Speciation of Total Organic Gas and
Particulate Matter Emissions from
On-road Vehicles in MOVES2014b

4%	United States
Environmental Protection
hI	Agency

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Speciation of Total Organic Gas and
Particulate Matter Emissions from
On-road Vehicles in MOVES2014b
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
&EPA
United States
Environmental Protection
Agency
EPA-420-R-18-012
July 2018

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Table of Contents
Table of Contents	1
1.	Introduction	2
2.	Speciation Glossary	3
3.	Organic Gas Aggregations	8
4.	Chemical Mechanism (CM) Speciation	14
5.	PM2.5 Speciation	22
Appendix A Methods used to derive NMOG/NMHC and VOC/NMHC parameters	30
Appendix B TOG Speciation Map	36
Appendix C Development of PM2.5 speciation profiles in MOVES2014	38
Appendix D PM10/PM2.5 Factors	53
Appendix E Peer-Review Comments and Responses	54
References	68
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1. Introduction
In addition to estimating emissions of pollutants that are discrete chemical compounds, such as
carbon monoxide (CO) and sulfur dioxide (SO2), MOVES2014 produces emission rates for
aggregates of individual chemical compounds, including total hydrocarbons (THC), volatile
organic compounds (VOC), total organic gases (TOG) and particulate matter (PM). These
pollutants are operationally defined, meaning that their definition depends on the measurement
technique(s) selected. For example, THC is defined as the hydrocarbons measured by a flame
ionization detector (FID). TOG is intended to include all organic gases. Because THC
measurements do not respond fully to carbon-oxygen bonds in oxygenated compounds, such as
aldehydes, alcohols, and ketones, these oxygenates need to be measured separately by gas and
liquid chromatography and added to the THC measurements to calculate TOG. Alternatively,
TOG measurements can be made solely with gas and liquid chromatography methods. Thus,
differences in measurement methods need to be considered when comparing THC to TOG
emission measurements1. Similarly, particulate matter is operationally defined as the measured
mass collected on a filter using EPA-defined sampling filter media, conditions, and practices2'3.
PM2.5 refers to particulate matter emissions collected downstream of a cyclone that removes the
particles with aerodynamic diameter greater than 2.5 microns, while PM10 refers to particulate
matter emissions with aerodynamic diameter less than 10 microns.
Previous versions of MOVES produced emission estimates for a subset of species that contribute
to TOG and PM2.5. These include important organic gaseous toxics (e.g., formaldehyde and
benzene), and toxic particle-phase elements (e.g., nickel and manganese). These also include
semi-volatile organic compounds, such as 15 individual polycyclic aromatic hydrocarbons (e.g.,
benzo(g;/zz',z)perylene) that can exist in both the gaseous and particle phases under different
measurement conditions. Individual toxic emission rates are detailed in the toxics report4, but are
peripherally discussed in this report in the context of their use in deriving speciated TOG and PM
emissions.
For air quality modeling purposes, further chemical characterization of TOG and PM2.5 is
required. Prior to MOVES2014, the individual species produced by MOVES (e.g., benzene,
elemental carbon) and aggregates (TOG and PM2.5) were processed outside MOVES by emission
pre-processors into a form suitable for air-quality modeling. The process of apportioning
aggregate TOG and PM2.5 into sets of separate components is called "speciation." MOVES2014
incorporates the process of TOG and PM2.5 speciation, and can produce the TOG and PM2.5
species needed by air quality models.
The reason for bringing the speciation capability inside MOVES is improved accuracy and
flexibility. Because the speciation of TOG and PM2.5 depends on technology, fuels, and emission
processes, speciation is approximate and cumbersome to implement outside MOVES. Pre-
MOVES2014, speciation profiles were applied outside the model primarily by aggregate
classifications called source classification code (SCC) that did not contain important distinctions
of emission standards, fuel types, and emission process, such as between start and running
exhaust. Pre-MOVES 2014 speciation profiles had to vary by county to account for combinations
of ethanol fuel blends that vary by county. This outside-of-MOVES speciation was limited as it
could not readily accommodate the application of technology-specific speciation profiles to
concurrent categories of model-year group, regulatory class, fuel subtype (e.g., gasolines with
different ethanol content), and MOVES emission process (see "process" in the glossary).
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Inside MOVES, speciation (like all calculations) is done on a model-year, fuel, vehicle class, and
emission-process basis, providing the ability to more easily reflect distinctions in different TOG
and PM2.5 profiles.
The purpose of this document is to describe how we have incorporated the speciation process,
which previously occurred outside of the MOVES framework, into MOVES2014 to better
provide model-ready species for air quality modeling. Limited data exist to support matching
speciated emissions data with all combinations of MOVES classifications (model-year group,
regulatory class, fuel subtype, emissions process), but we believe the speciated emissions data
cited below are the best available at the time this document was created. Furthermore, the new
structure allows us to continue to improve and expand the application of speciated emissions data
in MOVES based on the research and emissions test programs as new data become available.
This report was revised for MOVES2014a from a previous version (EPA-420-R-14-0205). Those
changes include: inclusion of the CB6 chemical mechanism into MOVES2014a (Section 4.3), a
correction made to the TOG speciation profile assignment (Table 4-1 and Table B-l), corrections
made to the NMOG and VOC factors (Sections 3.2 and 3.3), documentation of the values used to
calculate NMOG and VOC emissions from diesel refueling processes (Section 3.4), and edits to
Appendix C (Development of PM2.5 speciation profiles in MOVES2014) in response to peer-
review comments (Appendix E).
This report has also been updated for MOVES2014b. The only changes for MOVES2014b were
updates to chemical mechanisms CB05 and CB6 and the addition of another chemical
mechanism, SAPRC07T. For more details see Section 4.
2. Speciation Glossary
In the area of "speciation," many words have two or more meanings. The list below
distinguishes these to avoid confusion. The report tries to use unambiguous terms that are close
to common usage.
•	Aggregate species: groups of chemical compounds (or "real species"). These are often
defined operationally or may be defined for modeling purposes. For example, THC,
TOG and VOC are aggregate gaseous species. NonEC is an aggregate particulate matter
species.
•	Elemental Carbon (EC): "A descriptive term for carbonaceous particles based on
chemical composition rather than light-absorbing characteristics. Often used as a
synonym for black carbon."6 Elemental carbon is measured through thermal optical
techniques as particle-phase carbon that does not volatize at high temperatures in an
oxygen-free environment.7 In tailpipe exhaust, EC is one measure of carbonaceous soot
formed from fuel pyrolysis occurring during combustion.8
•	CMAQ: The Community Multiscale Air Quality system is a photochemical and transport
air quality model. CMAQ is an open source development project sponsored by the US
EPA Atmospheric Science Modeling Division (http://www.cmaq-model.org/).
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•	Chemical mechanism: In air-quality models, chemical mechanisms are simplified
representations of the full panoply of atmospheric chemical reactions. They have been
developed by air-quality modelers to speed up the atmospheric chemistry calculations in
their models. An aspect of these chemical mechanisms is the use of a relatively small set
of "chemical mechanism species," (CM species) into which all the real species can be
mapped, and which serve to model the atmospheric reactions of importance. For the
purposes of MOVES, a chemical mechanism may be thought of as a set of CM species
and the mapping between regular MOVES output species and the CM species. In the
original release of MOVES2014, we included only the CB05 version of the carbon-bond
mechanism.9 In MOVES2014a, we added CB6,10 and in MOVES2014b we updated
CB05 and CB6 (and updated the name to CB6CMAQ) and added SAPRC07T. However,
since the mapping is table-driven, MOVES2014 has the structure in place to generate CM
species for any chemical mechanism. OTAQ expects to add others over time.
•	Integrated species: Real species for which MOVES produces emissions that are
subtracted from TOG, leaving residual TOG. This residual TOG is speciated into CM
species using a CM speciation profile constructed from the real speciation profile from
which the integrated species have been removed. The integrated species, which are
produced by MOVES, are individually speciated into CM species. At present,
MOVES2014 integrates the 16 species shown in Table 2-1. MOVES is designed to
accept different sets of integrated species, if desired.
Table 2-1. Integrated MOVES pollutants
pollutant ID
Pollutant Name
5
Methane (CH4)
20
Benzene
21
Ethanol
22
MTBE
24
1,3-Butadiene
25
Formaldehyde
26
Acetaldehyde
27
Acrolein
40
2,2,4-Trimethylpentane
41
Ethyl Benzene
42
Hexane
43
Propionaldehyde
44
Styrene
45
Toluene
46
Xylene
185
Naphthalene gas
• Intermediate PM2.5 species: Groups of PM2.5 species used to improve computation time,
and reduce the size of the emission rate tables. They include the aggregate species: "non-
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elemental carbon particulate matter" (NonECPM) and "non-elemental carbon non-sulfate
particulate matter" (NonECnonS04PM), elemental carbon (EC), sulfate (SO4) and
particulate water (H2O). They are used to compute total PM2.5 emissions and speciated
PM2.5 emissions. The EC, SO4, and H2O species are reported as MOVES outputs.
•	Chemical Mechanism species (CM species): the species used by chemical mechanisms.
CM species include both artificial constructs (sometimes referred to as "lumped species")
and real species. CM species are unique to particular chemical mechanisms (e.g., CB05,
SAPRC07T). All real TOG species are mapped to CM species. For a particular chemical
mechanism, the associated group of CM species can be referred to by the name of the
mechanism, for example, CB05 species.
•	CM speciation profile: the mapping of a real species (e.g., hexane) or an aggregate
species (e.g., TOG) into CM species. The mapping of real species into CM species has
been created by the developers of chemical mechanisms for air quality modeling.9 The
mapping of real species is independent of process and fuel. The mapping of aggregate
species (e.g., residual TOG) represents the sum of the mappings of the individual real
species from the real speciation profiles. The mapping of aggregate species depends on
process and fuel.
•	Organic Mass (OM): Particle-phase organic mass. The mass of the organic material in
particulate: OM = organic carbon (OC) + non-carbon organic matter (NCOM).
•	Organic Carbon (OC): "The mix of compounds containing carbon bound with other
elements; e.g., hydrogen and oxygen. Organic carbon may be a product of incomplete
combustion, or formed through the oxidation of VOCs in the atmosphere."6 Organic
carbon is measured using thermal-optical methods as the particle-phase carbon collected
on a filter that volatizes at high temperatures in an oxygen-free environment.
•	Non-Carbon Organic Mass (NCOM): the mass of the oxygen, hydrogen, nitrogen and
other elements present in particle-phase organic mass. OC and NCOM are modeled
separately in air quality models in order to model the degree of oxidation of organic
matter, which depends on the emission source and the chemical transformation in the
atmosphere11.
•	Non-Elemental Carbon Particulate Matter (nonECPM): The PM2.5 that is not elemental
carbon. This is typically calculated as the difference between PM2.5 mass filter-based
measurements and elemental carbon measurements made using thermal optical
measurements, or surrogate elemental carbon measurements such as photoacoustic
sensors.
•	Non-Elemental Carbon, Non-Sulfate Particulate Matter (nonECnonS04PM): A MOVES
intermediate species used to represent the PM2.5 mass other than elemental carbon,
sulfate, and associated water. NonECnonS04PM includes organic matter, elements, and
ions. NonECnonS04PM is adjusted for fuel and temperature effects prior to speciation
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due to limited data on temperature and fuel effects on individual PM2.5 species in the
exhaust, and to improve computational time.
•	Non-Methane Hydrocarbons (NMHC): NMHC = THC - CH4 (methane).
•	Non-Methane Organic Gases (NMOG): NMOG = TOG - CH4 (methane).
•	Real species: "Species" in the normal chemical sense—a pure chemical substance. The
word "real" helps distinguish these species from chemical mechanism species or
aggregated species.
•	Real speciation profile: ideally, a complete listing of the real species and their quantities
of TOG. In practice, these profiles are incomplete; a certain fraction of the mass is
unresolved. Such a profile is produced by laboratory analysis of emissions. This is not a
CM speciation profile and is independent of chemical mechanism. Such a profile does,
however, depend on process, fuel, and technology, since the mix of real species in TOG
is different for different emission processes (e.g. evaporative and exhaust), for different
fuels, and for different technologies. The SPECIATE database is the EPA repository for
these profiles, (http://www.epa.gov/ttn/chief/software/speciate/index.html)
•	Residual TOG: TOG that remains after subtracting integrated species.
•	Process: MOVES2014 has twelve emission processes that are relevant for TOG
speciation. The Process IDs and names are included in Table 2-2. Within each process,
emission rates can potentially vary by operating mode. Running exhaust has different
operating modes to represent idling, coasting, and operating with different engine loads.
Start exhaust has different operating modes to differentiate a continuum of starts between
cold, warm, and hot starts. The operating modes are defined in the MOVES2014
emission rate reports30'33, and evaporative reports12. In MOVES2014, different TOG and
PM speciation profiles can be applied to different processes, but not to individual
operating modes.
Table 2-2. MOVES processes relevant for speciation profiles
Process ID
Process Name
1
Running Exhaust
2
Start Exhaust
11
Evap Permeation
12
Evap Fuel Vapor Venting
13
Evap Fuel Leaks
15
Crankcase Running Exhaust
16
Crankcase Start Exhaust
17
Crankcase Extended Idle Exhaust
18
Refueling Displacement Vapor Loss
19
Refueling Spillage Loss
90
Extended Idle Exhaust
91
Auxiliary Power Exhaust
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•	Source Classification Code (SCC): Standard code that identifies various emissions
sources for inventory reporting and air quality modeling.
•	SMOKE: Sparse Matrix Operator Kernel Emissions is a computer program used to
provide model-ready inputs into CMAQ. SMOKE produces gridded, speciated, and
hourly emissions input for use in CMAQ and other air-quality models.
(http ://www. smoke-model. org/index. cfm)
•	Species: Distinct chemical compounds, ions, groups of compounds, or other chemical
entities. In this report, we distinguish "real species," "aggregate species," "CM species,"
and "intermediate species," as explained in this glossary.
•	Total Hydrocarbons (THC): "THC is the measured hydrocarbon emissions using a Flame
Ionization Detector (FID) calibrated with propane. The FID is assumed to respond to all
hydrocarbons identically as it responds to propane in determining the concentration of
carbon atoms in a gas sample. Most hydrocarbons respond nearly identically as propane
with notable exceptions being oxygenated hydrocarbons such as alcohols and aldehydes
commonly found in engine exhaust." 1
•	Total Organic Gases (TOG): hydrocarbon emissions plus oxygenated hydrocarbons such
as alcohols and aldehydes1
•	Volatile Organic Compounds (VOC): TOG emissions minus those hydrocarbons that
contribute little to ozone formation, such as methane, ethane, and acetone.1 EPA may
over time exclude additional organic compounds from the definition of VOC which have
negligible photochemical reactivity. For the current list, see: Code of Federal
Regulations, 40: Chapter 1, Subchapter C, Part 51, Subpart F. 5 1 100(s). In mobile source
testing, typically only a few compounds with negligible photochemical reactivity are
measured in significant quantities. For the TOG speciation profiles used in MOVES,
VOC is defined as TOG minus methane, ethane, and acetone.
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3. Organic Gas Aggregations
MOVES provides estimates of organic gas emissions in a number of different aggregations.
Table 3-1 shows the composition of the various organic gas aggregate classes in MOVES. As the
table shows, the organic gas aggregations differ based on the presence or absence of methane,
ethane, alcohols, and aldehydes. Definitions for these species are also included in the glossary.
The term "FID-HC" refers to the total hydrocarbons detected by a Flame Ionization Detector
(FID). MOVES THC (pollutandID=l) is defined as FID-HC, and thus includes methane and
ethane. MOVES calculates emissions of total organic gases (TOG), nonmethane organic gases
(NMOG) and volatile organic compounds (VOC) using information regarding the total organic
gas speciation of emissions.
PollutantID
PollutantName
FID-
HC
Methane
Ethane
Acetone
Alcohols
Aldehydes
1
Total
Hydrocarbons
Yes
Yes
Yes
No
No
No
79
Non Methane
Hydrocarbons
Yes
No
Yes
No
No
No
87
Volatile Organic
Compounds
Yes
No
No
No
Yes
Yes
86
Total Organic
Gases
Yes
Yes
Yes
Yes
Yes
Yes
80
Non Methane
Organic Gases
Yes
No
Yes
Yes
Yes
Yes
In MOVES, THC emission rates are the base emission rates (field meanBaseRate in the
EmissionRateByAge table), from which each of the other hydrocarbon emissions are estimated.
The following sections present the equations and parameters used to derive these other aggregate
organic gas emission rates from THC.
3.1. Methane and Non-Methane Hydrocarbon Calculations
Exhaust regulations for hydrocarbons are often expressed in terms of non-methane hydrocarbons
(NMHC). MOVES calculates both methane and NMHC from the THC emissions using
methane/total hydrocarbon ratios (CH4THCRatio in the MethaneTHCRatio Table) as shown in
Equation 1 and Equation 2.
NMHC = THC ¦ (1 - MethaneTHCRatio)
Equation 1
Methane = THC ¦ (MethaneTHCRatio)
Equation 2
The development of the methane/total hydrocarbon ratios is documented in the MOVES2014
Greenhouse Gas and Energy Consumption Rates Report.13
3.2. Non-Methane Organic Gases Calculation
Non-Methane Organic Gas (NMOG) is defined as all non-methane organic gases, including
oxygenated hydrocarbons such as alcohols and aldehydes. To calculate NMOG from NMHC
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requires accounting for the FID response factor for the oxygenated hydrocarbons. For example,
formaldehyde generally has an FID response of ~0, so formaldehyde measurements need to be
fully added to the NMHC value. An approximate FID factor for acetaldehyde is -0.5, which
means that only V2 of the measured acetaldehyde emissions need to be added to the FID
measurements to calculate NMOG.
Within MOVES, the following equation is used to calculate NMOG.
NMOG = NMHC ¦
\speciationConstant + £f=i(oxySpeciation ¦ volToWtPercentOxyi ¦	Equation 3
oxyV olumei)]
Where:
i = one of four gasoline oxygenates: ethanol, methyl tert-butyl ether (MTBE), ethyl tert-butyl
ether (ETBE), or tert-amyl methyl ether (TAME).
SpeciationConstant =NMOG/NMHC conversion factor when the gasoline has no oxygenate
volume.
oxySpeciation = empirically derived value that adjusts the NMOG/NMHC according to
oxygenate volume. The values represent the adjustment for a 1 b-1 increase in oxygenate
volume.
volToWtPercentOxyi = term used to convert from the oxygenate percentage by volume (vol
percent) to the mass percentage of oxygen in the fuel(mass percent). volToWtPercentOxy is
calculated using Equation 4 and the values provided in Table 3-2. Equation 3 assumes that the
relationship between the oxySpeciation factor is linearly proportional to the mass fraction of
oxygen in the fuel.
oxyVolumei = the percent volume of each gasoline oxygenate in the respective fuel.
The methods used to derive the SpeciationConstant and the oxySpeciation terms are documented
in Appendix A. The volume to weight percent oxygen values are calculated using Equation 4.
volToWtPercentOxyi = Mass Fraction of Oxygeni x —	ffiliation 4
Where:
Pi = the density of the oxygenate (g/cm3)
pF = the density of the gasoline fuel, assume to be 0.75 g/cm3
The mass fraction of oxygen, densities of the oxygenates, and calculated volToWtPercentOxy
values are shown in Table 3-2.
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Table 3-2. Volume to Weight Percent Oxygen for Gasoline Oxygenates
Oxygenate
Name
Mass Fraction
of Oxygen
Density of the
Oxygenate (g/cm3)
Volume to Weight
Percent Oxygen
(volToWtPercentOxy),
assuming gasoline fuel
density of 0.75 g/cm3
Ethanol
0.3473
0.789
0.3653
MTBE
0.1815
0.7404
0.1792
ETBE
0.1566
0.7364
0.1537
TAME
0.1566
0.791
0.1651
Exhaust speciation factors for pre-2001 model year gasoline vehicles (pre-NLEV/Tier 2) remain
unchanged from MOVES2010. The pre-2001 - gasoline NMOG/NMHC factors in MOVES were
taken from MOBILE6.2 materials and were originally produced for MOBILE4.1 and
MOBILE5.14151617 These values are displayed in Table 3-3 for the pre-2001 model year groups.
As indicated previously, oxySpeciation is an empirically derived value that adjusts the
NMOG/NMHC relationship according to oxygenate volume. The pre-2001 oxySpeciation
constants are based on data from speciation profiles incorporated into SPECIATE (profiles 1313
and 1314). There is no oxyspeciation factor for ethanol blends greater than 10 percent, since
speciationConstant accounts for the oxygenate level.
Table 3-3. Parameters used to calculate NMOG/NMHC ratios for gasoline vehicle emissions
Fuel Subtype
Model Year
Group
Process
speciationConstant
oxySpeciation
E0 to E10
1960-1974
Start and
Running
Exhaust
1.0352
0.0062
1975-1986
1.02113
0.0062
1987-1989
1.0179
0.0062
1990-1993
1.0167
0.0062
1994-2000
1.0163
0.0062
2001-2050
Start
1.0078
0.0082
Running
1.0149
0.0028
E15
1960-2050
Start
1.0495
0
Running
1.0318
0
E20
1960-2050
Start
1.0703
0
Running
1.0367
0
E70 to E100
1960-2000
Start and
Running
Exhaust
1.4858
0
The organic gas speciation factors for NLEV and Tier 2 gasoline (2001+) and ethanol blends are
based on EPAct Phase 3 data.18 The E0, E10, E15, E20 and E70-E100 values are based on data
in SPECIATE profiles 8756, 8757, 8758, 8854, and 8855 profiles, respectively. For pre-2001
vehicles fueled on E70-E100 gasoline-ethanol blends, we calculate NMOG using the parameters
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in Table 3-3a. For 2001 and later E70-E100 fueled vehicles, the NMOG emissions are set equal
to the E10 emissions as discussed in the MOVES2014 fuel effects report.32
The NMOG/NMHC values for the pre-2007 trucks were based on more recent and extensive data
than were available in earlier versions of MOVES.19 MOVES2014 uses the pre-2007
NMOG/NMHC value for diesel auxiliary power units for all model years because they are not
subject to the same control as on-highway diesel engines'3. For 2007-and-later diesel engines,
data were available from the Advanced Collaborative Emissions Study (ACES).20
MOVES2014 also includes updated NMOG speciation factors for compressed natural gas (CNG)
transit buses. Two CNG speciation values are provided based on two model groups (pre-2004
and 2004-and-later), assuming full use of oxidation catalysts in 2004-and-later model year
vehicles. CNG exhaust contains high formaldehyde emissions, particularly for uncontrolled
compression ignition buses, which causes high NMOG/NMHC ratios. The derivation of the
CNG NMOG/NMHC and VOC/NMHC rates are documented in the 2014 Heavy-Duty
Emissions Report.30 The new speciationConstant and oxySpeciation coefficients for diesel
vehicles, and compressed natural gas vehicles are summarized in Table 3-4.
Table 3-4. Parameters used to calculate NMOG/NMHC ratios for diesel and CNG vehicle emissions
Fuel Type
Model Year Group
speciationConstant
oxySpeciation
Diesel
1960-2006
1.1455
0
2007-2050
1.3431
0
CNG
1960-2003
1.9
0
2004-2050
1.24
0
3.3. Volatile Organic Compound Calculation
In MOVES, Volatile Organic Compounds (VOC) are defined as the NMOG minus ethane and
acetone. MOVES uses the same calculator and table to calculate VOC emissions as NMOG
emissions. Equation 5 is used to calculate VOC emissions from NMHC, which has the same
structure as Equation 3 used for NMOG calculations. However, the coefficients are different to
account for the exclusion of ethane and acetone in the VOC emissions.
a MOVES2014 erroneously did not produce NMOG, VOC, and TOG emissions from MY 1998, 1998 and 2000
E85-fueled LDVs and LDTs. This has been fixed in MOVES2014a, which uses the NMOG/NMHC and
VOC/NMHC values documented in Table 3-3 and Table 3-5.
b MOVES2014a corrected the NMOG/NMHC and VOC/NMHC values for APUs to use the pre-2007 values for
2007-2050 (instead of the 2007-2050 exhaust values as in MOVES2014), and corrected the MY 2007 extended
idling values to use the 2007-2050 values (instead of the pre-2007 values).
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VOC = NMHC ¦
\speciationConstant + £f=i(oxySpeciation ¦ oxyMassFractioni ¦ oxyVolume;)] Equation 5
Where:
/ = one of four gasoline oxygenates: ethanol, methyl tert-butyl ether (MTBE), ethyl tert-butyl
ether (ETBE), or tert-amyl methyl ether (TAME).
SpeciationConstant = VOC/NMHC conversion factor when the gasoline has no oxygenate
volume.
oxySpeciation = empirically derived value that adjusts the VOC/NMHC according to oxidation
volume.
oxyMassFractiorii = term used to convert from the oxygenate percentage by volume (vol percent)
to the mass percentage of oxygen in the fuel(mass percent). volToWtPercentOxy is calculated
using Equation 4 and the values provided in Table 3-2. Equation 5 assumes that the relationship
between the oxySpeciation factor is linearly proportional to the mass fraction of oxygen in the
fuel.
oxyVolumei = the percent volume of each gasoline oxygenate in the respective fuel.
The same data sources are used to derive the VOC/NMHC ratios as the NMOG/NMHC ratios
presented earlier. The gasoline values are displayed in Table 3-5.
Table 3-5. Parameters used to calculate VOC/NMHC ratios for gasoline vehicle emissions
Fuel
Model Year



Subtype
Group
Process
SpeciationConstant
oxySpeciation

1960-1974

1.0239
0.0133

1975-1986
Start and
Running Exhaust
0.9799
0.0133

1987-1989
0.976
0.0133
E0 to E10
1990-1993
0.9787
0.0133

1994-2000

0.9797
0.0133

2001-2050
Start
0.9787
0.0068

Running
0.9148
-0.0013
E15
1960-2050
Start
1.0162
0
Running
0.9049
0
E20
1960-2050
Start
0.9233
0
Running
1.0436
0
E70 to

Start and


E100
1960-2000ac
Running
1.3981
0
0 For 2001 and later model year gasoline vehicles fueled on E70-E100, the VOC emissions are set equal to VOC
emissions from E10 vehicles, as discussed in the MOVES2014 fuel effects report.32
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The diesel and CNG values are shown in Table 3-6. These were updated in MOVES2014 based
on the data sources discussed in the NMOG section. As for NMHC, the diesel APUs use the
1960-2006 VOC/NMOG values for all model years'3.
Table 3-6. Parameters used to calculate VOC/NMHC ratios for diesel and CNG vehicle emissions
Fuel
Type
Model Year
Group
speciationConstant
oxySpeciation
Diesel
1960-2006
1.1243
0
2007-2050
1.3058
0
CNG
1960-2003
1.6808
0
2004 -2050
0.9471
0
3.4. NMOG and VOC Calculations for Evaporative, Refueling and
Permeation Emissions
Since no significant methane, ethane, or acetone emissions are found in evaporative or
permeation emissions, THC is equivalent to NMHC, and VOC is equivalent to NMOG and TOG
for these emissions. Speciation factors are only needed to convert THC to NMOG to account for
the mass of ethanol not measured by the FID. MOVES uses Equation 3 and Equation 5 with the
parameters reported in Table 3-7.
THC to NMOG factors for vehicles with fuel ethanol content at or below 20 percent are
unchanged from earlier versions of MOVES for fuel vapor venting, fuel leaks, and refueling
evaporative emissions, and were derived from SPECIATE profiles 1301 and 1305. The
speciation factors for E70-E100 were updated based on the analysis of the CRC E-80 program.21
Engine
Type
Fuel Subtype
Process
speciationConstant
oxySpeciation
Gasoline
<5% ethanol
Vapor Venting and
Refueling Vapor
Loss
1
0.0318
E5 to E20
1
0.0318

E70 to E100
1.511
0

<5% ethanol
Fuel Leaks and
1
0.025
Gasoline
E5 to E20
Refueling Spillage
1
0.025

E70 to E100
Loss
1.511
0
New permeation factors were developed for MOVES2014 for E0 to E10, El 5, and E20 based on
data from the CRC E-77 program.22'23 The CRC E-77 program did not measure emissions for an
El 5 blend; therefore, it was interpolated from E10 and E20 profiles. For E70-E100, the
speciation factor for permeation is identical to the factors for other evaporative processes (see
Table 3-7), developed from CRC E-80 program. These factors are provided in Table 3-8.
13

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Table 3-8 Gasoline Vehicle Permeation hydrocarbon THC to NMOG and VOC speciation factors
Engine Type
Fuel
Subtype
Process
speciationConstant
oxySpeciation
Gasoline
EO to E10
Permeation
1
0.036
Gasoline
E15
Permeation
1.1755

Gasoline
E20
Permeation
1.2235
0
Gasoline
E70 to E100
Permeation
1.511
0
Currently, MOVES produces THC emissions from diesel vehicles for refueling spillage loss
(processID 19), but not the other evaporative or refueling emission processes. The
NMOG/NMHC and VOC/NMHC value for diesel spillage is set to 1, with no adjustment for
oxygenate content, as shown in Table 3-9. These values are consistent with the chemical
speciation measurements in SPECIATE profile 4547 'Diesel Headspace (Table 4-1), where no
methane, ethane, acetone, formaldehyde, acetaldehyde, or ethanol were measured.
Table 3-9. Diesel Vehicle Refueling THC to NMOG and VOC speciation factors
Engine
Type
Fuel Subtype
Process
speciationConstant
oxySpeciation
Diesel
Conventional
Diesel and
Biodiesel
Refueling Spillage
Loss
1
0
3.5. Total Organic Gases Calculation
MOVES calculates Total Organic Gases (TOG) from NMOG by adding the methane emissions
to NMOG as shown:
TOG = NMOG + Methane	Fmmtinn i
4. Chemical Mechanism (CM) Speciation
4.1. Overview
MOVES2014b produces the output of the CM species of Total Organic Gases (TOG) in units of
moles, for use by air-quality models. MOVES2014a was capable of producing chemical-
mechanism species for two chemical mechanisms, CB05 and CB6. These have been updated in
MOVES2014b. The update to CB05 is still called CB05. The update to CB6 is now called
CB6CMAQ. A third mechanism, SAPRC07T, was added. Prior to MOVES2014, the mapping of
MOVES output of individual organic species (e.g., benzene, 1,3-butadiene) and aggregates (e.g.,
TOG) into CM species was done outside MOVES by emission pre-processors to air quality
models. Beginning with MOVES2014, this mapping is done inside MOVES. In this report, the
mapping process is referred to as TOG speciation.
14

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The component of TOG that remains after subtracting MOVES gaseous organic species is called
residual TOG:
Residual TOG = TOG - MOVES gaseous organic species	Equation 7
The MOVES gaseous organic species that are subtracted are referred to as "integrated species."
Currently, we are integrating 16 MOVES species, listed in Table 2-1. The MOVES species we
do not integrate are primarily the PAHs and the dioxins.
TOG speciation required for air quality models is different than PM speciation, due to the
concept of chemical mechanisms. Chemical mechanisms (defined in the glossary) are used to
simplify the thousands of individual organic compounds into a manageable set of CM species
used for air quality modeling. The profiles used in this process, and the mapping of real species
into CM species is discussed below. PM, on the other hand, is not mapped into CM species, but
is split into various real species and some aggregated groups for use in air quality models.
4.2. Real Speciation Profiles
A real speciation profile is, in principle, a complete listing of all the real species and their
quantities that make up an aggregate species such as TOG. Of course, the hundred or so
compounds listed in these profiles are not a complete listing, which would likely include
thousands of species. But they are the major species by mass and reactivity. Such a profile is
produced by laboratory analysis of emissions. These are not CM speciation profiles and are
independent of chemical mechanism. Table 4-1 summarizes the speciation profiles we are using
in MOVES, together with the fuels, regulatory classes, and MOVES emission processes to which
they apply. The emission processes associated with the MOVESProcessIDs are identified in
Table 2-2. MOVES processes relevant for speciation profiles.
The source of all the profiles listed in Table 4-1 is SPECIATE 4.4. SPECIATE is the EPA's
repository of volatile organic gas and particulate matter (PM) speciation profiles from air
pollution sources.24 The Speciate Database Project began at EPA in 1988; the current version,
SPECIATE 4.4, was released in February 2014. In 2005, an EPA SPECIATE Workgroup was
formed to assure inclusion of the most current data and to quality-assure the content.25 The
SPECIATE database contains a record of each profile including its referenced source, testing
methods, a subjective rating of the quality of the data, and other detailed data that allow
researchers to decide which profile is most suitable for model input. Table 4-2 lists the
referenced sources of the real speciation profiles used in MOVES.
15

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Table 4-1. Speciation profiles used for onroad TOG emissionsd
Profile
Profile Description
Fuel
Affected Vehicles
MOVES ProcessID



All CNG Transit

1001
CNG Exhaust
CNG
Buses
1,2,15,16
4547
Diesel Headspace
Diesel
All Diesel
11, 12,13,18,19
8753
E0 Evap
E0
All Gas
12,13,19
8754
E10 Evap
E10
All Gas
12,13,19
8756
Tier 2 E0 Exhaust
E0
2001+LD Gas
1,2,15,16
8757
Tier 2 E10 Exhaust
E10
2001+LD Gas
1,2,15,16
8758
Tier 2 E15 Exhaust®
E15, E20
All Gas
1,2,15,16
8766
E0 evap permeation
E0
All Gas
11
8769
E10 evap permeation
E10
All Gas
11
8770
E15 evap permeation
E15, E20
All Gas
11

Pre-2007 MY HDD

Pre-2007 HD

8774
exhaust
Diesel
Diesel
1,2,15,16,17,90

Pre-2007 MY HDD



8774
exhaust
Diesel
All APU
91

Pre-2007 MY HDD



8774
exhaust
Diesel
Pre-2007 LD Diesel
1,2,15,16
8775
2007+ MY HDD exhaust
Diesel
2007+ LD Diesel
1,2,15,16
8775
2007+ MY HDD exhaust
Diesel
2007+ HD Diesel
1,2,15,16,17,90
8855
Tier 2 E85 Exhaust
E85
All Ethanol
1,2,15,16
8869
E0 Headspace
E0
All Gas
18
8870
E10 Headspace
E10
All Gas
18
8871
E15 Headspace
E15, E20
All Gas
18
8872
E15 Evap
E15, E20
All Gas
12,13,19
8934
E85 Evap
E85
All Ethanol
11, 12,13,18,19
8750a
Pre-Tier 2 E0 exhaust
E0
Pre-2001 LD Gas
1,2,15,16



All MC and non-

8750a
Pre-Tier 2 E0 exhaust
E0
LD Gas
1,2,15,16
8751a
Pre-Tier 2 E10 exhaust
RFG, E10
Pre-2001 LD Gas
1,2,15,16



All MC and Non-

8751a
Pre-Tier 2 E10 exhaust
RFG, E10
LD Gas
1,2,15,16
d Appendix B Provides a complete mapping of the TOG speciation profiles to modelYearGroupID, processID,
fuelSubTypelD, and regClassID.
e MOVES2014, as well as the MOVES2014 October release with CB6 installer, incorrectly assigned two speciation
profiles (8751a and 8758) to start and running exhaust associated withpre-2001 MY gasoline vehicles andE15 or
E20 fuels. In MOVES2014a, only speciation profile 8758 is assigned to this vehicle/process/fuel combination as
shown in Table 4-1 and Table B-l. In MOVES2014 runs where this vehicle/process/fuel combination was assigned
the incorrect speciation profiles, the CB05 and CB6 chemical mechanism emissions are incorrect.
16

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Table 4-2. Data sources for the MOVES profiles
Profile
ID
Profile
Name
Source Data
Additional Documentation
1001
Internal
Combustion
Engine -
Natural Gas
Oliver, W. R. and S. H. Peoples, Improvement of the
Emission Inventory for Reactive Organic Gases and
Oxides of Nitrogen in the South Coast Air Basin,
Volumes I and II, Final Report (Prepared for California
Air Resources Board), May 1985.

4547
Gasoline
Headspace
Vapor - Circle
K Diesel -
adjusted for
oxygenates
Internal data collection effort, Charles Lewis, U.S. EPA
Office of Research and Development, with
Ying Hsu, E.H. Pechan & Associates, Inc., personal
communication (t), June 29, 2004.
SPECIATE 4.2. Speciation Database
Development Documentation. Report No.
EPA/600-R-09/038, U.S. EPA, June 2009.
Available at:
http ://¦www. epa. gov/ttn/ chief/ software/speciate/
8750a
Gasoline
Exhaust -
Reformulated
gasoline (pre-
Tier 2)
Kansas City PM characterization Study. Final Report.
EPA 420-R-08-009. U.S. EPA, April 2008. Available
at: http://www.epa.gov/oms/emission-factors-
research/index.htm.
Emission Profiles for EPA SPECIATE Database.
EPA Contract No. EP-C-06-094. Environ
Corporation, January 2008. Available at:
http://www.regulations.gov. Docket ID: EPA-HQ-
OAR-2005-0161, Document ID: EPA-HQ-OAR-
2005-0161-2710.
8751a
Gasoline
Exhaust - E10
ethanol
gasoline (pre-
Tier 2)
Kansas City PM characterization Study. Final Report.
EPA 420-R-08-009. U.S. EPA, April 2008. Available
at: http://www.epa.gov/oms/emission-factors-
research/index.htm.
Emission Profiles for EPA SPECIATE Database.
EPA Contract No. EP-C-06-094. Environ
Corporation, January 2008. Available at:
http://www.regulations.gov. Docket ID: EPA-HQ-
OAR-2005-0161, Document ID: EPA-HQ-OAR-
2005-0161-2710.
8753
Gasoline
Vehicle -
Evaporative
emission -
Reformulated
gasoline
Auto/Oil Air Quality Improvement Research Program.
Coordinating Research Council, 1990-1997. List of
reports at: http://www.crcao.com/reports/auto-
oil/default.htm
Emission Profiles for EPA SPECIATE Database.
EPA Contract No. EP-C-06-094. Environ
Corporation, January 2008. Available at:
http://www.regulations.gov. Docket ID: EPA-HQ-
OAR-2005-0161, Document ID: EPA-HQ-OAR-
2005-0161-2710.
8754
Gasoline
Vehicle -
Evaporative
emission -
E10 ethanol
gasoline
Auto/Oil Air Quality Improvement Research Program.
Coordinating Research Council, 1990-1997. List of
reports at: http://www.crcao.com/reports/auto-
oil/default.htm
Emission Profiles for EPA SPECIATE Database.
EPA Contract No. EP-C-06-094. Environ
Corporation, January 2008. Available at:
http://www.regulations.gov. Docket ID: EPA-HQ-
OAR-2005-0161, Document ID: EPA-HQ-OAR-
2005-0161-2710.
8756
Gasoline
Exhaust - Tier
2 light-duty
vehicles using
0% Ethanol -
Composite
Profile
Data Collected in EPAct Fuel Effects Study Pilot Phases
1 and 2. Memorandum to the Tier 3 Docket. U.S. EPA,
2013 Available at: http://www.regulations.gov. Docket
ID: EPA-HQ-OAR-2011-0135.
Exhaust Emission Profiles for EPA SPECIATE
Database: Energy Policy Act (EPAct) Low-Level
Ethanol Fuel Blends and Tier 2 Light-Duty
Vehicles. EPA Report No. EPA-420-R-09-002.
U.S. EPA, 2009. Available at:
http://www.regulations.gov. Docket ID: EPA-HQ-
OAR-2005-0161, Document ID: EPA-HQ-OAR-
2005-0161-2711.
8757
Gasoline
Exhaust - Tier
2 light-duty
vehicles using
10% Ethanol -
Composite
Profile
Data Collected in EPAct Fuel Effects Study Pilot Phases
1 and 2. Memorandum to the Tier 3 Docket. U.S. EPA,
2013 Available at: http://www.regulations.gov. Docket
ID: EPA-HQ-OAR-2011-0135.
Exhaust Emission Profiles for EPA SPECIATE
Database: Energy Policy Act (EPAct) Low-Level
Ethanol Fuel Blends and Tier 2 Light-Duty
Vehicles. EPA Report No. EPA-420-R-09-002.
U.S. EPA, 2009. Available at:
http://www.regulations.gov. Docket ID: EPA-HQ-
OAR-2005-0161, Document ID: EPA-HQ-OAR-
2005-0161-2711.
8758
Gasoline
Exhaust - Tier
2 light-duty
vehicles using
15% Ethanol -
Composite
Profile
Data Collected in EPAct Fuel Effects Study Pilot Phases
1 and 2. Memorandum to the Tier 3 Docket. U.S. EPA,
2013 Available at: http://www.regulations.gov. Docket
ID: EPA-HQ-OAR-2011-0135.
Exhaust Emission Profiles for EPA SPECIATE
Database: Energy Policy Act (EPAct) Low-Level
Ethanol Fuel Blends and Tier 2 Light-Duty
Vehicles. EPA Report No. EPA-420-R-09-002.
U.S. EPA, 2009. Available at:
http://www.regulations.gov. Docket ID: EPA-HQ-
OAR-2005-0161, Document ID: EPA-HQ-OAR-
2005-0161-2711.
17

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Profile
ID
Profile
Name
Source Data
Additional Documentation
8766
Diurnal
Permeation
Evaporative
Emissions
from Gasoline
Vehicles
using 0%
Ethanol -
Combined -
Composite
Profile
Evaporative Emissions from In-use Vehicles: Test Fleet
Expansion. CRC E-77-2b. SWRI Project No.
03.14936.05. Final report. Available at:
http://www.epa.gov/otaq/emission-factors-research/

8769
Diurnal
Permeation
Evaporative
Emissions
from Gasoline
Vehicles
using 10%
Ethanol -
Combined -
Composite
Profile
Evaporative Emissions from In-use Vehicles: Test Fleet
Expansion. CRC E-77-2b. SWRI Project No.
03.14936.05. Final report. Available at:
http://www.epa.gov/otaq/emission-factors-research/

8770
Diurnal
Permeation
Evaporative
Emissions
from Gasoline
Vehicles
using 15%
Ethanol -
Combined
Evaporative Emissions from In-use Vehicles: Test Fleet
Expansion. CRC E-77-2b. SWRI Project No.
03.14936.05. Final report. Available at:
http://www.epa.gov/otaq/emission-factors-research/

8774
Diesel
Exhaust
Emissions
from Pre-2007
Model Year
Heavy-Duty
Diesel Trucks
Heavy-duty Vehicle Chassis Dynamometer Testing for
Emissions Inventory, Air Quality Modeling, Source
Appointment and Air Toxics Emissions Inventory. CRC
Project No. E-55/E-59, Phase II Final Report.
Coordinating Research Council, July 2005. Available at:
http://www.crcao.com/publications/emissions/index.html

8775
Diesel
Exhaust
Emissions
from 2007
Model Year
Heavy-Duty
Diesel
Engines with
Controls
Phase 1 of the Advanced Collaborative Emissions Study.
Coordinating Research Council, July 2009. Available at:
http://www.crcao.com/publications/emissions/index.html

8855
Gasoline
Exhaust - Tier
2 light-duty
vehicles using
85% Ethanol -
Composite
Profile
EPAct/V2/E-89: Assessing the Effect of Five Gasoline
Properties on Exhaust Emissions from Light-Duty
Vehicles Certified to Tier-2 Standards:-Final Report on
Program Designand Data Collection. EPA-420-R-13-
004. U.S. EPA, April 2013. Available at:
http://www.epa.gov/otaq/models/moves/epact.htm.

8869
Gasoline
Headspace
Vapor - 0%
Ethanol (E0)
Combined -
EPAct/V2/E-
89 Program
Hydrocarbon Composition of Gasoline Vapor Emissions
from Enclosed Fuel Tanks, Report No. 420-R-11-018.
U.S. EPA, December 2011. Available at:
http://www.regulations.gov, Docket ID: EPA-HQ-OAR-
2011-0135, Document ID: EPA-HQ-OAR-2011-0135-
0027.
Mobile Source Hydrocarbon Speciation Profiles
for the Tier 3 Rule NPRM and Anti-backsliding
Study Air Quality Modeling. Memorandum to the
Docket. U.S. EPA, 2013. Available at:
http://www.regulations.gov. Docket ID: EPA-HQ-
OAR-2011-0135, Document ID: EPA-HQ-OAR-
2011-0135-0089.
18

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Profile
ID
Profile
Name
Source Data
Additional Documentation
8870
Gasoline
Headspace
Vapor - 10%
Ethanol (E10)
Combined -
EPAct/V2/E-
89 Program
Flydrocarbon Composition of Gasoline Vapor Emissions
from Enclosed Fuel Tanks, Report No. 420-R-11-018.
U.S. EPA, December 2011. Available at:
http://www.regulations.gov, Docket ID: EPA-HQ-OAR-
2011-0135, Document ID: EPA-HQ-OAR-2011-0135-
0027.
Mobile Source Hydrocarbon Speciation Profiles
for the Tier 3 Rule NPRM and Anti-backsliding
Study Air Quality Modeling. Memorandum to the
Docket. U.S. EPA, 2013. Available at:
http://www.regulations.gov. Docket ID: EPA-HQ-
OAR-2011-0135, Document ID: EPA-HQ-OAR-
2011-0135-0089.
8871
Gasoline
Headspace
Vapor - 15%
Ethanol (El 5)
Combined -
EPAct/V2/E-
89 Program
Hydrocarbon Composition of Gasoline Vapor Emissions
from Enclosed Fuel Tanks, Report No. 420-R-11-018.
U.S. EPA, December 2011. Available at:
http://www.regulations.gov, Docket ID: EPA-HQ-OAR-
2011-0135, Document ID: EPA-HQ-OAR-2011-0135-
0027.
Mobile Source Hydrocarbon Speciation Profiles
for the Tier 3 Rule NPRM and Anti-backsliding
Study Air Quality Modeling. Memorandum to the
Docket. U.S. EPA, 2013. Available at:
http://www.regulations.gov. Docket ID: EPA-HQ-
OAR-2011-0135, Document ID: EPA-HQ-OAR-
2011-0135-0089.
8872
Gasoline
Vehicle -
Evaporative
emission -
E15 ethanol
gasoline -
Calculated
Auto/Oil Air Quality Improvement Research Program.
Coordinating Research Council, 1990-1997. List of
reports at: http://www.crcao.com/reports/auto-
oil/default.htm
EPAct/V2/E-89: Assessing the Effect of Five Gasoline
Properties on Exhaust Emissions from Light-Duty
Vehicles Certified to Tier-2 Standards: Final Report on
Program Design and Data Collection. EPA-420-R-13-
004. U.S. EPA, April 2013. Available at:
http://www.epa.gov/otaq/models/moves/epact.htm.
Mobile Source Hydrocarbon Speciation Profiles
for the Tier 3 Rule NPRM and Anti-backsliding
Study Air Quality Modeling. Memorandum to the
Docket. U.S. EPA, 2013. Available at:
http://www.regulations.gov. Docket ID: EPA-HQ-
OAR-2011-0135, Document ID: EPA-HQ-OAR-
2011-0135-0089.
8934
Evaporative
Emissions
from Flexible-
Fuel Gasoline
Vehicles
using 85%
Ethanol
Exhaust and Evaporative Emissions Testing of Flexible-
Fuel Vehicles. Final report. CRC Report CRC-E-80.
Coordinating Research Council, Inc. August 2011.
Report and program data available at
http://www.crcao.org/publications/emissions/index.html

4.3. Mapping of Real Species to Chemical Mechanism Species and
of Residual TOG to Chemical Mechanism Speciation Profiles
The mapping of real species to CM species is mechanism-specific. Each chemical mechanism
maps real organic gas species to one or more CM species. Air quality models use these CM
species to model atmospheric chemistry. CB05, CB6CMAQ, and SAPRC07T are three widely
used chemical mechanisms for air quality modeling that are incorporated into MOVES2014b.
Emission estimates for species calculated directly by MOVES are based on more detailed and
accurate information than those estimated using the TOG speciation profiles; therefore, we use a
process called "integration" to subtract these species from the TOG speciation profiles. In
MOVES2014b, the integration process removes the 16 pollutants in Table 2-1 from the TOG
speciation profiles to leave residual-TOG (often called NONHAPTOG) speciation profiles,
which are renormalized without the integrated species. The mapping of both integrated species
and NONHAPTOG to chemical mechanism species is initially performed outside of MOVES by
a program called the Speciation Tool.26 This mapping is then incorporated into a table in the
MOVES2014b default database that maps both integrated species and NONHAPTOG to
chemical mechanism species during MOVES runs. After MOVES performs this mapping, all the
occurrences of each CM species are summed to produce the final output of chemical mechanism
species.
19

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Regular MOVES output is unchanged. All chemical mechanism species are in units of moles.
Because this process is table driven, MOVES is capable of providing CM species for multiple
chemical mechanisms. In MOVES2014b, the CB05, CB6CMAQ, and SAPRC07T mechanisms
are implemented. Figure 1 is a diagram of the process of TOG speciation for air quality
modeling.
20

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Speciation profiles
with all measured species
(e.g., based on EPAct data)
MOVES
Acetaldehyde
Formaldehyde
Benzene
Other
individual
species to be
integrated

speciation
Speciation of
each
integrated
species
Speciation of
Residual TOG
with
renormalized
profile
Summed CM species
Speciate
Tool
Tool for mapping
measured species into
CM species
New CM species profiles
renormalized without
integrated species
SMOKE
Air Quality Model
Figure 1. Diagram of the process of TOG speciation for air quality modeling as it occurs with MOVES2014
21

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5. PM2.5 Speciation
5.1. Overview
Modeling PM2.5 in CMAQ does not use simplifying chemical mechanisms, and the PM2.5 species
are input directly into the model. CMAQv5.0, which uses the CMAQ Aerosol Module, version 6,
or "AE6", requires 18 PM2.5 species as outlined in Table 5-127 Theses PM species are
compatible with previous versions of CMAQ and with the Comprehensive Air Quality Model
with Extensions (CAMx) as shown in Table 5-1, and will be beneficial to air-quality agencies
and researchers who use different air quality models.
Table 5-1. PM2.5 species required in CMAQv5.0 (this version uses the CMAQ Aerosol Module, version 6, or
"AE6")27, CMAQv4.7.1 (this version uses the CMAQ Aerosol Module, version 5, or "AE5"), and CAMx5.428
PM2 5 Species
CMAQv5.0
Species Name
Required in
CMAQv4.7.1
Required in
CAMx5.4
Primary organic carbon
POC
X
X
Elemental carbon
PEC
X
X
Sulfate
PS04
X
X
Nitrate
PN03
X
X
Ammonium
PNH4
X
X
Non-carbon organic matter
PNCOM

X
Iron
PFE


Aluminum
PAL


Silicon
PSI


Titanium
PTI


Calcium
PCA


Magnesium
PMG


Potassium
PK


Manganese
PMN


Sodium
PNA

X
Chloride
PCL

X
Particulate water
PH20

X
Primary unspeciated PM2 5f
PMOTHR
X
X
MOVES2014 is designed to produce all PM2.5 species required by CMAQv5.0. Previous
versions of MOVES (2010b and earlier) produced PM2.5 in the form of three PM2.5 species:
elemental carbon (EC), organic carbon (OC) and sulfate (SO4). Substantial post-processing of
MOVES PM2.5 outputs was needed to provide PM emissions inventories that could be
transformed by SMOKE into ready-inputs of speciated PM2.5 for CMAQ. For example,
MOVES2010b did not output nitrate, ammonium, and metals. These compounds were assumed
f The definition of the unspeciated PM2 5 depends on the set of identified PM2 5 species in each air quality model.
22

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to be included in the OC emission rates of PM2.5. This division required post-processing the
MOVES2010b OC emissions using PM2.5 speciation profiles, and created differences between
OC as defined by MOVES2010b and the post-processed OC used for air quality modeling.
MOVES2014 removes the distinction by defining OC consistently with air quality models as
defined in the glossary.
5.2. Steps
Figure 2 and Figure 3 provide an overview of the algorithm used to calculate speciated and total
exhaust PM emission rates in MOVES2014. The steps used to calculate PM2.5 emissions and
PM2.5 speciation are outlined in nine steps below. Additional details are provided in the
MOVES2014 Software Design Reference Manual29. Steps 1 - 4 are outlined in Figure 2.
Base EC and
NonECPM
exhaust emission
rates
at 72°
by polProcessID,
OpModelD,
ageGroupID,
SourceBinID
EC, NonECS04PM, S04, and
H20 exhaust emissions
adjusted by fuel and
temperature effects. Effects
differ by polProcessID
SourceType,fuelTypelD,
modelYearRangelD
NonEC
nonS04
PM
S04 fraction
by polProcessID,
SourceType,
fuelTypelD,
modelYearRangelD
Figure 2. Flow Chart of Calculation of the Intermediate PM2.5 Emission Rates
23

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Step 1. MOVES2014 stores PM2.5 exhaust emission rates by pollutant process (start, running,
extended idle), operating mode, sourcebin (fuelType, engine technology, regulatory class, model
year), and vehicle age. MOVES2014 stores base exhaust rates for PM2.5 divided into two primary
components (EC and nonECPM). The base rates are stored by EC and nonECPM so that the
EC/PM2.5 ratio can vary across operating modes. EC is formed within the engine due to pyrolysis
of fuel droplets in the engine, and researchers have determined that EC emissions from
conventional diesel engines are strongly correlated with the air-fuel ratio30. Within MOVES,
modal EC/PM ratios were developed as documented in the Exhaust Emission Rates for Heavy-
Duty On-road Vehicles in MOVES2014 Report30. Modal EC/PM2.5 ratios have not been
developed for other vehicle types (gasoline, CNG, ethanol, and modern diesel), so the EC and
NonECPM emission rates for these soucetypes and fuels have a constant ratio across operating
modes.
Step 2. MOVES2014 calculates sulfate and particulate water emissions from the nonECPM
using values obtained from the PM2.5 speciation profiles. S04 and H20 (particulate water)
emissions are calculated as a function of the nonECPM rates using the fuel sulfur level for the
model run, the fuel sulfur level used to develop the base PM emission rates, and the fraction of
sulfate coming from the fuel in the base PM emission rates, as described in the sulfate
calculator.32 The remaining nonECPM is renamed nonECnonS04PM. This intermediate species
contains organic matter, elements, ions, and the unspeciated portion of PM2.5.
Step 3. The intermediate PM species are adjusted for temperature effects such as inefficient
oxidation of emissions at cool catalyst temperatures and additional fuel needed to start an engine
at cold temperatures. The temperature effects can differ by intermediate species, process (e.g.
start exhaust, running exhaust, extended idle), model year groups, and fuel type. Currently,
temperature effects only apply to gasoline and ethanol-blend fueled vehicles. Currently, the EC,
nonECnonS04PM, S04, and H20 emissions are each adjusted using the same temperature
adjustments, because our data does not support individual temperature adjustments.37 The
temperature effects are documented in the report: Emission Adjustments for Temperature,
Humidity, Air Conditioning and Inspection and Maintenance for On-road Vehicles in
MOVES2014.31
Step 4. MOVES2014 adjusts the intermediate species (EC and NonECnonS04PM) according to
fuel effects. EC and nonECnonS04 are adjusted according to fuel properties depending on the
applicable model (e.g. EPAct model for 2001 and later light-duty gasoline). The fuel adjustments
and calculators are described in the Fuel Effects Report.32
Steps 5 - 8 are outlined in Figure 3.
24

-------
Exhaust and crankcase intermediate
PM2.5 species. Individual ratios for EC,
NonECnonS04PM,S04, and H20. Ratios
differ by polProcessID SourceType,
fuelTypelD, modelYearRangelD
EC Exhaust
Factor
EC Crankcase
Factor

nonS04
PM

NonECnonSCW
PM Exhaust
Factor
f NonECnonSCW
] PM Crankcase
¦ Factor
S04/H20
Exhaust
Factor
f S04/H20
| Crankcase
! Factor
Speciated PM2.5 emissions
by ProcessID (start/running/extended
idle exhaustand
start/running/extended idle crankcase
emissions),
SourceTypelD,fuelTypelD,
modelYearRangelD
NonEC
nonS04
PM
PMOther
nonS04
PM

Fe,AI,Si,Ti
Ca, Mg,K,
N03, NH4
PMOther
PM10 calculated
from totalPM2.5.
PM10/PM2.5 factors
by ProcessID,
SourceTypelD,
fuelTypelD,
modelYearRangelD
Tota
Exhaust
PM10
PM10/
PM2.5
Total
Exhaust
PM2.5
Sum intermediate
PM2.5 species to
output TotalPM2.5.
C Total ^
Crankcase I
PM10
PM10/
PM2.5
Total
Crankcase I
PM2.5 ^
Figure 3. Flow Chart of Calculation of exhaust and crankcase PM2.5 and PM10 emission rates, and PM2.5
exhaust and crankcase speciation
Step 5. Exhaust and crankcase emissions are calculated from the intermediate exhaust PM2.5
species (EC, NonECnonS04PM, S04, and H20), after the intermediate exhaust species have
been adjusted for fuel effects and temperature effects. The exhaust and crankcase emissions are
calculated from the intermediate exhaust rates with exhaust and crankcase ratios that can vary
25

-------
according to pollutant, process, source type, fuel type, and model year range as shown in Table
5-2.
For 2007 and later diesel engines, crankcase emissions are measured with exhaust emissions in
the certification data. The exhaust and crankcase emission ratios are used to split the PM rates
into exhaust and crankcase emissions. For 2007-and-later diesel, the exhaust and crankcase ratios
sum to one for each PM subspecies.
For other vehicles types (pre-2007 diesel, gasoline, CNG vehicles), this step accounts for the PM
crankcase emissions that are not measured in the exhaust emission rates (i.e., the exhaust and
crankcase ratios sum to greater than one for each PM subspecies). The exhaust emissions remain
constant in this step.
The sources of the diesel crankcase emission factors are documented in the heavy-duty exhaust
emissions rates report30 and the gasoline crankcase emission factors are documented in the light-
duty exhaust emissions rates report33. The factors are applied by intermediate subspecies, to
account for differences in PM2.5 speciation between crankcase and tailpipe particulate matter
emissions. MOVES2014 models different PM composition between exhaust and crankcase
emissions for pre-2007 conventional diesel, using the exhaust and crankcase ratios as shown in
Table 5-2.
Table 5-2. Exhaust and Crankcase Ratios by Pollutant, Process, Model Year Group, and Fuel Type, and
				Source Type		


Motor-
cycles
1960-1968
Gasoline,
1960-2000
Light-Duty
Diesel
1969-2050
Gasoline/CNG,
2000-2050
Light-Duty
Diesel
1960-2006 Heavy-Duty
Diesel
2007-
2050
Heavy-
Duty
Diesel
Pollutant

All
All
All
Start
Running
Extended
Idle
All
EC
Exhaust
1
1
1
1
1
1
0.62
nonECnonS04-
PM
1
1
1
1
1
1
0.62
S04
1
1
1
1
1
1
0.62
H20
1
1
1
1
1
1
0.62
EC
Crankcase
0
0.2
0.008
0.009
0.004
0.012
0.38
nonECnonS04-
PM
0
0.2
0.008
0.295
0.954
0.268
0.38
S04
0
0.2
0.008
0.295
0.954
0.268
0.38
H20
0
0.2
0.008
0.295
0.954
0.268
0.38
Step 6. The exhaust intermediate species and the crankcase intermediate species are summed to
calculate primary exhaust PM2.5 emissions. The intermediate species are used instead of the fully
speciated PM2.5 emissions to save computational time during MOVES runs.
Step 7. MOVES2014 calculates primary exhaust and crankcase PM10 emissions from the primary
PM2.5 emissions using PM10/PM2.5 ratios. The MOVES2014 PM10/PM2.5 ratio used for primary
26

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exhaust and crankcase emissions are listed in Table 5-3. MOVES2014 has the capability to apply
separate ratios by source type, emission process, and model year. At present, a single value of the
PM10/PM2.5 ratio is used for all source types, emission processes, and model years for primary
exhaust and crankcase emissions. No speciation is conducted within MOVES2014 for PM10
emissions, because it is not needed for air quality modeling purposes8'34. The derivation of the
PM10/PM2.5 ratio is presented in Appendix D.
Table 5-3 PM10/PM2.5 Ratios for Primary Exhaust and Crankcase Emissions

PM10/PM2.5
gasoline
1.130
diesel
1.087
Step 8. MOVES2014 calculates speciated PM2.5 emissions, by applying speciation profiles to the
adjusted nonECnonS04 fraction to calculate the individual PM2.5 species. The data sources and
documentation for the PM2.5 profiles are included in Table 5-4. Each of the PM2.5 profiles for use
in MOVES2014 was created or updated recently, thus we included documentation of their
development in Appendix C.
Table 5-4. MOVES2Q14 PM2.5 Speciation Profiles
Profile ID
Profile
Name
Profile
Source
Source Data
8992
Light-duty
Gasoline
Exhaust - Start
SPECIATE 4.4
Kansas City PM characterization Study. Final Report. EPA 420-R-08-009. U.S.
EPA, April 2008. Available at: http://www.epa.gov/oms/emission-factors-
research/index.htm.
8993
Light-duty
Gasoline
Exhaust- Hot
Stabilized
Running
SPECIATE 4.4
Kansas City PM characterization Study. Final Report. EPA 420-R-08-009. U.S.
EPA, April 2008. Available at: http://www.epa.gov/oms/emission-factors-
research/index.htm.
8994
Conventional
HDD - Idle
SPECIATE 4.4
Clark, N.N. and Gautam, M. HEAVY-DUTY Vehicle Chassis Dynamometer
Testing for Emissions Inventory, Air Quality Modeling, Source Apportionment and
Air Toxics Emissions Inventory. August 2007. CRC Report. No. E55/59
8995
Conventional
HDD - Hot
Stabilized
Running
SPECIATE 4.4
Clark, N.N. and Gautam, M. HEAVY-DUTY Vehicle Chassis Dynamometer
Testing for Emissions Inventory, Air Quality Modeling, Source Apportionment and
Air Toxics Emissions Inventory. August 2007. CRC Report. No. E55/59
8996
2007 and Newer
Diesel Exhaust
Composite
SPECIATE 4.4
Khalek, I. A.; Bougher, T. L; Merrit, P. M.; Phase 1 of the Advanced Collaborative
Emissions Study. CRC Report: ACES Phase 1, June 2009.
95219
CNG transit bus
exhaust from a
lean-burn engine
- no
aftertreatment
Next release of
SPECIATE
Okamoto, R. A.; Kado, N. Y.; Ayala, A.; Gebel, M.; Rieger, P.; Kuzmicky, P. A.;
Kobayashi, R.; Chemical and Bioassay Analyses of Emissions from Two CNG
Buses with Oxidation Catalyst, http://www.arb.ca.gov/research/veh-emissions/cng-
diesel/cng-diesel.htm.
95220
CNG transit bus
exhaust from a
lean-burn engine
- oxidation
catalyst
Next release of
SPECIATE
Okamoto, R. A.; Kado, N. Y.; Ayala, A.; Gebel, M.; Rieger, P.; Kuzmicky, P. A.;
Kobayashi, R.; Chemical and Bioassay Analyses of Emissions from Two CNG
Buses with Oxidation Catalyst, http://www.arb.ca.gov/research/veh-emissions/cng-
diesel/cng-diesel.htm.
g Within CMAQv5.0, the US EPA assumes a single speciation profile for all anthropogenic coarse PM34.
27

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The PM2.5 profiles used for the applicable source type, fuel, pollutant process, and model year
ranges are shown in Table 5-5.
Table 5-5. Application of MOVES2Q14 PM2.5 Speciation Profiles
Profile ID
Description
Fuel
Affected Vehicles
MOVES ProcessID
8992
Light-duty Gasoline Exhaust -
Start
All gasoline
vehicles (E0
to E85)
All model years
2,16
8993
Light-duty Gasoline Exhaust-
Hot Stabilized Running
All gasoline
vehicles (E0
to E85)
All model years
1,15
8994
Conventional HDD - Idle
Diesel
Pre-2007 and all
MY auxiliary power
units
2,16,17,90,91
8995
Conventional HDD - Hot
Stabilized Running
Diesel
Pre-2007
1,15
8996
2007 and Newer Diesel
Exhaust Composite
Diesel
2007+
1,2,15,16,17,90
95219
CNG transit bus exhaust from
a lean-burn engine - no
aftertreatment
CNG
pre-2002 transit
buses
1,2,15,16,17,90
95220
CNG transit bus exhaust from
a lean-burn engine - oxidation
catalyst
CNG
2002+ transit buses
1,2,15,16,17,90
MOVES2014 uses two light-duty gasoline profiles to characterize PM2.5 emissions from all
gasoline vehicles, including motorcycles, light-duty passenger cars and trucks, and medium and
heavy-duty gasoline trucks and buses.
The pre-2007 diesel profiles are used to represent all pre-2007 on-highway diesel vehicles in
MOVES, including light-duty passenger cars and trucks, medium, and heavy-duty trucks, and
diesel buses. Tailpipe exhaust and crankcase nonECnonS04 emissions emitted during extended
idle and start are speciated using the Idle Profile (8994). Tailpipe exhaust and crankcase
nonECnonS04emissions emitted during running operation are speciated using the running
profile (8995). In addition, the idle profile (8994) is used to characterize
nonECnonS04emissions from diesel-powered auxiliary power units used on heavy-duty diesel
trucks.
The ACES Phase 1 profile (8996) is used for all 2007-and-later diesel sources, including light-
duty passenger cars and trucks, medium and heavy-duty trucks and diesel buses. The ACES
Phase 1 16-hour cycle is used to develop the profile, which includes both exhaust and crankcase
emissions, as well as start, extended idle and running emission processes. For this reason, the
composite profile is also used to speciate all emission processes for 2007-and-later diesel
engines.
28

-------
The CNG compression ignition profile is applied to the pre-2002 model CNG transit buses, and
the CNG profile with oxidation catalyst profile is applied to the 2002+ model year CNG transit
buses. This technology is determined to be most representative of the available PM2.5 speciation
data according to the analysis conducted in the heavy-duty vehicle emissions rate report30.
Step 9. (Not shown in Figure 2 or 3). MOVES2014 calculates additional particulate-phase
species, required for the National Emission Inventory (NEI) and National Air Toxics Assessment
(NATA). Listed in Table 5-6, these include: manganese, nickel, chromium, arsenic, and
particulate mercury. The metals are emitted in exhaust as PM2.5, but are calculated with a
separate calculator than the other PM2.5 species. The emission rates for these metals are not
chained from NonECS04PM, but are provided with their own mass/distance rates as
documented in the Air Toxic Emissions Report4. The mass of these compounds is not used in the
summation to calculate PM2.5 due to the very small mass, but they are important PM2.5 exhaust
species from a health effects perspective. Of the toxic metals, CMAQv5.0 only requires
manganese as a required PM2.5 species. By default, MOVES2014 calculates manganese emission
rates when the user requests PM2.5 speciation. Chromium, nickel, arsenic, and particulate
mercury emission rates are produced when requested by the user.
Table 5-6. Metal Air Toxics produced by MOVES2014
Pollutant
Chromium 6+
Manganese
	Nickel	
Particulate Hg
Arsenic
29

-------
Appendix A Methods used to derive NMOG/NMHC and
VOC/NMHC parameters
A.1 Background
In MOVES, the base organic gas emission rates are in terms of total hydrocarbon emissions
(THC). THC emissions are operationally defined by a FID. Other measures of organic gas
emissions include nonmethane hydrocarbon (NMHC) emissions, non-methane organic gas
(NMOG) emissions, volatile organic gas emissions (VOC), and total organic gas emissions
(TOG). Definitions for each of these emissions are provided in the glossary in the main chapter.
NMHC, NMOG, VOC, and TOG are referred to as 'chained pollutants' because we calculate
their emissions based on the emissions of THC and other variables. Two important inputs to
these calculations are the NMOG/NMHC ratio and the VOC/NMHC ratio. The sections below
explain how these ratios are used and how they were derived.
A. 2 NMOG/NMHC Meth od Description
NMOG emissions are calculated from NMHC emissions using Equation 3, provided below.
NMOG = NMHC ¦
\speciationConstant + £f=i(oxySpeciation ¦ oxyMassFractioni ¦	Equation 3
oxyV olumei)]
Where:
i = one of four gasoline oxygenates: ethanol, methyl tert-butyl ether (MTBE), ethyl tert-butyl
ether (ETBE), or tert-amyl methyl ether (TAME).
SpeciationConstant =the NMOG/NMHC conversion factor when the gasoline has no oxygenate
volume.
oxySpeciation = an empirically derived value that adjusts the NMOG/NMHC according to
oxidation volume.
oxyMassFractiorii = the mass fraction of oxygen within each of the gasoline oxygenates. The
oxygen mass fraction is included in Equation 3 to adjust the oxySpeciation factor relative to the
mass fraction of oxygen in the fuel. Due to limited data, we assume that the oxySpeciation
relationship is linearly proportional to the oxygen content of the fuel oxygenate.
oxyVolumei = the percent volume of each gasoline oxygenate in the respective fuel.
Two methods were used to calculating the SpeciationConstants and oxySpeciation constants for
Equation 3. The formulation of Equation 3 is generic enough to use ratios calculated using either
methods. For fuel with similar fuel properties, the two methods give equivalent results.
30

-------
A. 2.1 Method 1
The first method is documented in a technical report used to develop VOC emission inventories
for Mobile4.1 14 This method was used in subsequent versions of MOBILE and MOVES. It is
used to derive the NMOG/NMHC ratio for all light-duty gasoline vehicles, and diesel vehicles in
MOVES. This method is based on the relative carbon fraction within each species. This method
calculates the measured mass per carbon molecule by the FID (as NMHC in the denominator),
and compares it to the true mass per carbon molecule of the exhaust (calculated as NMOG in the
nominator). The equation form is shown below. It uses measurements of three oxygenated
species: formaldehyde (HCHO), acetaldehyde (C2H40), and ethanol (C2H50H), and all other
organic emissions are classified as NMHC.
The equation form of this method is below:
NMOG _ (CFhcHoMPChcHo) ^ (CFacetald-MPCacetald) (^^EtOH MPCEtoH ) +	) E(|U ilti0H 8
NMHC FID	[(CFacetald FID&ce\a\&) (^^EtOH -^^EtOH) + fC^NMHC^NMHC^ X MPC
NMHC
Where:
CF = carbon fraction
MFC = mass per carbon
FIDx = FID response factor
As documented in the Mobile4.1 technical memorandum14 describing this method, the assumed
values for the mass per carbon, and the FID response factors are:
Table A-l. Mass per Carbon and FID response factors
Compound
Mass per carbon (MPC) (g/gC)
FID response factor
Gasoline Exhaust HC
13.8758
1.0
Formaldehyde
30.0264
0
Acetaldehyde
22.0267
0.50
Ethanol
23.0347
0.80
MTBE
17.6301
0.90
For Tier 2 vehicles, the original values from MOBILE4.1 were used, with the exception that the
FID response for ethanol was updated with analysis done at Southwest Research Institute for the
EPAct test program35 using a FID response of 0.74, and mass/carbon of 23.0347.
This method was used for the development of the NMOG/NMHC ratios for per-Tier 2 gasoline
vehicles, and pre and post-2007 diesel vehicles in MOVES2014.
31

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A.2.2 Method2
The second method used to develop NMOG/NMHC parameters is the measurement method
outlined in the Code of Federal Regulations36. Rather than using relative concentrations of each
species, this method uses the absolute concentrations to calculate NMOG/NMHC. Using the
same notation as the federal register, the mass of NMOG is calculated from the mass of NMHC,
the important oxygenated species, the FID response of the oxygenated species, and the density of
each of the species, as shown in Equation 9 (Equation 1066.635-1 in the Federal Register):
N mr
w
"'nmog
= m -o ¦ V 0HCi • RF	+V/«	Equation 9
"'NMHC A^NMHC	OHCirTHC.-FTDl ^ / /"OHCi
i=1 PoHCi	i= 1
Where:
= the sum of the mass of NMOG in the exhaust.
wnmhc = the mass of NMHC and all oxygenated hydrocarbons (OHCs) in the exhaust, as
determined using Eq. 1066.605-1. Calculate NMHC mass based on />nmhc.
jOnmhc = the effective Ci-equivalent density of NMHC as specified in §1066.1005(f):.
in OHCi = the mass of oxygenated species i in the exhaust calculated using Eq. 1066.605-1.
pocHi = the Ci-equivalent density of oxygenated species i.
i?FoHCi[THc-FiD] = The response factor of a THC-FID to oxygenated species i relative to propane
on a Ci-equivalent basis as determined in 40 CFR 1065.845.
In this method, the NMOG is estimated from the NMHC. The NMOG/ NMHC ratio is then
calculated by dividing the estimated NMOG from the NMHC measurements. This method is
used to calculate the NMOG/NMHC ratio for CNG vehicles as documented in the Exhaust
Emission Rates for Heavy-duty On-Road Vehicles in MOVES2014 Report.30
A. 2.3 Comparison of the Two Methods
The first method is based on the relative carbon mass fraction of each species, while the second
method is based on the absolute mass of each species. Because both methods are used to supply
NMOG/NMHC ratios in MOVES2014, we applied both methods to demonstrate that they
provide consistent NMOG/NMHC ratios. We used summary data reported for LDGV (3-way)
catalysts in the MOBILE4.1 documentation14, shown in Table A-2 below.

Mass fraction
Mass/carbon
Carbon fraction
Ethane
0.0350
1.2518
0.3913
Formaldehyde
0.0119
30.0264
0.0055
Acetaldehyde
0.0056
22.0267
0.0036
Gasoline NMHC
0.9825
13.8758
0.9909
32

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Example, Method 1:
NMOG (0.0056 X 30.0264) + (0.0036 X 22.0267) + (0.9909 X 13.8758)
NMHC ~ [(0.0036 X 0.5) + (0 X 0.8) + (0.9909 X 1)] X 13.8758
NMOG 13.9940
= 1.01599
NMHC 13.7742
Example, Method 2:
Assume 0.9825 grams of NMOG, 0.0119 grams of Formaldehyde, and 0.0056 grams of
Acetaldehyde, to be equivalent masses with the relative mass fractions in Table A-2.
NMOG _ 0-9825 - 576.816 X	X 0 +	X 0.5] + 0.119 + 0.0056
NMHC ~	0.9825
NMOG 0.9982
= 1.01602
NMHC 0.9825
As shown, the two methods yield the same NMOG/NMHC fractions to five significant figures.
The comparability of the methods depends on the exhaust composition of the fuels, and this
comparison is not comprehensive. However, considering that different assumptions were used
regarding the carbon fraction/density of the NMHC, we believe the agreement of the methods to
be well within the uncertainty of the emission measurements used as input into MOVES. As
such, we have used both methods in MOVES for developing NMOG/NMHC ratios.
A. 3 VOC/NMHC Meth od Description
Volatile Organic Compounds (VOC) are defined as the reactive organic gases that contribute to
ozone formation. For MOVES, VOCs are defined as NMOG minus ethane and acetone. Within
MOVES, VOC emissions are calculated from NMHC emissions using Equation 5, provided
below.
VOC = NMHC ¦
\speciationConstant + Hf=1(oxySpeciation ¦ oxyMassFractiorii ¦	Equation 5
oxyVolumei)]
Where:
/ = one of four gasoline oxygenates: ethanol, methyl tert-butyl ether (MTBE), ethyl tert-butyl
ether (ETBE), or tert-amyl methyl ether (TAME).
SpeciationConstant = VOC/NMHC conversion factor when the gasoline has no oxygenate
volume.
oxySpeciation = empirically derived value that adjusts the VOC/NMHC according to oxidation
volume.
oxyMassFractiorii = the mass fraction of oxygen within each of the gasoline oxygenates (shown
in Table A-l). The oxygen mass fraction is included in Equation 5 to adjusts the oxySpeciation
33

-------
factor relative to the mass fraction of oxygen in the fuel. Due to limited data, we assume that the
oxySpeciation relationship is linearly proportional to the oxygen content of the fuel oxygenate.
oxyVolumei = the percent volume of each gasoline oxygenate in the respective fuel.
As for NMOG, the VOC/NMHC ratio coefficients are calculated using two methods. Both
methods are described using examples.
A. 3.1 Method 1
Method 1 is the method documented in the Mobile4.1 documentation14, and uses the same
methodology as for NMHC, except the ethane fraction is subtracted from the nominator term, as
shown in Equation 10.
voc
NMHCfid	Equation
(CFHCHO MPCnCno) + (CT^acetald MPCacetald/' + (C^EtOH ^^EtOH ) + (^^NMHC^^^NMHC ) ~~ (pFethaneMPCetham )
[(CT^acetald FIDzxb&i) + (C^EtOH '^•®E10h) (^^NMHC^®NMHC)] X ^^^NMHC
Where:
CF = carbon fraction
MPC = mass per carbon
FIDx = FID response factor
A.3.2 Method2
Method 2 is consistent with the Federal Register method in calculation of NMOG. After NMOG
is calculated using Equation 9, VOC is calculated by subtracting ethane and acetone from
NMOG as shown in Equation 11. We assume that the FID response factor for ethane is 1.0.
_	Equation 11
mVOC ~ mNMOG methane macetone
A. 3.3 Comparison of the Two Methods:
Again, we used the data presented in Table A-2 to evaluate the two methods.
Example, Method 1:
VOC (0.0056 X 30.0264) + (0.0036 X 22.0267) + (0.9909 X 13.8758) - (0.3913 X 1.2518)
NMHC
Example, Method 2
[(0.0056 X 0) + (0.0036 X 0.5) + (0.9909 X 1)] X 13.8758
NMOG 13.5046
NMHC 13.7742
= 0.98043
34

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VOC 0.9982 - 0.350 0.9632
	=	=	= 0.98039
NMHC	0.9825	0.9825
As shown, the two methods yield the same VOC/NMHC fractions to four significant figures in
the example calculation. Numerically, the methods are shown to give equivalent VOC/NMHC
parameters for emission modeling purposes.
A. 3.4 Estimating the OxySpeciation Constant
Equation 3 and Equation 5 enable the calculation of NMOG/NMHC and VOC/NMHC as a
function of gasoline oxygenates (primarily ethanol), using the oxySpeciation constant, an
empirically derived value that adjusts the NMOG/NMHC or VOC/NMHC ratio according to the
oxygen content.
While either of the methods in the previous section could be used to derive this constant, we
used Method 1 to estimate NMOG/NMHC and VOC/NMHC at E0 and E10. The effect of the
oxygenate blend level was estimated using a linear interpolation between these two values with
the intercept term representing the NMHC/NMOG ratio (or VOC/NMOG) at E0. The
oxySpeciation constants for pre-2001 model year vehicles were derived from data used in
SPECIATE profiles 1313 and 1314, and for 2001+ model year vehicles were derived from data
used in SPECIATE profiles 8756 and 8757. The gasoline oxySpeciation factors for NMOG and
VOC are displayed in Table 3-3 and Table 3-5, respectively.
The scalar oxyMassFraction is included in Equation 3 and Equation 5 so that relationships
developed from one oxygenate (e.g. ethanol) can be applied to other gasoline oxygenates in
MOVES. We assume that the gasoline oxygenate impact on the NMOG/NMHC and
VOC/NMHC ratio is directly related to the oxygen mass content. As such, the impact of the
gasoline oxygenates in Equation 3 and Equation 5 are directly proportional to the oxygenate fuel
volume, and the mass fraction of oxygen in the oxygenate (oxyMassFraction).
35

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Appendix B TOG Speciation Map
Table B-l provides a complete speciation map between MOVES profiles and the distinguishing
factors used in MOVES: modelYearGroupID, processID, fuelSubTypelD, and regClassID. This
is more complete than the more readable Table 4-1 provided in the text.
36

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Table B-l. TOG Speciation Map

Profile
modelYear-



Profile
Description
GroupID
processID
fuelSubTypelD
regClassID
1001
CNG Exhaust
19602050
1,2,15,16
30
48

Diesel




4547
Headspace
19602050
11
20,21,22
0

Diesel




4547
Headspace
19602050
12,13,18,19
20,21,22
10,20,30,40,41,42,46,47,48
8753
E0 Evap
19602050
12,13,19
10
10,20,30,40,41,42,46,47,48
8754
E10 Evap
19602050
12,13,19
12,13,14
10,20,30,40,41,42,46,47,48

Tier 2 E0




8756
Exhaust
20012050
1,2,15,16
10
20,30

Tier 2 E10




8757
Exhaust
20012050
1,2,15,16
12,13,14
20,30

Tier 2 E15




8758
Exhaust6
19602050
1,2,15,16
15,18
10,20,30,40,41,42,46,47,48
8766
EO evap
permeation
19602050
11
10
0
8769
E10 evap
permeation
19602050
11
12,13,14
0
8770
El5 evap
permeation
19602050
11
15,18
0

Pre-2007 MY




8774
HDD exhaust
19602006
1,2,15,16,17,90
20,21,22
40,41,42,46,47,48

Pre-2007 MY




8774
HDD exhaust
19602050
91
20,21,22
46,47

Pre-2007 MY




8774
HDD exhaust
19602006
1,2,15,16
20,21,22
20,30

2007+ MY




8775
HDD exhaust
20072050
1,2,15,16
20,21,22
20,30

2007+ MY




8775
HDD exhaust
20072050
1,2,15,16,17,90
20,21,22
40,41,42,46,47,48

Tier 2 E85




8855
Exhaust
19602050
1,2,15,16
50,51,52
10,20,30,40,41,42,46,47,48
8869
E0 Headspace
19602050
18
10
10,20,30,40,41,42,46,47,48
8870
E10 Headspace
19602050
18
12,13,14
10,20,30,40,41,42,46,47,48
8871
E15 Headspace
19602050
18
15,18
10,20,30,40,41,42,46,47,48
8872
El5 Evap
19602050
12,13,19
15,18
10,20,30,40,41,42,46,47,48
8934
E85 Evap
19602050
11
50,51,52
0
8934
E85 Evap
19602050
12,13,18,19
50,51,52
10,20,30,40,41,42,46,47,48

Pre-Tier 2 E0




8750a
exhaust
19602000
1,2,15,16
10
20,30

Pre-Tier 2 EO




8750a
exhaust
19602050
1,2,15,16
10
10,40,41,42,46,47,48

Pre-Tier 2 E10




8751a
exhaust
19602000
1,2,15,16
11,12,13,14
20,30

Pre-Tier 2 E10




8751a
exhaust
19602050
1,2,15,16
11,12,13,14
10,40,41,42,46,47,48
37

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Appendix C Development of PM2.5 speciation profiles in
MOVES2014
MOVES2014 includes updated PM2.5 exhaust speciation profiles. For MOVES2014, updated
PM2.5 profiles were developed for gasoline sources and conventional diesel sources. The new
profiles were developed to be consistent with the data used to derive the PM2.5 emission rates,
and to take advantage of the added capability of MOVES2014. This report includes the
derivation of each PM2.5 profiles used in MOVES2014.
Details on the PM2.5 species are provided in this report because 1) the new PM2.5 profiles were
developed specifically for MOVES2014 and 2) the updated PM2.5 speciation profiles change the
EC, OC, and the total PM2.5 emission rates. MOVES2014 applies separate fuel effects to PM2.5
components and then sums the components to calculate the total exhaust PM2.5. Thus, the
updated speciation profiles change the primary PM2.5 exhaust emission rates from MOVES2014
compared to MOVES2010b. The PM2.5 profiles are presented here so that users can understand
the reasons for these differences.
For comparison purposes, the seven PM2.5 profiles developed for MOVES are presented in Table
C-l. In the following subsections, the analyses to derive each of these profiles are presented.
38

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Table C-l. PM2.s Profiles developed for MOVES2Q14

Light-duty Gasoline Exhaust
- Start (8992)
Light-duty Gasoline Exhaust-
Hot Stabilized (8993)
Conventional HDD- Idle
(8994)
Conventional HDD- Hot
Stabilized Running (8995)
2007 and Newer Diesel
Exhaust Composite (8996)
CNG transit bus exhaust from
a lean-burn engine - no
aftertreatment (95219)
CNG transit bus exhaust from
a lean-burn engine - no
aftertreatment (95220)
Elemental Carbon
(EC)
44.37%
14.00%
46.40%
78.97%
9.98%
9.25%
11.12%
Organic Carbon (OC)
42.64%
55.70%
34.74%
14.52%
22.33%
36.99%
37.45%
Non-carbon Organic
Matter (NCOM)
8.53%
11.14%
6.95%
2.90%
4.47%
7.40%
7.49%
S04
0.95%
7.19%
5.27%
1.03%
59.91%
0.64%
1.04%
N03
0.26%
0.29%
1.25%
0.18%
0.00%


NH4
0.43%
2.78%
1.74%
0.36%
0.00%


Fe
0.31%
1.83%
0.34%
0.13%
0.64%
0.25%
0.25%
A1

0.32%
0.06%
0.06%
0.11%
0.89%
0.89%
Si

0.32%
0.30%
0.22%
0.09%
0.46%
0.59%
Ti

0.03%
0.01%
0.01%
0.02%


Ca
0.39%
1.44%
0.58%
0.35%
0.47%
0.21%
0.44%
Mg
0.02%
0.14%
0.13%
0.01%
0.14%


K

0.09%
0.26%
0.02%
0.05%


Na
0.01%
0.04%
0.31%
0.03%
0.99%


CI
0.02%
0.10%
0.38%
0.13%
0.04%


CMAQ5.0 unspeciated
(PMOTHR)
2.09%
4.58%
1.28%
1.09%
0.78%
43.90%
40.74%
C.l Development of Gasoline Profiles from the Kansas City Light-
duty Vehicle Emissions Study
The Kansas City Light-duty Vehicle Emissions Study (KCVES) is the primary source of PM2.5
emission rates for light-duty vehicles in MOVES201433. The KCVES sampled PM2.5 emissions
from 496 vehicles recruited in a stratified random sample. The KCVES also measured speciated
PM2.5 on a subset of 99 of these vehicles. An overview of the vehicles included in the chemical
subset is included in Table C-2.
39

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Table C-2. Vehicle sample size in the Kansas City Light Duty Vehicle Emissions Study
Vehicle
Type1
Strata
Model
Year
Group
% of KC
LDGV
Vehicle
Population
% of KC
LDGV
Vehicle
Miles
Traveled
(VMT)
Summer Round
Sample
Winter Round
Sample
Full
Sample
Chemical
Subset
Full
Sample
Chemical
Subset
Truck
1
pre-1981
1.1%
0.6%
2
2
10
3
2
81-90
3.7%
2.4%
21
4
33
3
3
91-95
7.2%
6.5%
18
6
33
7
4
96-2005
28.6%
34.2%
39
8
59
11
Car
5
pre-1981
1.3%
0.7%
6
5
17
3
6
81-90
7.4%
4.6%
49
4
40
5
7
91-95
13.4%
11.2%
39
6
44
9
8
96-2005
37.3%
39.8%
87
14
41
9


Sum =
100%
100%
261
49
277
50
The derivation of the PM2.5 gasoline profile for MOVES2014 is documented in Sonntag et al.
(20 1 3)37. A summary of the speciation derivation is included in this report, as well as a
discussion on implementing the profile into the MOVES2014 framework. Two gasoline profiles
are developed to maintain differences between start and running processes. Minor differences
were detected between the PM2.5 compositions between seasons, which were confounded by the
different vehicles tested in each season. The data used equally weighted data from the summer
and winter tests to calculate a profile that incorporates data from both seasons.
We discovered high concentrations of silicon in some of the PM2.5 measurements, likely due to
contamination from silicone rubber couplers used in KCVES. The silicone contamination
occurred primarily on bag 2 of the LA-92 drive cycle which was used for developing the running
PM2.5 speciation profile and emission rates. The silicone contamination was larger for trucks than
cars due to their higher exhaust temperatures. The effect of the silicone contamination was
removed from the developed profile using the silicon emissions measurement by X-ray
florescence. The primary exhaust PM2.5 emission rates were corrected in MOVES2014 to
account for the silicone contamination.33 After removing the silicone contamination from the
speciated data, no significant differences were detected between passenger cars and light-duty
trucks, and the data from the cars and trucks were pooled together to develop single start and
running PM2.5 speciation profiles for all light-duty gasoline vehicles.
Important differences in the PM2.5 composition were detected among model year groups. Rather
than calculating model-year-group-specific profiles, fleet-average profiles were calculated to
better capture the impact of deterioration within all model year groups and to avoid over-fitting
the data to model year group trends. Malfunctioning high-emitting vehicles are known to
contribute a significant share of in-use PM emissions from light-duty vehicles.38'39'40'41 High-
emitting gasoline emissions have a highly variable PM composition due to failed emission
control systems, excessive oil consumption, and poor fuel control. Previous analysis of the
KCVES suggested that the speciation subsample (102 tests) provides a reasonable estimate of the
total PM mass compared to the full sample (522 tests), but the speciation sample underestimated
the high emitting vehicles in the newer model year groups.42 Other test programs have confirmed
40

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that high emitting gasoline vehicles also occur in modern vehicle fleets such as 1990-era vehicles
with electronic fuel injection.38'39'40 The speciation sample size was deemed too limited to
accurately capture the impact of deterioration and high-emitting vehicles within each model-year
group. By using all the data in a fleet-average approach, we incorporated the impact of
deteriorated vehicles on the fleet-average PM2.5 emissions.
The fleet-average PM speciation profiles are calculated using seasonal, vehicle-miles-traveled
(VMT), and PM mass-weighting. The PM profile is calculated using the ratio of the means, also
referred to as a mass-normalized emission profile.43 The ratio of means is calculated by first
calculating the mean emission rate of the total PM2.5, and the mean emission rate of each PM
species (EC, OC, Fe, etc.). Then the speciation profile is calculated, by calculating the ratio of
the mean emission rate from each species, to the mean PM2.5 emission rate, e.g.,
mean(EC)/mean(PM). The vehicle tests from each season are equally weighted, and averaged
according to the calculated contribution to annual VMT in the Kansas City MSA (Table C-2).
By using VMT and mass weighting, the profile scales up the contribution of older and higher
emitting vehicles according to their high PM emissions, but also scales their down their
contribution based on the relatively small number of vehicle miles traveled associated with these
vehicles. For application in MOVES2014, the fleet-average profile is used to characterize PM2.5
emissions across all model year groups, and all ages of vehicles used to represent deterioration.
Because the PM2.5 speciation varied significantly by model year group,37 the fleet average
speciation profile is sensitive to the averaging assumptions. As mentioned above, we did not
maintain the difference in speciation in model year groups, due to concern that the model-year
groups would not be representative of the PM emissions as the vehicles aged. Given the
uncertainty of the PM speciation profiles, we thought it would be unreasonable to model
differences in PM speciation according to different ages of vehicle fleets in different areas in the
US. For simplicity, we assume that the fleet-average PM2.5 profile from Kansas City to be
representative of the US gasoline fleet.
We recognize the need to incorporate speciation data on newer vehicles. For the next generation
of vehicles, the composition of PM is expected to become increasingly dominated by black
carbon emissions from both low-emitting port-fuel injected vehicles38'44'45'46 and gasoline-direct
injection (GDI) vehicles47'48'49. We plan on incorporating light-duty gasoline PM profiles to
MOVES and SPECIATE as such data on representative, in-use vehicles becomes available.
The developed PM2.5 profiles used in MOVES2014 for gasoline exhaust are included in Table
C-3. The number of samples for each PM2.5 species are also shown in Table C-3. EC was
measured on each vehicle test and has a much greater sample size than the other species. The EC
and nonECPM emission rates in MOVES201433 are updated to be consistent with the EC
fractions developed in Table C-3.
For application in MOVES2014, only the PM2.5 species required by CMAQv5.0 are reported. A
revision of the metal emission rates for Mn, Cr, and Ni for gasoline vehicles based on the
KCVES is provided in the Fuels and Toxics Report. The PM2.5 ratios that were not significantly
greater than 0 at the 95 percent confidence intervals were reported as 0, which removed five
PM2.5 species pollutants from the start profile. Fuel samples analyzed for 171 of the vehicles
tested in KCVES yielded an average fuel sulfur content of 161.2 ppm. Fuel sulfur content in the
US is now lower after implementation of the Tier 2 Vehicle & Gasoline Sulfur Program Final
Rule (effective beginning 2006-2008), which set a gasoline sulfur fuel limit of 30 ppm. In
41

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MOVES2014, the baseline sulfate emissions estimated from the PM2.5 profile are adjusted
according to the user-supplied fuel sulfur content as discussed in the Fuel Effects on Exhaust
Emissions from On-road Vehicles in MOVES2014.32
Details on the data, quality control measures, and statistical methods used to develop the profile
are documented in the Sonntag et al. (20 1 3).37 The paper also introduces methods to identify
significant measurements, correct for organic carbon positive artifact, control for contamination
from the testing environment on the PM2.5 speciation profiles, and impute missing PM2.5 species
in the KCVES measurements from other light-duty gasoline PM emission studies. Speciation
factors for additional PM2.5 species (P, Cu, Zn, Br, Mo, and Pb) that are not included in
MOVES2014 are also presented.
Table C-3. Gasoline PM2.5 Profile for Start and Running Emissions weighted average using Vehicle Miles
	 Traveled (VMT)		
PM Species
Start (8992)
Running (8993)

n
mean ratio +/- 95% CI
n
mean ratio +/- 95% CI
Elemental Carbon (EC)
484
44.37%
+/- 4.30%
531
14.00%
+/- 2.68%
Organic Carbon (OC)
66
42.64%
+/- 6.63%
99
55.70%
+/- 4.02%
Non-carbon Organic Matter (NCOM)
66
8.53%
+/- 1.33%
99
11.14%
+/- 0.80%
S04
66
0.95%
+/- 0.24%
99
7.19%
+/- 1.90%
N03
66
0.26%
+/- 0.08%
99
0.29%
+/- 0.08%
NH4
66
0.43%
+/- 0.10%
99
2.78%
+/- 0.73%
Fe
66
0.31%
+/- 0.21%
99
1.83%
+/- 0.53%
Al



99
0.32%
+/- 0.10%
Si



99
0.32%
+/- 0.10%
Ti



99
0.03%
+/- 0.01%
Ca
66
0.39%
+/- 0.14%
99
1.44%
+/- 0.26%
Mg
66
0.02%
+/- 0.02%
99
0.14%
+/- 0.02%
K



99
0.09%
+/- 0.03%
Mn



99
0.02%
+/- 0.02%
Na
66
0.01%
+/- 0.00%
99
0.04%
+/- 0.01%
CI
66
0.02%
+/- 0.01%
98
0.10%
+/- 0.04%
CMAQ5.0 unspeciated (PMOTHR)
66
2.09%
+/- 1.75%
99
4.56%
+/- 1.10%
C. 2 Development of E55/59 Profile for Use in MOVES2014 for Pre-
2007 Conventional Diesel
An updated PM2.5 profile for pre-2007 conventional diesel trucks was developed from the CRC
E55/59 Study: Heavy-Duty Vehicle Chassis Dyno Testing for Emissions Inventory50. The
E55/59 program is the current source for PM2.5 emission rates for medium and heavy-duty
conventional diesel trucks in MOVES2014, and is the source of the conventional diesel TOG
speciation profiles (Table 4-2). By using the E55/59 study for PM2.5 speciation profiles we are
using a consistent study with both the PM2.5 emission rates and the TOG speciation profiles in
MOVES2014.
42

-------
The E55/59 profile replaces SPECIATE profile # 91106 used to conduct PM2.5 speciation based
on the Northern Front Range Study Air Quality Study (NFRAQS) 51 conducted in the late
1990's. The MOVES2014 E55/59 PM2.5 profile includes measurements from eight heavy-duty
trucks, ranging from a 1985 to 2004 model year as shown in Table C-4. The E55/59 fuel
properties are more aligned with those in-use today, with sulfur content -172 ppm, as opposed
to ~ 340 ppm sulfur used in NFRAQS.41'51 The CRC E55/59 study was conducted from 2001-
2005 in several phases. Chemical characterization of PM2.5 emissions was conducted for nine of
the 75 trucks tested in the E55/59 study, ranging from 1985 to 2004 model year.
Table C-4. Vehicle Information from the Speciated E55/59 Trucks
Phase
ID
Medium/
Heavy
Duty
Vehicle
Model
Year
Vehicle
Manufacturer
Engine
Model Year
Engine
Model
Engine
Power
(hp)
Engine
Disp.
(Liter)
Engine
Manufacturer
Odometer
Reading
(mi)
1
1
H
1994
Freightliner
1994
Series
60
470
12.7
Detroit
639105
1
2
H
1995
Freightliner
1995
3406B
375
14.6
Caterpillar
241843
1
3
H
1985
International
1985
NTCC-
300
300
14
Cummins
501586
2
39
H
2004
Volvo
2003
ISX
530
14.9
Cummins
45
2
40
H
2004
Freightliner
2003
Series
60
500
14
Detroit
8916
2
41
M
1998
Ford
1997
B5.9
210
5.9
Cummins
13029
2
42
H
2000
Freightliner
1999
3406
435
14.6
Caterpillar
576998
2
43
H
1995
Peterbilt
1994
Series
60
470
12.7
Detroit
899582
2
44
H
1989
Volvo
1989
3406
300 (est.)
14.6
Caterpillar
811202
In all, 65 tests were conducted on the nine trucks selected for PM speciation. Phase 1 tested three
heavy heavy-duty diesel trucks (HHDTs) for PM speciation on four modes of the Urban
Dynamometer Driving Schedule (UDDS), including: Idle, Creep, Transient, and Cruise. Phase 2
tested six additional heavy heavy-duty diesel trucks, and one medium heavy-duty truck (MHDT).
In Phase 2, the HHDTs were also tested on the UDDS, as well as a high speed cruise mode
added after Phase 1. The MHDT was tested on MHDT schedule developed by the California Air
Resources Board that included two transient modes and a cruise mode. For chemical speciation,
some tests were repeated in sequence to collect additional mass on the filter, including extended
idle and extended creep. In Phase 2, the speciation data was not collected for the creep mode.50
The total and speciated PM2.5 emissions data from the E55/59 study was compiled from the
speciation database compiled in CRC Report No. E75-2: Diesel Unregulated Emission
Characterization Report52 and from Table 17 of the E55/59 Phase 1 report.53 The data reduction
steps used to develop a PM2.5 speciation profile from the E55/59 speciated data are outlined in
the following paragraphs.
43

-------
Step 1. We first calculated the average PM2.5 profile for each individual truck and four generic
classifications of test cycle, namely: idle, creep, cruise, and transient. The composite UDDS
cycle is classified as a transient cycle, similar to the classification conducted of speciation
profiles by E75-2.51 The truck and test cycle average PM profiles are calculated as ratios of the
means, also called a PM mass-weighted profile. In this manner, idle tests that contain three
repeat idle cycles contribute more to the average than tests that include only one idle cycle. The
average profile for each vehicle/test cycle classification is shown in Figure C-l. Thirty average
speciation profiles were calculated from the 65 tests as shown in Figure C-l. Typically, each
truck/cycle average contains two tests.
3:5
3:0
2:5
2X1
1
1
0:5
0
XI
6-
5-
4-
3-
2-
1"
0-
1-4
1
1:0
0:6
0:6
0"4
0:
0:0
3:5
3X1
2:5
2:0
1:
1:
0:5
0:0
XI
39

40
41
42
43
44
llll
O
O
n
MR MR MR MR MR MR MR MR
M R
Pollutant.lD
PM2.5
I Elemental carbon
Organic carbon
ions
S04-2
elements
Figure C-l. Average PM2.5 Speciation Profiles by Truck and Test Cycle from the E55/59 Program. M =
Measured total PM2.5, R = Reconstructed total PM2.5 from the speciated measurements
Step 2. We removed the average PM2.5 profiles with suspect data. As shown in Figure C-l, the
MMHDT truck (Truck 41) had very low PM emissions on the transient cycle, and a very large
contribution of ammonium to the idle cycle. This PM composition does not compare well with
previous data in the literature54, so the medium-duty truck was removed from further analysis.
Step 3. We calculated a median PM profile using the individual truck/test-cycle PM profiles
calculated in steps 1 and 2. The median is used rather than the mean due to the small sample
(eight trucks), in contrast to the variety of truck technologies, exhaust control systems, and ages
of the trucks in the real-world fleet. A mass-weighted mean would have been dominated by the
results for Truck 3 and Truck 44, which had the highest PM emission rates. Instead we calculated
the median of the PM fractions, and not a fraction of the median emission rates. In this manner,
the final PM speciation profile is not overly dependent on any one vehicle. Additionally, there
44

-------
may be systematic differences between the Phase 1 and Phase 2 measurements that could impact
a mass-weighted profile. By calculating the PM2.5 species fraction before computing the median,
any differences impacted the absolute PM2.5 emission rates between phases do not impact the
resulting speciation profile.
Step 4. We adjust the median profile to account for unmeasured PM2.5 species including metal-
bound oxygen and non-carbon organic matter. The additional oxygen mass associated with the
metal oxides are calculated using the oxide state assumptions in Sonntag et al. (2013)37
reproduced in Table C-5.
Table C-5. Oxide states assumed for calculation of metal-bound oxygen
Element
Oxide Form 1
Oxide Form 2
Oxide Form 3
Oxide/Element
Mass Ratio
Na
Na20


1.35
Mg
Mg


1.0
Al
A1203


1.89
Si
Si02


2.14
P
P04


3.07
CI
CI


1.0
K
K20


1.20
Ca
Ca


1.0
Ti
Ti02


1.67
Cr
Cr203
Cr03

1.69
Mn
MnO
Mn02
\111O
1.63
Fe
FeO
FC2O3

1.36
Ni
NiO


1.27
Cu
CuO


1.25
Zn
Zn


1.0
Rb
Rb20


1.09
Br
Br


1.0
Mo
M0O2
M0O3

1.42
Pb
PbO
Pb02

1.12
For the Phase 1 samples, the molar concentration of ammonium balances within 5 percent of the
molar concentrations of 2*SC>4 + NO3. This is what would be expected if the ammonium exists
as ammonium sulfate [NH4]2S04 and ammonium nitrate, NH4NO3. For the Phase 2 samples,
ammonium balances within 25 percent of the molar concentrations of 2*SC>4 + NO3. Due to the
relatively good agreement between the measurements, it appears that the sulfate on the filter
exists as ammonium sulfate. As such, we did not account for sulfate-bound water contributing to
filter mass.
The sum of the PM fractions from the median profiles is greater than one. To achieve mass
balance, we are scaled down the organic carbon fraction to correct for positive artifact inherent in
organic carbon (OC) filter measurements, as was done in previous work including for the light-
duty gasoline profile37 and analysis of emissions from other combustion sources55. We calculated
the organic matter (OM) as the remainder of the PM2.5 using Equation 12.
45

-------
0M% = 100 — EC% — elements% — metal bound oxygen% — ions% Equation 12
Then we split the OM into OC and non-carbon organic matter (NCOM) using the following
relationship: OM = 1.2 * OC used by Kleeman et al. (2000)56 and developed from work
conducted on medium-duty diesel emissions.54
OC% = ^ OM%	Equation 13
/1\	Equation 14
NCOM% = (— ) OM%
The initial and corrected OC/PM factors are shown in Table C-6. The adjusted OC speciation
factors are smaller than the initially measured OC/PM fraction, which is expected due to the
higher affinity for OC artifact to collect on the quartz fiber filters, as compared to the Teflon
filters used to measure PM2.5 mass.57
Table C-6. Impact of mass-balance correction on organic carbon and organic matter emission rates
PM factors
IDLE
CRUISE
TRANSIENT
Initial OC/PM factor
54.1%
36.3%
30.1%
Mass-balance OM/PM factor
41.7%
36.1%
17.4%
Corrected OC/PM factor
34.7%
30.1%
14.5%
The resulting profiles for the PM2.5 species are located in Table C-7. The Start/Extended Idle
profile is based on the idle test cycles, and the running emissions are based on the transient
cycles. These cycles are selected for use for modeling these emission processes because they
have similar PM characteristics (EC/PM) ratio as the PM2.5 MOVES emission rates for
conventional diesel as discussed next.
46

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Table C-7. PM2.5 Profiles for Conventional Diesel Exhaust developed for MOVES2Q14

Start/Extended
Idle (Profile
8994)
Running
(Profile
8995)
Elemental Carbon
46.40%
78.97%
Organic Carbon
34.74%
14.52%
NonCarbon OM
6.95%
2.90%
S04
5.27%
1.03%
N03
1.25%
0.18%
NH4
1.74%
0.36%
Fe
0.34%
0.13%
A1
0.06%
0.06%
Si
0.30%
0.22%
Ti
0.01%
0.01%
Ca
0.58%
0.35%
Mg
0.13%
0.01%
K
0.26%
0.02%
Na
0.31%
0.03%
CI
0.38%
0.13%
CMAQ5.0 unspeciated
1.28%
1.09%
As discussed in PM2.5 overview, the exhaust PM2.5 speciation profiles are used to speciate the
non-EC emission rates in MOVES2014. In the case of conventional diesel, the EC emission rates
were developed separately by weight class, and operating mode bin as discussed in the
MOVES2014 Heavy-duty report.30 The EC fraction from a MOVES calendar year 2014 model
run are compared to the EC fraction in the developed profile in Table C-8. The MOVES2014
EC/PM factor varies by operating mode and regulatory class, and thus changes for different
MOVES scenarios depend on the age distribution, fleet characteristics, and driving mix on
different road types. MOVES2014 reflects the lower EC/PM fraction for extended idle and start
emissions, which was also shown in the E55/59 profile. Running emissions represent over 80
percent of the PM2.5 emissions from conventional diesel trucks. The EC/PM ratio for running
compares very well (<1 percent) between the MOVES estimates and the E55/59 running PM2.5
speciation profile. The comparison validates the consistency in using the operating mode specific
values in MOVES for the EC emission rates, and using the E55/59 profile to calculate the
remaining PM2.5 species.
Table C-8. MOVES EC/PM2.5 fraction from conventional Diesel (pre-2007) calendar year 2014, compared to
the EC/PM2.5 fraction from the developed profile from E55/59

Extended Idle
Start
Running
MOVES2014 EC/PM Rates
26.6%
33.2%
79.4%
E55/59 PM2 5 Speciation profile
46.4%
46.4%
79.0%
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The MOVES2014 conventional diesel profiles developed from the E-55/59 Study are compared
to composite profile developed by Schauer et al. (2006)43 from measurements taken from the
DOE Gasoline/Diesel PM Split Study, as well as the NFRAQS heavy-duty diesel profile
(SPECIATE Profile 91106) in Table C-9. The EC/PM fraction from the transient cycle compares
well to both the composite profiles. The MOVES2014 idle profile has a substantially lower
EC/PM fraction than the composite profiles, with a corresponding higher fraction of organic
matter. The MOVES2014 sulfate fractions appear are more aligned with the DOE Split study,
which could be due to newer technology diesel and lower altitude testing. Elements and ion
emission rates compare well to the DOE gasoline/diesel PM split study. Even though the E55/59
speciation sample is limited, it appears valid in comparison to other available studies.
Table C-9. Comparison of MOVES2014 Conventional Diesel Profiles with other PM2.5 Conventional Diesel
Profiles

MOVES2014 E55/59
DOE Gasoline/
Diesel PM Split
Study
Northern
Front Range
Air Quality
Study

Start/
Extended
Idle (8994)
Running
(8995)
Composite
Composite
(91106)
Elemental carbon
46.4%
79.0%
72.7%
77.1%
Organic matter
41.7%
17.4%
24.1%
17.6%
S04
5.3%
1.0%
1.3%
0.3%
CI, nh4, no3
3.4%
0.7%
0.4%
0.1%
Elements
2.1%
1.1%
1.5%
0.5%
C.3 Development of the ACES PM2.5 Profile for 2007 and Newer
Technology Diesel
The PM2.5 speciation profile for 2007-and-later technology is based on Phase 1 of the Advanced
Collaborative Emissions Study (ACES) Report58. The purpose of the ACES report was to
characterize criteria and toxic emissions from advanced technology diesel engines and control
systems. Phase 1 of ACES tested four heavy-duty diesel engines each equipped with a catalyzed
diesel particulate filter (C-DPF). The PM2.5 profile is based on a 16-hour cycle which is
composed of FTP and CARB 5-Modes, developed specifically to gain sufficient PM mass to
measure the emission rates of trace metals and toxics and to capture diesel particulate filter
regeneration events. The PM2.5 measurements from the 16-hour cycle include the exhaust
measurements downstream of the C-DPF and crankcase blow-by emissions. Crankcase blow-by
emissions contributed 38 percent of the combined crankcase and tailpipe PM2.5 emissions on the
FTP cycle.
The SPECIATE contractor (Abt Associates) developed the PM2.5 profile from the ACES
program Phase 1 with input from the US EPA, with the intent of maintaining consistency with
the summarized results in the ACES Phase 1 report. The 16-hour results yielded the most
accurate measurements at the low levels of PM2.5 and are used to represent all PM2.5 emission
processes from 2007-and-newer on-highway diesel vehicles.
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The following decisions were made to develop a profile to be consistent with the results in the
ACES Phase 1 report.
1.	The original measurements were used rather than background or tunnel corrected
measurements. EC and OC were not corrected for background, or backup quartz filters.
Background correcting the EC/OC filters caused negative EC/OC emission rates on three
of the four engines. The ACES researchers did not report OC corrected by a backup-
quartz filter because of concern of under-representing OC emissions59. Similarly, species
for elements and ions were not corrected for tunnel blanks. Using uncorrected OC
measurements likely contributed to the mass of the sum of the speciated measurements
being higher than Teflon filter measurements60. By using the original measurements,
rather than the background or tunnel corrected measures, we are likely overestimating the
emissions from some of the individual species that are subject to positive artifact like OC.
The ACES researchers discuss possible approaches for correcting the measured OC
emission rates, and mention this as an area for future work for 2007 diesel engines.
2.	Unmeasured species that likely contribute to particulate matter were not included in the
profile, including sulfate-bound water and metal-bound oxygen from the profile. The PM
collected on the filter were analyzed for nitrate and ammonium, however no ammonium
or nitrate was detected58. In the absence of these species, the sulfate is expected to exist
as hydrated sulfuric acid. Khalek et al. 201159 reported that accounting for the water-
bound sulfate would increase the summed mass of the individual species 37 percent
beyond the measured filter mass. Rather than lowering the factors for other species by
including the sulfate-bound water, it was excluded from the profile. Converting the
measured organic carbon to organic matter and accounting for the oxide state of the
elements was considered by Khalek et al. (2011)59, but was not conducted due to the
uncertainty of reconciling the filter mass and the sum of the measured species
3.	According to the SPECIATE database, the profile was normalized to the gravimetric
mass of PM. Gaseous and particulate phase sulfate are combined in the PM profile. More
information on the profile itself can be found in the SPECIATE database, and the
database's supporting documentation outlines specific procedures for creating PM
profiles.61
The ACES Profile is included in the SPECIATE database as profile #5680. This profile is the
basis of SPECIATE profile 8996 used in MOVES2014 with one adjustment. CMAQ5.0 needs
organic matter reported as OC and non-carbon organic matter (NCOM). We treated the reported
OC in the SPECIATE profile 5680 as OM, and calculate OC and NCOM using the same split
(5:1) as used for conventional diesel and light-duty gasoline. The species not needed by
CMAQ5.0 from the ACES Phase 1 profile are summed into the CMAQ5.0 unspeciated fraction.
Metal emission rates for manganese, chromium, and nickel from MOVES2014 are derived from
the ACES Phase 1 data4. They are estimated using the metals calculator with mass/distance
emission rates, and are not reported in the SPECIATE profiles.
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Table C-10. SPECIATE PM2.5 Profile 8996 developed from the 16-hour cycle from four heavy-duty diesel
engines with C-DPFs in the ACES Phase 1 Program

Weight %
Elemental Carbon
9.98%
Organic Carbon
22.33%
Non Carbon Organic Matter
4.47%
Sulfate
59.91%
Nitrate
0.00%
Ammonium
0.00%
Iron
0.64%
Aluminum
0.11%
Silicon
0.09%
Titanium
0.02%
Calcium
0.47%
Magnesium
0.14%
Potassium
0.05%
Sodium
0.99%
Chlorine
0.04%
CMAQ5.0 unspeciated
0.78%
The 2007+ diesel EC/PM fraction in MOVES2014 is a constant 8.61 percent based on previous
analysis documented in the heavy-duty diesel report. This value is quite similar to the 9.98
percent EC/PM fraction estimated from Phase 1 of the ACES program. Due to the similarity in
the EC/PM fraction, the previous value of 8.61 percent is also used in MOVES2014. However,
the ACES Phase 1 data is used to speciate the remaining species listed in Table C-10.
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C.4 Development of the Compressed Natural Gas (CNG) Transit
Bus Profile
The California Air Resource Board (CARB) conducted several emission characterization studies
on compressed natural gas vehicles. We used test data collected on CNG New Flyer bus with a
2000	MY Detroit Diesel (DDC) Series 50G engine, equipped with and without an oxidation
catalyst to develop PM2.5 speciation profiles. CARB also conducted tests on a CNG bus with a
2001	Cummins Westport engine. We developed the profile on the DDC engine, with and without
catalyst to estimate the impact of oxidation catalyst control, without introducing differences in
engine technology. CARB characterized the PM emissions on a steady-state cycle, and a central
business district cycle (CBD). We used the CBD data, which was consistent with the criteria
pollutant analysis in the MOVES2014 Heavy-duty Emissions Report30, and was considered more
representative of typical transit bus behavior.
We elected to use only the data reported by CARB on the DDC 50G engine to develop the
profile. Using a single profile provides consistency in the PM characterization estimates and
assures that the organic carbon emissions are reduced with implementation of oxidation catalyst
controls. Other studies that reported EC/OC did not measure emission rates for elements62. We
used measurements made on the same tests to construct the profile in Table C-l 1. The PAH/OC
ratios documented in the MOVES2014 toxics report4 were also developed from the CARB
measurements on the DDC 50 G.
Table C-ll. PM2.5 Speciation Profiles for CNG Compressed Ignition Transit Bus Exhaust
Pollutant
Uncontrolled
(95219)
Oxidation
Catalyst
(95220)
Elemental Carbon (EC)
9.25%
11.12%
Organic Carbon (OC)
36.99%
37.45%
Non-carbon Organic Matter (NCOM)
7.40%
7.49%
S04
0.64%
1.04%
aluminum
0.89%
0.89%
calcium
0.21%
0.44%
chromium
0.25%
0.25%
cobalt
0.39%
0.40%
iron
0.25%
0.25%
nickel
0.04%
0.00%
phosphorus
0.04%
0.15%
silicon
0.46%
0.59%
zinc
0.14%
0.20%
Unspeciated PM2 5
43.04%
39.74%
We used PM, EC, OC, and element emission rates for two repeat tests both with and without the
oxidation catalyst.63'64 CARB measured 13 elements by X-ray fluorescence but no ions (sulfate,
ammonium, or nitrate) were measured. The sulfate emissions were estimated by assuming that
all elemental sulfur is in the form of sulfate. This assumption is consistent with sulfate and
51

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elemental sulfur measurements reported for natural gas combustion in the speciate database
(SPECIATE 91112). We assume that the missing ammonium and nitrate emissions are zero,
based on the negligible ammonium and nitrate measurements from modern spark-ignition CNG
buses equipped with three-way catalysts.65 Sodium and magnesium were the largest elements
measured (sodium was over 7 percent of the PM2.5 measured in the uncontrolled test), which is
likely due to known measurement artifact for XRF measurements of sodium and magnesium. As
such the sodium and magnesium emission rates are reported as zero.
The use of the oxidation catalyst reduced the PM2.5 emission rates from 28 mg/mile to 20.3
mg/mile on the CBD cycle (a 27.5 percent decrease). As shown in Table C-l 1, the composition
of the PM2.5 stayed fairly constant. The EC and OC fractions between the two control conditions
are not statistically different. The estimated sulfate emissions are significantly higher with the
oxidation catalyst, which is to be expected. Both profiles contain a large amount of unspeciated
PM2.5 emissions. The source of the large unspeciated PM2.5 emissions is unknown, but may be
attributed to the different sampling media for the total and speciated PM2.5 emissions, which is
amplified at the low PM2.5 concentrations measured from CNG exhaust. The absence of ion
measurements may also be a contributing factor.
The real-world variability in the PM2.5 composition is larger than the developed profiles suggest.
The OC/PM fraction for the 2001 Cummins Westport with oxidation catalyst was 61.9 percent,
which is much larger than that measured on the 2000 Detroit diesel engine. Lanni et al. (2003)62
reported that the OC/PM fraction on three CNG transit buses with DDC Series 50 G engines
ranged from 29 percent to 74 percent of the PM2.5. The EC emissions measured by Lanni el al.
(2003)62 were below the detection limit, but the presented results compare well with the 2001
Cummins Westport measured by CARB (12.7 percent EC/PM). The sulfate fraction for the
oxidation catalyst presented in Table C-l 1 compares well with the sulfate fraction reported for
the 2001 Cummins Westport by CARB64 (2.8 percent), and by Lanni et al. (2003)62 (1.5 percent
to 2.4 percent).
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Appendix D PM10/PM2.5 Factors
The gasoline PM10/PM2.5 factor is based on measurements of 1991-1997 model year vehicles
tested by Norbeck et al. (1998)66. This ratio estimates that roughly 10 percent of the PM emitted
from gasoline vehicles is in the coarse range, which agrees with the size-distributions reported
from cascade impactor measurements on light-duty gasoline exhaust from Schauer et al.
(2008)67.
The diesel PM10/PM2.5 factor is based on a 1985 EPA report68, which reports that 92 percent of
particulate mass is measured below a 2.5 |im cut-off. Although derived from measurements on
older technologies, the diesel PM10/PM2.5 ratio compares well with observations of the particle
size distribution of diesel exhaust by Kittelson et al. (1998)69, who states that the coarse mode
contains 5-20 percent of the total aerosol mass. Unfiltered crankcase emissions published by
Donaldson Company Inc. (2011)70 have similar reported mass distributions with ~ 93 to 97
percent of the cumulative mass particles smaller than 2.5 |im. In contrast, Tatli and Clark
(2008)71 report that the particle mass size distribution is significantly different from crankcase
and tailpipe diesel emissions for particles below 1 |im. Due to the limited information on coarse-
mode crankcase particulate emissions, we assume the same PM10/PM2.5 fraction for diesel
crankcase emissions.
Filtered diesel crankcase and exhaust emissions are expected to have smaller PM10/PM2.5 ratios,
due to the higher filter capture efficiency of coarse mode particles.70'72 However, the same
PM10/PM2.5 ratios are used for the later model year groups, due to limited coarse mode
particulate exhaust measurements, and limited information on the failure rates of these
technologies in real-world use.
No information was available on the PM10/PM2.5 ratio for CNG emissions, and the gasoline ratio
is used for CNG emissions. Table D-l contains the selected exhaust PM10/PM2.5 ratios used in
MOVES.
Table D-l. PM10/PM2,5 Ratios for primary exhaust and crankcase emissions by fuel type
Fuel
PM10/PM2.5
Gasoline, E85, CNG
1.130
Diesel
1.087
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Appendix E Peer-Review Comments and Responses
This report was reviewed for the MOVES2014 release. The draft report that was subject to peer-
review and the peer-review comments are available at EPA's science inventory webpage.73 The
peer-review comments and EPA responses are summarized below, and were originally included
in the MOVES2014 version of this report.5 The speciation updates made for MOVES2014a and
MOVES2014b were not peer-reviewed.
E. 1 Adequacy of Selected Data Sources
Does the presentation give a description of selected data sources sufficient to allow the reader to
form a general view of the quantity, quality and representativeness of data used in the
development of emission rates? Are you able to recommend alternate data sources might better
allow the model to estimate national or regional default values?
E.l.l Dr. Tom Durbin
For the "TOG and PM Speciation in MOVES for Air Quality Modeling" and the "Appendix:
PM2.5 Speciation in MOVES" reports, there are several other data sets should be considered for
inclusion in the model as the model continues to be developed. The California Air Resources
Board has been looking at the toxicity of advanced technology diesel vehicles, and some of this
data has sulfate emissions that could be of relevance here. The South Coast Air Quality
Management District has also conducted a study to evaluate the in-use emission rates of 2007+
technology, heavy-duty diesel and natural gas vehicles. These data will probably not be available
until the first part of next year, but they could be considered for future application to the model.
Phase 2 of the ACES program is another data set that could be of value for future model
revisions.
For CARB studies, see http://www.arb.ca.gov/research/veh-emissions/veh-emissions.htm noting
that there have been some publications more recent that those listed on the website.
UC Riverside program with the South Coast Air Quality Management District (SCAQMD),
"Determining the Physical & Chemical Composition & Associated Health Effects of Tailpipe
PM Emissions"
UC Riverside program with the Coordinating Research Council (CRC), "Biodiesel and
Renewable Diesel Characterization & Testing in Modern LD Diesel Passenger Cars & Trucks"
UC Riverside program with the South Coast Air Quality Management District (SCAQMD),
"Determining the Physical & Chemical Composition & Associated Health Effects of Tailpipe
PM Emissions"
UC Riverside and West Virginia University program with the SCAQMD, "In-Use Emissions
Testing and Demonstration of Retrofit Technology for Control of On-Road Heavy-Duty
Engines"
Durbin, T.D., Karavalakis, G., Johnson, K.C., Miller, J.W., and Hajbabaei, M. (2013) Evaluation
of the Performance and Air Pollutant Emissions of Vehicles Operating on Various Natural Gas
Blends - Heavy-Duty Vehicle Testing - Regulated Emissions and PM, Final Report for the
California Energy Commission by the University of California at Riverside, June.
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Durbin, T.D., Karavalakis, G., Miller, J.W., Hajbabaei, M., Bumiller, K., Villela, M., and Xu,
K.H., 2012. Effects of Olefins Content on Exhaust Emissions: CRC Project E-83, Final report for
the Coordinating Research Council by the University of California at Riverside, June.
Durbin, T.D., Miller, J.W., Johnson, K.C., Hajbabaei, M., KadoN.Y., Kobayashi, R., Liu, X.,
Vogel, C.F.A., Matsumura, F., Wong, P.S., and Cahill, T. (2011) Assessment of the Emissions
from the Use of Biodiesel as a Motor Vehicle Fuel in California - Biodiesel Characterization and
NOx Mitigation Study, Final report for the California Air Resources Board by the University of
California at Riverside, the University of California at Riverside, and Arizona State University,
October.
Durbin,T.D., J.W. Miller, T. Younglove, T. Huai, andK. Cocker. 2006. Effects ofEthanol and
Volatility Parameters on Exhaust Emissions: CRC Project No. E-67. Final report for
Coordinating Research Council, CRC Project No. E-67, January.
Durbin, T. D., J. W. Miller, J. T. Pisano, C. Sauer, T. Younglove, S. H. Rhee, T. Huai, and G.I.
MacKay. 2003. The Effect of Fuel Sulfur on NH3 and Other Emissions from 2000-2001 Model
Year Vehicles. Final report for Coordinating Research Council, CRC Project No. E-60, CE-
CERT Technical Report No. 02-VE-59971-E60-04, May.
Response: We appreciate these references to past and future emission test programs.
These references will be consideredfor the next update to MOVES.
E.1.2 Dr. Allen Robinson
The report provides some description of data sources. For example Table 12 points the reader to
different EPA reports. That is valuable, but it is not clear that the information in the Table is
sufficient if a reader wanted to truly understand where the source profile came from. I have been
frustrated in the past trying to track down the source data for speciation profiles used in EPA
models. Sometimes there are no references (not a problem here), but other times the references
point to a large report (the case here). However, these reports can be massive documents that
describe lots of data, but the reader has no idea which specific data were actually used to develop
the input for the model (or how they were used). Maybe that is not an issue here (I have not
gone and looked at the underlying reports), but I would encourage the authors to make sure the
reader truly can figure out where the source profiles came from so that can start with the actual
data and recreate the actual profiles. For example, the report could refer to specific emissions
data form the underlying report.
The report seems to do a better on the PM side of things (PM speciation appendix, which is built
upon this unpublished paper). It is very helpful that the PM appendix includes the actual
profiles. I would encourage EPA to write a similar Appendix for the TOG speciation.
Response: The source for speciation profiles used in MOVES is EPA's SPECIATE
database. SPECIATE is an EPA-maintained database ofVOC and particulate matter
(PM) speciation profiles for various emission sources, including mobile sources. This
database comprises the record of each profile including its referenced source, testing
methods, a subjective rating of the quality of the data, and other detailed data that allow
researchers to decide which profile is most suitable for model input.
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We note that the purpose of this MOVES document is not to replicate the SPECIATE
documentation, but to describe the incorporation of the speciation process into
MOVES2014 to provide model-ready species for air quality modeling, whereas
previously the process occurred in SMOKE or as a pre-processor to SMOKE. The
advantage of this change in approach is improved accuracy in speciation by regulatory
class and fuel. The TOG profiles themselves are not new, nor is their use in air quality
modeling, i.e., they have all been used previously to develop air quality modeling
inventories for various rule makings. Because the PM speciation profiles were new at the
time we submitted this document for review, we included these profiles in the appendix.
One of the new PM profiles has since been published in peer-reviewed literature.
I was surprised that there modeling assumes that a constant EC/PM emission ratio for LDGV.
This may be because the KCVES did not test many Tier 2/LEV2 vehicles. The CRC A74/E96
project found a pretty significant increase in the EC/PM for newer Tier 2/LEV2 vehicles. This
has been presented in project reports and will be published shortly.
Response: We plan on examining these studies and may utilize their data to create
speciation profiles for use with future versions of MOVES.
It also seems like default LDGV EC/PM ratio is not appropriate for GDI, which are becoming a
larger part of the fleet. ARB has been doing a fair bit of testing of GDI - presumably those data
are available. This will be critical for MOVES to be able to predict emissions from future fleets.
Response: We had limited data on speciation of GDI vehicles. We plan on including data
on representative Tier 2/LEVII and later technology vehicles (including GDI vehicles) in
the future.
E.2 Clarity of Analytical Methods and Procedures
Is the description of analytic methods and procedures clear and detailed enough to allow
the reader to develop an adequate understanding of the steps taken and assumptions
made by EPA to develop the model inputs? Are examples selectedfor tables andfigures
well chosen and designed to assist the reader in understanding approaches and methods?
E.2.1 Dr. Tom Durbin
Sections 3.1 to 3.5 - The description here is not clear. In equation 1, defines a "speciation
factor". Then later on the page there is a "speciationConstant" that is not defined. Similarly,
"oxySpeciation" does not appear to be defined. The equations above table 4 are also not clear.
Does this mean that the speciation is defined separately for the pure gasoline as opposed to the
oxygenate part of the fuel. What is the voltowtpercentoxy term?
Response: This section was significantly revised in response to this comment, and similar
comments from Dr. Allen Robinson. We removedformer equation 1 from the main text to
the appendix (as discussed in responses Robinson's comments, E.3.2). We reduced the
equations referenced above from four to one, to help clarify that MOVES is using the
same calculation for all oxygenates. We also included definitions for each of the terms,
which were missing in the draft report. We added the complete derivation of the volume
to Weight Percent Oxygen term to provide transparency on the assumptions used to
derive this term. .
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Table 13 is useful, providing a link with other models, as our Figure 2 and Figure 3.
Section 5.1 step 1 - It would be useful to provide a one sentence explanation as to why the
EC/PM2.5 ratios vary across operating modes.
Response: We added a sentence explaining that EC is dependent on engine conditions,
and varies accordingly. However, at this time we have only developed modal EC/PM
emission rates for conventional diesel vehicles.
Step 2 - last sentence "the nonECnonS04PM as a whole.... (potential suggestion)
Response: The reviewer suggested new text to clarify the explanation of Step 2. We
incorporated the suggestion.
Step 4 - It would be useful to give a simple example of a basis temperature effect (effect on
catalyst temp, for example).
Response: We added a simple example of temperature effects on PM emissions, (cool
catalyst and additional fueling needed to start an engine at cold temperatures).
Step 5 - For the crankcase emissions for the pre-2007 diesel, there are some important factors
that are left out that would be useful in interpreting Table 14. In particular, from the
MOVES2014 Heavy-duty Emissions Rate Report it indicates that "The crankcase emission
factors shown in Table 51 are derived such that the crankcase PM2.5 emissions are 20 percent of
the PM2.5 exhaust measurements, and have an EC/PM split of 1.57 percent."
Response: We added text clarifying why the ratios were derived differently for 2007-2050
diesel and other sources. We also added the text that the reviewer suggested, and we
referenced the Heavy-Duty Report where the crankcase emission factors are discussed in
more detail.
Top of page 28 - refers to Table 7, but this deals with VOC/NMHC not PM.
Response: The cross-references to Tables and Figures were reviewed and updated where
necessary.
Step 8 - It seems like since there are only 7 categories that a table could actually be included
with the speciation profiles used for each of the categories.
Response: We added Table C-l which includes the seven PM2.5profiles used in
MOVES2014.
p. 3 Why was EC measured for considerably more vehicles for the KCVES than OC. What
method was used for the EC?
Response: As discussed in more detail in Sonntag et al. (2013)31, we used the
photoacoustic black carbon measurements made on each vehicle as a surrogate for
elemental carbon (EC). Sonntag et al. (2013)31 contains further discussion that supports
this decision, including a comparison of the IMPROVE-TOR elemental carbon and
photoacoustic black carbon made on the same vehicle tests.
The comparisons in Table A-8 [now Table C-9] and the associated discussion is valuable in that
it ties the current estimates to earlier model estimates and data in the literature.
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Under Table A-4 [now under Table C-5\. The discussion needs to be clarified about how OM is
split into organic carbon and non-carbon organic matter using the relationship: OM = 1.2 * OC.
The table seems to show that the OC is scaled down and then renamed OM, which is
subsequently modified by the 1.2 factor. It seems that it would be best to start out by saying that
the initial OC includes organic carbon, a positive artifact, and other non-carbon species
associated with the organic carbon (such as hydrogen, oxygen, etc.).
Response: We added Equations 12, 13, and 14 with accompanying text to clarify how the
corrected OC and NCOM values are calculated.
E.2.2 Dr. Allen Robinson
No response.
E.3 Appropriateness of Technical Approach
Are the methods and procedures employed technically appropriate and reasonable, with respect
to the relevant disciplines, including physics, chemistry, engineering, mathematics and statistics?
Are you able to suggest or recommend alternate approaches that might better achieve the goal of
developing accurate and representative model inputs? In making recommendations please
distinguish between cases involving reasonable disagreement in adoption of methods as opposed
to cases where you conclude that current methods involve specific technical errors.
E.3.1 Dr. Tom Durbin
The methods and procedures appear to be reasonable for this document. The bigger question is
probably the description of the methods and the evaluation of the data sets, as described above.
One major category that is missing is pre-2007 retrofit heavy-duty diesel engines and how these
are modeled. Also, GDI vehicles for future years.
Response: See response E.4.2 andE.5.2 (Regarding GDI vehicles)
Although the silicone contamination from the connecting pieces from the transfer line can be
removed, is it possible that some other PM species relating the transfer line heating/burning. I
see in another section that there is some compensation for other species, but it reinforces the idea
that EPA should consider a broader range of data sources in its modeling.
Response: Comparisons with literature on individual PM species measured from the
KCVES are made within Sonntag et al. (2013')31. We agree that including additional data
sources in the future will improve the robustness of MOVES.
Although the Kansas City study is one of the more recent comprehensive studies of gasoline PM,
it is not obvious that fleet average composition profiles would be representative of the fleet going
into the future. On page 2, it does indicate that there were differences in PM2.5 composition
between different model year groups. If there are differences between Tier 0, Tier 1, and
NLEV/Tier 2 vehicles, will a fleet average profile be adequate for the fleet going into the future?
Of course, future generations of the model will need to include GDI vehicles, as more
information on their PM species profiles become more available.
Response: As mentioned on page 40 and page 41, we used a fleet-average profile
because it incorporates vehicles at representative deterioration, and we did not want to
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extrapolate forward the PM speciation values based only on newer model year groups.
Additionally, we plan to incorporate PM speciation data on GDI vehicles as mentioned.
Additionally, how are light-duty diesel vehicles accounted for in the model?
Response: The light-duty diesel emission rates for PM (EC and NonECPM) are identical
to the light-duty gasoline emission rates in MOVES2014 as documented in the light-duty
emission rate report. MOVES2014 uses diesel PM speciation profiles to speciate the
NonECPM emissions from light-duty diesel vehicles, as shown in Table 5-5.
E.3.2 Dr. Allen Robinson
I like the approach of defining nonECPM because EC is refractory while other components, in
particular OC, are semivolatile. This addition is an important step towards implementing a more
physically realistic treatment of OC. However, I am concerned that the model continues to treat
OC as an inert, non-volatile component of the exhaust. Presumably MOVES is supposed to
estimate the PM emissions at typical atmospheric conditions (not those in CVS). The problem is
that the low levels of dilution commonly often used in vehicle testing campaigns such as the
KCVES create high PM concentrations in the CVS. This biases the gas-particle partitioning of
the OC. Few studies have quantified the behavior, but the recent CRC A74/E96 project
demonstrates the issues with fleet of 60+ LDGV and MDDV/HDDV vehicles (see May et al.
dx.doi.org/10.102l/es400782j | Environ. Sci. Technol. 2013, 47, 8288-8296, May et al.
Atmospheric Environment 77 (2013) 128el39). At a minimum the report should point out this
limitation that the emission rates may be overestimated because of partitioning biases. I would
encourage EPA to start explicating accounting for these biases in both the MOVES emission
rates and source profiles. This can be done using the volatility distributions in the May et al.
papers and the measured CVS concentrations.
Response: As mentioned in the Toxics report (Section 2.1.2 Poly cyclic Aromatic
Hydrocarbons)4, the particulate matter (PM) emission rates are derivedfrom emission
test programs, but the gas-particle partitioning is not adjusted to be representative of
ambient conditions. We agree that differences between the dilution conditions of the
emission test programs and ambient conditions, introduce differences in the PM
emissions. However, a comprehensive reevaluation of the PM emission rates was not
within the scope of the updates for MOVES2014.
I was confused with section 3 which describes the method for converting between different
classes of gas phase organics (NMOG, TOG, THC, etc.).
Response: This section has been significantly revised to improve clarity. Dr. Robinson's
concern is addressed in more detail in his following comments.
First, Title of section 3. Hydrocarbon speciation. I found this confusing. Hydrocarbons are
organic compounds that contain carbon and hydrogen. This is a subset of the organic, which can
contain compounds in addition to C and H. This should be called total organic gas speciation.
Response: Title has been changed to Organic Gas Aggregations
Second I am concerned with defining the THC emissions based on what is measured by the FID.
I realize that this is standard definition but it is not scientifically correct. The FID measures
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carbon. A problem is that the measurement efficiency is species dependent (as mentioned in the
document). The FID quantitatively measure carbons in hydrocarbons (organic compounds
comprised of carbon and hydrogen) and the standard propane calibration works well. However,
the FID can also measure some of the carbon in oxygenated organics (especially carbons not
associated with oxygen atoms) so some of the signal in the FID comes from oxygenated
organics, which are not hydrocarbons. Therefore, there is no straightforward interpretation of the
FID signal, but it does detect more than just the hydrocarbon emissions.
Response: We have kept our current definition of total hydrocarbons. We discuss the
issues regarding partial responses to FID measurements from oxygenated organics in the
main document (Section 3) and we added details on calculating other organic gas classes
from THC in Appendix A.
Third, I could not follow the equations used to convert between the different classes of organic
gases (NMOG to NMHC, etc. - e.g. section 3.2). This correction seems to be relatively
straightforward - it appears that you are simply using different ratios of, e.g. NMOG to FID
defined THC. Not surprisingly, these ratios depend on vehicle MY and type of fuel.
Response: Only the equations that are used in MOVES are presented. Definitions of the
terms (that were previously undefined) have been included in the report. The equations
usedfor the derivation of parameters have been moved to Appendix A, as discussed in the
next response. The parameters for all gasoline vehicles are presented together to improve
interpretation and comparison ofparameters between different fuel types and model
years.
I will focus my comments on section 3.2 but the same comments to apply to the other sections
(e.g. 3.3) that perform the same analysis. What is the basis of equation (1)? Some underlying
physical or chemistry principle? How is equation (1) used? Is equation (1) used to derive un-
numbered equations later on page 9? What is the definition CF is molar or mass carbon fraction?
MPC is mass of what? per carbon? Where is FIDx defined - give table or reference? Is the
speciation constant listed in Table 5 the same as the speciation factor defined by equation 1? If
so then you need to reconcile the names. I tried played with equation with equation (1) but could
not figure out some of the inputs. It should be clear that I found this whole section pretty
confusing and do not have a basic understanding of what MOVES is doing, never mind being
able to reproduce the calculations.
Response: Equation 1 in the draft report is an equation used to derive the NMOG/NMHC
parameters, which are subsequently used in the MOVES calculation. This equation is not
used within MOVES, but is one method to derive the speciation factors used in the
MOVES calculations.
The derivation of the NMOG/NMHC ratios has been moved to a new appendix (Appendix
A), where the equation, terms, are explained in much more detail. Example calculations
are also added to demonstrate how the NMOG/NMHC parameters are calculated, to
enable readers to reproduce the calculations using their own data. The NMOG/NMHC
ratios are calculated using two methods. We also demonstrated that equivalent results
can be obtained using both methods.
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Similar changes were also made to the section concerning VOC/NMHC. The former
equation 2 was removed from the main text, and more in depth discussion of the former
equation 2 is included in Section A. 3.
It seems that the key to calculating the needed ratios is not equation (1) but the un-numbered
equations listed on page 9. The inputs for these equations appear to be given in Table 4 and 5. I
assume that these values are fixed (or can the user input a difference volume to weight percent
oxygen)? Where did these values come from? Derived from fuel analyses? Derived from fitting
experimental data? If they are fixed, then it seems like one could get rid of Table 4 and simply
replace Table 5 with the actual ratios used to convert between NMHC and NMOG for the
different model year groups. That would be much simpler. I think that the equations make it
appear that what is being done is more sophisticated then it is.
Response: We removed the former equation (1), and moved it to Appendix A. (see
previous comment). In the revised report main text, we emphasize the equations MOVES
uses, by changing them from a set of previously unnumbered equations, to a single
equation (Equation 3), with defined variables. We did this to clarify that MOVES is using
the same calculation for all oxygenates.
We added the complete derivation of the volume to Weight Percent Oxygen term
(Equation 4), and added information in Table 3-2, to provide transparency on the
assumptions used to derive this term.
We also added references to provide the data sources from which the parameters were
derived for each model year group and fuel type.
Page 25 "Step 2" states that sulfate and particulate water emissions were obtained by speciation
profiles. However, I thought these were calculated with the sulfate model?
Response: We added clarification that the sulfate and particulate water emissions are
adjusted according to the sulfate calculator in Step 2.
The report should define what is meant by the ratios of means (or mass weighted means) used to
create average profiles. Right now the report assumes the reader can knows this.
Response: We added clarification by adding the following sentence, defining the ratio of
means.
"The ratio of means is calculated by first calculating the mean emission rate of the total
PM2.5, and the mean emission rate of each PM species (EC, OC, Fe, etc.). Then the
speciation profile is calculated, by calculating the ratio of the mean emission rate from
each species, to the mean PM2.5 emission rate, e.g., mean(EC)/mean(PM). "
E. 4 Appropriaten ess of Assumptions
In areas where EPA has concluded that applicable data is meager or unavailable, and
consequently has made assumptions to frame approaches and arrive at solutions, do you agree
that the assumptions made are appropriate and reasonable? If not, and you are so able, please
suggest alternative sets of assumptions that might lead to more reasonable or accurate model
inputs while allowing a reasonable margin of environmental protection.
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E.4.1 Dr. Tom Durbin
Again, the most critical assumption appears to be where the datasets sufficiently cover the
vehicle categories that are needed for the model. Additional categories that could be added
include pre-2007 retrofit heavy-duty diesel engines and GDI vehicles for future years, as well as
some of the data sets described above.
Response: See response to E.4.2 andE.5.2 (Regarding GDI vehicles)
Although the silicone contamination from the connecting pieces from the transfer line can be
removed, is it possible that some other PM species relating the transfer line heating/burning.
Response: See our response to E.3.1 regarding silicone contamination.
It seems reasonable that the sample size might be too [low] high to capture high emitters in each
of the model year groups, especially for newer model years. It would be interesting to know if
the population of high emitters in the KCVES was comparable to that found in previous studies
of high emitters, although many of those estimates were made in older studies.
Response: Nam et al. (2008) 74conducted comparisons of the CO and HC measurements
from the KCVES compared to I/M data, and concluded that the high emitter rates for
older vehicles were comparable, but there was less certainty regarding the high emitter
rates vehicles within the newer model year groups.
How different is the PM2.5 composition by model year groups? As this would be an important
consideration in terms of using the fleet average approach.
Response: Sonntag et al. (2013j37 provides a detailed comparison of the PM2.5
composition by model year groups, cold and hot starts, and pollutant. We felt the large
amount of information is best presented in that paper rather than in this report.
There are some differences between the cruise and transient OC/PM factors. How was it
determined that the transient cycle is more representative than the cruise for heavy-duty vehicles.
Is this based on more urban driving?
Response: As shown in Table C-8 the EC/PMfraction from the transient cycle (79
percent) compares very well with the EC/PM emission rates producedfrom MOVES
(79.4percent). As discussed on page 47, we used the transient cycle, because it is
consistent with PM values produced by MOVES2014.
For the 2007+ heavy-duty vehicles, while it is understandable to utilize measurements that are
not background corrected and the associated negative numbers, it should be noted and
understood that this would likely overestimate the contributions of different individual species.
Nevertheless, the breakdown in Table A-9 [now Table C-10], with a predominantly sulfate
contribution and minimal contribution from minor species seems reasonable.
Response: We added text on page 50, discussing that by not conducting background
correction, we ae likely overestimating PM species that are subject to positive artifact
like OC.
The discussion relating to the exclusion of sulfate-bound water provides a good basis for this
assumption and is adequately described.
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E.4.2 Dr. Allen Robinson
Limited data for GDI. This is not mentioned in report. ARB has been doing some work on this.
Limited data for CNG. This is acknowledged in the report. Not clear how critical a gap that is
given the limited number of CNG vehicles (maybe important in places like LA or NYC with lots
of CNG buses?).
Limited data for post-2007 diesels, especially on long-term performance on aftertreatment
devices.
These limitations are expensive to address. They should be pointed out in the report.
Response: The purpose of this document is to describe how we have incorporated the
speciation process, which previously occurred outside of the MOVES framework, into
MOVES2014 to better provide model-ready species for air quality modeling. Limited
data exist to support matching speciated emissions data with all combinations of
MOVES' classifications (model-year group, regulatory class, fuel subtype, emissions
process, etc.). We plan continue to improve and expand the application of speciated
emissions data in future versions of MOVES as new data become available. We have
added text in the report that describes our intention to improve future versions of the
model with newer speciated emissions data.
Additionally, see response toE.5.2 (Regarding GDI vehicles).
E. 5 Consistency with Existing Body of Data and Literature
Are the resulting model inputs appropriate, and to the best of your knowledge and experience,
reasonably consistent with physical and chemical processes involved in emissions formation and
control? Are the resulting model inputs empirically consistent with the body of data and
literature that has come to your attention?
E.5.1 Dr. Tom Durbin
The resulting model inputs appear to be consistent with exhaust emissions formation and the
associated literature.
The intercomparisons between the model inputs and the available data for the pre-2007 heavy-
duty vehicles indicate that the model inputs are reasonably representative. The relatively low
sulfate contribution in these profiles may not be appropriate for retrofit heavy-duty diesel
vehicles, however.
Response: At this time, MOVES does not incorporate effects of retrofits on the default
emission rates or speciation of PMemissions of pre-2007 trucks. MOVES has a retrofit
importer75 which can be used to adjust the emissions of pre-2007 trucks, but it does not
change the TOG or PM Speciation of the retrofitted vehicles.
E.5.2 Dr. Allen Robinson
The PM profiles were weighted using Kansas City MSA VMT data. How sensitive are the
profiles to that assumption? If they are sensitive then that potentially creates a number of
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concerns. How representative is that of other areas in the country? How representative are they
of future vehicle fleets?
Response: We added two paragraphs in response to this point, regarding the sensitivity
to the averaging assumptions, selection with Kansas City to represent the fleet average,
and the need for incorporating data on newer port-fuel injected vehicles, and gasoline-
direct (GDI) injected vehicles.
Section 4.2 - "But they are the major species by mass and reactivity" I am concerned about the
gaps between speciated and total emissions. The standard approach (adopted here), assumes that
the unspeciated portion of the NMOG behaves the same as the speciated. This likely is not the
case when it comes to secondary organic aerosol (SOA) formation. The unspeciated emissions
are likely a complex mixture of higher molecular weight species - these species contribute
disproportionately to SOA formation relative to lighter species (e.g. propane).
Response: The purpose of this MOVES document is to describe the incorporation of the
speciation process into MOVES2014 to provide model-ready species for air quality
modeling (previously the process occurred in SMOKE or as a pre-processor to SMOKE).
Issues involving the treatment of unknowns or unspeciated emissions pertain to sample
measurement and analysis, speciation profile development, and chemical mechanism
development and, as such, fall beyond the scope of this document. We will note that
OTAQ's approach to developing real TOG speciation profiles from mobile source
emissions data is to retain the unknown portion of the mass reported by analytical
laboratory.
For PM2.5profiles, our current modeling needs only require organic carbon as a broad
category, which does not require resolving the organic carbon into individual species
and unknown species. Discussion on achieving mass-balance for the PM2.5 profiles is in
Appendix C for each profile.
"while assuring that the PM2.5 species achieved a 100 percent mass balance" I find these sorts of
statements very concerning, especially given that these sorts of renormalizations are often poorly
documented resulting in users not being aware of these assumptions. It is important to document
if there are significant mass balance discrepancies, not just normalize them away. I realize that
the profiles don't have a PMunknown species, but enforcing mass balance may create other
problems.
Other studies with diesel (e.g. Schauer et al. 1999 EST, Subramanian et al. 2009 EST) show a
pretty significant gap in PM mass balance for diesels (sum of speciated low).
Response: We added the following text in Appendix C.3 to explain why we had over 100
percent mass closure species, because we did not use background corrected OC.
"Using uncorrected OC measurements likely contributed to the mass of the sum of the
speciated measurements being higher than Teflon filter measurements (Subramanian et
al. 2009) "
We incorporated the Subramanian et al. 2009 reference, which includes the references to
Schauer et al (1999) work.
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We give reasons in Section C. 3 for why Khalek et al. (2011) did not background correct
the OC measurements.
We also clarified the way in which the profile achieved mass balance, by adding
paragraph (3) in Section C.3 by clarifying that the sum of the individual species were all
renormalized to the PM2.5 filter measurements, and citing the SPECIATE 4.2
documentation that provides information on how this is done.
E. 6 General/Catch-All Reviewer Comments
Please provide any additional thoughts or review of the material you feel important to note that is
not captured by the preceding questions.
E.6.1 Dr. Tom Durbin
extra space - page 3 1st sentence (THC)page 4 elemental carbon " 5; Page 7 last sentence 1
might be extra space; page 8 under table 3 (field meanbase rate in..; page 14 section heading ...
for Evaporative
add space - page 8 (TOG): h;
add comma - page 3 3rd sentence , such as; page 6 nonECPM , such as; page 28 2nd full
paragraph (i.e.,;
page 3 sentence 4 add "to make TOG" to end of sentence,
page 3 last sentence first paragraph ..seems to be missing something
page 3 second paragraph 3rd sentence - under different measurement
page 4 elemental carbon - can a reference to the TOR method be provided?
page 4 chemical mechanism - to speed up the atmospheric...
page 5 integrated species - 3rd sentence CM-speciate is unclear
page 8 Table 4 not centered - some headings are centered but not others throughout
page 12 and 13 - there is an issue with the paging
page 14 & 15- issue with section numbering should be 3.4 and 3.5
page 15- section 4.1 1st sentence - MOVES2014 produces an or the output
page 28- 3rd full paragraph there is a reference in (EPA, 2014) and not number format
page 28- last paragraph "capability"
Response:
These suggestions regarding additional clarity in text, added references to the TOR
method, and grammar were addressed.
Comments on the PM2.5 Appendix C
p. 2. Missing high emitter study
page 1 2nd paragraph - updated speciation profiles changes
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the references are numbered in the main document, but use the name/year format in the
Appendix
add comma - page 3 (effective beginning 2006-2008),;
page 3 3rd paragraph. Missing period after	161.2 ppm. Fuel sulfur....
page 3 2nd to last sentence, imnpute
page 5 The CRC E-55/59 is listed three different was ... .E55/59, -55/59, E-55/59
page 6 first sentence - extra space 2010). 1; and 1st full sentence begins with number; 2nd to last
full sentence on page beings with a number
page 7 2nd paragraph "Instead we used calculated"; last sentence in paragraph impacteding
page 8 last sentence - the adjusted OC speciation factors are
Response: These suggestions regarding grammar, consistent formatting, and clarifying
text were addressed.
E.6.2 Dr. Allen Robinson
Page 5 Intermediate PM section — EC is not a "real" species in that it is not a distinct chemical
substance but something that is operational defined. Although not defined, I assumed a real
species was an actual chemical species like CO.
Response:
We clarified the definition of EC, in that it a measurement from thermal optical methods.
We removed the 'real'for EC, and instead classify it more correctly as a CMAQ PM2.5
species in the context in which it is discussed.
Page 7 Real speciation profile - A key shortcoming is that these real profiles are incomplete -
they are typically missing around a quarter of the TOG mass. This point is mentioned later but
should be mentioned here as well.
Response: The wording has been changed:
"Real speciation profile: ideally, a complete listing of the real species and their
quantities for TOG. In practice, these profiles are incomplete; a certain fraction of the
mass is unresolved."
The qualifier "start" is often used to characterize the emissions. Every instance of that should be
further classified as cold or hot start, as that can make a big difference on emissions. Many times
it was not clear what type of start the text was referring too.
Response: We added the following clarification regarding starts under "Process" in the
glossary term.
Within each process, emission rates can potentially vary by operating mode. Running
exhaust has different operating modes to represent, idle, coast, and different engine
loads. Start exhaust has different operating modes to differentiate a continuum of starts
between cold, warm, and hot starts. Definitions of the operating modes are contained in
the MOVES2014 emission rate reports30,33, and evaporative reports.12 For TOG and PM
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speciation in MOVES, different speciation profiles can be applied to each processes, but
not individual operating modes.
Page 3 defined by discrete - missing by
Response: We changed " which are defined discrete chemical species" to " which are
discrete chemical species."
Page 3 although "county"? Not sure what county is
Response: Text changed to:
"Sometimes speciation profiles varied by county to account for combinations of ethanol
fuel blends that varied by county. "
Page 9 "as the all" delete the
Page 14 - "3.1 NMHC and VOC calculations ..." this section heading is misnumbered.
Response: Corrected.
PM fractions of median profile greater than 1 -> how much greater than 1?
Response: We added the following text. "The sum of the PM fractions from the median
profiles is greater than one (112 percent of the Teflon mass for the Idle cycle, and 113
percent of the Teflon mass for the Transient Cycle). "
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References
1	USEPA (2003). Conversion Factors for Hydrocarbon Emission Components. EPA420-P-03-002. May 2003
2	40 CFR 1065 "Engine-Testing Procedures." Code of Federal Regulations.
3	40 CFR 1066 "Vehicle-Testing Procedures." Code of Federal Regulations.
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17	USEPA (1992) Procedure for Generating MOBILE5 Oxygenate Composite Correction Factors. Memorandum
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18	USEPA (2013). EPActA/2/E-89: Assessing the Effect of Five Gasoline Properties on Exhaust Emissions from
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28	CAMx v5.40 User's Guide. Chemistry Mechanisms Chemistry Mechanisms. Sep-11.
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30	USEPA (2015). Exhaust Emission Rates for Heavy-Duty On-road Vehicles in MOVES2014. EPA-420-R-15-015a.
Ann Arbor, MI, Assessment and Standards Division. Office of Transportation and Air Quality. US Environmental
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31USEPA (2015). Emission Adjustments for Temperature, Humidity, Air Conditioning, and Inspection and
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technical-reports
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Ann Arbor, MI, Assessment and Standards Division. Office of Transportation and Air Quality. US Environmental
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33	USEPA (2015). Exhaust Emission Rates for Light-Duty On-road Vehicles in MOVES2014. EPA-420-R-15-005.
Ann Arbor, MI, Assessment and Standards Division. Office of Transportation and Air Quality. US Environmental
Protection Agency. October, 2015. https://www.epa.gov/moves/moves-technical-reports
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