MEMORANDUM 

SUBJECT: Updates to MOVES for the Tier 3 NPRM Analysis

FROM: Megan Beardsley, Environmental Scientist

Assessment and Standards Division 

TO: Docket Number EPA-HQ-OAR- 2011-0135 

DATE: March 11, 2013 

The U.S. Environmental Protection Agency (EPA) is proposing new vehicle emission 

standards and fuel quality standards to reduce emissions of criteria pollutants. Collectively, 

these proposed standards are referred to as “Tier 3 vehicle standards” and “Tier 3 fuel 

standards.” 

As part of this analysis we estimated the impact of the Tier 3 proposal on the nationwide 

highway vehicle emissions of criteria pollutants, criteria pollutant precursors and selected air 

toxics. We made these estimates using an updated version of the EPA’s Motor Vehicle Emission 

Simulator (MOVES2010). 

The attached document details how the MOVES default code and databases were updated for 

the Tier 3 NPRM analysis. 
Updates to MOVES for the Tier 3 NPRM Analysis

March 2013

Air Quality & Modeling Center

Assessment & Standards Division

Office of Transportation & Air Quality

U.S. EPA
2

I. Introduction............................................................................................................................. 4

II. Fuel Effect Updates................................................................................................................. 5

A. Fuel Sulfur Impacts............................................................................................................. 5

1. New Research of Fuel Sulfur Effects on Emissions..................................................... 5

2. Implementation in MOVES.......................................................................................... 6

B. Fuel Effects from EPAct Study........................................................................................... 7

1. EPAct Fuel Effects on Criteria Pollutants.................................................................... 7

2. EPAct Fuel Effects on Selected Air Toxics.................................................................. 9

3. Additional Adjustments for Benzene and 1,3-Butadiene ........................................... 12

C. Additional Fuel-Related Changes to MOVES.................................................................. 12

III. Evaporative Emission Updates......................................................................................... 13

A. Permeation ........................................................................................................................ 13

B. Vapor Venting................................................................................................................... 14

1. Update of Vapor Venting Algorithms with new DELTA Model............................... 14

2. Multiple Day Diurnals................................................................................................ 14

3. Vapor Leaks................................................................................................................ 15

4. Summary of Updated MOVES Inputs for Vapor Venting ......................................... 18

IV. Update of Air Toxics and HC Speciation ......................................................................... 21

A. Algorithms for 2003-and-Earlier Gasoline Vehicles........................................................ 21

B. Estimating Emissions for Additional Air Toxics.............................................................. 23

1. Additional Air Toxics: Inputs for Gasoline Vehicles................................................ 24

a) Exhaust.................................................................................................................... 24

b) Evaporative and Permeation ................................................................................... 28

2. Additional Air Toxics: Inputs for Emissions from Diesel Vehicles.......................... 30

a) Exhaust.................................................................................................................... 30

b) Evaporative ............................................................................................................. 34

C. Hydrocarbon Speciation Factors....................................................................................... 35

1. HC Speciation of Exhaust Emissions......................................................................... 36

2. HC Speciation of Permeation Emissions.................................................................... 38

D. Additional Updates to Air Toxics and HC Speciation...................................................... 38

V. Updated Heavy Duty and Diesel Emission Rates................................................................. 38

A. Changes to Heavy Duty Gasoline Vehicle Rates.............................................................. 38

1. Regulatory Class Definition and Vehicle Composition ............................................. 39
3

2. Estimating Emission Rates......................................................................................... 40

B. Changes to Heavy- and Light-Duty Diesel Vehicle Rates................................................ 43

VI. Other Changes................................................................................................................... 43

A. Changes to Model Year Groups........................................................................................ 44

B. Changes to County Allocations ........................................................................................ 44

C. Repair of Errors................................................................................................................. 44

D. Changes to Facilitate Large Numbers of Runs................................................................. 44

VII. Impact of MOVES Changes ............................................................................................. 45

References..................................................................................................................................... 46
4

I. Introduction

The U.S. Environmental Protection Agency (EPA) is proposing new vehicle emission 

standards and fuel quality standards to reduce emissions of criteria pollutants. Collectively, 

these proposed standards are referred to as “Tier 3 vehicle standards” and “Tier 3 fuel 

standards.” 

As part of this analysis we estimated the impact of the Tier 3 proposal on the nationwide 

highway vehicle emissions of criteria pollutants, criteria pollutant precursors and selected air 

toxics. We made these estimates using an updated version of the EPA’s Motor Vehicle Emission 

Simulator (MOVES2010). This document describes how the MOVES default code and databases 

were updated for the Tier 3 NPRM analysis. 

MOVES2010 is EPA’s official model for estimating emissions from cars and trucks. At the 

time of its release, it incorporated EPA's most up-to-date information on gasoline vehicle 

emissions. Exhaust emission rates for HC, CO and NOx were developed based on an analysis of 

state inspection/maintenance and roadside remote sensing data from millions of vehicles.1 

Emissions of particulate matter are based on EPA's Kansas City gasoline PM study.

2

,

3

 

Evaporative emission rates were updated based on extensive evaporative testing conducted by 

EPA and the Coordinating Research Council (CRC) 4. 

However, since the release of MOVES2010, we have continued to collect and analyze 

emission data. In particular, we have completed two major studies of fuel effects on emissions in 

Tier 2 light duty gasoline vehicles, and an important collection of studies on evaporative 

emissions. Because fuels and evaporative emissions are affected by Tier 3 standards, it was 

important to include this data in our analysis. Sections below describe this data in detail and 

explain how it was incorporated into an April 14, 2011 version of the MOVES model software 

(MOVESGHGSource20110414a) and a May 12 version of the MOVES default database 

(MOVESTier3db20110512). Collectively, this memo refers to this software and database as 

MOVEST3NPRM.

When we updated the MOVES fuel effects and evaporative emissions, we also had an 

opportunity to improve the model’s emission estimates in other areas. Notably, we updated 

emissions for the air toxics and hydrocarbon species addressed in MOVES2010, and we 

expanded MOVES capabilities to include estimating all the air toxic pollutants in the National 

Emission Inventory (NEI) and National Air Toxics Assessment (NATA) that are emitted by

mobile sources.5 We also made some updates to heavy duty emission rates for diesel and 

gasoline vehicles. The sulfate, sulfur dioxide, organic carbon and elemental carbon emission 

rates for 2007-and-later heavy duty diesel vehicles were updated to include information from a 

recent study that examined the composition of particulate emissions from advanced diesel 

engines.6 HC, CO and NOx start and running emission rates for light heavy duty gasoline 

vehicles were updated to fix an error in these rates for 2007-and-later emissions, And, we made a 

number of miscellaneous changes including changes to fleet and activity inputs, repairs of minor 

errors, and changes to facilitate the large number of parallel runs required for the Tier 3 NPRM 

analysis.

Details on all these changes are provided in the sections below.
5

II. Fuel	Effect	Updates

A. Fuel	Sulfur	Impacts

MOVEST3NPRM includes updates to the effect of fuel sulfur levels below 30ppm on 

exhaust emissions. In MOVES2010 these effects were based on extrapolation from data on 

sulfur levels above 30 ppm. The updates made for this analysis were based on significant new 

data generated through EPA research on low sulfur fuels conducted in 2010 and 2011. 

1. New	Research	of	Fuel	Sulfur	Effects	on	Emissions

The EPA study assessed the emission reductions expected from the in-use Tier 2 fleet with a 

reduction in fuel sulfur level from current levels. The study was designed to take into 

consideration what was known from prior studies on sulfur build-up in catalysts over time and 

the effect of periodic regeneration events that may result from high speed and load operation 

over the course of day-to-day driving. The study sample consisted of 81 cars and light trucks 

covering model years 2007-9 , each with approximately 20,000-40,000 odometer miles. The 

makes and models targeted for recruitment were chosen to be representative of high sales 

vehicles covering a range of types and sizes. Test fuels were two non-ethanol gasolines with 

properties typical of certification fuel, one at a sulfur level of 5 ppm and the other at 28 ppm. All 

emissions data was collected using the Federal Test Procedure (FTP) cycle at a nominal 

temperature of 75°F. A draft report on this research is available.

7

Major findings from this study include:

 Reversible sulfur loading is occurring in in-use fleet of Tier 2 vehicles and has a 

measureable effect on emissions of NOx, hydrocarbons, and other pollutants of 

interest.

 The effectiveness of high speed/load procedures in restoring catalyst efficiency is 

limited when operating on higher sulfur fuel.

 Reducing fuel sulfur levels from 28 to 5 ppm is expected to achieve significant 

reductions in emissions of NOx, hydrocarbons, and other pollutants of interest in 

the in-use fleet, as summarized in Table 1, below.
6

Table 1 In-use emission reductions from 28 to 5 ppm sulfur

NOX (pvalue)

THC

(p-value)

CO

(pvalue)

NMHC

(p-value)

CH4

(p-value)

NOx+NMO

G

(p-value)

PM

‡

Bag 1 10.7%

(0.0033)

8.5%†

(0.0382)

7.5%†

(0.0552)

7.5%

(< 0.0001)

13.9%†

(< 0.0001)

N/A –

Bag 2 59.2%

(< 0.0001)

48.8%

(< 0.0001)

–

‡

44.8%†

(0.0260)

49.9%

(< 0.0001)

N/A –

Bag 3 62.1%

(< 0.0001)

40.2%

(< 0.0001)

20.1%

(< 0.0001)

49.9%

(< 0.0001)

29.2%

(< 0.0001)

N/A –

FTP 

Composite

23.0%†

(0.0180)

13.0%†

(0.0027)

11.9%†

(0.0378)

10.6%†

(0.0032)

25.8%†

(< 0.0001)

17.3%

(0.0140)

–

Bag 1 – Bag 

3

–

‡

5.2%

(0.0063)

4.3%

(0.0689)

5.1%

(0.0107)

4.6%

(0.0514)

N/A –

† Model with significant sulfur and mileage interaction term. ‡

Sulfur level not significant at α = 0.10. For THC Bag 

1 and CH4 Bag 1, because the effect of clean-out was not statistically significant, the reduction estimates are based 

on the estimates of least squares means.

2. Implementation	in	MOVES

The results shown in Table 1 were applied in MOVEST3NPRM for model year 2004-andlater gasoline vehicles (the nominal start of the Tier 2 phase-in) to estimate sulfur effects below 

30 ppm. The sulfur fuel effect applies multiplicatively to other gasoline fuel effects in MOVES, 

and applies only for sulfur levels below 30ppm. For sulfur levels above 30 ppm, and for all pre2004 model year vehicles, the sulfur effect originally used in MOVES2010 remains in place. 

Equation 1 shows the generic form of the new sulfur correction. Table 2 shows the specific 

values for the sulfur coefficients by pollutant, process, and vehicle type.

  = 1.0 −  ∗ (30 − )

Equation 1 Low Sulfur Effect

Table 2 Low Sulfur Coefficients by Vehicle Type, Process and Pollutant

Vehicle Type

THC CO NOX PM

Starts Running Starts Running Starts Running Starts Running

Motorcycle 0 0 0 0 0 0 0 0

Passenger Car, 

Passenger Truck & 

Light Commercial Truck

0.002237 0.020336 0.001866 0 0 0.024459 0 0

All other Vehicle Types 0 0.015488 0 0.009436 0 0.027266 0 0

These equations were then used to fill in the database table that houses fuel effect equations 

in the MOVES database (“GeneralFuelRatioExpression”). This table allows the MOVES model 
7

to compute fuel effects based on the fuel properties of any fuel contained in the fuel supply and 

fuel formulation database tables. 

In addition, in order to properly model fuel sulfur levels below 30 ppm using Equation 1 in 

MOVEST3NPRM, we had to modify an existing “floor” to the sulfur correction. In

MOVES2010, the MOBILE6 fuel sulfur algorithms, which utilized log-log relationship, were 

extrapolated for fuels with sulfur level below 30 ppm. To prevent highly non-linear relationships 

inherent in log-log equation from dominating the MOVES emission results, a fuel adjustment 

‘floor’ of 0.85 was added. This ‘floor’ prevented MOVES2010 from reducing the emission rate 

by more than 15 percent from the ‘base’ emission rate as a result of changing the base fuel 

formulation (30 ppm sulfur) to some other low level (i.e., 0.01 ppm sulfur). The floor is still 

needed for estimating sulfur reductions for model years 2001-2003 (which continue to be 

modeled with the original log-log equation), however, considering the reduction in emissions 

seen for fuel sulfur levels below 30 ppm in the latest EPA analysis, it was necessary in 

MOVEST3NPRM to change the sulfur ‘floor’ to 0.40. 

B. Fuel	Effects from	EPAct Study

As required by the Energy Policy Act of 2005 (EPAct), the EPA conducted an extensive 

evaluation of the effects of fuel properties other than sulfur on emissions from Tier 2 gasoline 

vehicles. The EPAct exhaust research program and analysis are extensively documented in the 

“EPAct Test Program Report” 8and “EPAct Analysis Report.”9 Information about the study is 

not repeated here. Because the fuel effects in MOVES were based on analysis of the Tier 0 and 

Tier 1 vehicles typical of the 1990s, we felt it was important to incorporate the EPAct study

results into our air quality analysis. However, given the many months of work needed for this 

analysis, we had to develop the fuel inputs for MOVEST3NPRM before the EPAct analysis 

described the second report was finalized. This section describes the preliminary analysis results 

that were used to generate the fuel effects inputs used in MOVEST3NPRM. Note, information 

on how the EPAct data was used to update hydrocarbon speciation rates is provided in Section

IV.C, below.

1. EPAct	Fuel	Effects	on	Criteria	Pollutants

MOVES estimates emissions immediately following engine starts (“start emissions”) as 

distinct from those from warmed-up operation (“running emissions”), and allows different fuel 

effects for these two modes of operation. Two sets of exhaust fuel effect coefficients were 

therefore employed in the model; one set of coefficients was applied to represent start emissions 

and a second set was applied to represent hot-running emissions. In some cases fuel effects 

estimated for these two processes differed substantially, as the effects of fuel properties on start 

emissions are dominated by changes in combustion and catalyst warm-up, while the impact of 

running emissions is dictated by catalyst efficiency when fully operational. 

The MOVES model accounts for the effect of fuel properties on vehicle emissions by

estimating emissions from vehicles operating on a “base fuel,” and multiplying these “base 

emissions” by a fuel adjustment to represent emissions on various in-use fuels. Different fuel 

adjustments have been developed to represent each pollutant and emission process. The fuel 

adjustment varies depending on the properties of the in-use fuel. It also varies depending on the 
8

type of vehicle, the model year and the age of the vehicle. The fuel effects used in MOVES2010 

are documented in an EPA technical report.10 The paragraphs below explain how these fuel 

effects were updated for purposes of the current analysis.

MOVEST3NPRMallows a very flexible input data format for incorporating and applying 

coefficients within a wide variety of mathematical forms. These “fuel-effect ratio expressions” 

can include up to 32,000 characters and are stored in a database table dedicated to this purpose 

(GeneralFuelRatioExpression).

The statistical models generated using EPAct results allow estimation of emissions 

effects related to five fuel properties: ethanol content (%), aromatics content (%), RVP (psi), T50 

(°F) and T90 (°F), as well as selected interaction terms among these five parameters. The 

statistical models generated from the EPAct exhaust data follow the general structure of 

Equation 2below. In this equation, β denotes a model coefficient, ZetOH and ZT90 denote 

“standardized” fuel terms for these properties, and ZetOH×T90 denotes a “standardized” term for an 

etOH×T90 interaction term.a For simplicity, only the terms for ethanol, T90 and their interaction 

have been shown; linear and interaction terms for the remaining three properties are not shown

here. Finally, the term sε

2

represents the residual error or “mean square error” for the model. Note 

that the subsets of the potential terms vary by emission and process, depending on the results of 

the statistical model fitting. Relative fuel effects are calculated by applying the models to 

specific “in-use” fuels and pre-defined “base fuels” and taking the ratio of the emissions on the 

in-use fuel to those on the base fuel, as shown in Equation 2 . 

e

2

0 etOH etOH [other linear terms] T90 T90 etOH T90 etOH T90 [other 2nd-order terms] 0.5

Emissions (g/mi) e

      Z   Z  Z   s  

 

Xβ

Equation 2. Generic Form of Statistical Model for Emissions in relation to Selected Fuel 

Properties.

base

in use

e

e

Fuel Effect Xβ

Xβ 



Equation 3 Generic Form of Relative Fuel Effect

Table 3 shows the coefficients for models used in Equation 3 Generic Form of Relative 

Fuel Effect

for four individual pollutants, including total hydrocarbons (THC) and the criteria 

pollutants CO, NOx, and PM. The application of these models has been integrated into 

MOVEST3NPRM. For implementation in MOVES, Equation 1Equation 3 is input directly into 

the GeneralFuelRatioExpression table using sets of coefficients from Table 3. The table presents 

two sets of coefficients for each pollutant, representing the effects of the fuel properties on start 

 

a Note that these coefficients apply to fuel properties that have been “standardized,” i.e., centered on their means and 

scaled by their standard deviations, based on the fuel-property matrix used to develop the models. To properly apply

the models, this process must be applied for the specific fuels under consideration. For more information on this 

technique, please see the EPAct analysis report.
9

and running exhaust emissions, respectively.

b Because these coefficients apply to “standardized” 

fuel properties, as mentioned above, the magnitude and sign of each term gives a sense of the 

influence of each term in the estimation of that pollutant relative to the others. For example, for 

PM start emissions, changes in aromatics and T90 are very influential, and are positively related 

with PM emissions (e.g., when aromatics increase, PM increases). For THC start emissions, on 

the other hand, the negative sign of the coefficient indicates that the relationship is inverse, i.e., 

increases in RVP are associated with decreases in THC. It is also important to note that the 

values of the coefficients presented in Table 3 represent the status of analysis and interpretation 

of the EPAct results at the time they were applied to this analysis. Thus, they sometimes differ 

from values presented the final analysis report9, which represent the outcome of additional 

analysis and interpretation.

Table 3. Coefficients for Models representing Regulated Gaseous Emissions and 

Particulated, from the EPAct Program.

Parameter THC CO NOX PM

Start Running Start Running Start Running Start Running

Intercept -0.86577 -4.90925 1.347166 -1.38957 -2.85935 -4.56921

etOH 0.067934 0.068143 -0.06967 0 0.067502 0.062989 0.1807 0.1158

aromatics 0.083434 -0.02281 -0.01156 0.097982 0.133931 0.044062 0.3792 0.1988

RVP -0.04669 -0.03953 0.020631 0.028383

T50 0.148984 0.071538 0.021592 0.024856 0.047821 0.1004 -0.0037

T90 0.014347 0.066813 -0.14685 0.041802 0.3034 0.0953

etOH×etOH 0.040652 0.085346

T50×T50 0.075548 0.030543 0.07222 0.0806

etOH×Arom 0.022971 0.040277 0.062441 -0.02369

T50×T90 0.050029 0.028862 0.021773 0.1059

etOH×T50 0.034265 0.111736

etOH×T90 0.047815 0.0647

arom×RVP 0.025524 0.0537

arom×T50 0.033858 0.058589

arom×T90 0.022605 0.038612 0.0665

variance 1.0443

 

2. EPAct	Fuel	Effects	on	Selected	Air	Toxics

For use in MOVEST3NPRM, inputs were also developed and applied to estimate 

emissions of selected toxic compounds and ethanol, but the approach differed from that 

described above for hydrocarbons and the criteria pollutants. Rather than estimating the change 

in emissions for one compound relative to two different fuels, the approach for toxics estimates 

the toxic emissions as a fraction of theVOC emissions on the same fuel. The compounds 

selected for this analysis include acetaldehyde, formaldehyde, acrolein, benzene and 1,3-

 

b

For all models, “start” and “running” emissions are represented by results measured on Bags 1 and 2 of the LA92 

cycle, respectively.
10

butadiene, all identified as national or regional risk drivers in the 2005 National-scale Air Toxics 

Assessments (NATA).11 

Table 4 shows coefficients for statistical models for ethanol and the five toxics. These 

models were developed using techniques similar to the models shown in Table 3, using speciated 

results obtained from the EPAct exhaust program. The coefficients for the toxics models are 

interpreted and applied in the same way. However, two differences must be noted: as resources 

limited the number of tests for which hydrocarbons could be speciated, some statistical models 

were developed using smaller subsets of data and are thus simpler in structure, including only 

subsets of the four linear terms etOH, arom, T50 and T90 and no second-order terms. In the 

table, models fit using reduced data subsets contain no cells for the terms not included, and the ‘-

--“ symbol indicates that RVP was not included. 

In addition, as VOC are calculated as non-methane organic gases (NMOG) minus ethane 

(H3CCH3), it was necessary to develop analogous models for are both NMOG and ethane. 

Coefficients for these two models are shown in Table 5. Models for these two compounds were 

calculated in the same manner as those shown in Table 3 and Table 4. Note that models for both 

start and running ethane were developed using reduced data subsets.

Thus, if we let Xβtoxic, XαNMOG and Xθethane represent models for a selected toxic 

compound, NMOG, and ethane, respectively, calculated by applying Equation 2 to each 

compound for a specified fuel, the toxic emissions as a fraction of VOC emissions is given by

NMOG ethane

toxic

e e

e

Toxic Fraction toxic Xα Xθ

Xβ



 f 

Equation 4. General expression for toxic fractions.

Also note that models representing running emissions are not available for three compounds: 

acrolein, benzene and 1,3-butadiene. For these compounds, the relevant subsets of data were 

inadequate to allow model fitting. Therefore, for these compounds, running emissions were 

represented as constant fractions of VOC, with values derived from the available data. For 

acrolein, benzene and 1,3-butadiene, the values of the fractions were 0.00077, 0.047 and 0.0, 

respectively. 
11

Table 4. Fuel Effect Coefficients for Selected Toxic Pollutants from EPAct Exhaust 

Program

Parameter Acetaldehyde Formaldehyde Acrolein Ethanol Benzene 1,3-

Butadiene

Start Running Start Running Start Start Running Start Start

Intercept -5.23229 -9.41919 -5.97707 -8.65741 -7.93381 -4.90805 -9.56335 -4.1074 -5.91748

etOH 0.81449 0.190954 0.229862 0.078035 0.247572 1.462653 0.816632 -0.12725

arom 0.034835 0.028224 0.112172 0.403208

RVP -0.0417 --- -0.04718 --- -0.0645 -0.06054 --- --- ---

T50 0.086703 0.167177 0.188036 0.070291 0.039682

T90 0.038013 0.13018 -0.08322 0.248876 -0.09923

etOH^2 -0.16694 -0.0831 -0.49699

T50^2 0.066653 0.052617 0.110804

etOH*arom 0.018402 0.016505

etOH*RVP 0.02194

T50*T90 0.039593 0.034887 0.059859

etOH*T50 -0.01627 -0.11858

etOH*T90 0.020043 0.046167

Variance 

(sε

2

)

0.2034 0.46902 0.4765 0.45999 0.46611 0.701256 1.927463 0.4635 0.13059

Table 5. Fuel Effect Coefficients for NMOG and Ethane, from EPAct Exhaust Program

Parameter NMOG Ethane

Start Running Start Running

Intercept -0.9574 -5.5218 -4.3412 -7.7241

etOH 0.08783 0.09213 0.05222

arom 0.1037 0.02477 -0.1925 -0.1092

RVP -0.04745 -0.03752 --- ---

T50 0.1535 0.092137 0.1830 0.1452

T90 0.009353 0.1114 0.1270

etOH^2 0.0414

T50^2 0.07934 0.06726

etOH*arom 0.02172 0.07561

etOH*RVP -0.0303

T50*T90 0.05249

etOH*T50 0.03658 0.04477

etOH*T90 0.04798

Arom*RVP 0.02616

Arom*T50 0.07454

Arom*T90 0.02022 0.03430

RVP*T90

Variance (sε

2

) 0.1949 1.853 0.2750 2.822
12

3. Additional	Adjustments for	Benzene	and	1,3-Butadiene

For two compounds, benzene and 1,3-butadiene, additional refinements were applied to 

address limitations of the EPAct study design. For benzene, the issue was that the fuel matrix 

included aromatics generally, but not benzene specifically. We considered it inadequate to model 

benzene in exhaust without explicitly accounting for benzene levels in fuel, so we chose to 

develop a post-hoc refinement using data external to the EPAct program. In this case the source 

was a program conducted in support of the 2007 MSAT2 rule. This program performed 

measurements on nine Tier 2 certified vehicles on fuels with benzene levels ranging from 0.6 to 

1.1 percent by weight.12,13 With benzene represented as a fraction of VOC (as in Equation 4) 

denoted as fbenzene, a value modified to account for benzene levels in different fuels (f*benzene) is 

calculated as shown in Equation 5 where xbenzene is the benzene level for the fuel modeled 

(weight percent), A is the mean benzene level in the EPAct exhaust program fuel set (0.66 

weight percent), and B is a coefficient, taking a value of 0.24. 

   benzene benzene benzene

*

benzene f  x  A  B f  f

Equation 5. Benzene Correction

Similarly, given the importance of olefins to estimation of emissions for 1,3-butadiene, and the 

fact that the EPAct exhaust program study design did not incorporate olefins as a factor, we 

developed a post-hoc adjustment explicitly accounting for olefin level. This adjustment was 

derived by varying olefin levels in the Complex Model14 and fitting a polynomial trend to the 

results.15 Starting with an unadjusted toxic fraction for 1,3-butadiene (fbuta), the modified fraction 

f

*

buta is calculated using Equation 6, in which xolefin is the olefin level, and A, B, C and D are 

coefficients, taking values of 0.000008, 0.0002, 0.0069 and 0.008823, respectively.











  



D

Ax Bx C

f f

olefin

2

olefin

buta

*

buta

Equation 6. 1,3-Butadiene Correction

To estimate emissions for other gaseous air toxics, additional updates were incorporated 

into MOVES for this analysis. Additional compounds include 2,2,4-trimethylpentane, 

ethylbenzene, n-hexane, methyl-tert-butyl ether, propionaldehyde, styrene, toluene, and xylenes. 

For these pollutants, toxic-to-VOC ratios were derived from speciation profiles and applied to 

VOC as estimated by MOVES. These ratios varied between pre-2004 and 2004 and later 

vehicles, and also among E0, E10 and E15 blends. For more information, see Section IV.B. 

below.

C. Additional	Fuel-Related	Changes	to	MOVES

Quantifying emissions from the proposed Tier 3 rule required a number of other minor 

changes to the MOVES2010 fuel databases and fuel effects code.

Because MOVES2010 models distinct fuel supplies only through 2012, we updated the fuel 

supply support tables to supporting tables to allow distinct fuel supplies for calendar years 
13

through 2050. Also, as described in Section III.A below, we updated the permeation calculation 

to allow modeling of E15 fuels.c

Additional fuel related changes to the MOVES model include the addition of T50 and T90 as 

fuel parameters in the FuelFormulation table (these parameters will be calculated from E200 and 

E300 if not present, otherwise the MOVES model will default to using T50 and T90 values); a 

correction to an error in the fuel effects generator; and a correction to ensure that ethanol 

emissions are modeled as zero in counties where ethanol fuel blends are not present. Other fuelrelated changes included replacing the “NULL” values in the default fuel descriptions with 

actual values, and deleting most fuels from the MOVES default database, since they were 

provided in county-specific databases. We also changed the operation of the fuel importer to 

require users to import all fuel formulations needed for a given county, year, and month.

III. Evaporative	Emission	Updates

Evaporative emissions account for a significant portion of the gaseous hydrocarbon 

inventory. For MOVEST3NPRM, the evaporative emission calculations were updated 

significantly. We changed the calculation of permeation emissions to account for the E15 fuels 

modeled in the reference and control scenarios. More importantly, we updated the calculation of 

vapor venting emissions to account for results from a multi-year research program that improved 

our understanding of the vapor venting process, the emission consequences of long-duration 

parking (“multi-day diurnals”) and the prevalence of vapor leaks. These updates are detailed in 

the sections below. We made no changes to the modeling of liquid leaks.

A. Permeation

MOVES2010 already included effects of E10 on permeation emissions for newer technology

vehicles, based on data collected by Coordinating Research Council (CRC) in the E-65.3

program and as part of the more recent CRC E-77 series of evaporative emissions programs.16

These data showed a significant change in the relative impact of E10, from a 65 percent increase 

for pre-enhanced vehicles, to a 213 percent increase for newer technology vehicles.17 The CRC 

E-77 analysis also confirmed the E-65.3 finding that there is no significant difference between 

emission effects on E5.7 and E10. 

The use of E15 in the reference and control fuel supplies modeled for the Tier 3 NPRM 

required that MOVES model E15 permeation effects as well. The E-77 program evaluated 

permeation emissions on E20 as well as E10, and found that there was not a significant 

difference in permeation emissions between these two blends. These data, in conjunction with 

the E-65.3 data discussed above, suggest that any level of ethanol in the fuel results in large 

increases in permeation emissions, but that the magnitude of increases are largely insensitive to 

 

c We also began to add tables and code to the MOVES model to facilitate the modeling of 

flexible fuel vehicles (FFVs) operating on E85. When it became clear that FFV usage was 

negligible in the scenarios to be modeled for the NPRM, this work was not completed. Thus, 

while some portions of the MOVEST3NPRM appear to provide the capability to model E85 

emissions, the model should not be used for that purpose.
14

how much ethanol is in the fuel. As a result, in MOVEST3NPRM, we applied the E10 

permeation effects to E15 as well. 

These data also indicated significant impacts on toxics that differed from other types of 

evaporative emissions. The toxics impacts were not analyzed in time for inclusion in 

MOVES2010, but were included in MOVEST3NPRM, as explained in Section IV.B.1.b) ,below. 

B. Vapor	Venting

When a vehicle’s fuel system warms (due to ambient temperature rise while a vehicle is 

parked, or from vehicle operation), fuel vapors are generated. These may escape into the 

atmosphere if the capacity of the evaporative control system is exceeded, or through system 

leaks. 

In particular, as a vehicle sits, without driving, through multiple diurnal cycles, the carbon 

canister accumulates vapor every day. It can only adsorb vapor until it reaches its finite capacity;

then it begins to vent to the atmosphere. A canister with degraded/damaged carbon may have 

reduced capacity, but eventually every canister will vent to the atmosphere when the carbon 

reaches saturation. Upon reaching saturation, a canister acts in a relatively predictable manner. 

During cooling hours, the canister backpurges to the fuel tank and regains some of its capacity. 

Then, during the subsequent warming period, that capacity is re-filled with vapor and any excess 

vapor generated will escape to the atmosphere.

MOVES2010 has a specific Tank Vapor Venting emission module to account for vapor 

venting emissions, but does not account for soaking periods of longer than 24 hours. Based on 

new research findings, updates to MOVES were required to account for longer duration diurnal 

events, to improve the distinction between evaporative canister breakthrough and vapor leaks, 

and to reflect new vapor venting emissions data from the CRC E-77 program. 

1. Update	of	Vapor	Venting	Algorithms	with	new	DELTA	Model

MOVES2010 estimates vapor venting emissions by calculating vapor generated as a function 

of temperature rise and fuel RVP, and a test-data-based relationship between the amount of 

vapor vented compared to the amount generated based on available diurnal emission test data.

The MOVES2010 evaporative emissions estimates were based on in-use data collected between 

1994 and 1996.

18 This dataset provides SHED evaporative emissions (in grams) for a large set of 

vehicles undergoing a single diurnal cycle. Although the data used in MOVES 2010 provided a 

large and robust dataset for one day of emissions, and the resulting emissions rates provided a 

good estimate of average overall venting emissions, we wanted to improve our ability to model 

emissions in situations where the cannister capacity might be exceeded, such as when vehicle 

uses high RVP fuels (e.g. E15) or parks for multiple days.

To improve MOVES’ ability to model this breakthrough effect, the “Diurnal Emissions Lost 

to Atmosphere” (DELTA) model was developed.19This model applied theoretical vapor 

generation models to data from the CRC E-77 program on 9 and 10 RVP fuel, to produce vapor 

venting emission rates for MOVES. 

2. Multiple	Day	Diurnals

The DELTA model described above provided a way for us to estimate emissions for longduration parking (multi-day diurnals) episodes, but did not address the question of the frequency

of such events. While there have been many activity studies that track vehicle operation, very
15

few have focused on the question of vehicle inactivity. The only source of data we found to 

address this question was a study performed by Georgia Tech, which instrumented vehicles for 

two year time periods, and also surveyed participating households on the driving patterns of all 

vehicles in a household20. It was found that 16 percent of all household vehicles surveyed drove 

less than 3,000 miles per year21. We lack information to know how many of these vehicles are 

driven on frequent short trips or very infrequent longer trips, but assuming that at least half of 

these vehicles have long soaks or drive without purging the canister, we used this value to 

estimate that at a given time 8 percent of the fleet has been soaking for 5 days or longer (the 

maximum soak length we’ve included in MOVES). For implementation in MOVES, the number 

of vehicles experiencing day 2 through 5 of a diurnal are modeled as a percent of the vehicles 

that have been soaking since the beginning of the day. The resulting estimate of the percent of 

vehicles soaking for multiple days, by time of day, is shown in below.

Figure 1 Percentage of Vehicles Soaking By Time of Day

Although a relatively small number of vehicles soak beyond one day, they are important 

because their emissions are disproportionately high. The MOVEST3NPRM code was modified 

to incorporate the DELTA model and to model the complex processes of backpurge and canister 

capacity over multiple days. 

3. Vapor	Leaks

MOVES was also updated to reflect the prevalence of vehicles with evaporative leaks based 

on field research conducted in Denver between 2008 and 2010.

22

 In MOVES2010, emissions for 

properly functioning and leaking vehicles were averaged into a single rate. In MOVEST3NPRM, 

we have distinguished the emission rate for a properly functioning evaporative control system 

from the rate for vehicles with leaks. A leaking vehicle essentially 'bypasses' the canister system, 

and generated vapor will escape through the leak location.
16

In the Denver field studies, a remote sensing device (RSD) was used to recruit vehicles 

which were prepped and measured in a PSHED (Portable Sealed Housing for Evaporative 

Determination). The vehicles’ hydrocarbon emissions were recorded for 15 minutes and leaking 

vehicles were inspected to identify the cause/source of the vapor leak. Using the individual 

vehicle data along with the data on the population of vehicles passing the RSD, the prevalence of 

vapor leaks in the fleet was estimated (see Figure 2).

We have classified a “vapor leaker” as any vehicle that would fail the enhanced 

evaporative standard of 2 grams. The standard sums the emissions from the worst day of a 3-day

diurnal test and the hot soak. To develop a surrogate standard for a 15 minute hot soak test, we 

used knowledge of certification testing to attribute 0.4g of the 2g standard to the hot soak 

portion, and, 0.3 grams of 0.4 grams to the first 15 minutes of the hour-long hot soak test. This

approach results in 0.3g as a surrogate standard for a 15 minute hot soak. 

Figure 2 Estimated Distribution of PSHED values in the Ken Caryl Fleet by Model Year 

Group

When observing the difference between two points in the above figure, one can determine 

how many vehicles fall into a particular emission range. For example, in model year group 1981-

1995, 2.6% of vehicles are leaking at more than 20g/15min and 6.5% of vehicles are leaking at 

0.0

0.1

0.2

0.3

0.4

0.5

0.6

1 10 100

High-PSHED Definition (g/Qhr)

E

stim

ate

d

Fra

ctio

n

o

f

K

e

n

C

aryl Fle

et

with

Hig

h

P

S

H

E

D

1961-1970

1971-1980

1981-1995

1996-2003

2004-2010
17

more than 10g/15min. Subtracting these two values yields that 3.9% of vehicles in the model 

year group have a leak between 10g/15min and 20g/15min. This process reveals that older 

vehicles not only have more leaks, but larger leaks.

Because the detailed, by model year, data only contain prevalence rates for PSHED 

measurements as low as 1.0g/15min, failure rates are extrapolated to 0.3g/15min. Using 

aggregate data from the Ken Caryl station, it is found that 0.3g/15min PSHED measurements are 

50% more prevalent than 1.0g/15min PSHED measurements.

Linear extrapolation and interpolation is used to model vapor leak prevalence for ages 

and model years not represented in this cross-sectional study. We assume newer cars will have 

lower leak prevalence than older cars. We also divide model year groups at the year new 

technology was introduced. However, because we know vapor leaks also occur due to 

tampering, mal-maintenance, and other non-durability related issues, technology is not the only

factor in a vehicle having a vapor leak. The older model year regressions always have a more 

severe deterioration than newer model years. Failure rates at different severities are included 

below for two of the different age groups (see Figures 3 and 4).

Figure 3 Extrapolated Prevalence Rates for Binning Leaks in MOVES, Age 0-3
18

Figure 4 Extrapolated Prevalence Rates for Binning Leaks in MOVES, Age 20+

4. Summary	of	Updated	MOVES	Inputs	for	Vapor	Venting

The MOVES cumtvvcoeffs table in the default database was updated to include the new 

inputs required to more accurately model cold soak vapor venting emissions and separate nonleaking from leaking vehicles. The new fields are described below in

Table 6.
19

Table 6 New Columns in ‘cumtvvcoeffs’ Table

Column Name Brief Explanation How it’s used

backPurgeFactor The percent of canister 

capacity regained during the 

diurnal cooling cycle. 

For example: A canister with a gasoline 

vapor capacity of 200 grams fills to 100 

grams in the first day. With a 

backPurgeFactor of 35%23, it will begin 

day 2 filled to 65 grams.

averageCanister This is the sales-weighted 

average Gasoline Working 

Capacity. Canisters have 

typically increased in size over 

time and with new regulations.

When vapor generated > averageCanister

capacity, emissions are released to the 

environment. This is also the maximum 

value to which backPurgeFactor can be 

applied.

tvvEquation An equation representing how 

much vapor is vented per unit 

vapor generated for nonleaking vehicles

These emissions are weighted with the 

leaking vehicle emissions estimated with

leakEquation.

leakEquation A linear equation representing 

how much vapor is vented per 

unit vapor generated for 

leaking vehicles

These emissions are weighted with the 

vapor venting emissions estimated with 

tvvEquation.

leakFraction The fraction of vehicles 

leaking. Used to weight 

together tvvEquation and 

leakEquation. The leak 

fraction is a function of model 

year and age.

weightedLine = 

leakFraction*leakEquation+(1-

leakFraction)*tvvEquation

tankSize The Sales-weighted average 

size of gas tank.

The tankSize is a key factor in calculating 

how much vapor is generated. A larger 

tank with the same tankFillFraction as a 

smaller tank will generate more vapor due 

to a larger headspace.

tankFillFraction The average fill level of gas 

tanks.

This is applied to the tankSize to calculate 

how much headspace is available for 

vapor generation.

A key improvement facilitated by these new coefficients is the development of 

tvvEquation and leakEquation. The emission curves that were previously in the model were 

drawn in grams of vapor generated per gallon of headspace, and only intended for one day of 

emissions. The new curves use total grams as the unit and are intended to model the complex 

processes of backpurge, canister capacity, and multiple days. The tvvEquations are complex 

exponential curves created using data from the E-77 programs24 using the DELTA model25. The 

leak equations are linear equations developed using emission rates of known leakers. The data on 

leaking vehicles comes from the E-77 program and Colorado High Evap program26. These two 

curves are generated in the database for each source type, model year group, and age group. Each 
20

set of curves has a leak fraction (representing the percent of leaking vehicles in that population) 

that is used to weight the two curves together to produce a composite curve.

We model mission rates for vapor leaks as a linear relationship between total tank vapor 

generated (TVG) and tank vapor vented (TVV). TVG is calculated using the Wade-Reddy 

equation which determines TVG as a function of fuel RVP, fuel ethanol content, temperature 

rise, and tank fill level. There are two datasets used to develop vapor leak emission rates. The E77 program supplied information on high emitting vehicles, with known fuel properties and 

implanted leaks, that were tested on the California diurnal cycle. The Colorado program

provided information on 16 leaking vehicles. They performed a 6-hour SHED test consisting of a 

controlled heat rise from 72F-96F. This test provides us with enough information to calculate 

TVG. For both programs, the Sealed Housing for Evaporative Determination (SHED) emission 

measurements along with calculated TVG obtain enough information to apply a linear regression 

model of the relationship between fuel vapor generated and fuel vapor vented.

Vapor leak emissions span many orders of magnitude given their diverse locations and 

sizes. Since our leak prevalence estimates were measured at high altitude in Denver, we must use 

a correction factor for the way we bin the leaking vehicles. Using the Wade-Reddy equation, we 

can calculate that Denver E10 fuel generates 1.41 times as much vapor as Sea Level gasoline. 

For example, a vapor leak at the rate of .3g/15min in Denver will equate to a .21g/15min leak at 

Sea Level. The bins used to categorize vapor leak severity as well as the average vapor leak 

emission rate for that bin are listed in the table below.

Table 7 Vapor leak emission rates by bin

Denver bins 

(grams/15min)

Sea Level bins Grams vented / grams generated

0.3-2 0.21-1.42 0.1191

2-5 1.42-3.55 0.2686

5-10 3.55-7.09 0.6492

>10 >7.09 1.3273

The hot soak measurements from the E-77 programs and the PSHED (Portable SHED) 

measurements from the Denver program are used to bin each vehicle. In addition, the 

corresponding diurnal test provides information necessary to determining the leak emission rate.

For each model year and age group combination, the vapor leak prevalence for each severity bin 

is applied to the corresponding vapor leak emission rate. The result is a vapor leak emission rate 

representative of all vapor leaks greater than 0.3g/15min. This representative leak emission rate 

is then weighted by the leak prevalence with the non-leaking emission rate. See Figure 5.
21

Figure 5 Example of how leak emission rates are calculated using prevalence rate bins

IV. Update	of	Air	Toxics and	HC	Speciation

The calculation of air toxics and the speciation of hydrocarbons was updated in the version of 

MOVES used for the Tier 3NPRM analysis. As described in Section II.B above, the EPAct 

analysis led to changes in the fuel effects for some major air toxics. Other changes to MOVES 

included the capability to estimate emissions for many air toxics not available in MOVES2010a

(but now available in MOVES2010b). The section below details these changes.

Also, the documentation of toxic calculations for MOVES2010 did not include details on the 

calculation of some toxics for 2003-and-earlier gasoline vehicles. These calculations are 

unchanged from MOVES2010, but are documented here for completeness.

A. Algorithms	for	2003-and-Earlier	Gasoline	Vehicles

For 2003-and-earlier model year gasoline vehicles, the algorithms for calculating emissions 

of major air toxics are unchanged from MOVES2010a. The algorithms used for benzene, 1,3-

butadiene, formaldehyde, and acetaldehyde are documented in this subsection for completeness.

 For 2003-and-earlier light-duty cars and trucks, all heavy-duty gasoline vehicles and all 

motorcycles, algorithms used to calculate toxic ratios are the same as in MOBILE6.2. In 

MOBILE6.2 toxic ratios between light-duty gasoline vehicles and heavy-duty gasoline vehicles 

differed; however, since the only available data for heavy-duty gasoline vehicles were extremely

limited, and mostly from vehicles with either no emission controls or early oxidation catalysts, 

> 10g / Qhr > 5g / Qhr > 2g / Qhr > 0.3g / Qhr < 0.3g / Qhr

Non-leak 

measurem

ents

mean mean mean mean

x x x x

5% 10% 25% 60%

weighted

leak rate

mean nonleak rate

x x

5% 95%

MOVES 

Emission 

Rate

Leak Measurements
22

for MOVES we decided to apply toxic to VOC ratios from light-duty gasoline vehicles to VOC 

emissions for this vehicle class.

Toxic to VOC ratios for benzene, 1,3-butadiene, formaldehyde, and acetaldehyde exhaust 

emissions from light-duty gasoline vehicles with three-way or three-way plus oxidation catalysts 

were estimated using algorithms developed for the Complex Model for Reformulated Gasoline.27

For MTBE, a draft fuel effects model based on the Complex Model database was used.28 This 

model is based on algorithms from underlying data of nearly 900 observations. However, 

instead of using model algorithms directly, MOBILE6.2 was run at different fuel MTBE levels 

and a curve of fuel MTBE to MTBE/VOC ratios was developed. This curve was then used in 

MOVES. It should be noted that the sulfur effects terms in the algorithms were not used; 

instead, sulfur impacts on toxic emissions were assumed to be proportional to the sulfur impacts 

on total VOC estimated by MOVES. The Complex Model algorithms are based on data from 

vehicles representing a 1990 model year fleet. 

For benzene, 1,3-butadiene, formaldehyde, and acetaldehyde, the algorithms are based on 

about 1800 observations. The algorithms are applied by stratifying the light-duty gasoline fleet 

into ten Technology Groups and applying the algorithms individually to each group (this is 

known as the unconsolidated Complex Model). The ten groups are formed as a combination of 

fuel system, catalyst type, air injection (y/n toggle), EGR, and Normal / High emitter status. 

These groups are listed in Table 8. The first nine groups represent only normal emitting vehicles. 

The tenth group represents all of the high emitters, regardless of technology. Separate toxic

ratios are calculated for each of the groups and weighted together by the fraction of the fleet 

attributable to each technology group in MOBILE6. 

Table 8 Technology groups in the Complex Model for Reformulated Gasoline

Technology Group Definitions

Technology Group Fuel System Catalyst Air Injection EGR

1 PFI 3WAY NO AIR EGR

2 PFI 3WAY NO AIR NO EGR

3 TBI 3WAY NO AIR EGR

4 PFI 3WAY + OX AIR EGR

5 PFI 3WAY AIR EGR

6 TBI 3WAY AIR EGR

7 TBI 3WAY + OX AIR EGR

8 TBI 3WAY NO AIR NO EGR

9 CARB 3WAY + OX AIR EGR

High Emitters ALL ALL ALL ALL

PFI = port fuel Injection, TBI = throttle body injection, CARB = carburetor, 3WAY = three way catalyst, 3WAY + 

OX = three way plus oxidation catalyst, ERG = exhaust gas recirculation

For light-duty gasoline vehicles with oxidation catalysts only or no catalysts, toxic to VOC 

ratios for these pollutants are determined using algorithms derived from a more limited data set 
23

of about 50 vehicles tested on a baseline fuel and a small number tested on reformulated fuels. 

Data were not available to develop algorithms for ETBE and TAME blends; thus, the algorithms 

for ethanol oxygenated gasoline were used for ETBE blends, and the algorithms for MTBE 

oxygenated gasoline were used for MTBE blends. 

For vehicles running on 10 percent ethanol, 2.39 percent of exhaust VOC was estimated to be 

ethanol. This estimate is based on tests on nine vehicles from four test programs.29, 30, 31, 32 

MOVES also has ethanol to VOC ratios for E5 and E8, based on linear interpolation from the 

E10 value (0.01195 for E5 and 0.01912 for E8).

B. Estimating	Emissions	for	Additional	Air	Toxics

The version of MOVES used for the Tier 3 NPRM analysis was expanded to include all air 

toxic pollutants in the National Emission Inventory (NEI) and National Air Toxics Assessment 

(NATA) that are emitted by mobile sources. This list of pollutants is provided in Table 9. These 

pollutants are organized into four categories:

1) Gaseous hydrocarbons

2) Polycyclic aromatic hydrocarbons (PAHs) – These hydrocarbons which contain fused 

aromatic rings can be found in the gas phase, particle phase, or both, depending on 

properties of the compound, particle characteristics, and atmospheric conditions

3) Dioxins and furans – polychlorinated organic compounds which are persistent and 

bioaccumulatived

4) Metals

Emissions for gaseous HAPs and PAHs are reported in analyses for the Tier 3 regulatory

analysis. The pollutant “xylenes” represents the sum of emissions from three isomers of xylene: 

o-xylene, m-xylene, and p-xylene. Emissions of metals and dioxins and furans are not reported, 

since MOVES estimates these using straight emission rates which do not change with fuel 

properties or criteria pollutant emission levels. Thus, scenarios being evaluated will have no 

impact on inventories for these pollutants. 

 

d MOVEST3NPRM should not be used for dioxin modeling. The dioxin rates in MOVEST3NPRM were entered 

using incorrect units. This error does not affect our analysis which did not consider dioxin emissions.
24

Table 9 Air toxics included in MOVESTier3NPRM

Pollutant

MOVES Pollutant 

ID CAS Number

Gaseous Hydrocarbons

1,3-Butadiene 24 106990

2,2,4-Trimethylpentane 40 540841

Acetaldehyde 26 75070

Acrolein 27 107028

Benzene 20 71432

Ethanol 21 64175

Ethyl Benzene 52 100414

Formaldehyde 25 50000

Hexane 55 110543

Methyl Tert Butyl Ether (MTBE) 22 1634044

Propionaldehyde 58 123386

Styrene 60 100425

Toluene 61 108883

Xylenes 62 1330207

PAHs

Acenaphthene 41 83329

Acenaphthylene 42 208968

Anthracene 44 120127

Benz(a)anthracene 45 56553

Benzo(a)pyrene 46 50328

Benzo(b)fluoranthene 47 205992

Benzo(g,h,i)perylene 48 191242

Benzo(k)fluoranthene 49 207089

Chrysene 50 218019

Dibenzo(a,h)anthracene 51 53703

Fluoranthene 53 206440

Fluorene 54 86737

Indeno(1,2,3,c,d)pyrene 56 193395

Naphthalene 23 91203

Phenanthrene 57 85018

Pyrene 59 129000

1. Additional	Air	Toxics:		Inputs	for	Gasoline	Vehicles

Data methodologies and sources are provided for gasoline vehicles running on E0, E10, 

E15 and E20 gasoline.

a) Exhaust

Exhaust inputs developed for the additional air toxics do not vary by temperature or 

operating mode. While empirical data suggest toxic to VOC and toxic to PM ratios differ for 

start versus running emissions, we decided not to vary these inputs in the model by operating 
25

mode for two key reasons. First, for advanced technology vehicles, HAP emissions during 

running operation are often below levels of quantitation in test programs. Thus, using data from 

running operation only would necessitate heavy reliance on imputed data. Second, with the large 

number of toxics modeled, applying separate inputs would be place additional computational 

demands on the model. Ambient temperature also affects these ratios, but we assumed toxic 

emission of gaseous toxics and PAHs change proportionally with VOC and PM as temperature 

varies. In general, data are inadequate to account for temperature effects on toxic to VOC and 

toxic to PM ratios. Emission rates for metals are assumed to be independent of operating mode 

and temperature; very little data exist to account for impacts of these parameters.

For 2003 and earlier vehicles, toxic to VOC ratios for E0 an E10 were developed by Sierra 

Research33 using estimates from EPA’s SPECIATE 4.2 database (Table 10). Toxic to VOC 

ratios for MTBE blends, however, were obtained from the National County Database in the 

National Mobile Inventory Model (NMIM).

34

 NMIM uses the toxic to VOC ratios described in 

the documentation for the 1999 NEI for HAPS, version 3, and summarized in Volume 1, 

Appendix D, Table 1 of the documentation.35 Ratios for LDG vehicles were used for all gasoline 

vehicle classes. These ratios were based on older speciation profiles than the E0 and E10 data. 

Separate ratios are used for each of the following four categories of gasoline blends:

1. Baseline Gasoline. All cases that do not fall into categories 2-4 below. 

2. 10 perecent Ethanol Gasoline - Used where the fuel contains ethanol which is greater than or 

equal to 5 percent by volume or ETBE greater than or equal to 5 percent by volume. 

3. Winter Oxygenate MTBE/TAME Gasoline (MTBE1) - Used where the fuel contains MTBE 

which is greater than or equal to 12 percent by volume or TAME greater than or equal to 

13percent by volume. 

4. RFG/MTBE/TAME (MTBE2) - Used where the fuel is RFG and where the fuel contains 

oxygenate greater than 5percent by volume and where the fuel contains MTBE which is less 

than 12percent by volume or TAME less than 13 percent by volume.

Table 10 Toxic to VOC ratios for selected air toxics from Tier 1 and earlier gasoline 

vehicles and trucks

Pollutant

Name E0 E10 MTBE1 MTBE2

2,2,4-Trimethylpentane 0.01823 0.01849 0.04327 0.04327

Acrolein 0.0006 0.0006 0.0006 0.0006

Ethyl Benzene 0.02147 0.01932 0.01398 0.01484

Hexane 0.01570 0.01593 0.00861 0.00888

Propionaldehyde 0.00086 0.00086 0.00073 0.00073

Styrene 0.00108 0.00097 0.00328 0.00340

Toluene 0.09619 0.08657 0.09873 0.10494

Xylene 0.07814 0.07032 0.05557 0.05910

For 2004-and-later vehicles running on E0 and E10, and for all vehicles running on E15, 

ratios for additional gaseous HAPs for E0, E10 and E15 were obtained from Phase 1 of the 
26

EPAct test program. These profiles were based on tests from 3 vehicles.36 Toxic to VOC ratios 

for E10 are used in MOVES for all gasoline above 5 percent ethanol by volume. Ratios are 

provided in Table 11.

Table 11 Toxic to VOC ratios for selected air toxics from Tier 2 gasoline vehicles and 

trucks

Pollutant

Name E0 E10 E15

2,2,4-Trimethylpentane 0.03188 0.01227 0.0220

Ethyl Benzene 0.01683 0.01660 0.0157

Hexane 0.00279 0.02911 0.0110

Propionaldehyde 0.00122 0.00054 0.0006

Styrene 0.00085 0.00083 0.0046

Toluene 0.07542 0.07440 0.0727

Xylene 0.06127 0.06047 0.0690

In the NMIM model, PAH emissions were estimated as ratios to PM. This approach was 

used, even though PAHs are found in the gas, semi-volatile and particle phase, because there is 

generally reasonable correlation between PAH and PM emissions.37, 38 However, for 

MOVESTier 3NPRM, PAH mass emissions are apportioned into the gas and particle phase, and 

gas phase PAHs are estimated using toxic/VOC ratios and particle phase PAHs were estimated 

using toxic to OC2.5 (organic carbon less than 2.5 microns) ratios. Although partitioning of 

PAHs into the gas and particle phases depends on concentration, temperature and other factors, 

MOVES applies one set of allocation factors under all conditions in order to streamline data 

processing. These allocation factors were developed by Sierra Research39 using estimates from 

EPA’s SPECIATE 4.2 database40 and information on compounds’ physical and chemical 

properties. Table 12 provides molecular weights and allocation factors. The allocations from 

SPECIATE were based on medium duty diesel engine data.41 Using PAH and VOC emissions 

data from Norbeck et al. (1998)42 and the allocation factors in Table 12, the toxic/VOC ratios in 

Table 14 were developed. Norbeck et al. data were also used to develop toxic/PM10 ratios. 

These ratios were then converted to toxic/OC2.5 ratios for start and running operation. These 

conversions were made using assumptions that 90 percent of PM10 is PM2.5

43, 87.3 percent of 

running PM2.5 is OC, and 66.6 percent of start PM2.5 is OC. OC percentages of PM2.5 were 

obtained from MOVES runs. PAH to VOC and PAH to OC2.5 ratios do not vary between E0 and 

E10 fuels.
27

Table 12 PAH gas/particle phase allocation factors

PAH Species

Molecular

Weight

Allocation Fraction

PM Phase Gaseous Phase

Acenapthene 154 0 1

Acenaphthylene 152 0 1

Anthracene 178 0.466 0.534

Benz(a)anthracene 228 0.723 0.277

Benzo(a)pyrene 252 1 0

Benzo(b)fluoranthene 252 1 0

Benzo(g,h,i)perylene 276 0.773 0.227

Benzo(k)fluoranthene 252 1 0

Chrysene 228 0.823 0.177

Dibenzo(a,h)anthracene 278 1 0

Fluoranthene 202 0.516 0.484

Fluorene 166 0.215 0.785

Indeno(1,2,3-cd)pyrene 276 1 0

Phenanthrene 178 0.335 0.665

Pyrene 202 0.552 0.448
28

Table 13 PAH/VOC and PAH/PM ratios for gasoline vehicles and trucks.

PAH

Start 

Fraction of 

OC2.5

Running 

Fraction of 

OC2.5

Fraction of 

VOC

Benzo(a)anthracene 0.0001237 0.0000944 0.0000007

Benzo(a)pyrene 0.0001711 0.0001306 0.0000000

Benzo(b)fluoranthene 0.0002032 0.0001551 0.0000000

Benzo(k)fluoranthene 0.0002032 0.0001551 0.0000000

Chrysene 0.0001408 0.0001075 0.0000005

Dibenz(a,h)anthracene 0.0000000 0.0000000 0.0000000

Indeno(1,2,3-cd)pyrene 0.0001283 0.0000979 0.0000000

Acenaphthene 0.0000000 0.0000000 0.0000185

Acenaphthalene 0.0000000 0.0000000 0.0001040

Anthracene 0.0006577 0.0005020 0.0000114

Benzo(ghi)perylene 0.0003306 0.0002524 0.0000015

Fluoranthene 0.0007834 0.0005980 0.0000111

Fluorene 0.0005425 0.0004141 0.0000300

Naphthalene 0.0000000 0.0000000 0.0022928

Phenanthrene 0.0014184 0.0010827 0.0000427

Pyrene 0.0011450 0.0008740 0.0000141

b) Evaporative and Permeation

Toxic to VOC ratios for evaporative non-permeation emissions of benzene, ethanol, MTBE 

and naphthalene remain unchanged from those in MOVES2010. In summary, benzene and 

MTBE ratios are estimated using algorithms originally developed for MOBILE 6.2. However, 

evaporative emissions processes for MOVES differ from those in MOBILE6.2. Thus, 

algorithms for hot soak in MOBILE6.2 are used for vapor venting and refueling vapor loss in 

MOVES, and algorithms for running loss are used for fuel leaks and refueling spillage loss 

(Table 14). Ratios for naphthalene and ethanol are given in Table 15. 

Ratios for the additional air toxics found in evaporative non-permeation emissions (2,2,4-

trimethylpentane, ethyl benzene, hexane, propionaldehyde, toluene and xylenes) were obtained 

from profiles developed for EPA by Environ Corporation, using data from the Auto/Oil test 

program conducted in the early 1990’s.44 These ratios are also given in Table 15. Conventional 

gasoline ratios are also used for MTBE oxygenated gasoline. Since no emissions data exist for 

evaporative and permeation emissions from E15 vehicles, E15 and E10 fuel speciation data from 

the EPAct test program were used to adjust the E10 evaporative emissions speciation.45 For all 

pollutants except benzene and MTBE, ratios are the same for all types of non-permeation 

evaporative emissions. The ratios for 10 percent ethanol are used for all fuels with greater than 

or equal to 5 percent ethanol and less than 12 percent.
29

Table 14 Toxic/VOC algorithms for benzene and MTBE gasoline vehicle evaporative 

emissions

Pollutant Process Toxic Fraction Equation (Toxic/VOC)

Benzene

Vapor Venting/Refueling Vapor

Fuel Leaks/Spillage

(-0.03420*OXY - 0.080274*RVP + 1.4448)*BNZ/100

(-0.03420*OXY - 0.080274*RVP + 1.4448)*BNZ/100

MTBE

Vapor Venting/Refueling Vapor

Fuel Leaks/Spillage

(24.205 - 1.746*RVP)*MTBE/1000

(17.8538 - 1.6622*RVP)*MTBE/1000

Note: OXY = wt percent oxygen

RVP = Reid vapor pressure in psi

BNZ = vol percent benzene

MTBE = vol percent MTBE

Table 15 Evaporative Toxic/VOC ratios for other toxics from gasoline vehicles (Auto/Oil)

Pollutant E0 E10 E15

Ethanol 0.00000 0.11896 0.193458

Naphthalene 0.00040 0.00040 0.000000

2,2,4-Trimethylpentane 0.01984 0.03354 0.053129

Ethyl Benzene 0.02521 0.01721 0.016616

Hexane 0.02217 0.02536 0.007478

Toluene 0.09643 0.14336 0.140632

Xylene 0.07999 0.06423 0.057348

The composition of permeation emissions differs significantly from other types of 

evaporative emissions. Work to better characterize these permeation emissions was recently

conducted by Southwest Research Institute for EPA and the Coordinating Research Council.46 

Data from 3-day diurnal tests on vehicles meeting Tier 1 and near zero evaporative emission 

standards were used. Toxic to VOC ratios for E0 and E10 were estimated by averaging data 

from gasolines of different RVPs. Resulting ratios are provided in Table 16, for all compounds 

except benzene, MTBE and naphthalene. For benzene, the diurnal emissions algorithm from 

MOBILE6.2 was used instead, since this algorithm account for impacts of changing oxygenate, 

RVP and fuel benzene levels. However, a study of permeation emissions suggests that the ratio 

of benzene from permeation to total VOC is about 1.77 times higher than the ratio associated 

with evaporation.47 Thus the diurnal emissions algorithm was multiplied by 1.77. This 

algorithm is:
30

1.77[(-0.02895*OXY - 0.080274*RVP + 1.3758)*BNZ/100]

Equation 7 Diurnal Emissions of Benzene

In the absence of data on permeation emissions for MTBE, the resting loss algorithm from 

MOBILE6.2 was used:

(22.198-1.746RVP)*MTBE/1000

Equation 8 Diurnal Emissions of MTBE

For naphthalene, the toxic to VOC ratio for non-permeation evaporative emissions was also 

applied to permeation.

For E15, model inputs were developed by interpolating between E10 and E20 permeation 

toxic/VOC ratios. The E10 and E20 ratios were obtained from the CRC E-77-2b and CRC E-77-

2c test programs.48,49 Inputs are provided in Table 16.

Table 16 Gasoline vehicle permeation toxic/VOC ratios for air toxics except benzene, 

naphthalene and MTBE (CRC E-77-2b)

Pollutant E0 E10

2,2,4-Trimethylpentane 0.036 0.024

Ethyl Benzene 0.003 0.001

Hexane 0.050 0.065

Toluene 0.110 0.101

Xylene 0.016 0.011

Ethanol 0.202

2. Additional	Air	Toxics:		Inputs	for	Emissions from	Diesel

Vehicles

Toxic/VOC ratios, PAH/VOC ratios, PAH/PM ratios and metal emission factors were 

developed for exhaust emissions from heavy-duty diesel vehicles and applied to all diesel vehicle 

categories. There are no separate emission ratios or factors for diesel engines running on 

biodiesel fuels or synthetic diesel fuels, due to very limited data. 

a) Exhaust

The composition of VOCs for heavy-duty diesel engines without model year 2007-and-later 

emission controls versus those engines with such controls varies significantly. Thus, we 

developed one set of toxic to VOC ratios for pre-2007 diesel engines and another set for 2007 

and later engines. Since extended idle emissions associated with auxiliary power units (APUs) 

are not subject to 2007 standards, toxic to VOC ratios for pre-2007 diesel engines were used for 
31

them. Since light-duty diesels comprise a very small portion of the fleet, the same ratios were 

applied to all diesel vehicle classes to streamline modeling

EPA relied on a database compiled for the Coordinating Research Council (CRC E-75) and 

National Renewable Energy Laboratory (NREL) to develop toxic to VOC ratios for pre-2007 

engines.50 This database was developed from a literature survey and included data from 13 

different studies. The studies included in this database were conducted in a number of different 

countries, included heavy-duty and light-duty engines, a variety of diesel and biodiesel fuels, and 

a number of different operating modes and cycles. For 2,2,4-trimethylpentane, hexane, 

propionaldehyde, and toluene, toxic to VOC ratios developed by Sierra Research from CRC E75 data were used. The methodology they used to develop ratios is described in detail in their 

technical report.51 Data from tests using non-conventional diesel fuel (Fischer-Tropsch, 

bioDiesel, ethanol-Diesel blends, emulsified fuel, European blends, and other obvious research 

fuels) were excluded, as were data from non-heavy duty engines. The ratios are provided in 

Table 10.

Toxic to VOC ratios for benzene, 1,3-butadiene, formaldehyde, acetaldehyde, acrolein, 

naphthalene, ethylbenzene, styrene and xylenes were developed by EPA from the E-75 database. 

We relied on United States data from heavy-duty diesel engines running on conventional diesel 

fuels, collected on test-cycles representative of real world operation. Some studies measured 

emissions over distance, while other studies measure emissions relative to brake horsepower. 

For studies which measured emissions relative to distance, we calculated mean emissions per 

mile for toxics and VOC, then calculated a ratio of toxics to VOC. For studies which measured 

emissions relative to brake horsepower-hour, we calculated mean emissions per brake 

horsepower-hour for toxics and VOC, then calculated a second ratio of toxics to VOC. We then 

calculated a composite ratio using sample size to weight the two ratios. The resulting ratios are 

provided in Table 17.

Table 17 Toxic to VOC Ratios for pre-2007 diesel engines (CRC E-75)

Pollutant Toxic/VOC

1,3-Butadiene 0.002918

2,2,4-Trimethylpentane 0.001808

Acetaldehyde 0.035559

Acrolein 0.006622

Benzene 0.007835

Ethyl Benzene 0.002655

Formaldehyde 0.078225

Hexane 0.00197

Propionaldehyde 0.00468

Styrene 0.001312

Toluene 0.00433

Xylenes 0.003784
32

For 2007 and later heavy-duty diesels, and 2004 and later light-duty diesels which meet Tier 

2 vehicle standards, advanced emission controls change the composition of VOCs. For these 

engines, we relied on speciated emissions data from the Advanced Collaborative Emissions 

Study (ACES), directed by the Health Effects Institute and Coordinating Research Council, with

participation from a range of government and private sector sponsors.52 Detailed emissions data 

from the study were provided to EPA at the request of the Coordinating Research Council.

The data were collected on four engines on several test cycles with low sulfur diesel fuel. 

EPA used data from a 16-hour transient cycle. Toxic to VOC ratios obtained from the ACES 

data are provided in Table 18.

Table 18 Toxic to VOC Ratios for 2007 and later diesel engines

Pollutant Toxic/VOC

1,3-Butadiene 0.00080

2,2,4-Trimethylpentane 0.00782

Acetaldehyde 0.06934

Acrolein 0.00999

Benzene 0.01291

Ethyl Benzene 0.00627

Formaldehyde 0.21744

Hexane 0.00541

Propionaldehyde 0.00314

Styrene 0.00000

Toluene 0.02999

Xylenes 0.03800

As with gasoline vehicles, PAH mass emissions from diesel engines were apportioned into 

the gas and particle phase, using a single set of allocation factors for all conditions. Gas phase 

PAHs were estimated using toxic/VOC ratios and particle phase PAHs were estimated using 

toxic to OC2.5 ratios. Toxic to VOC and toxic to PM2.5 ratios for pre-2007 diesel engines were 

developed by EPA from the E-75 database. Toxic to PM2.5 ratios were converted to toxic to 

OC2.5 ratios using OC2.5 to PM2.5 percentages from MOVES. We relied on United States data 

from heavy-duty diesel engines running on conventional diesel fuels, collected on test-cycles 

representative of real world operation. It should be noted that for some PAHs, there were 

substantially more data than for others; thus the level of confidence in emission factors varies 

among individual compounds. For instance, while data from 66 tests were available for 

acenaphthene, data from only two tests were available for dibenz(a,h)anthracene. Table 19

provides VOC and PM ratios for PAHs from these older technology engines. 
33

Table 19 PAH/VOC and PAH/ OC2.5 ratios for pre-2007 diesel engines

PAH

Start 

Fraction of 

OC2.5

Running 

Fraction of 

OC2.5

Fraction of 

HC

Benzo(a)anthracene 0.0002100 0.0005806 0.0000445

Benzo(a)pyrene 0.0000789 0.0002180 0.0000000

Benzo(b)fluoranthene 0.0000234 0.0000648 0.0000000

Benzo(k)fluoranthene 0.0000033 0.0000091 0.0000000

Chrysene 0.0001327 0.0003667 0.0000235

Dibenz(a,h)anthracene 0.0000032 0.0000087 0.0000000

Indeno(1,2,3-

cd)pyrene

0.0000060 0.0000166

0.0000000

Acenaphthene 0.0000000 0.0000000 0.0003210

Acenaphthalene 0.0000000 0.0000000 0.0005009

Anthracene 0.0001058 0.0002924 0.0002353

Benzo(ghi)perylene 0.0000038 0.0000104 0.0000276

Fluoranthene 0.0004058 0.0011217 0.0006108

Fluorene 0.0001818 0.0005025 0.0005914

Naphthalene 0.0000000 0.0000000 0.0090464

Phenanthrene 0.0004187 0.0011574 0.0019446

Pyrene 0.0005865 0.0016213 0.0007577

For 2007 and later diesels, advanced emission controls change the composition and reduce 

the total mass of PAHs. For these engines, we relied on speciated emissions data from the ACES 

study. Table 20 provides provides VOC and OC2.5 ratios for PAHs from these newer 

technology engines.
34

Table 20 PAH/VOC and PAH/PM ratios for 2007 and later diesel engines

PAH

Start 

Fraction of 

OC2.5

Running 

Fraction of 

OC2.5

Fraction of 

HC

Benzo(a)anthracene 0.0000015 0.0000010 0.0000003

Benzo(a)pyrene 0.0000061 0.0000042 0.0000000

Benzo(b)fluoranthene 0.0000026 0.0000018 0.0000000

Benzo(k)fluoranthene 0.0000026 0.0000018 0.0000000

Chrysene 0.0000046 0.0000031 0.0000005

Dibenz(a,h)anthracene 0.0000018 0.0000013 0.0000000

Indeno(1,2,3-

cd)pyrene

0.0000009 0.0000006

0.0000000

Acenaphthene 0.0000000 0.0000000 0.0000526

Acenaphthalene 0.0000000 0.0000000 0.0000853

Anthracene 0.0000488 0.0000334 0.0000304

Benzo(ghi)perylene 0.0000004 0.0000003 0.0000002

Fluoranthene 0.0000896 0.0000613 0.0000457

Fluorene 0.0000990 0.0000677 0.0001963

Naphthalene 0.0000000 0.0000000 0.0163278

Phenanthrene 0.0007886 0.0005395 0.0008507

Pyrene 0.0000859 0.0000588 0.0000379

b) Evaporative

MOVES estimates evaporative emissions associated with spillage for diesel vehicles. Since 

there are no speciated emissions of diesel spillage emissions, we developed toxic to VOC ratios 

based on a diesel headspace profile, profile number 4547 from the SPECIATE database. These 

ratios are provided in Table 21.

Table 21 Toxic to VOC ratios for diesel spillage emissions

Pollutant Toxic/VOC

2,2,4-Trimethylpentane 0.00974

Ethyl Benzene 0.00324

Hexane 0.01076

Toluene 0.01419

Xylene 0.01222

Benzene 0.00410
35

C. Hydrocarbon	Speciation Factors

MOVES provides estimates of hydrocarbon emissions in a number of different groupings or 

“hydrocarbon speciations.” The choice depends on application. The following metrics are 

commonly used in EPA and produced by the MOVES model as documented in a MOVES 

technical report:

53

Total hydrocarbons (THC) -- Organic compounds in exhaust, as measured by a flame 

ionization detector (FID). A FID does not accurately measure all of the mass of oxygenated 

organic gases, such as ethanol, acetaldehyde, and formaldehyde.

Non-methane hydrocarbons (NMHC) – THC minus the mass of methane.

Total organic gases (TOG) -- All organic gas compounds emitted to the atmosphere, 

including all of the mass of oxygenated organic gases.

Non-methane organic gases (NMOG) – TOG minus the mass of ethane.

Volatile organic compounds (VOC) – Organic gas compounds that participate in atmospheric 

photochemical reactions. Does not include the mass of methane and ethane. Does include 

organic compounds not measured by the FID.

Basic exhaust emission rates in MOVES are expressed as THC. NMHC is then estimated by

applying a methane adjustment provided in the MOVES database. The following equation is 

used to calculate NMHC in MOVES: 

 =  − 

Equation 9 Calculating NMHC from THC

The methane estimates used in the NMHC calculation were updated from MOVES2010 to 

MOVES2010a as described in an EPA technical report.54 The methane estimates for gasoline 

vehicles of model year 2004-and-later were further updated for MOVEST3NPRM as described 

in Section IV.C.1 below. 

NMOG, TOG, and VOC are other MOVES outputs. These metrics are obtained by applying 

NMHC-to-NMOG and NMHC-to-VOC speciation factors. Although TOG emissions were not 

calculated for the Tier 3 NPRM analysis, this version of MOVES changed the way TOG is 

calculated, setting it to equal NMOG plus methane. 

NMHC to VOC factors are calculated using the following equation:

Equation 10 NMHC to VOC

acetald acetald EtOH EtOH NMHC NMHC NMHC

HCHO HCHO acetald acetald EtOH EtOH NMHC NMHC ethane ethane

FID

VOC

[(CF X FID )+ CF X FID (CF X FID )] X MPC

(CF X MPC )+(CF X MPC )+ CF X MPC (CF X MPC )-(CF X MPC )

=

NMHC

VOC Speciation Factor =





( )

( )
36

NMHC to NMOG factors are calculated using the following equation:

Where:

CF = carbon fraction

MPC = mass per carbon

FIDX = FID response factor

Equation 11 NMHC to NMOG

The FID does not measure any of the mass of formaldehyde; thus for that pollutant a FID 

response factor of zero was used. The FID measures roughly half the mass of acetaldehyde; thus 

a FID response of 0.5 was used. For ethanol, a FID response of 0.74 was used, based on 

analyses done at Southwest Research Institute for the EPAct test program.55

1. HC	Speciation	of	Exhaust	Emissions

Exhaust speciation factors for pre-Tier 2 gasoline vehicles remain unchanged from 

MOVES2010. However, since exhaust hydrocarbon emissions from Tier 2-and-later vehicles 

are substantially different in composition from pre-Tier 2 vehicles, new speciation factors were 

developed, based on EPAct Phase 3 data.

56

 The new factors are summarized in Table 23 below. 

The EPAct data also was used to update methane/total hydrocarbon ratios for 2004-and-later 

gasoline light-duty cars and trucks. Separate ratios were calculated for running and starts, 

keeping the age effect in MOVES2010.

e

 Updated methane to THC ratios for light-duty cars and 

trucks for model years 2004-and-later are provided in Table 22. In the process of updating these 

rates, we also identified and fixed some errors and missing values found in these ratios for pre2004 gasoline vehicles. 

 

e

Simple ratios between methane and THC were calculated for LA92 Bag 1 and Bag 2 from EPAct data, for starts 

and running, respectively. Gasoline light-duty cars and trucks were analyzed separately. Since the vehicles from 

EPAct program were less than four years old, for age groups four and later, the age trend in MOVES2010, which 

assumes that the proportion of methane declines as vehicles age, were applied. As a means of verification, 

calculated ratios from EPAct were compared to the ratios from the In-Use Verification Program (IUVP) and the 

results showed similar results. 

acetald acetald EtOH EtOH NMHC NMHC NMHC

HCHO HCHO acetald acetald EtOH EtOH NMHC NMHC

FID

NMOG

[(CF X FID )+ CF X FID (CF X FID )] X MPC

(CF X MPC )+(CF X MPC )+ CF X MPC (CF X MPC

=

NMHC

NMOG Speciation Factor =





( )

( ) )
37

Table 22 Methane/THC ratios for gasoline light-duty cars and trucks (MY2004 and later)

Light-Duty Cars (LDV) Light-Duty Trucks (LDT)

Age Group Running Starts Running Starts

0 – 3 0.454054 0.082814 0.520114 0.107257

4 – 5 0.235549 0.050193 0.269818 0.066915

6 – 7 0.207525 0.04565 0.237717 0.059709

8 – 9 0.17483 0.040697 0.200266 0.053998

10 – 14 0.11926 0.030697 0.136611 0.04364

15 – 19 0.101667 0.028455 0.116458 0.040392

20 + 0.100044 0.028016 0.1146 0.038834

More recent and extensive data were available for pre-2007 diesel engines than those used in 

earlier versions of MOVES, and for 2007-and-later diesel engines, data were available from the 

Advanced Collaborative Emissions Study (ACES).57,58 The new diesel speciation factors and the 

speciation factors for gasoline vehicles are summarized in Table 23.

Table 23 Exhaust hydrocarbon speciation factors

Engine Type Fuel Subtype Operating Mode Speciation Factor

NMHC to VOC

Gasoline Tier 2 E0 to E10 Start 0.9787 + (0.0068 * 

wt. % oxygen)

Gasoline Tier 2 E0 to E10 Running 0.9148 - (0.0013 * 

wt. % oxygen)

Gasoline E15 Start 1.0162

Gasoline E15 Running 0.9049

Diesel – pre-2007 All Start and Running 1.1243

Diesel – 2007+ All Start and Running 1.3058

NMHC to NMOG

Gasoline Tier 2 E0 to E10 Start 1.0078 + (0.0082 * 

wt. % oxygen)

Gasoline Tier 2 E0 to E10 Running 1.0149 + (0.0028 * 

wt. % oxygen)

Gasoline E15 Start 1.0495

Gasoline E15 Running 1.0318

Diesel – pre-2007 All Start and Running 1.1455

Diesel – 2007+ All Start and Running 1.3431
38

2. HC	Speciation	of	Permeation Emissions

Since no methane or ethane are found in evaporative or permeation emissions, THC is 

equivalent to NMHC, and VOC is equivalent to NMOG and TOG. Thus, speciation factors are 

only needed to convert THC to VOC, to account for the mass of ethanol not measured by the 

FID:

Equation 12 VOC speciation for permeation

For evaporative emissions, THC to VOC factors are unchanged from earlier versions of 

MOVES. However, factors were developed for permeation emissions, based on data from the 

CRC E-77 test program.59,60 These factors are provided in Table 24.

Table 24 Gasoline Vehicle Permeation hydrocarbon THC to VOC speciation factors

Fuel Subtype Speciation Factor

E0 to E10 1.0000+(0.0360* wt. % oxygen)

E15 1.1755

D. Additional	Updates	to	Air	Toxics	and	HC	Speciation

We made a number of other small changes to air toxics and HC speciation for 

MOVEST3NPRM. We updated the General Fuel Expression Ratio table to fix a bug in acrolein 

running and start emissions for model years 1960 through 2003. We fixed a small bug in the 

calculation of ethanol emissions, and we fixed an error in the HC speciation factors for diesel 

and biodiesel running,start and extended idle emissions. 

V. Updated	Heavy Duty	and	Diesel	Emission	Rates

A. Changes	to	Heavy	Duty	Gasoline	Vehicle	Rates

The “2007 Heavy Duty rule”61 reduced both start and running emissions from heavy duty on 

gasoline vehicles. The reduction to running rates was inadvertently omitted from the 

MOVES2010 model. This subsection documents the detailed analysis that was conducted to 

include this rule in MOVEST3NPRM, and also reflect the requirement that Medium Duty 

Passenger Vehicles (MDPVs) be certified under Tier 2 regulations.62 While the 2007 Heavy 

EtOH EtOH THC THC THC

EtOH EtOH THC THC

FID

VOC

CF X FID (CF X FID )] X MPC

CF X MPC (CF X MPC )

=

NMHC

VOC Speciation Factor =





( )

( )
39

Duty rule affects emissions in all Heavy Duty (HD) gasoline categories,fthere are very few 

gasoline vehicles in the largest classes. As a result, revisions were made only to MOVES 

regulatory class 41, which are commonly called light HD or Medium Duty vehicles (8,500 to 

14,000 pound GVWR). 

1. Regulatory	Class	Definition	and	Vehicle	Composition

Gasoline vehicles in MOVES regulatory class 41 are a mixture of engine certified HD 

vehicles, chassis certified HD vehicles, and MDPVs. Each has separate set regulations 

governing their emissions, which are summarized below (Table 25). 

Table 25 Useful Life FTP Standards

MDPV

(Tier 2 Bin 5)

8.5k – 10k 

(Class 2B)

10k-14k

(Class 3)

Engine

Certified

Units g/mile g/mile g/mile g/bhp-hr

Fully Phased in MY 2009 2008 2008 2010

HC 0.09 NMOG 0.195NMHC 0.230 NMHC 0.14 NMHC

CO 4.2 7.3 8.1 14.4

NOx 0.07 0.2 0.4 0.2

The relative proportions of the vehicles within this weight class vary each year depending on 

economic demand. Consequently, we estimated proportions based on existing data and 

engineering judgment. MOBILE6 documentation indicates that MDPVs are approximately 16

percent of the gasoline 8,500 to 10,000 truck class.63 Based on the estimate that MDPV sales 

have increased since the 2003 release of the MOBILE6 report, we project that MDPVs are 15

percent of total MOVES regulatory class 41. The MOBILE6 document64 further asserts that 

more than 95 percent of class 2B trucks are chassis certified. Consequently, we estimate that 5

percent of all vehicles in the 41 regulatory class are engine certified. Based on analysis from the 

recent medium and heavy duty greenhouse gas rulemaking, we assume that sales of 2B class 

trucks vehicles were triple that of 3 class trucks (Table 26).65 This is roughly consistent with 

recent model year sales totals, and yields the sales fractions below.66

Table 26 Population Percentage

percent of Reg Class 41

MDPV 15%

Class 2B 60%

Class 3 20%

Engine Certified 5%

 

f MOVES regulatory classes 41 (8,500 to 14,000 pounds GVWR), 42 (14,000 to 19,500 pounds GVWR), 46 (19,500 

to 33,000 GVWR) and 47 (GVWR above 33,000 pounds).
40

2. Estimating	Emission	Rates

We weighted the individual FTP standards together using the proportions shown in Table 26, 

which yields an aggregate MOVES gasoline FTP useful life standard shown below. While we 

do not expect the model to produce these rates, it is a useful benchmark for the modeled rates. 

The distinction between NMHC and NMOG was ignored in calculating the aggregate FTP, and 

would have yielded only minor variation in the final aggregate FTP (Table 27).

Table 27 Aggregate Useful Life FTP

Reg Class 41 g/mile

NMOG 0.18

CO 7.49

NOx 0.22

We then compared this aggregate FTP standard to the emissions calculated by MOVES 

2010a. The Physical Emission Rate Estimator (PERE),67 modified to produce Scaled Tractive 

Power (STP) distributions, was used to generate the bin mix of a regulatory class 41 vehicle on 

the federal test procedure (FTP) drive cycle. The STP modification required shifting the vehicle 

weight to match Source Type 32 in MOVES (2.06 Tons). We pulled rates by hour from the 

MOVES DB for the age 0 -3 group, and added in a cold start (operating mode 108) and a hot 

start (operating mode 102) from the MOVES database. The modified version of PERE produced 

the operating mode distribution shown in Table 28.

.

Table 28 Operating Mode Bin Mix for a MD FTP

STPpbin N percent vspbin N percent

0 160 12% 25 41 3%

1 258 19% 27 49 4%

11 94 7% 28 17 1%

12 68 5% 29 13 1%

13 70 5% 30 15 1%

14 36 3% 33 13 1%

15 48 3% 35 12 1%

16 141 10% 37 13 1%

21 68 5% 38 17 1%

22 44 3% 39 15 1%

23 97 7% 40 6 0%

24 77 6%

Total 1372 100%

Using this operating mode distribution, we constructed a simulated FTP out of four 

components (bag 1/3 running, cold start, hot start, and bag 2 running). We constructed bag 1 

(cold start + bag 1/3 running) and bag 3 (hot start + bag 1/3 running) and weighted the resulting 
41

components together according to the FTP formula,g and compared the 2007 and later rates in 

MOVES to the aggregate standard shown in Table 29. The MOVES 2010a estimates at age 3 are 

2.5x to 11x the standard, which indicates that the average vehicle is significantly out of 

compliance with the 2010 standard.

Table 29 Comparison between MOVES DB FTP and Aggregate FTP 

MOVES FTP Aggregate FTP MOVES /Aggregate FTP

NMOG 0.45 0.18 2.51

CO 16.21 7.37 2.20

NOx 2.53 0.23 11.06

Based on this analysis, we reviewed In Use Verification Program (IUVP) data from MYs 2004-

2008 vehicles with estimated test weights of 7,500 pounds-or-above to determine the average inuse compliance ratio. Non-sales weighted, and after accounting for the individual standards 

applicable to each vehicle, this yielded average ratios of FTP to the standard of 0.42 (NMOG) 

and 0.23 (NOx) (Table 30and 

Figure 6). MOVES, which includes all vehicles and is a broader sample than the IUVP program, 

would be expected to yield somewhat higher emissions. Further, while the Heavy Duty 2007 

rule does not fully phase-in until 2010, we would anticipate that manufacturers would achieve 

similar compliance ratios as in past MYs. 

Table 30 Average Compliance Margin and Headroom

Average Average

Ratio FTP/Standard Headroom

NMOG 0.42 0.58

Nox 0.23 0.77

 

g

FTP =( (Bag 1 + Bag 2)*0.43+ (Bag 3+ Bag 2)*0.57)/ 7.45
42

Figure 6 Distribution of IUVP FTP Tests

To produce similar compliance ratios in MOVES, we applied the following ratios to the 

running and start rates, incorporating the assumption that it is much more difficult to reduce start 

emission than running emissions. 

Table 31 Ratios applied to MOVES Rates

HC CO Nox

Running 0.2 0.2 0.05

Start 0.4 0.4 0.3

Applying these ratios against the MOVES2010 default rates yields the new regulatory class 

41 rates. These are shown compared against the aggregate FTP from Table 27.
43

Table 32 Comparison of FTPs using Preliminary New MOVES Rates

MOVES FTP Aggregate FTP MOVES /Aggregate FTP

NMOG 0.10 0.18 0.56

CO 4.72 7.37 0.64

NOx 0.13 0.23 0.58

This process yielded a number of medium duty rates, which by operating mode, were lower 

than the Light Duty Tier 2 Bin 8 rates. Specifically, most of the higher power modes such as 27-

30 and 37-40 were reduced to below the Bin 8 rates. These operating modes are likely the least 

affected by the MY 2010 HD Gas standards, which include no SFTP component.

To account for the lack of SFTP control on these vehicles we bounded the emission rates so 

that rates for individual operating mode could be lower than Bin 8 rates * 1.2, and no higher than 

the MD rates currently in MOVES. This yielded rates that are slightly higher than the 

unbounded rates, with NOx is slightly over the Aggregate FTP standard. These rates were 

phased in at a rate of 25 percent per year between MY 2007 and 2010 and placed in the MOVES 

emission rate database.

Table 33 Comparison of Outputs after accounting for SFTP emissions

MOVES FTP Aggregate FTP

MOVES 

/Aggregate FTP

NMOG 0.13 0.18 0.74

CO 5.31 7.37 0.72

NOx 0.28 0.23 1.20

B. Changes	to	Heavy- and	Light-Duty Diesel Vehicle Rates

We updated sulfate, sulfur dioxide, organic carbon and elemental carbon emissions for 2007-

and-later diesel vehicles based on data from the ACES study. In 2007-and-later diesel vehicles, 

more of the fuel sulfur is converted to SO4 and less to SO2 compared with earlier diesel 

vehicles. However, in this update, total PM is unchanged, so organic carbon is reduced. The 

details of the data, its analysis, and its application in MOVES are explained in a separate 

memo.,

68

VI. Other	Changes

Other changes made for MOVEST3NPRM did not impact MOVES results, but improved our 

ability to generate the necessary emission rates for air quality modeling. For example, we made 

finer divisions in MOVES model year groups to allow the phase-in of emission standards. More 

important in this category of changes were changes to allow MOVES to run a cloud computing 

environment. This was necessary because evaporative emissions were expected to be important 

in this analysis, so we wanted to be sure to capture fine distinctions in fuel characteristics and 
44

ambient temperatures. Instead of running MOVES to generate state-level inventories as we did 

for the recent Heavy Duty Greenhouse Gasoline rule analysis,

69 we ran MOVES in emission rate 

mode and calculated rates for “representative counties.” As explained in the RIA for this 

proposal, these rates were then applied to other similar counties. This approach allowed us great 

precision in modeling temperatures, but it required more than 14,000 runs for each scenario-- an 

unprecedented requirement for computing power. 

To meet this requirement, we adapted MOVES to run in a cloud computing environment 

with a Linux operating system. We improved MOVES error handling and the ability to 

distribute MOVES functions among computers. We truncated the IMCoverage table to facilitate 

the input of local inspection and maintenance data for each county. We adjusted the 

zoneroadtype and sccroadtypedistribution table to assure that all roadtypes could be modeled in 

all counties. We also made changes to reduce the runtime for each run.

A. Changes	to	Model	Year	Groups

MOVES2010a grouped emissions for 2021-and-later model years together with a single 

emission rate. Because the Tier 3 analysis had to estimate the impact of phasing in a new 

emission standard in this time period, MOVES was revised to use year-by-year model year 

groups for all years 2021 through 2030. We also introduced a new model year group of 2031-

2050. This change required modification of many MOVES tables, but had no impact on 

emission estimates for the baseline and reference case.

B. Changes	to	County	Allocations

In the tables zoneroadtype and sccroadtypedistribution, zeros were replaced with the value 

10-15. This facilitates our approach of using representative counties; it allows the model to 

calculate emission rates on roadtypes that do not exist in a given county so they can be applied to 

a similar county that does have that roadtype.

C. Repair of Errors

An error was found in the algorithm for aggregating Inspection /Maintenance effects to the 

state-level. This was fixed, facilitating the use of the MOVES model at the national level for 

inventory calculations. We also updated the modelyear groups used for ammonia extended idle 

emissions to allow the model to correctly generate these emissions. And we updated model year 

groups for sulfate, NO and NO2 to allow the model to correctly estimate emissions for model 

year 2021. 

D. Changes	to	Facilitate	Large	Numbers	of	Runs

For air quality modeling, we ran MOVES for a very large number of counties. To facilitate 

this, we adapted MOVES to improve the model’s operation in diverse computing environments, 

including large computer clusters and services available over the Internet from commercial

providers. 

The MOVES air quality runs were performed with IMCoverage tables for each county. This 

change avoided conflicts between the default and the input data.
45

MOVES now provides a message when users create a user input database with the same 

name as an existing database, and we added the ability to omit roadtypes when modeling 

evaporative processes, thus facilitating faster production of RatePerProfile and RatePerVehicle 

output. We improved the use of indices to speed model runs.

We made many changes to the MOVES code to facilitate running MOVES on Linux 

operating systems, to allow the operation of MOVES with local MySQL, to allow separate 

processing of “TODO” and “Done” files, to better manage independent “worker” computers, to 

improve the MOVES log file, and to allow longer names for MOVES worker and master 

computers

None of the changes described in this subsection changed MOVES emission results.

VII. Impact	of	MOVES	Changes

To assess the overall impact of the MOVES changes described above in emissions with the 

updated version of MOVES were evaluated by conducting a national run with MOVES2010a

and the updated MOVES version, using the reference case fuels described the Tier 3 RIA for 

2017. The results are shown in Table 34 Impact of MOVES updates to U.S. emissions in 2017 

(annual tons).

Table 34 Impact of MOVES updates to U.S. emissions in 2017 (annual tons)

MOVES2010a MOVEST3NPRM Percent Change

NOx 3,584,299 3,452,314 -4%

VOC 1,922,560 1,614,384 -16%

CO 23,663,807 20,915,593 -12%

PM 111,928 115,098 3%

Benzene 39,567 39,695 0%

1,3-Butadiene 6,950 6,022 -13%

Acetaldehyde 23,433 23,918 2%

Formaldehyde 25,496 29,446 15%

Acrolein 1,193 1,814 52%

Ethanol 66,563 111,629 68%

Naphthalene 4,786 3,953 -17%

As illustrated in the table, the revision to air toxics inputs had a major impact on the 

emissions of these compounds. Moreover, the changes between MOVES2010 and 

MOVEST3NPRM led to a substantial reduction in the emissions of CO and VOC. These 

reductions will be seen in both the reference and control cases of the Tier 3 NPRM analysis.
46

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48

 

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49

 

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