.4 Summary of MOVES Brake Wear Rates

Figure 2-14 through Figure 2-20 below summarize the MOVES brake wear emission rates across model
years for light and heavy-duty vehicles. The gram-per-mile rates in the figures are averaged at the
national scale and are calculated using the vehicle populations modeled by MOVES. Some changes in
rates, especially for heavy-duty vehicles, reflect changes in source type populations and operating mode
distributions rather than base rates. For example, the increase in HHD gasoline brake wear from MY 2010
to MY 2011 reflects a change in underlying rates while the changes before MY 2010 and after MY 2011
reflect changes in the relative population of the HD source types within the HHD regulatory class.

Finally, the figures below present brake wear emission rates for PM2 5. These trends do not necessarily
apply to PM10 because the calculation of brake wear PM10 rates depends on the ratios in the
PMlOEmissionRatio table.

Overall, these figures are intended to provide a summary of the MOVES brake wear rates that result
from the base rates developed in Sections 2.2.1 through 2.2.4 and the braking activity described in
Section 2.2.5. For the purpose of comparison, these figures are presented in the same format as the
analogous figures presented in the MOVES reports for exhaust emissions from light and heavy-duty
vehicles.26 28

-------
0.003-

|
D)

0)
TO

0.002-

1 0.001-

Reg Class

10-MC
20-LDV
30-LDT

0.000-

1980

2000 2020

Model Year

2040

Figure 2-14 Brake wear PM2.5 emission rates for light-duty gasoline vehicles averaged over a nationally
representative operating mode distribution

0.003

0.002

Q)
TO

CL
u>

i 0.001

0.000

Reg

Class

—

20-LDV

—

30-LDT

1980

2000

2020

2040

Model Year

Figure 2-15 Brake wear PM2.5 emission rates for light-duty diesel vehicles averaged over a nationally

representative operating mode distribution0

-------
0.003

£ 0.002-

+¦»

Reg Class

20-LDV
— 30-LDT

I 0.001-

0.000-

2010

2020

2030
Model Year

2040

2050

Figure 2-16 Brake wear PM2.5 emission rates for light-duty electric vehicles averaged over a nationally

representative operating mode distribution

° MOVES defaults have no light-duty diesel vehicles after model year 2019.
46

-------
0.00-

1980

2000 2020

Model Year

2040

Reg Class

41-LHD2b3

42-LHD45
46-MHD67

-+¦ 47-HHD8

Figure 2-17 Brake wear PM2.5 emission rates for heavy-duty gasoline vehicles averaged over a
nationally representative operating mode distribution

-------
0.04'

2
a)
ro
K
m
ci
S

Q- 0.02

§
m

0.00'

V~—

1980

2000

2020

2040

Reg Class

-- 41-LHD2b3
42-LHD45
46-MHD67
-*¦ 47-HHD8

48-Urban Bus

49-Gliders

Model Year

Figure 2-18 Brake wear PM2.5 emission rates for heavy-duty diesel vehicles averaged over a nationally
representative operating mode distributionp

0.06

a>
|

0.04

5
m

0.02

0.00'

Reg Class

47-HHD8

48-Urban Bus

1980

2000

2020

2040

Model Year

p MOVES defaults have no gliders after model year 2020.
48

-------
Figure 2-19 Brake wear PM2.5 emission rates for heavy-duty compressed natural gas (CNG) vehicles
averaged over a nationally representative operating mode distribution

0.015

S 0.010'

•*->
cs
DC

cvi
2
CL

m 0.005'

0.000'

. . I I I I I

Reg Class

41-LHD2b3

42-LHD45

46-MHD67

47-HHD8

48-Urban Bus

2020

2030 2040

Model Year

2050

Figure 2-20 Brake wear PM2.5 emission rates for heavy-duty electric vehicles averaged over a nationally

representative operating mode distribution

3 Tire Wear

3.1 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.29

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 2-3.30

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
49

-------
turning and road grade) especially increase 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.31 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.32 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 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.33 Table 3-1 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.34

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.35 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.36 Rauterberg-Wulff (1999) determined particle emission factors
for tire wear using modeling in combination with measurements conducted in the Berlin-Tegel tunnel.37

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 3-1 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.38

Table 3-1 - 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)39

Measured tire wear rate

9 mg/km - PMio
2 mg/km -PM2.5

Luhana et al (2003)

Measured tire wear rate

Councell,T.B. et al (2004)

Calculated rate based on literature

200

U.S. Geological Survey40

Warner etal. (2002)41

Average tire wear for a vehicle

Kolioussis and Pouftis (2000)42

Average estimated tire wear

EMPA (2000)43

Light duty vehicle tire wear rate

Heavy duty vehicle tire wear rate

798

SENCO (Sustainable
Environment

Light duty vehicle tire wear rate

Consultants Ltd.) (1999)44

Wear rate for trucks

1403

Estimated rate for light duty vehicles

Legret and Pagotto (1999a)

Estimated rate for heavy vehicles (>3.5t)

136

Baumann (1997)45

Passenger car tire wear rate

Heavy duty vehicle tire wear rate

189

Articulated lorry tire wear rate

234

Bus tire wear rate

192

Garben (1997)46

Passenger car tire wear rate

Light duty vehicle tire wear rate

112

Heavy duty vehicle tire wear rate

768

Motorbike tire wear rate

Gebbe (1997)47

Passenger car tire wear rate

Light duty vehicle tire wear rate

110

Heavy duty vehicle tire wear rate

539

Motorbike tire wear rate

26.4

-------
Lee et al (1997)48

Estimated tire wear rate

Sakai,H (1995)

Measured tire wear rate

184

Baekken (1993)49

Estimated tire wear rate

200

CARB (1993)

Passenger car tire wear rate

120

Muschack (1990)

Estimated tire wear rate

120

Schuringand Clark (1988)50

Estimated tire wear rate

240-360

Pierce,R.N. (1984)

Estimated tire wear rate

120

Malmqvist (1983)51

Estimated tire wear rate

120

Gottle (1979)52

Estimated tire wear rate

120

Cadle et al. (1978)53

Measured tire wear rate

Dannis (1974)54

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.

3.2 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.38 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 respectively5) 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 3-2 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.

q vkm is "vehicle kilometer" and assumes four times a per tire rate for light-duty vehicles.
53

-------
Table 3-2: 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)

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

3.3 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 3-3.

-------
Table 3-3: 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

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
3-1.

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).

0.25 -
0.20 -

"a 0.15 -
E
u>

V)
in
o

- 0.10 -
.c
g)

'
-------
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 3-4 below.

Table 3-4 Average Number of Tires per Vehicle - Calculated from 2002 VIUS Survey of axle count.

RegClassID

RegClass name

Average Tires Per
Vehicle

2.0

LDV

4.0

LDT

4.0

LHD2b3

5.5

LHD45

6.0

MHDD

7.0

HHDD

14.9

Urban Bus

8.0

* Note: Tires per vehicle for LDT is the same as that for LDV

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 PMi0 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 PMi0 (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.39 Based on this study, it is assumed that 1.2 percent of the
total tire wear is emitted as PIVh.sto 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 PM25.

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 A. 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 3-5.

-------
Table 3-5 Average PM2.5and PMi0 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

Motorcycle

0.64

0.40

4.29

2.66

Passenger Car

1.28

0.80

8.55

5.32

Passenger Truck

1.28

0.80

8.57

5.32

Light Commercial Truck

1.37

0.85

9.16

5.69

Intercity Bus

3.87

2.40

25.77

16.01

Transit Bus

2.35

1.46

15.68

9.74

School Bus

2.30

1.43

15.31

9.51

Refuse Truck

3.93

2.44

26.19

16.27

Single Unit Short-haul Truck

2.25

1.40

15.03

9.34

Single Unit Long-haul Truck

2.17

1.35

14.48

9.00

Motor Home

2.21

1.37

14.75

9.16

Combination Short-haul Truck

3.81

2.37

25.39

15.78

Combination Long-haul Truck

4.13

2.56

27.51

17.10

3.3.1 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)r.
Grigoratos et al. (2018)55 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 MOVES3 are displayed in Table 3-5.

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)39.

-------
3.4 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 distribution (using the opModeDistribution table)s. 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 A) used at all scales of analysis.

-------
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

^ 40

a>
a>
a.

-------
-0.2

-0.4

-0.6

8 -1

T3
O)

^ -1 2
w 1

o
o

-1.4

-1.6

y = -0.0001454x2 + 0.0000622x - 0.1758
R2= 1.0

Speed (mph)

Figure A-2. Coastdown 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).

-speed
- brake

6800
time

Figure A-3 Braking Episodes over the FTP cycle

-------
Appendix B Literature Review conducted for MOVES2009

Table B-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 DG TrEn, 5th Framework
PARTICULATES project, Contract No. 2000 -
RD.11091, Version 2.0 , October 2004.

2004

Non-exhaust particle research was conducted

in the Hatfield road tunnel. Combined tire
and brake wear emissions for PMi0 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. Technol., 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 1. McCrae, "Non-
exhaust particle Emissions 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,!.; 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-01-023,Laxenburg, Austria,2001.

Westerlund,K.G.," Metal emissions from
Stockholm traffic - wear of brake linings ",The
Stockholm Environment and Health Protection
Administration, 100,64,Stockholm,Sweden,2001.

2001

Westerlund estimated the amount of material
lost due to brake wear from passenger cars
and heavy goods vehicles. The PM10 emission

factors were 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 PM10 and PM2.5
respectively.

Annette Rauterberg-Wulff, "Determination of
emission factors for tire wear particles up to
lOum by tunnel measurements", Proceedings of

1999

PM10 emission factors were determined for
tire and brake wear using receptor modeling
in combination with measurements
conducted in the Berlin-Tegel tunnel. Tire

-------
8th International Symposium on Transport and Air
Pollution, Graz, 1999.

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
",Arbeitsun terlage, ,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.

-------
4 References

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-------
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-------
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