MOVES2010 Fuel Adjustment and Air 

Toxic Emission Calculation Algorithm – 

Development and Results 
MOVES2010 Fuel Adjustment and Air 

Toxic Emission Calculation Algorithm – 

Development and Results 

Assessment and Standards Division 

Office of Transportation and Air Quality 

U.S. Environmental Protection Agency 

NOTICE 

This technical report does not necessarily represent final EPA decisions or 

positions. It is intended to present technical analysis of issues using data 

that are currently available. The purpose in the release of such reports is to 

facilitate the exchange of technical information and to inform the public of 

technical developments. 

EPA-420-R-11-009 

July 2011 
 

 

 

 

 

 

 

 

1. Introduction

 This document describes in detail the default fuels, fuel adjustment and air toxic 

calculation algorithms contained in the MOVES2010 model released in December 2009. 

It also describes the minor changes made for MOVES2010a, released in September 2010. 

The MOVES2010 algorithms were substantially redesigned from those contained in 

previous versions of the MOVES model. The revisions make the MOVES model more 

robust in terms of fuel modeling, easier to use, and removes a number of coding errors 

and problems. 

This document discusses the impact of fuel properties on emissions, particularly 

the fuel adjustments applied to base emission results in MOVES. It details the fuel 

adjustment model methodology, and presents limited results pertaining to the following 

pollutants and their associated exhaust processes. These include the ‘running’, ‘start’ and 

‘extended idle’ processes. It also includes evaporative processes for Benzene, MTBE and 

Ethanol where simple ratios are used. This document does not cover the impact of 

gasoline properties on the total hydrocarbon evaporative emission process algorithms 

such as permeation, vapor venting or leaks, which are described in the MOVES draft 

technical report on evaporative emissions (Development of Evaporative Emissions 

Calculations for the Motor Vehicle Emissions Simulator (Draft MOVES2009) EPA-420-

P-09-006, August 2009, 

http://www.epa.gov/otaq/models/moves/techdocs/420p09006.pdf ) 

In general, the MOVES model calculates detailed “base emissions” on a base fuel, 

sums the emissions to develop total emissions for a given model year, source type and 

fuel type, and then applies a fuel adjustment to this aggregate emission quantity. The 

fuel adjustment is a weighted average for the fuels in a given area, as defined by their fuel 

properties and the market share listed in the MOVES fuel supply table. Air toxic 

emissions are calculated as a ratio to the emission of other pollutants (usually total 

hydrocarbons), and the ratio may or may not vary with fuel properties. 

Different algorithms are used to calculate fuel effects for different fuel properties 

and for different air pollutants. Each is covered in a separate section of this report: 

•	 Complex Model Algorithms for Gasoline Vehicle Air Toxic Fuel Effects - this 

covers benzene; 1, 3 butadiene, acetaldehyde and formaldehyde 

•	 MTBE Complex Model (revised between December, 2009 and September, 2010) 

provides algorithms for emissions of methyl tertiary-butyl ether from gasoline 

fueled vehicles 

•	 Algorithms for other toxics from gasoline vehicles in MOVES2010, covering 

ethanol, acrolein, and naphthalene 

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•	 Complex Model Algorithms for Carbon Monoxide 

•	 Predictive Model for Total Hydrocarbon (THC) and Oxides of Nitrogen (NOx) 

Fuel Effects 

•	 MOBILE6.2 Fuel Sulfur Effects Model applies to start and running THC, CO and 

NOx emissions. 

•	 Combining the Complex/Predictive Models with the Fuel Sulfur Effects Model 

•	 Bio-Diesel Criteria Pollutant Emission Effects 

•	 Toxic Emissions for Diesel Vehicles 

•	 Hydrocarbon Speciation Adjustments 

The report ends with a description of the data sources for MOVES default fuels 

and with a section on results. 

The algorithms used in MOVES2010 for gasoline and diesel vehicles were 

developed over 10 years ago. EPA is currently completing analysis of more recent data, 

representing more extensive testing, modern vehicles and engines, and fuels more 

representative of what is currently being sold. EPA is planning a more comprehensive 

fuels update that will include data from test programs being completed as part of the 

analysis mandated by the 2005 Energy Policy Act (EPACT) 

(http://www.epa.gov/otaq/fuels.htm ) However, this document only covers analysis, code 

and data that were analyzed and implemented in the MOVES2010 and MOVES2010a 

version of the model. None of the EPAct study results were available for the 

MOVES2010a version of September, 2010, and are not discussed here. 

As noted by the nomenclature of the above list, various existing fuel models were 

incorporated into the MOVES algorithm. These models are: 

1.	 EPA Complex Model – This model was published in 1993 and is based on 

emissions from 1990 technology light duty vehicles. It estimates fuel effects on 

exhaust emissions of volatile organic compounds (VOC), carbon monoxide (CO), 

NOx and air toxics; and evaporative emissions of HC, including benzene. Normal 

emitters and high emitters are treated separately. The output of the model 

compares emissions of a test fuel to the Base Fuel defined in the Clean Air Act 

Amendments of 1990. See the link below to download the Complex Model. 

http://www.epa.gov/otaq/rfg.htm. 

2.	 EPA Predictive Model – This model was originally created to evaluate a 

California request for a waiver of reformulated gasoline requirements. It is based 

on more recent data than that used for the Complex Model but only predicts VOC 

and NOx. The model was revised when EPA evaluated the Renewable Fuel 

Standard (RFS). It is described in some detail in an EPA report (EPA 420 R-07-

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004, “Regulatory Impact Analysis: Renewable Fuel Standard Program”, USEPA, 

OTAQ, Assessment and Standards Division, April 2007). 

3.	 ARB Predictive Model – Last updated in 2006, this model predicts emissions of a 

test fuel compared to California Air Resources Board (ARB) Phase 3 gasoline. It 

estimates exhaust emissions of non-methane organic gases (NMOG), NOx, and 

air toxics; and evaporative emissions of NMOG and benzene. The time period of 

the estimate is 2015, and all light duty vehicles (cars and light trucks) were 

considered in developing the model. No distinction is made in the model between 

normal and high emitters. This model was not explicitly included in the 

MOVES2010a version. The link for additional documentation is: 

www.epa.gov/otaq/regs/fuels/rfg/r01016.pdf 

4.	 MOBILE6/MOBILE6.2 – This model is a precursor to MOVES and predicts 

inventory emissions for mobile sources. Within MOBILE6 is a fuels module that 

estimates how emissions will change as a function of Reid Vapor Pressure (RVP), 

oxygenate and sulfur content. The sulfur portion of MOBILE6.2 is described in 

an EPA report. (EPA420-R-01-039, “Fuel Sulfur Effects on Exhaust Emissions, 

Recommendations for MOBILE6”, Venkatesh Rao, July 2001). 

Both the Complex and Predictive models rely on the concept of a Base Fuel(s). 

These are specific fuel formulations at which the underlying vehicle tests that were used 

to generate the basic emission factors in MOVES were assumed “on average” to be 

conducted. In the MOVES model, a Base Fuel will produce a MOVES fuel correction 

factor of unity. The emission effects of other ‘target’ fuels are “ratioed” to the Base Fuel, 

and the subsequent product is the MOVES fuel correction factor for that ‘target’ fuel. 

The specific MOVES Base Fuels were chosen because they best represent the typical inuse fuel during the period in which the MOVES test vehicle emission data were 

collected. This choice was based on local fuel survey data of the Phoenix area during the 

1995 through 2002 time period when the primary MOVES vehicle dataset was tested. 

(see Section 2.0 for a more complete discussion of the Base Fuels). 

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2. Complex Model Algorithms for Gasoline Vehicle Air 

Toxic Fuel Effects 

This section details the calculations used to compute the air toxic emission rates

in MOVES for selected air toxic compounds. These calculations were taken from the 

EPA Complex Model developed in the early 1990’s. The air toxic compounds which use 

these algorithms are: 

Benzene
 

Acetaldehyde

Formaldehyde

1,3 Butadiene
 

The Complex Model algorithms are applied to running, start and extended idle

emissions for gasoline fueled vehicles for all 1975 and later model years for these four 

pollutants. While MOBILE6 included algorithms for older technologies not included in 

the Complex Model, such as non-catalyst and oxidation catalyst vehicles, these 

algorithms are not in MOVES since these vehicles now comprise such a small portion of

the fleet. In addition, while MOBILE6.2 relied on very limited data from heavy-duty

gasoline vehicles to develop toxic to VOC ratios for that vehicle type, MOVES applies

Complex Model algorithms to both light-duty and heavy-duty gasoline vehicles. The 

general structure of this section and all subsequent ones will be to describe and discuss

the calculation algorithms in mathematical terms, show the underlying equation 

coefficients and present some limited results in graphical form for selected cases (All 

results are shown in a Results section at the end of the document). 

MOVES2010a also models methyl tertiary butyl ether (MTBE), ethanol, acrolein 

and naphthalene. In MOVES2010a, acrolein is not affected by fuel properties and is

modeled with a simple acrolein/VOC ratio as discussed later in this document. MTBE is 

modeled using algorithms developed from the same dataset as the Complex Model.

Ethanol and naphthalene are modeled with simpler algorithms described later in this 

report. 

2.1 Complex Model Mathematical Overview 

Complex Model (CM) algorithms are used to compute the fuel effects for the

pollutants benzene (exhaust and evaporative), 1,3-butadiene (exhaust), formaldehyde

(exhaust) and acetaldehyde (exhaust). These algorithms were based on testing of a

sample of Tier 0 vehicles (1990 and earlier model years) over a wide variety of gasoline

fuel formulations. A complex statistical analysis using multivariate regression techniques

was performed on the primary data set, and a set of statistical models were developed. 

These statistical models were originally programmed into the Unconsolidated Complex

Model spreadsheet, and have now been programmed into the MOVES model and 

described in this document. The reader who is interested in the original test program 

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design, the data processing, and/or the details of the statistical analysis should refer to the 

original primary documents of the study.1 

The underlying goal of the CM algorithm is to compute an “air toxic ratio”. This 

is the ratio (or proportion) of the particular air toxic pollutant to the amount of VOC in 

the exhaust. In MOVES, this air toxic ratio is multiplied by the MOVES VOC estimate. 

Mathematically, this is shown in Equation 2-1. 

AT Emission (g/hr) = AT Ratio * VOC Emission (g/hr) Eq 2-1 

“AT Emission” is the final emission estimate for the air toxic pollutant as

reported by MOVES, and “AT Ratio” is the multiplicative factor calculated by the CM

algorithm that reflects the fuel properties. The “VOC Emission” variable is the 

underlying VOC emissions calculated by MOVES. 

In its native form, the CM model produces the (AT Ratio) by comparing the air

toxic emission of a given “target” fuel to those produced by a “base” gasoline fuel (see 

Table 2.1). Mathematically, this relationship is shown in Equation 2-2. 

AT Ratio = 1.0 + [ (ATTarget – ATBase ) / ATBase ] Eq 2-2 

2.1.1 Base Fuel Concept 

The ‘base’ fuel in MOVES2010a is a specific fuel at which the basic emission

rates in MOVES remain uncorrected for fuel effects. MOVES2010a contains three 

‘base’ fuels. There are shown in Table 2-1. Base Fuel A represents gasoline vehicles

with model years 2001 and later, Base Fuel B represents gasoline vehicles with model

years 2000 and earlier. Both Base Fuel A and B are used in the calculation of HC, CO 

and NOx emission fuel effects. Base Fuel C is used as the base fuel in the air toxic 

equations for all model years. 

Base Fuels A and B were chosen because they best represent the typical in-use 

fuel during the period in which the MOVES test vehicle emission data were collected.

The underlying test vehicle emission data is a large sample of in-use vehicles as they

received their state transient IM240 or IM147 test. Since fuel properties were not

measured on individual test vehicles during their emission test, it is presumed that the

base (uncorrected) emissions best represent “on average” the presence of these fuels and

their properties. The assumption of ‘best represent’ is based on local fuel survey data of

the Phoenix area during the 1995 through 2002 time period when the primary MOVES

vehicle dataset was tested. 

Over the time period of the emission testing, the general in-use sulfur level varied

due to EPA fuel sulfur regulations. As a result, MOVES2010a contains two base fuels 

1

 U. S. EPA. 1993. Final Regulatory Impact Analysis for Reformulated Gasoline. 

December 13, 1993. http://www.epa.gov/otaq/regs/fuels/rfg/ (ria.zip) 

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with the same fuel properties except fuel sulfur. Base Fuel A (a lower sulfur fuel) is used

to model the 2001 and later model year vehicles, and Base Fuel B is used to model the

2000 and earlier model year vehicles. The properties of each fuel are shown in Table 2-1 

below. 

Base fuel C is the base fuel used only in the air toxic ratio calculations. It is a fuel 

which was prevalent in the early 1990’s, and is the base fuel for the Complex model. 

This fuel formulation is central to the “centering values” and other coefficients and

algorithms in the Complex model, and was the baseline fuel specified in the 1990 Clean 

Air Act Amendments for air toxic calculations. 

2.1.2 Target Fuel Concept 

The “target” gasoline is the gasoline which is to be evaluated for its effect on air

toxic emissions. The target gasoline may vary by county, year and month. 

MOVES2010a contains a large set of fuel formulations and associated fuel market share 

fractions for each of the 3,222 United States counties, for each month and for calendar 

years 1990 and 1999 through 2012. These fuel data were assembled under EPA contract 

with EH Pechan who analyzed in-use fuel surveys from 2005 and made projections based 

statistics and EPA fuel regulations. In addition, to the large set of built-in fuel data, the

user may enter their own fuel formulations and market share information, if available.

Note, that the use of a ‘base’ fuel as a ‘target’ fuel will produce a fuel correction of unity. 

Table 2-1 

MOVES Base Fuel Properties 

Fuel Property

Name 

Base Fuel A Base Fuel B Base Fuel C 

Fuel Sub-Type Conventional Gas Conventional Gas Conventional Gas 

RVP 6.9 psi 6.9 psi 8.7 psi 

Sulfur Level 30.0 ppm 90.0 ppm 338.0 ppm * 

ETOH Volume 0.0 % 0.0 % 0.0 % 

MTBE Volume 0.0 % 0.0 % 0.0 % 

ETBE Volume 0.0 % 0.0 % 0.0 % 

TAME Volume 0.0 % 0.0 % 0.0 % 

Aromatic Content 26.1 % 26.1 % 26.4 % 

Olefin Content 5.6 % 5.6 % 11.9 % 

Benzene Content 1.0 % 1.0 % 1.64 % 

E200 41.1 % 41.1 % 50.0 % 

E300 83.1 % 83.1 % 82.0 % 

Volume to percent

Oxygen 

0.0 % 0.0 % 0.0 % 

• Air toxic computation is not a function of sulfur level 

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For both the “Target” and “Base” fuels, the overall Complex model consists of ten

individual, statistically derived models (see Section 2.2 below for more details). Each of 

these ten fuel models predicts emissions as an exponential function of fuel parameters

and associated coefficients. Each has a weighting factor which varies by vehicle model

year that is used to weight the contribution of all ten models into a composite result. 

The MOVES algorithm to compute these emission effects is complex and is

detailed in the next section. In summary, for each of the ten Complex Model submodels, MOVES sums the coefficients for each model parameter, calculates the 

difference between the fuel value and an average fuel value, multiples the coefficient sum

by this difference, computes the sum of the resulting values across the complex model

parameters and computes the exponential function of this value. 

MOVES then calculates a ratio between the exponential values for the target and

base fuels for each of the Complex Model sub-models. The sub-model ratios are 

weighted together to create a weighted average fractional difference in air toxic emissions

between the base and target fuels. This information is used to predict the toxics 

emissions for each target fuel. Similar calculations are used to predict the VOC

emissions for the same fuels, and the resulting ratios of the predicted toxics and VOC are

calculated. 

2.2 Complex Model Mathematical Algorithm 

The Complex Model algorithm is presented in this section in a series of nine 

calculation steps. Each variable is defined in the steps and where and in some cases an

example calculation is provided. 

2.2.1 Step 1 

This series of steps are used only for pollutants: 

Benzene,
 

1,3-butadiene, 

Formaldehyde

Acetaldehyde
 

They are performed for each of the MOVES emission processes: 

running
 

start 

evaporative processes
 

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There are up to 64 different Complex Model parameter (cmpID) variables that

represent the effects of individual fuel parameters and cross products of individual fuel

parameters determined from statistical analysis of the data. Each of the ten Complex

Model sub-models has coefficients that must be added. The addition for each parameter is

done across each model. 

The variable baseSumCoeff is the sum of coefficients for the base fuel, and the 

variable targetSumCoeff is the sum of coefficients for the target fuels. The structure of 

the table containing the coefficients is given in Table 2-2. 

basesumcoeff = coeff1 + coeff2 Eq 2-3a 

targetsumcoeff = coeff1 + coeff2 Eq 2-3b 

The calculations are performed for each fuel-type (i.e., gasoline and E-85 only),

for each fuel formulation, for each fuel model year combination and for all cmpID

variables (denoted as cmpID in Table 2-2). Currently, the variable “coeff3” is not used 

in the calculation. It is reserved for possible future use. 

Table 2-2 ComplexModelParameters 

Fields Datatype Description 

polProcessID smallint(6) PK: standard polProcessID variable 

fuelModelID smallint(6) PK: basic fuel and technology model index 

cmpID smallint(6) PK: all fuel property variable 

coeff1 float First order coefficients used in calculations 

coeff2 float Second order coefficients used in calculations 

coeff3 float Third order coefficients (placeholder) used in 

calculations. None are currently used. 

2.2.2a Step 2a 

In this step 2a, the baseSumCoeff variable computed in Step 1 along with two 

additional variables “baseValue” and “centeringValue” are used to calculate a subsequent

variable BaseProd. This calculation is performed only for the ‘base’ fuel (an analogous

calculation is performed for the target fuel). Like Step 1 this calculation is performed for

each pollutant / process / fuel-type / fuelformulation (base only) / fuelModelID and 

cmdID combination. Mathematically, the equation is given by Eq 2-4a. 

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Baseprod = basesumcoeff * (baseValue – centeringValue) Eq2-4a 

The variable “baseValue” is found in Table 2-1 for all of the parameters. The 

‘baseValue’ variable and the “centeringValue” variable are listed. The table 

MeanFuelParameters has the following structure as used in MOVES. 

fueltypeid

modelyeargroupid

fuelparameterid

fuelparametername

basevalue 

centeringvalue 

The baseValue variable is the actual value for the base fuel (i.e., sulfurlevel, RVP, 

E200, etc). The “centering value” a mean value used in the calculations. 

Some cmdIDs describe the product of two fuel parameters such as oxygen and 

RVP. This special case is illustrated in Eq2-4b for a baseprod for the cmpID that is the

product of oxygen and RVP. 

Baseprod = basesumcoeff * (Oxygen – Oxygen centering value) *

(RVP-RVP centering value) Eq2-4b 

Table 2-3 MeanFuelParameters 

Fields Datatype Description 

polProcessID smallint(6) PK: standard polProcessID variable 

fuelTypeID smallint(6) PK: fuelTypeID = 1 only 

modelYearGroupID int(11) PK: two new mygIDs added 

fuelParameterID Smallint(6) PK: major fuel property variable 

baseValue float Baseline fuel properties. 

centeringValue float Fuel parameter mean value used in calculations. 

stdDevValue float Fuel parameter standard deviation used only in 

HC and NOx calculations. 

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2.2.2b Step 2b 

In this step 2b, the targetSumCoeff variable (calculated in Step 1) along with the

variables “fuelParameter” and “centeringValue” are used to calculate a subsequent

variable TargetProd. This calculation is performed for each of the target fuels which are 

being evaluated. Like Step 1 this calculation is performed for each pollutant / process / 

fuel-type / fuelformulationID (target fuels only) / fuelModelID and all possible cmdID

combinations. Mathematically, the equation is given by Eq 2-5a. The variable 

“centeringValue” comes from the MeanFuelParameters.xls table. The fuelparameter

variable is the particular fuel parameter for the target fuel (i.e., sulfurlevel, RVP, E200, 

etc) that the user wishes to evaluate. The calculation is performed separately for each 

fuel parameter. 

Targetprod = targetSumCoeff * (fuelparameter – centerValue) Eq 2-5a 

In some cases for the Target fuel, a particular cmdID may include a fuel

parameter which is a product of two fuel parameters. This special case is illustrated in

Eq2-5b for a Targetprod that is the product of oxygen and RVP. 

Targetprod = Targetumcoeff * (Oxygen – Oxygen centering value) *

(RVP-RVP centering value) Eq2-5b 

2.2.3 Step 3 

In this step the variables eBaseProdSum and eTargetProdSum are calculated for each

pollutant, process, fuel-typeID, fuel-formulationID (base and target), and fuelModelID

combination. The variables eBaseProdSum and eTargetProdSum are the exponential sum of

each of the individual BaseProd and TargetProd variables. The sums are across all of the 

possible cmdID (1 to 64) groups. 

eBaseprodSum = EXP [SUM(Baseprod) where cmdID = 1 to 64 ] Eq2-6a 

eTargetprodSum = EXP [SUM(Targetprod) where cmdID = 1 to 64 ] Eq2-6b 

In cases where the SUM(Baseprod) or SUM(Targetprod) equals zero, the value of

eBaseprodSum or eTargetprodSum is set to zero rather than calculated as unity. 

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2.2.4 Step 4 

In this step the variable Ratio1 is calculated for each pollutant, process, 

fueltypeID, fuelModelID, fuelformulationID (the unchanging base fuel and variable

target fuel) and fuelModelID combination using Equation 2-7. There are eleven 

fuelModelID’s for the primary exhaust air toxic pollutants. 

Ratio1 = ( (eTargetprodSum / eBaseprodSum ) – 1.0 ) Eq2-7 

2.2.5 Step 5 

In this step, the variable Ratio2 is computed by multiplying Ratio1 by a

fuelModelWtFactor variable. This accounts for the mix of technologies and high emitters 

by model year. Each of the ten fuel models has an associated weighting factor which is a 

function of ageID, and two broad model year groups (1960-2000 and post-2000). The 

structure of the table is shown in Table 2-4, and the names of the individual fuel models 

for air toxic emissions are provided in Table 2-5. The individual fuel models represent

fuel metering, EGR, catalyst and air injection technology groupings, as well as high

emitters. The weighting factors account for the prevalence of each type of vehicle. 

The weighting factors which are used in MOVES differ from those used in the

original Complex model. They vary by model year group because of the changing 

important of technology groupings (the original does not vary), and there is now less 

emphasis on so called “High emitters”. The original Complex model gave a 55 percent

weighting to high emitters (i.e., fuel model = 10). The fraction of high emitters now 

varies with age. It ranges from 0.01 percent at age zero to 32.8 percent at 30 years. 

Table 2-4 FuelModel Weighting Factors 

Fields Datatype Description 

fuelModelID smallint(6) PK: basic fuel and technology model index 

modelYearGroupID int(11) Only two groups 

ageID smallint(6) Age 0 through 30 

fuelModelWtFactor float Weight factor that sums to unity for each 

fuelModelID and modelYearGroupID 

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Table 2-5 FuelModel Names 

Fuel Model ID Fuel Model Name 

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 

10 All High Emitters 

11 All Tier2 

Ratio2 = Ratio1 * fuelModelWtFactor Eq2-8 

Note that FuelModel = 11 (the All Tier2 model) is not part of the calculation or the

weighting (it currently receives a weighting factor of zero). It is reserved for future use. 

2.2.6 Step 6 

In this step, the Ratio2 variables are summed across the ten fuel models. This 

produces the variable atDifferenceFraction. It is a weighted sum of all of the fuel models 

and the base and target fuel effects. In essence, it is the fractional difference in air toxic 

emissions between the base and target fuels. It is calculated for each combination of 

pollutant, process, fueltypeID, ageID and fuelformulationID. 

atDifferenceFraction = SUM (Ratio2) where i = 1,max(fuelmodels) Eq2-9 

fuelmodel [i]

max(fuelmodels) = 10 for air toxic pollutants
 

2.2.7 Step 7 

In this step the variable RelATEmissions is calculated for the Target fuel using

Equation 2-10. This variable represents the air toxic emissions on the target fule with no

other adjustments. The variable RelATEmissions includes the air toxic emissions effect 

of the change in fuel properties of the Target fuel versus the Base fuel. If the base fuel 

were identical to the Target fuel, the variable atDifferenceFraction would be zero and the 

RelATEmissions would be the same as the atBaseEmissions. 

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The atBaseEmissions are the air toxic emission rates in units of grams per mile, 

and are a function of month of the year. They were taken directly from the Complex 

Model Spreadsheet “CM Final.xls”. They are the base air toxic emissions for the Base 

Fuel in the air toxics model. These base emissions were calculated from air toxic 

emission data from the Tier 0 vehicles in the original air toxic / fuel effects studies on

which the Complex Model was based. They are used in conjunction with similar VOC

emissions (see Step 8 below) to compute a final air toxic to VOC emission ratio which is

used in the MOVES model. The MOVES air toxic algorithm is based on the assumption 

that within a fuel model group (i.e., technology group) the air toxic pollutant to VOC

ratio has remained constant even as vehicle emission standards have been lowered from 

Tier0 to Tier2 levels. When the results of the EPACT test program are fully available,

this assumption will be re-evaluated and new ratios / fuel models may be developed for

Tier2 vehicles. The “All Tier2” fuel model is currently a placeholder for these new

values / coefficients. 

RelATEmissions = atBaseEmissions + atBaseEmissions * atDifferenceFraction Eq2-10 

2.2.8 Step 8 

Steps 1 through 7 are repeated for the VOC pollutant. Only the final equation 

where the RelVOCEmissions variable is shown in Equation 2-11 is repeated. It is the 

denominator for the final air toxic to VOC ratio. This is NOT the computation of the 

standard VOC pollutant in MOVES. These steps compute a VOC value for the variables

atDifferenceFraction and RelATEmissions. Like the air toxic pollutant, the

atBaseEmission value for VOC was also based the original testing of Tier0 vehicles. 

RelVOCEmissions = VOCBaseEmissions + VOCBaseEmissions * atDifferenceFraction Eq2-11 

2.2.9 Step 9 

This step in Equation 2-12 calculates the final air toxic to VOC ratio which is

used in the MOVES model. This algorithm is used for processes of running and start and 

for pollutantID {20, 24, 25 and 26}. It is used only for gasoline fueled vehicles. It shall 

be computed for each pollutant-process, fuelformulationID, and monthGroupID. 

atRatio = RelATEmissions / RelVOCEmissions Eq2-12 

The variable atRatio is used in MOVES to compute the air toxic emissions for benzene, 

1,3-butadiene, formaldehyde and acetaldehyde. This is done by multiplying the appropriate 

atRatio by the final MOVES VOC emission rate after fuel, temperature and I/M effects have 

been applied. 

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2.3 MTBE Complex Model Algorithm 

2.3.1 MTBE Exhaust Model 

As of calendar year 2008, MTBE (MOVES pollutantID = 22) has been almost

completely phased-out of the fuel supply of the United States due to ground water

contamination concerns. Thus, its inventory levels in the MOVES output from default

inputs should be very small if not zero in future years. It is present in the MOVES model

as mostly a legacy pollutant for calendar years 1990, 1999 – 2005. However, the MTBE 

fuel volume is a user input, and MOVES has the capability to calculate MTBE emissions

for any calendar year. 

The MTBE Exhaust model was developed from a simple empirical analysis of

MOBILE6.2 outputs. MOBILE6.2 relied on a draft MTBE fuel effects model.2,3 This 

process included several detailed MOBILE6.2 runs, and a simple regression of the

exhaust MTBE / VOC ratio versus MTBE fuel volume. A quadratic equation fixed at the 

origin was found to be the best fit. The equation is shown in Equation 2-13 and the 

parameters are shown in Table 2-6. The same equation is used for both start and running 

processes. 

MTBE/VOC ratio = A * MTBEVolume + B*(MTBEVolume)^2 Eq2-13 

Where 

A = ComplexModelParameters.coeffA 

B = ComplexModelParameters.coeffB 

Table 2-6 

MOVES MTBE Exhaust Calculation Coefficients 

polProcessID Process Description Coeff A Coeff B 

2201 Running Exhaust 0.00007809 0.00007537 

2202 Start Exhaust 0.00007809 0.0007809 

Like the other air toxic ratios, the MTBE / VOC ratio is multiplied by the

MOVES VOC emission factors to produce a MOVES MTBE emission factor in the 

2 Wyborny, L. 1998. Methyl Tertiary Butyl Ether (MTBE) Emissions from Passenger Cars. Draft 

Technical Report. U. S. Environmental Protection Agency, Office of Mobile Sources. April, 1998. 

3 Rich Cook and Edward L. Glover. 2002. Technical Description of the Toxics Module for MOBILE6.2 

and Guidance on Its Use for Emission Inventory Preparation. Assessment and Standards Division, Office 

of Transportation and Air Quality, Ann Arbor, MI. Report No. EPA420-R-02-011. 

http://www.epa.gov/otaq/models/mobile6/r02029.pdf 

14 
 

 

 

 

 

 

 

appropriate units (i.e., grams per hour, grams per start, grams per mile). In MOVES the 

MTBE / VOC ratio ranges from 0.015 to 0.15 in cases where MTBE is present in the 

fuel. The MTBE ratio is 0.000 in cases where no MTBE is present in the fuel. 

2.3.2 MTBE Evaporative Model 

MTBE ratios are estimated using algorithms originally developed for MOBILE

6.2, using the MTBE fuel effects model cited above. 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. The 

MOBILE6.2 algorithm for resting loss is used for permeation. 

The equation for MTBE fuel vapor venting and refueling displacement vapor loss: 

MTBE / VOC = MTBEVolume*(24.2050 - 1.7460*RVP)/1000.0 

The equation for MTBE fuel leaks and refueling spillage loss: 

MTBE / VOC = MTBEVolume*(17.8538 - 1.6622*RVP)/1000.0 

The equation for MTBE Permeation: 

MTBE / VOC = MTBEVolume*(22.1980 - 1.7460*RVP)/1000.0 

2.4 Benzene Evaporative Model Algorithm 

The equations for Benzene evaporative emissions are simpler that the ones used 

for exhaust Benzene, and there are no Base fuels in the equations. 

The equation for Benzene Permeation is: 

Benzene / VOC = (BenzeneContent * (-0.02895*OXY - 0.080274*RVP + 1.3758)/100.0) + 

(0.77*(benzeneContent*(-0.02895*ETOHVolume*0.3488 – 

0.080274*RVP + 1.3758)/100.0)*ETOHVolume/10.0) 

This equation is based on the diurnal emissions algorithm from MOBILE6.2. The diurnal 

emissions equation accounts 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.4

 Thus the ratio predicted by the diurnal emissions algorithm was multiplied 

by 1.77. 

4 Haskew, H. M., Liberty, T. F., and McClement, D. 2004. Fuel Permeation from Automotive Systems. 

Prepared for the Coordinating Research Council by Harold Haskew and Associates and Automotive 

Testing Laboratories, Inc. September 2004. CRC Project No. E-65. http://www.crcao.com. 

15 
 

 

 

 

For other evaporative processes, equations for hot soak in MOBILE6.2 are used: 

Benzene / VOC = (BenzeneContent * (-0.03420*OXY - 0.080274*RVP + 1.4448)/100.0) 

Where OXY is: 

OXY = ETOHVolume*0.3488 + MTBEVolume*0.1786 + ETBEVolume*0.1533 

+ TAMEVolume*0.1636 

16 
 

 

 

 

 

 

 

 

 

 

 

3.	 Algorithms for Ethanol, Acrolein and Naphthalene from 

Gasoline Vehicles in MOVES2010 

3.1 Ethanol 

Ethanol emissions in MOVES are calculated by applying an Ethanol / VOC ratio to the

calculated VOC emissions in MOVES. Equation 3-1 is used. 

Ethanol = Ethanol/VOC Ratio * VOC	 Eq3-1 

For vehicles running on 10% ethanol, 2.39 percent of exhaust VOC is 

estimated to be ethanol. This estimate is based on tests on 9 vehicles from 4 test 

programs.5, 6, 7, 8 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). The exhaust

ethanol / VOC ratios for gasoline fuels (i.e. pure gasoline or E10 or less) are shown in 

Table 3-2. 

Table 3-2 

Exhaust Ethanol / VOC Ratios for Gasoline Fuels 

Ethanol Fuel Volume (%) Ethanol / VOC Ratio 

0 0.00000 

5 0.01195 

8 0.01912 

10 0.02390 

Toxic to VOC ratios for E85 and E70 are given in Table 3-3. E85 exhaust ratios for all 

pollutants except naphthalene were obtained from data on seven vehicles from a 1995 test

program in EPA’s Office of Research and Development, along with data from a 2007 test

program at Southwest Research Institute and a 2005 test program at Environment 

5 Southwest Research Institute, 2007. Flex Fuel Vehicles (FFVs) VOC/PM Cold Temperature 

Characterization When Operating on Ethanol (E10, E70, E85). Prepared for U. S. Environmental 

Protection Agency. 

6

Environment Canada, 2007. Comparison of Emissions from Conventional and Flexible Fuel Vehicles 

Operating on Gasoline and E85 Fuels. ERM Report No. 05-039, Emissions Research Division. 

7

Durbin T. D., Miller J. W., Younglove T., Huai T., Cocker K., 2007. Effects of fuel ethanol content and 

volatility on regulated and unregulated exhaust emissions for the latest technology gasoline vehicles. 

Environmental Science and Technology 41, 4059-4064. 

8 U. S. EPA, 1995. Office of Research and Development, unpublished data. 

17 
 

 

 

 

 

 

 

 

 

 

 

 

 

Canada.9,10,11 E70 exhaust ratios are from the 2007 test program at Southwest Research

Institute cited above.9 E85 benzene evaporative emission ratios were derived from

speciation data collected as part of the Auto/Oil test program in the early 1990’s.12E85 

benzene permeation ratios are from the CRC E-65 test program.4 Ratios for evaporative

and permeation emissions from E70 fuel were estimated by multiplying the E85 ratios by

70/85. 

Table 3-3 

Ethanol / VOC Ratios for High Ethanol Fuels 

Ethanol Fuel Volume Process Ethanol / VOC Ratio 

E85 Running 0.5348 

E85 Start 0.5348 

E85 Permeation 0.5940 

E85 Fuel Vapor Venting 0.6123 

E85 Fuel Leaks 0.6123 

E85 Refueling Vapor Loss 0.6123 

E85 Refueling Spillage 0.6123 

E70 Running 0.7036 

E70 Start 0.7036 

E70 Permeation 0.4892 

E70 Fuel Vapor Venting 0.5042 

E70 Fuel Leaks 0.5042 

E70 Refueling Vapor Loss 0.5042 

E70 Refueling Spillage 0.5042 

3.2 Acrolein and Naphthalene 

The toxic to VOC ratio for acrolein carries over from MOBILE6.2. Acrolein is 

found only in exhaust. Naphthalene is carried over from the National Mobile Inventory 

Model (NMIM).13 Exhaust naphthalene and other PAH emissions are estimated as a ratio 

9 Southwest Research Institute. 2007. Flex Fuel Vehicles (FFVs) VOC/PM Cold Temperature 

Characterization When Operating on Ethanol (E10, E70, E85). Prepared for U. S. Environmental 

Protection Agency. Available in Docket EPA-HQ-OAR-2005-0161. 

10 Environment Canada. 2007. Comparison of Emissions from Conventional and Flexible Fuel Vehicles 

Operating on Gasoline and E85 Fuels. ERM Report No. 05-039, Emissions Research Division. Available 

in Docket EPA-HQ-OAR-2005-0161. 

11 Graham, L. A.; Belisle, S. L. and C. Baas. 2008. Emissions from light duty gasoline vehicles 

operating on low blend ethanol gasoline and E85. Atmos. Environ. 42: 4498-4516. 

12 Auto/Oil Air Quality Improvement Research Program. 1990. Phase 1 Working Data Set (published in 

electronic form). Prepared by Systems Applications International, San Rafael, CA. 

13 Michaels, H., Brzezinski, D., Cook, R. 2005. EPA’s National Mobile Inventory Model (NMIM), A 

Consolidated Emissions Modeling System for MOBILE6 and NONROAD. U. S. EPA, Office of 

18 
 

 

 

to PM in NMIM. This approach is used, even though naphthalene is found in the gas, 

semi-volatile and particle phase, because there is generally reasonable correlation

between PAH and PM emissions. However, for future versions of MOVES, PAH 

exhaust emissions will be apportioned into the gas and particle phase, and gas phase

PAHs such as naphthalene will be estimated using toxic/VOC ratios and particle phase 

PAHs will be estimated using toxic to OC2.5 (organic carbon less than 2.5 microns)

ratios. Evaporative naphthalene is estimated as a ratio to VOC in MOVES2010a. 

Table 3-3 

Toxics Ratios for Acrolein and Naphthalene from Gasoline Vehicles 

Pollutant Emission Type Ratio Type Ratio 

Acrolein Exhaust VOC 0.00063 

Naphthalene Exhaust PM 0.0880 

Naphthalene Evaporative and 

Permeation 

VOC 0.0004 

Transportation and Air Quality, Assessment and Standards Division, Ann Arbor, MI, March 2005; Report 

No. EPA-420-R-05-003. Available at http://www.epa.gov/otaq/nmim.htm. 

19 
 

 

 

 

 

 

4.	 Complex Model Algorithms for Carbon Monoxide Fuel 

Effects 

This section describes in detail the calculations used to compute the fuel effects

for carbon monoxide emission in MOVES. These calculations were taken from the EPA 

Complex Model developed in the early 1990’s. The algorithms include methodologies

for calculating running and start emissions from gasoline vehicles. The general structure 

of this section will be to describe and discuss the calculation algorithms in mathematical 

terms, show the underlying equation coefficients and present some limited results in 

graphical form for selected cases. 

The Complex Model (CM) algorithm is used to compute the fuel effects for

carbon monoxide. This algorithm was developed in the mid-1990’s based on testing of a

sample of mostly Tier0 vehicles (1993 and earlier model years) over a wide variety of

gasoline fuel compositions. A complex statistical analysis using multivariate regression

techniques was performed on the primary database and a set of statistical models were 

developed. These statistical models were originally programmed into the Unconsolidated 

Complex Model spreadsheet, and have now been programmed into the MOVES model

and described in this document. The reader who is interested in the original test program

design, the data processing, and/or the details of the statistical analysis must refer to the 

original primary documents of the study. 

http://www.epa.gov/oms/models.htm 

The algorithm for the Complex Model for CO emission fuel effects is almost 

completely analogous to the Complex Model for air toxic emissions. However, there are 

some important differences. The first difference is that the CO fuel effects are not a ratio 

to VOC emissions. Instead, the fuel effects for a given target fuel are a ratio to a base 

reference fuel whose fuel adjustment is defined as one. This reference fuel is the fuel(s) 

that best represent(s) the test conditions at the Arizona IM lane where the primary

emission factor data were acquired. See Section 2.1 and Table 2-1 for more details on the 

base / reference fuels. The second difference is the use of the Complex model only to 

compute the emission effect contributions from the non-sulfur fuel parameters. For CO, 

a separate fuel sulfur model (MOBILE6 Sulfur Model (M6SM)) is applied to compute

the fuel sulfur effects after the basic complex model calculations are done (see Section 

5.0 - Fuel Sulfur Model). 

3.1 Carbon Monoxide Complex Model Mathematical Algorithm 

The Complex Model algorithm is presented in this section in a series of nine 

calculation steps. Each variable is defined in the steps and where possible the actual 

calculation coefficients (or at least a sample calculation) are provided. 

20 
 

 

 

 

 

 

 

 

Because the effects of fuel sulfur are applied in the MOVES Sulfur model, they

have been removed from the CO Complex model by setting the fuel sulfur level to a

dummy value of 30 ppm for all of the target fuels. This will cause the multiplicative 

sulfur effects to be unity. The multiplicative MOVES Sulfur model is applied subsequent

to the CO Complex model. 

The CO algorithm uses the same algorithm as the Complex model air toxics 

algorithm for Steps 1 through 6 (i.e., Section 2.2). Different values for the coefficients 

are used, and a different set of Excel workbooks are used to contain the coefficients and 

other parameters. These steps are repeated in this section with only minor name changes

for the sake of the reader who only reads the carbon monoxide section. The reader who 

has already read Sections 2.2.1 through 2.2.6 may find this section redundant. 

3.1.1 Step 1 

This series of steps are used only for the carbon monoxide (CO) pollutant. 

They are performed for each of the MOVES emission processes: 

running, 

start 

extended idle / crankcase 

They are performed for both the Target and Base fuels. The variable 

baseSumCoeff is the sum for the base fuel, and the variable targetSumCoeff is the sum 

for the target fuels. 

basesumcoeff = coeff1 + coeff2 Eq 3-1a 

targetsumcoeff = coeff1 + coeff2 Eq 3-1b 

The calculations are performed for each fueltype (i.e., currently gasoline only), 

for each fuelFormulation, for each fuel model year combination and for all cmpID

variables (denoted as cmpID in Table 3-1). There are up to 64 different cmpID variables

that represent the effects of individual fuel parameters and cross products of fuel

parameters determined from statistical analysis of the data. Most of the individual CO 

fuel models only use a fraction of the 64 different cmpID variables. Currently, the 

variable “coeff3” is not used in the calculation. It is reserved for future possible use. 

21 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 3-1 ComplexModelParametersCO 

Fields Datatype Description 

polProcessID smallint(6) PK: standard polProcessID variable 

fuelModelID smallint(6) PK: basic fuel and technology model index 

cmpID smallint(6) PK: all fuel property variable 

coeff1 float First order coefficients used in calculations 

coeff2 float Second order coefficients used in calculations 

coeff3 float Third order coefficients (placeholder) used in 

calculations. 

3.1.2a Step 2a 

In this Step 2a, the baseSumCoeff variable computed in Step 1 along with two 

new variables “baseValue” and “centeringValue” are used to calculate a subsequent

variable BaseProd. This calculation is performed only for the ‘base’ fuel (an analogous

calculation is performed for the target fuel). Like Step 1 this calculation is performed for

each pollutant / process / fuel-type / fuelformulationID (base only) / fuelModelID and 

cmdID combination. Mathematically, the equation is given by Eq 3-2a. 

Baseprod = basesumcoeff * (baseValue – centeringValue) Eq3-2a 

The variable “baseValue” is found in Table 2-1 for all of the parameters. The 

table MeanFuelParametersCO has the following structure as used in MOVES. 

fueltypeid

modelyeargroupid

fuelparameterid

fuelparametername

basevalue 

centeringvalue 

The baseValue variable is the particular fuel parameter cmpID for the base fuel

(i.e., sulfurlevel, RVP, E200, etc). The calculation is performed separately for each fuel 

parameter. The “centering value” is a mean value variable used in the calculations. It 

was determined as part of the original statistical analysis of the data using a mixed model 

regression. 

In some cases for the Base fuel, a particular cmdID may include a baseValue fuel

parameter which is a product of two fuel parameters such as oxygen and RVP. This 

special case is illustrated in Eq3-2b for a baseprod that is a function of oxygen and RVP. 

22 
 

 

 

 

 

 

 

 

 

 

Baseprod = basesumcoeff * (Oxygen – Oxygen centering value) *

(RVP-RVP centering value) Eq3-2b 

Table 3-2 MeanFuelParameters 

Fields Datatype Description 

polProcessID smallint(6) PK: standard polProcessID variable 

fuelTypeID smallint(6) PK: fuelTypeID = 1 only 

modelYearGroupID int(11) PK: two new mygIDs added 

fuelParameterID Smallint(6) PK: major fuel property variable 

baseValue float Baseline fuel properties. Compared to Arizona 

fuel parameters for HC, CO and NOx. 

centeringValue float Fuel parameter mean value used in calculations. 

stdDevValue float Fuel parameter standard deviation used only in 

HC and NOx calculations. 

3.1.2b Step 2b 

In this step 2b, the targetSumCoeff variable (calculated in Step 1) along with the

variables “fuelParameter” and “centeringValue” are used to calculate a subsequent

variable TargetProd. This calculation is performed only for each of the target fuels which 

are being evaluated. Like Step 1 this calculation is performed for each pollutant / process

/ fuel-type / fuelformulation (target fuels only) / fuelModelID and all possible cmdID

combinations. Mathematically, the equation is given by Eq 3-3a. The fuelparameter

variable is the particular fuel parameter for the target fuel (i.e., sulfurlevel, RVP, E200, 

etc) that the user wishes to evaluate. The calculation is performed separately for each 

fuel parameter. 

Targetprod = targetSumCoeff * (fuelparameter – centerValue) Eq 3-3a 

In some cases for the Target fuel, a particular cmdID may include a fuel

parameter which is a compounding of two fuel parameters such as oxygen and RVP. 

This special case is illustrated in Eq3-3bfor a Targetprod that is a function of oxygen and 

RVP. 

Targetprod = Targetumcoeff * (Oxygen – Oxygen centering value) *

(RVP-RVP centering value) Eq3-3b 

23 
 

 

 

 

 

 

 

 

3.1.3 Step 3 

In this step the variables eBaseProdSum and eTargetProdSum are calculated for each

pollutant, process, fueltypeID, fuelformulationID (base and target), and fuelModelID

combination. The variables eBaseProdSum and eTargetProdSum are the exponential sum of

each of the individual BaseProd and TargetProd variables. The sums are across all of the 

possible cmdID (1 to 64) groups. 

eBaseprodSum = EXP [SUM(Baseprod) where cmdID = 1 to 64 ] Eq3-4a 

eTargetprodSum = EXP [SUM(Targetprod) where cmdID = 1 to 64 ] Eq3-4b 

In cases where the SUM(Baseprod) or SUM(Targetprod) equals zero, the value of

eBaseprodSum or eTargetprodSum is set to zero rather than calculated as unity. 

4.1.4 Step 4 

In this step the variable Ratio1 is calculated for each pollutant, process, 

fueltypeID, fuelModelID, fuelformulationID (the unchanging base fuel and variable 

target fuel) and fuelModelID combination using Equation 3-5. There are ten 

fuelModelID’s for the carbon monoxide model. 

Ratio1 = ( (eTargetprodSum / eBaseprodSum ) – 1.0 ) Eq3-5 

3.1.5 Step 5 

In this step, the variable Ratio2 is computed by multiplying Ratio1 by a

fuelModelWtFactor variable. Each of the ten fuel models has an associated weighting

factor which is a function of ageID (31 years) and two broad model year groups (1960-

2000 and post-2000). The structure of the table is shown in Table 3-3, and the names of 

the individual fuel models are provided in Table 3-4. The individual fuelmodelID’s 

represent fuel metering, EGR, catalyst and air injection technology groupings, and the

weighting factors provide a relative weighting between these groups. The weighting

factors which are used in MOVES are different from those used in the original Complex

model. They now vary by model year group because of the changing important of

technology groupings (the original does not vary). There is now less emphasis on so 

called “High emitters”. The original Complex model gave a 55 percent weighting to high

emitters (i.e., fuel model = 10). The fuelmodelID weighting factors now weight the

models according to vehicle age. With fuelmodel=10 getting a weighting (based on 

MOBILE6.2 – MOVES does not contain the concept of “High” and “Normal” emitters)

that ranges for 0.01 percent at age zero to 32.8 percent at 30 years. 

24 
 

 

 

 

 

 

 

 

 

Table 3-3 FuelModel Weighting Factors 

Fields Datatype Description 

fuelModelID smallint(6) PK: basic fuel and technology model index 

modelYearGroupID int(11) Only two groups 

ageID smallint(6) Age 0 through 30 

fuelModelWtFactor float Weight factor that sums to unity for each 

fuelModelID and modelYearGroupID 

Table 3-4 FuelModel Names 

Fuel Model ID Fuel Model Name 

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 

10 All High Emitters 

11 All Tier2 

Ratio2 = Ratio1 * fuelModelWtFactor Eq3-6 

Similar to the air toxics model, model #11 - the All Tier2 model is not part of the 

calculation and receives a weighting of zero. 

3.1.6 Step 6 

In this step, the Ratio2 variables are summed across the ten fuel models. This 

produces the variable CODifferenceFraction. It is a weighted sum of all of the fuel 

models and the base and target fuel effects. In essence, it is the fractional difference in 

25 
 

 

 

 

 

 

 

 

 

CO emissions between the base and target fuels. It is calculated for each combination of
 

pollutant, process, fuel type, age and fuel formulation. 

CODifferenceFraction= SUM (Ratio2) where i = 1,max(fuelmodels) Eq3-7 

fuelmodel [i]

max(fuelmodels) = 10 for carbon monoxide
 

3.1.7 Step 7 

This step differs from the air toxics algorithm described in Section 2. The non 

sulfur fuel effects on CO emissions are contained in the CODifferenceFraction variable. 

By definition, the Base fuel is the fuel formulation that was generally available in the

State of Arizona during the period where EPA primary test data were collected on carbon 

monoxide emissions. Since sulfur effects are not included in this model only the low

sulfur (30 ppm sulfur) reference - base fuel A (see Table 2-1) may be used as the Base 

fuel. The target fuel is the fuel which is to be evaluated. The variable 

CODifferenceFraction computed in Eq3-8 contains the fractional emission difference

between the target and the base fuels. 

COFuelEffectNoSulfur = 1.0 + CODifferenceFraction eq3-8 

Eq3-8 calculates the CO fueladjustment factor without sulfur. This algorithm is

used only for the processes of running and start and for the CO pollutant, and is used only

for gasoline fueled vehicles. It is computed for each age, fuel formulation and model

year group (MOVES contains two distinct model year groups with different base sulfur

levels). 

3.1.8 Step 8 

Apply the MOBILE6 Sulfur Model (M6SM) to CORatioNoSulfur to compute the

final CO FuelAdjustment Factor which is used to correct the CO emission factors in 

MOVES for gasoline fuel effects. The details on the M6SM model are shown in Section 

5.0 and the process for combining the sulfur and non sulfur fuel models is shown in 

Section 6.0. 

26 
 

 

 

 

 

 

 

 

4.0	 Predictive Model Algorithms for Total Hydrocarbon and 

Nitrogen Oxide Fuel Effects 

4.1 Predictive Model Overview 

The MOVES model uses the Predictive Model to simulate the effect of gasoline 

fuel parameters on hydrocarbon (HC) and nitrogen oxide (NOx) emissions. The HC and 

NOx Predictive Models utilize two base fuels (30 ppm Sulfur and 90 ppm Sulfur). The 

30 ppm fuel is the base fuel for 2001-and-later model years, and 90 ppm sulfur is the base 

fuel for 1975 through 2000 model years. The remaining fuel parameters are identical 

between the two base fuels (see Table 2-1). 

The Predictive Model effects from all fuel parameters are applied to 1960 through 

1993 model years. The effects are not applied for model years 2004-and-later (Tier2-

and-later emission standards). This means that in MOVES2010a, for 2004-model-yearand-later gasoline vehicles, exhaust HC and NOx emissions are insensitive to all fuel 

parameters (vapor pressures, aromatic contents, distillation fractions, etc.), EXCEPT for 

the fuel sulfur level parameter. 

The decision to apply no Predictive Model effects for 2004-and-later model years 

in MOVES2010 is based on limited test evidence, and on engineering judgment that the 

advanced combustion and emission control technologies used in Tier2-and-later gasoline 

vehicles are likely to be insensitive to most fuel parameters (other than sulfur). However, 

the EPAct test program and analysis are designed to provide data on this question. 

Since the release of MOVES2010a, EPAct testing and statistical analysis on 

2004 and later model years has shown that virtually all of the pollutants (criteria and air 

toxic) are sensitive to a full array of fuel parameters – not just fuel sulfur. Consequently, 

the assumption of ‘insensitivity’ to fuel parameters now used in MOVES2010a will be 

substantially changed in future versions of the MOVES model. 

4.2	 Predictive Model Step 1 

The overall goal of the Predictive model algorithm is to develop a multiplicative

fuel correction factor for a given fuel formulation which can be applied to the base 

emission rates (BaseE) as calculated by MOVES. This is shown mathematically in the 

simple Equation 4-1. 

Fuel Corrected Emissions = Fuel Correction * Sulfur Correction * BaseE Eq 4-1 

The Fuel Correction shown in Eq 4-1 is the ratio between the Predictive model

output for the Target fuel and the Predictive model output for Base fuel. This is shown in 

Equation 4-2 

Fuel Correction = PredictiveModel{Target} / PredictiveModel{Base} Eq 4-2 

27 
 

 

 

Where Target is the emissions using the Target fuel formulation and Base refers

to emissions with the Base fuel formulation. The same algorithms are used for both the

Target and Base Predictive model calculations. The only difference between the two

calculations is the different fuel properties for the Target fuel and the Base fuel. 

4.3 Predictive Model Step 2 

The Predictive model is a series of statistically derived fuel and emission models. 

During the analysis process, several models were developed but only three models were 

chosen for HC, and six models were chosen for NOx. For a given pollutant, each model 

is equally weighted for the computation of the final result. Table 4.1 lists the individual 

models. 

Table 4-1 

MOVES Fuel Model Naming Conventions 

Model Number HC NOx 

1 107 302 

2 108 303 

3 112 304 

4 305 

5 306 

6 307 

Each of the fuel models (three for HC and six for NOx) are function of 19 fuel 

parameters and combinations (products) of fuel parameters. All of the models have the same list 

of parameters. However, some models have coefficients of zero for certain parameters. The 

parameters are listed in Table 4-2 contains a complete list of all of the Predictive model 

parameters and equations. In the MOVES algorithm the “Intercept” and “HI” terms are set to 

unity. 

28 
 

 

 

 

Table 4-2 Fuel Parameters for the Predictive 

Models 

Parameter Number Fuel Parameter(s) 

1 Intercept 

2 RVP 

3 T50 

4 T90 

5 AROM 

6 OLEF 

7 OXYGEN 

8 SULFUR 

9 HI 

10 T90*T90 

11 T50*T50 

12 T90*OXY 

13 SUL*HI 

14 OXY*OXY 

15 T90*ARO 

16 T50*HI 

17 OLE*OLE 

18 T90*OLE 

19 ARO*ARO 

The first step in applying the model is to create a normalized fuel parameter

(N_Parameter) as shown in Equations 4-3a and 4-3b. It is performed for each of the

parameters listed in Table 4-2, for each of the three HC models or each of the six NOx

models, and for both the Target and Base fuels. 

N_Parameter = (fuelParmeter –centeringValue) / stdDevValue Eq 4-3a 

Where: 

fuelParameter - is the particular fuel parameter value of either the target or base fuel 

(i.e., RVP(psi)). The values for the Target and Base fuels are taken from the MOVES

Fuel Formulation table. 

The related Equation 4-3b is used for a compound term (i.e., T90*OLE) 

N Parameter = ((T90-centeringValue)/stdDevValue)*((Olefin-centeringValue)/stdDevValue) 

Eq4-3b 

CenteringValue and the stdDevValue are fuel parameter constants. These are shown in Table 

4-3. 

29 
 

 

 

 

 

Table 4-3 

MOVES Predictive Model CenteringValues and StdDevValues 

Standard 

Term Mean Deviation 

RVP 8.51 0.781459 

T50 205.62 17.612534 

T90 310.65 20.869732 

AROM 27.64 6.561886 

OLEF 6.93 5.143184 

OXYGEN 1.49 1.249356 

SULFUR 183.14 143.055894 

4.4 Predictive Model Step 3 

In this step the normalized fuel parameter from Eq 4-3a and Eq 4-3b are 

multiplied by the variable “coeff1” for each of the each of the parameters (i) listed in

Table 4-2, for each of the fuel models (i.e., HC has three and NOx has six), and for both 

the Target and Base fuels. This produces a matrix of products for both the Target and 

Base fuels. The values for the variable coeff1 are shown in the attached spreadsheet

PredictiveModelCoefficients.xls. 

Product (i) = N Parameter * coeff1(i) Eq 4-4 

4.5 Predictive Model Step 4 

For each of the fuel models, and the Target and Base fuel formulations the values

of Product(i) are summed across the 19 fuel parameters listed in Table 4-2. The 

Exponent of the sums is calculated. 

ModelResult(j) = EXP [SUM(Product(i,j)) i = 1, 19 ] Eq 4-5 

Where (i) is the fuel parameter and (j) is the fuel model. 

4.6 Predictive Model Step 5 

In this step the ModelResult calculated in Step 4 for each fuel model (three HC

models and six NOx models) are weighted (averaged) together. This operation is done

for both the Target and Base fuels to produce the variable “WeightedResult”. For both 

HC and NOx, each of the fuel models is equally weighted. 

30 
 

 

 

 

 

 

WeightedResult[target]= sum[fuelModelWtFactor * ModelResult(j)] Eq 4-6 

WeightedResult[base] = sum[fuelModelWtFactor * ModelResult(j)] Eq 4-7 

Where (j) is three for HC and (j) is six for NOx. 

4.7 Predictive Model Step 6 

We next calculate the Fuel Correction variable shown in Equation 4-1 and 4-2. 

This is the fuel adjustment factor WITHOUT the effects of sulfur. In MOVES it is 

computed for each emission process (running and start), each target fuel formulation 

which is being evaluated, each model year group / age group and each source type. 

Fuel Correction= WeightedResult[target] / WeightedResult[base] Eq 4-8a 

By definition, for Tier2-and-later model years the Fuel Correction variable is set

to one for all non sulfur effects. Since there are no sulfur effects in this algorithm 

Equation 4-8b is used. 

Fuel Correction = 1.0 Eq 4-8b 

4.8 Predictive Model Step 7 

In this step the Sulfur Correction factor is applied to Fuel Correction variable

calculated in Eq 4-8a or Eq 4-8b. The Sulfur Correction factor is computed by applying

the MOBILE6 Sulfur Model (M6SM). The details on the M6SM model are shown in 

Section 5.0 and the process for combining the sulfur and non sulfur fuel models is shown 

in Section 6.0. 

31 
 

 

 

5.0 Fuel Sulfur Model 

5.0 Fuel Sulfur Model Background 

In the MOVES application of the Complex and Predictive Models, the emission 

effects of fuel sulfur were removed and the multiplicative correction factors for sulfur 

were set to one. Instead of using the sulfur effects from these two models, the fuel sulfur 

effects from the MOBILE6.2 Fuel Sulfur Model (M6Sulf) were applied to both start and 

running emissions for HC, CO and NOx emissions for all model years (the exception is 

the final sulfur adjustment factor for pre-1975 model years which is unity, ie. no 

adjustment). In MOVES2010a, the Tier2 (2004 and later model years) utilize the M6Sulf 

model, but this assumption will likely be reviewed once substantial emission / fuel data is 

available from the EPAct testing. 

Two issues become apparent when applying the M6Sulf effects in the MOVES 

model. These are: (1) The MOBILE6.2 model contains separate effects for High and 

Normal emitters, but MOVES does not classify emissions or vehicles according to these 

terms. (2) The MOVES model needs to model Tier2 vehicles using low sulfur fuel (i.e., 

< 30 ppm sulfur). However, the MOBILE6.2 sulfur factors are based entirely on preTier2 vehicles operating on sulfur levels of 30 ppm or higher. 

In MOBILE6.2, different fuel sulfur effects (coefficients) and equations (i.e., loglog and log-linear) were used for High and Normal emitters (a “High” emitter was 

defined as a vehicle which emitted twice it applicable HC or NOx standard or three times 

its CO standard). MOBILE6.2 computes emission rates for High and Normal emitters 

separately and weights them according to a complex algorithm that is built into the 

model. However, in general the weighting between High and Normal emitters was 

frequently about equal for the typical vehicle on the road (new vehicles had lower rates of 

high emitters, though). For the MOVES sulfur effect, a straight arithmetic average 

between the High and Normal effects was calculated and used for consistency with the 

MOBILE6 approach. 

For some of the late model year vehicles (2001 – 2003), this approach may model 

these vehicles to be less sensitive to sulfur than more recent data from 2004+ model year 

– Tier2 vehicles would suggest. This is because (1) the distribution of “high” emitters in 

the fleet is smaller (< 50%) than it has been historically – although, their emission 

contribution is probably still very significant, and (2) the “high” emitter corrections are 

typically log-linear relationships and less sensitive to sulfur than the log-log “normal” 

emitter corrections. 

To model very low sulfur fuels in MOVES, we extrapolated the MOBILE6 

emission / fuel sulfur relationship to fuels below 30 ppm sulfur. Since some of these 

relationships are log-log in structure, such an extrapolation could lead to meaningless 

results. To prevent highly non-linear relationships which are inherent in log-log 

mathematics from dominating the MOVES emission results, a fuel adjustment ‘floor’ of 

0.85 was placed in the code. This ‘floor’ prevents MOVES from reducing the emission 

32 
 

 

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

fuel formulation (30 ppm sulfur) to some other lower level (i.e., 0.01 ppm sulfur). This 

floor should prevent the most asymptotic portion of the log-log relationship from being 

utilized. 

As a final thought on this topic, EPA realizes the inherent problems associated 

with using these out of date fuel relationships on Tier2 and later vehicles operating on 

low sulfur fuels. As such, EPA plans to revise them as soon as sufficient new data are 

collected and analyzed as part of the EPAct test program. 

5.1 MOBILE6 Sulfur Algorithm in MOVES 

In MOVES, the M6Sulf model data are stored as a set of equation coefficients in a 

database table. It has the following table structure: 

pollutantID
 

processID
 

fuelMYGroupID
 

M6emitterID
 

SourceTypeID
 

SulfurFunctionID
 

SulfurCoefficient
 

The M6emitterID is designated as either “Normal” or “High” and the 

SulfurFunctionID is designed as either “Log-Log” or “Log-Linear”. The “Log-Log” 

designation refers to a model with a natural log – natural log form and the “log-linear” 

refers the natural log-linear model. 

The M6Sulf algorithm as programmed into the MOVES model contains four 

separate fuel sulfur models. This document and section details the algorithms in the 

MOVES model. It also discusses the minor changes and assumptions that had to be made 

to fit the MOBILE6 algorithms into the MOVES structure. The reader who is interested 

in the primary development of these fuel models needs to refer to the primary 

documentation in the EPA report EPA420-R-01-039 “Fuel Sulfur Effects on Exhaust 

Emissions – Recommendations for MOBILE6” by Venkatesh Rao. The internet link is: 

http://www.epa.gov/otaq/models/mobile6/r01039.pdf 

The individual models which are used in the MOVES model are: 

Short Term Sulfur model
 

Long Term Sulfur model
 

Sulfur Irreversibility model
 

Sulfur GPA model
 

33 
 

 

 

 

 

 

 

 

 

 

 

 

In addition, space is reserved in the MOVES model to incorporate a new fuel 

sulfur model for Tier2 (2004-and-later model year vehicles) if and when it become 

available. 

5.2 Short Term Sulfur Effects 

The Short Term Sulfur Effects is an adjustment to the base emissions as a 

function of the sulfur volume of the gasoline in parts per million. The calculations begin 

by using Equations 5-1a and 5-1b. These are used in cases where the log-log relationship 

is required (the variable SulfurFunctionID is set to ‘log-log’. This is for Tier0 and LEV+ 

vehicles. The variable “sulfShortTarget” is the correction factor for the sulfur level of the 

fuel which is being modeled. SulfShort30 is the correction factor for the basis sulfur 

(table SulfurBase. sulfurBasis variable) level. The sulfur basis is always 30 ppm – even 

for model year groups which use 90 ppm Sulfur as the baseline. A 90 ppm sulfur base 

fuel will not have a SulfShortAdj that is equal to 0.0. 

sulfShortTarget = EXP(sulfurCoeff*LN(sulfur)) Eq 5-1a 

sulfShort30 = EXP(sulfurCoeff*LN(sulfurBasis)) Eq 5-1b 

The Short Term Sulfur effects for Tier1 vehicles (i.e. model years 1994-2000} ) 

use a log-linear algorithm as in equations 5-2a and 5-2b. Again the base fuel sulfur is 30 

ppm. High emitters may use a different equational form (i.e, log-log) in some cases. The 

“Sulfur Model Coefficients.xls” workbook in the variable SulfurFunctionID shows which 

form of the equation is used. 

sulfShortTarget = EXP(sulfurCoeff*(sulfur)) Eq 5-2a 

sulfShort30 = EXP(sulfurCoeff*(sulfurBasis)) Eq 5-2b 

The Short term sulfur effect (SulfAdj) for all groups is computed using Eq 5-3. 

SulfShortAdj = (SulfShortTarget – SulfShort30 ) / SulfShort30 Eq 5-3 

5.3 Calculate Long Term Sulfur Effects 

The long term sulfur effects account for sulfur exposure over several thousand 

miles of driving. They values used in MOVES are stored in the sulfurLongCoeff

variable in the MOVES table M6SulfurCoeff. The values for sulfurLongCoeff are a 

function of pollutant. They are: 

HC 2.50 

CO 2.36 

NOx 1.47 

34 
 

 

 

 

 

 

 

 

 

 

 

 

 

These effects are multiplied by the short term sulfur effects calculated above in

Eq 5-3 to produce the variable sulfAdj2. Sulfur levels of 30 ppm or less are assumed to 

have no Long Term effects. 

sulfAdj2 = SulfShortAdj * sulfurLongCoeff Eq 5-4 

5.4 Calculation of the Sulfur Irreversibility Effects 

In this step, the average emission effects of sulfur which cannot be reversed if 

exposure is recorded are computed. They apply to only Tier2 (2004+ model years

vehicles only), and apply only to Target fuel sulfur levels which are greater than 30 ppm

sulfur. Fuel sulfur levels less than or equal to 30 ppm do not cause such effects to occur. 

The same effects are applied to all three pollutants (HC, CO and NOx) and processes

(start and running). The SulfurCap is a function of model year group. 

Model Year Group SulfurCap 

2004 – 2005 303 ppm sulfur 

2006 – 2007 87 ppm sulfur 

2008 + 80 ppm sulfur 

If the fuel sulfur level is greater than 30 ppm but less than the SulfurCap, 

Equation 5-5a is used to compute the SulfIRR effects, and the effect is applied as a

function of model year group. 

If sulfur < sulfurCap 

SulfIRR = EXP (sulfurCoeff * LN(sulfurCap)) Eq 5-5a 

Eq5-5b computes the sulfur irreversibility effects if the selected sulfur level is

greater than the maximum sulfur level. Sulfur levels above the SulfurCap are not

expected in normal use of the MOVES model. 

If sulfur > sulfurCap 

SulfIRR = EXP (sulfurCoeff * LN(sulfur)) Eq 5-5b 

35 
 

 

 

 

 

 

 

 

 

5.5 Putting the Short, Long and Irreversibility Sulfur Effects Together 

Equation 5-7 puts all of the sulfur effects together into the final fuel sulfur effects. 

It is labeled as sulfAdj3. This variable contains the short term, long term and irreversible 

effects together. Equation Eq5-6 calculates the intermediate sulfMax variable. 

sulfMax = (SulfIRR – sulfShort30) / sulfShort30 Eq 5-6 

Where 

SulfIRR is from Eq 5-5a or Eq 5-5b.

sulfShort30 is from Eq5-1b or Eq5-2b 

sulfAdj3 = 1.0 + [ IRFactor * sulfMax + (1.0-IRFactor) * sulfAdj2 ] Eq 5-7 

Where 

sulfAdj2 is the result of Eq5-4 

IRFactor is equal to 0.425. 

To prevent the log-log based sulfur corrections from rapidly approaching zero as

the sulfur levels approach zero, the following limit is placed. 

sulfAdj3 = 0.85 Where sulfAdj3 <= 0.85 Eq 5-8 

5.6 Sulfur GPA Effects 

During the years 2004-2006, gasoline sulfur levels in the Sulfur “Geographical

Phase-In Area” (Sulfur GPA) were allowed to be higher than elsewhere in the nation.

MOVES accounts for this with the Sulfur GPA Effects. The algorithm applies a

maximum sulfur exposure of 330 ppm sulfur to areas that are GPA areas. The GPA areas 

are mostly Rocky Mountain areas and are identified in the county table ofthe 

MOVES2010 database. 

In this step (Eq 5-9) the sulfurGPA effects are calculated for both Normal and 

High emitter groups. Sulfur GPA is only applied to model years 2004, 2005 and 2006, 

and for fuel sulfur levels which are greater than 30 ppm sulfur. It is also limited to GPA 

areas, and is a sulfur phase-out strategy. In all other cases GPAsulfAdj is equal to the

regular sulfur adjustment, and no additional GPA effect is applied in the MOVES model. 

SulfurGPA uses the same basic algorithm as the regular sulfur adjustment, except the 

variable SulfurBase. The sulfurGPAMax (330 ppm sulfur) is substituted in the equation 

in place of the actual sulfur level of the fuel to be evaluated. The value of 330 ppm is a 

typical worse case GPA scenario sulfur level. 

36 
 

 

 

 

 

 

 

 

 

 

 

 

 

sulfGPA1 = EXP ( sulfurCoeff * LN(sulfurGPAMax) ) Eq 5-9 

SulfGPA = (sulfGPA1 – sulfShort30) / sulfShort30 Eq 5-10a 

For NOx High emitters the numerator (sulfGPA1 and sulfShort30) is multiplied by 0.60. 

sulfGPA = SulfGPA * sulfurLongCoeff Eq 5-10b 

GPASulfadj = 1.0 + [ IRFactor * sulfGPA + (1.0-IRFactor) * sulfAdj2 ] Eq 5-11a 

Where 

sulfAdj2 is the product of Eq5-4 

IRFactor is equal to 0.425. 

In non GPA years, or in areas where sulfur < 30 ppm, Eq 5-11b is used. It is also 

used in cases if the sulfur level is greater than sulfurGPAMax (i.e., 330 ppm. As a 

general rule, the GPASulfadj can NEVER be smaller than sulfAdj3, and the two are equal

most of the time. 

GPASulfadj = sulfAdj3 Eq 5-11b 

The GPASulfadj is applied in the model by weighting it by the fraction of GPA is a

particular county. In the default cases, this fraction is always zero or one. However, GPA 

fraction is a user input, so alternative values between zero and one may be entered as

inputs. 

Final Sulfur Adj = SulfAdj3 * (1-GPAFraction) + GPASulfadj * GPAFraction Eq 5-12 

5.7 Normal and High Emitter Correction Factor Weighting 

As discussed in general in Section 5.0, the M6Sulf algorithm produces a sulfur

correction for both “Normal” and “High” emitters. Since MOVES does not define vehicles 

as “Normal” and “High” emitters in terms of emissions rates, the sets of model coefficients

were regarded as independent models and equaled weighted for consistency with the

MOBILE6 model. The variable wtHigh is set equal to 0.50. 

37 
 

 

 

 

 

 

 

 

sulfAdj3(Target) = (1-wtHigh)*sulfAdj3(normal) + wtHigh*sulfAdj3(high) Eq 5-13a 

sulfAdj3(Base) = (1-wtHigh)*sulfAdj3(normal) + wtHigh*sulfAdj3(high) Eq 5-13b 

Likewise, a composite of normal and high emitter GPAsulf adjustments are

calculated using the same wtHigh factors. 

GPAsulfAdj3(Target) = (1-wtHigh)* GPASulfadj (normal) + wtHigh* GPASulfadj (high) Eq 5-14a 

GPAsulfAdj3(Base) = (1-wtHigh)* GPASulfadj (normal) + wtHigh* GPASulfadj (high) Eq 5-14b 

5.9 Computing the Sulfur Adjustment for the Base Fuels. 

Sections 5-2 through 5-7 must be repeated and applied for the two base fuels of 90 

ppm sulfur and 30 ppm sulfur corresponding to the two model year groups (1960-2000 and 

2001-2050), respectively. This is because the final sulfur fuel adjustment (see Eq 5-15)

factor is the ratio of the Target fuel adjustment and its Base fuel adjustment. The M6Sulf 

model calculations for the Base fuel are exactly the same as those presented in the sections

above and are not repeated here. All other properties of these fuels are held constant for 

the sulfur correction. The Final fuel sulfur correction for the 30 ppm case is one because 

the base fuel of 30 ppm sulfur is equal to the 30 ppm sulfur basis. The 30 ppm sulfur level 

is called the basis (i.e., sulfShort30 variable) because the entire MOBILE6.2 Fuel Sulfur

algorithm was developed based on this level. The calculation result is not one for the 90 

ppm base sulfur. 

FinalSulfAdj = sulfAdj3(Target) / sulfAdj3(Base) Eq 5-15 

Where sulfAdj3 is the sulfur adjustment from Sections 5.2 through 5.8 and the

sulfAdj3(base) is the sulfur adjustment for either the 30 ppm or 90 ppm sulfur base (or

reference) cases. 

The calculation is similar for the GPA case (Eq 5-16). 

FinalGPASulfAdj = GPASulfadj (Target) / GPASulfadj(Base) Eq 5-16 

38 
 

 

 

 

6.0 Combining the Predictive and Complex Model with the Sulfur 

Model 

This section describes how the fuel adjustment factors generated by the Predictive 

and Complex model without sulfur effects are combined with the fuel adjustment factors

generated by the M6Sulf model in Section 5.0. This combination is done only for 

pollutants HC, CO and NOx. The air toxic pollutants do not use the M6Sulf model (i.e., 

the air toxics CM model contains sulfur effects). 

Since all three of these models produce multiplicative correction factors the final 

combination of the two factors is multiplicative. The general equation is shown in Eq 6-

1. 

MOVES Fuel Adjustment = Non Sulfur Fuel Adjustment * M6Sulf Adjustment Eq 6-1 

6.1 Overall Fuel Adjustment for Model Year 1960 through 1974 Vehicles. 

In the case of all 1960 through 1974 vehicles, the Overall Fuel Adjustment is set 

to one. This was done because little or no data are available for these model years and 

most of the vehicles do not contain a catalytic converter or modern electronic fuel /

engine management components which would be sensitive to changes in fuel 

composition. 

FuelAdjustment = 1.0 Eq 6-2 

6.2 Overall Fuel Adjustment for Model Year 1975 through 2003 Vehicles. 

The Overall Fuel Adjustment for HC, CO and NOx pollutants for 1975 through 

2003 model year vehicles is the product of the final fuel adjustments calculated with the

Complex or Predictive models (i.e., COFuelEffectNoSulfur or Fuel Correction (Eq 4-8a), 

and the FinalSulfAdj calculated in the M5Sulf model. 

FuelAdjustment = finalSulfAdj * RatioNoSulfur Eq 6-3 

Where 

Model Year >= 1975 and Model Year <= 2003 and Pollutant in (HC, NOx) or

Model Year >= 1975 and Pollutant in (CO) 

39 
 

 

 

 

6.3 Overall Fuel Adjustment for Model Year 2004 and Later Vehicles. 

The Overall Fuel Adjustment for HC and NOx pollutants for model year 2004 and 

later model year vehicles is the Final Sulfur Adjustment computed by the M6Sulf model. It 

contains only fuel sulfur effects. 

FuelAdjustment = finalSulfAdj Eq 6-4 

Where 

Model Year >=2004 and Pollutant in (HC, NOx) 

6.4 Overall fuelAdjustmentGPA for Model Years 2004 Through 2006 

In this step the fuelAdjustmentGPA is set to the final value for use in the MOVES. 

fuelAdjustmentGPA = FinalGPASulfAdj Eq 6-5 

Where 

Modelyear in (2004, 2005, 2006) and finalGPASulfAdj < 1.0; 

fuelAdjustmentGPA = fuelAdjustment Eq 6-6 

for all other cases 

40 
 

 

 

 

 

7.0 Biodiesel Fuel Effects
 

The Draft MOVES2009 version released in April 2009 contains diesel fuel

parameters and emission effects only for diesel fuel sulfur level (ppm sulfur in the fuel).

This parameter is used in a fuel-sulfur mass balance equation to calculate sulfate PM

emission levels, and was expanded in MOVES2010 to include gaseous SO2 emissions. 

The fuel sulfur mass balance methodology was taken from EPA PART5 / MOBILE6.2 

model and is fully documented in the MOBILE6.2 documentation. See the link: 

http://www.epa.gov/oms/models/mobile6/m6tech.htm 

New sulfate (SO4) and sulfur dioxide (SO2) emission factors were also developed 

for MOVES2010a for gasoline vehicles. The data were obtained from a set of about 30 

vehicles in the EPA Kansas City test program in which both fuel sulfur measurements

and SO4 particulate measurements were made. See the document “Development of 

Gasoline and Diesel Vehicle Sulfate and Sulfur Dioxide Emissions for the MOVES 

Model”. The sulfate and sulfur dioxide emissions for diesels and pre-1980 gasoline

model years were unchanged from MOBILE6.2 

MOVES2010 contains an additional parameter called BioDieselEsterVolume. It 

represents the percentage of biodiesel ester by volume in a Target fuel. Currently all 

entries in the default fuel supply for MOVES2010 are NULL and the model performs no 

biodiesel calculations. However, users could enter local information about biodiesel 

fuels. 

Mathematically, the BioDieselEsterVolume variable is used with the BioDiesel 

Fuel Adjustment Factors (presented in Table 7-1). Together these two parameters

produce an overall diesel Fuel Adjustment factor for biodiesel fuels. These fuel 

adjustment factors (shown as percentages) give the relative increase or decrease in

emissions as the result of adding biodiesel to standard on-road diesel fuel. The equation 

for calculating the BioDiesel adjustment factor is shown in Eq 7-1. Analogous to the

gasoline fuel adjustment, the BioDiesel factor gets multiplied by the base emission rate of

standard diesel vehicles. 

FuelAdjustment factor = 1.0 + (BiodieselEsterVolume/100.0) * BioDieselFactor Eq 7-1 

The Biodiesel Fuel Adjustment factors are shown in Table 7-1. 

41 
Table 7-1 

Biodiesel Fuel Adjustment Factors as a Function of Pollutant 

Pollutant Name BioDiesel Factor 

HC -14.1 

CO -13.8 

NOx 2.2 

PM2.5 and PM10.0 -15.6 

Benzene -14.1 

1,3 Butadiene -14.1 

Acetaldehyde -14.1 

Formaldehyde -14.1 

Naphthalene -15.6 

Acrolein -14.1 

The individual pollutant impacts of biodiesel (B20) listed in Table 7-1 are relative 

to conventional diesel fuel. For example, the -14.1 factor for HC would reduce the 

hydrocarbon emissions from a standard diesel fuel by 14.1 percent. The biodiesel factors 

were based on very limited EPA testing of such fuels. See the link below. 

http://www.arb.ca.gov/fuels/diesel/altdiesel/100519BiodieselWorkshopPresB&W.pdf 

No data were available on air toxic pollutants tested on biodiesel fuels. 

Consequently, biodiesel will use the same air toxic / VOC ratios as are used in the 

computation of emissions from vehicle operating on ordinary diesel fuels (see Section 

8.0). 

42 
 

 

 

 

 

 

 

 

 

 

 

8.0 Toxic Emissions from Diesel Vehicles 

The toxics ratios in MOVES2010 for diesel vehicles were developed well over 10 

years ago, and were used in MOBILE6.2.14 These ratios are provided in Table 8-1. 

More extensive data are now available, including recent test data on diesel engines

meeting 2007 heavy-duty emission standards.15,16 EPA intends to update the equations

and the methodology in MOVES using these data, and release the updated version at a 

later date. Whereas MOBILE6.2 had separate ratios for light-duty diesel vehicles and

trucks based on very limited data, MOVES2010a applies the same ratios to all diesel 

vehicles, heavy and light-duty. 

Table 8-1 

Toxics Ratios for Diesel Vehicles 

Pollutant Ratio Type Ratio 

Benzene VOC 0.0108 

Formaldehyde VOC 0.0807 

Acetaldehyde VOC 0.0298 

Acrolein VOC 0.0036 

Naphthalene PM10 0.001289 

The air toxic pollutants for diesels are computed using equations 8-1 and 8-2. 

The equations are completely analogous to the simple equations used for gasoline

vehicles (see Eq 2-1). 

AT Emission (g/hr) = AT Ratio * VOC Emission (g/hr) Eq 8-1 

AT Emission (g/hr) = AT Ratio * PM10 Emission (g/hr) Eq 8-2 

14 Cook, R., and E. L. Glover. 2002. Technical Description of the Toxics Module for MOBILE6.2 and 

Guidance on Its Use for Emission Inventory Preparation. Assessment and Standards Division, Office of 

Transportation and Air Quality, Ann Arbor, MI. Report No. EPA420-R-02-011. 

http://www.epa.gov/otaq/m6.htm 

15 Hsu ,Y., and Mullen, M. 2007. Compilation of Diesel Emissions Speciation Data. Prepared by E. H. 

Pechan and Associates for the Coordinating Research Council. CRC Contract No. E-75, October, 2007. 

Available at www.crcao.org. 

16 Khalek, I., Bougher, T., and Merritt, P. M. 2009. Phase 1 of the Advanced Collaborative Emissions 

Study. Prepared by Southwest Research Institute for the Coordinating Research Council and the Health 

Effects Institute, June 2009. Available at www.crcao.org. 

43 
 

 

 

 

 

 

 

 

Hydrocarbon Speciation Factors 

Table 8-1 shows a simple relationship between the various hydrocarbon species in 

MOVES, and their relationship to the base, total hydrocarbons (THC). As the table 

shows the individual hydrocarbon species differ based on the presence or absence of the

hydrocarbon compounds of methane, ethane and aldehydes. The term FID HC refers to 

the total hydrocarbons detected by a Flame Ionization Detector (FID) instrument. 

All factors used in MOVES were taken from MOBILE6.2 materials and were 

originally produced in 1991. No new speciation factors were developed for 

MOVES2010a. 

Table 8-1 

Hydrocarbon Speciation Types 

PollutantID PollutantName FID HC Methane Ethane Aldehydes 

1 

Total 

Hydrocarbons Yes Yes Yes No 

79 

Non Methane 

Hydrocarbons Yes No Yes No 

87 

Volatile Organic

Compounds Yes No No Yes 

86 

Total Organic 

Gases Yes Yes Yes Yes 

80 

Non Methane 

Organic Gases Yes No Yes Yes 

8.1 Non Methane Hydrocarbon Factors 

The MOVES model calculates non-methane hydrocarbons (NMHC). The 

MOVES model computes this hydrocarbon species by first independently calculating

THC emissions and methane emissions. 

(see http://nsdi.epa.gov/otaq/models/ngm/420p05003.pdf) . 

As a result of this dependence, NMHC is ‘chained’ to both THC and methane. 

The NMHC calculator subtracts the resulting methane emissions from the THC emissions

(mechanically in MOVES it multiples methane by negative one and adds the result). If a 

negative emission value for NMHC is calculated, it is set to zero. The formula for 

calculating NMHC is shown in Eq 8-1. This formula is used only for gasoline fuels 

NMHC = THC - Methane Eq 8-1 

44 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

8.2 VOC Speciation Calculation 

The MOVES model calculates Volatile Organic Compounds (VOC). VOC is 

calculated from NMHC using Eq 8-2a through 8-2d and the variables

‘speciationConstant’ and ‘oxySpeciation’ coefficients. The variable 

‘volToWtPercentOxy’ is a standard chemical conversion to converts percent oxygen in 

the fuel from a volume basis to a weight basis for variety of oxygenated fuels. 

Consequently, all of the standard MOVES fuel inputs for oxygenate (i.e., ETOHVolume, 

MTBEVolume, etc) are in terms of a percentage of oxygen by fuel volume. 

For fuels containing ethanol 

VOC = NMHC * 

(speciationConstant + oxySpeciation* volToWtPercentOxy*ETOHVolume) Eq 8-2a 

For fuels containing MTBE 

VOC = NMHC * 

(speciationConstant + oxySpeciation* volToWtPercentOxy*MTBEVolume) Eq 8-2b 

For fuels containing ETBE 

VOC = NMHC * 

(speciationConstant + oxySpeciation* volToWtPercentOxy*ETBEVolume) Eq 8-2c 

For fuels containing TAME 

VOC = NMHC * 

(speciationConstant + oxySpeciation* volToWtPercentOxy*TAMEVolume) Eq 8-2d
 

For pure gasoline fuels the second term drops off and only the speciationConstant

is applicable. The speciationConstant is a function of fuel model year group. The 

variable volToWtPercentOxy is a function of oxygenate type. The values for each 

oxygenate type are: 

Ethanol 0.3488 

MTBE 0.1786 

ETBE 0.1533 

TAME 0.1636 

The general equation for volToWtPercentOxy in MOVES is equation 8-3e. 

volToWtPercentOxy = 

(ETOHVolume * 0.3488 + MTBEVolume * 0.1786 + ETBEVolume * 0.1533 +TAMEVolume * 0.1636) 

/ (ETOHVolume+MTBEVolume+ETBEVolume+TAMEVolume) Eq 8-3e 

45 
 

 

 

 

 

 

 

 

 

 

 

 

8.3 NMOG Speciation Calculation 

The MOVES model calculates Non Methane Organic Gases (NMOG). NMOG 

is calculated from NMHC using Eq 8-3a through 8-3d and the variables

‘speciationConstant’ and ‘oxySpeciation’ coefficients. The values for the variable 

volToWtPercentOxy are provided in Section 8.2. 

For fuels containing ethanol 

NMOG = NMHC *
 

(speciationConstant + oxySpeciation* volToWtPercentOxy*ETOHVolume) Eq 8-3a
 

For fuels containing MTBE 

NMOG = NMHC *
 

(speciationConstant + oxySpeciation* volToWtPercentOxy*MTBEVolume) Eq 8-3b
 

For fuels containing ETBE 

NMOG = NMHC *
 

(speciationConstant + oxySpeciation* volToWtPercentOxy*ETBEVolume) Eq 8-3c
 

For fuels containing TAME 

NMOG = NMHC *
 

(speciationConstant + oxySpeciation* volToWtPercentOxy*TAMEVolume) Eq 8-3d
 

For pure gasoline fuels the second term drops off and only the speciationConstant

is applicable. The speciationConstant is a function of fuel model year group. 

8.4 TOG Speciation Calculation 

The MOVES model calculates Total Organic Gases (TOG). These are calculated 

by calculating both the NMOG emissions and the methane emissions in their respective 

calculators. TOG is depend (i.e., chained) to both NMOG and methane. The TOG 

calculator in Equation 8-4 simply adds the resulting methane emissions to the NMOG 

emissions. 

TOG = NMOG + Methane Eq 8-4 

46 
 

 

 

9.0 Fuel Formulation and Fuel Supply in MOVES2010 

9.1 Introduction 

The MOVES2010 model contains about 10,000 default fuel formulations and 

default market share values. The large number of fuel formulations reflects a 

combination of ten different fuel parameters, and the need to supply a default fuel 

formulation for each combination of U.S. county, month and fuel year. Each fuel 

formulation describes a unique set of fuel properties. 

In MOVES, the fuel models (i.e., complex, predictive, sulfur, etc) are applied to 

each fuel formulation selected by the user. The user selects at least one fuel formulation 

for each county, calendar year, month and fuel type (i.e., gas or diesel) combination they 

wish to model. Some combinations have two or more fuel formulations which represent 

a blend of fuels during that time and in that area. The individual market share values 

represent the distribution of fuel formulations within a county, calendar year, month and 

fuel type combination, and must sum to unity within the combination. 

9.2 Data Sources 

The fuel supply and fuel formulation data in the MOVES2010 model was 

assembled from several sources as part of the EPA National Emission Inventory (NEI) 

development process. The process of assembling these data for the MOVES model 

consisted of a detailed analysis which is described in the references listed in Section 9.4. 

It consisted of a fairly complicated data review and analysis process that utilized several 

sources, and will not be repeated here. The following sources of fuel supply and fuel 

property data for MOVES are: 

o EPA fuel survey data from RFG areas 

o Vehicle manufacturer fuel surveys 

o Other commercial fuel surveys 

o Proprietary Refinery modeling results 

o State supplied fuel data 

The EPA fuel survey data from RFG areas is an important data source for in-use 

fuel property information, and market share data of specific fuels. It is an annual survey 

done in RFG areas. Unfortunately, it is limited to RFG areas, and often is limited to just 

a single county in the area. Another shortcoming is that EPA has only analyzed and 

incorporated surveys from the 2005 and earlier calendar years. Vehicle manufacturer and 

other commercial fuel surveys were also incorporated into the database, or used to 

confirm existing data whenever possible. The proprietary refinery modeling results were 

a very important source of information and allowed EPA to model areas which did not 

have fuel surveys. This data-source frequently had refinery, pipeline and other 

distribution system volume data on particular fuel formulations and individual fuel 

parameters such as the volume of ethanol or the concentration of sulfur in the fuel flow. 

The pipeline fuel flow data could be distributed according to vehicle miles traveled 

47 
 

 

 

 

 

 

 

 

(VMT) through the fuel distribution system so as to produce more complete fuel 

information on counties that did not have a fuel survey. State data on fuel properties and 

fuel supplies were also obtained and used where possible. In most cases, individual states 

do not have complete or detailed data on their fuel supplies. 

9.3 Analysis Process Overview 

An analysis process was used to assemble the MOVES fuel supply and fuel 

formulation tables for use in the model. For calendar years 1990, 1999, 2002 and 2005 

historical fuel data were collected and processed, and used in the National Emission 

Inventory (NEI) process. These data were generally ‘clean’ and easily processed into the 

required format for MOVES. Analogous tables for calendar years 2000, 2001, 2003 and 

2004 were generated by interpolating the primary dataset. 

Calendar years 2005 and 2012 are the key years for fuel property definition. 

After 2012, the fuel properties and supplies become constant. The data for calendar years 

2005 are from the 2005 NEI and the data (projections) for 2012 are from refinery 

modeling done for the RFS rulemaking. The 2012 calendar year data are projections 

which start with the 2005 fuels and project the 2012 fuels based on ethanol volume 

increases, benzene controls, MTBE phase-out and RVP waiver for ethanol blends. The 

impact of future fuel regulations is a major factor in these projections. Fuel data for all 

intervening years between 2005 and 2012 are interpolations between these two years. 

Local fuel regulations and local fuel data, where available, were also incorporated in the 

analysis for each of the counties and calendar years. 

The fuel data is often only by season with winter – summer blends and one or two 

shoulder seasons. As a result, the data are further processed to allow it to be on a 

monthly basis. Frequently, in MOVES2010a, this processing consists of merely copying 

it into the monthly database entries. Within a given season, the fuel formulations often 

do not vary by month. 

9.4 References 

9.4.1	 1999 NEI report that includes description of how the fuels were developed "DOCUMENTATION FOR THE 

ONROAD NATIONAL EMISSIONS INVENTORY (NEI) FOR BASE YEARS 1970-2002" 

ftp://ftp.epa.gov/EmisInventory/finalnei99ver3/haps/documentation/onroad/nei_onroad_jan04.pdf 

9.4.2	 Updated 2002 report, "DOCUMENTATION FOR THE FINAL 2002 MOBILE NATIONAL EMISSIONS 

INVENTORY, VERSION 3" 

ftp://ftp.epa.gov/EmisInventory/2002finalnei/documentation/mobile/2002_mobile_nei_version_3_report_09280.pdf 

9.4.3	 Updated 2005 report, "DOCUMENTATION FOR THE 2005 MOBILE NATIONAL EMISSIONS INVENTORY, 

VERSION 2" 

ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile/2005_mobile_nei_version_2_report.pdf 

9.4.4	 EPA RFG fuel survey data: 

http://www.epa.gov/otaq/regs/fuels/rfg/properf/rfgperf.htm 

9.4.5	 RFS1 Regulatory Impact Assessment document "Draft Regulatory Impact Analysis: Changes to Renewable 

Fuel Standard Program" 

http://www.epa.gov/otaq/renewablefuels/420d09001.pdf 

48 
 

 

 

 

 

 

 

 

 

 

 

 

10.0 Results 

This section contains some limited emission results based on the algorithms in the

Predictive, Complex and MOBILE6 Sulfur Models. These results were obtained by

running the MOVES model and charting the emission results. Results are shown for the 

criteria pollutants and the major air toxic compounds. The results are limited in that they

are shown only for areas of the MOVES model that have received substantial changes

from previous versions. They are also limited because they model the base fuel and vary

only one fuel parameter at a time over its range. For example, in the sulfur effects chart,

fuel sulfur is varied from 4 ppm to 500 ppm and the remaining fuel parameters are kept

constant at the Base Fuel level. The reader who is interested in a complete set of emission

results for all combinations of fuel parameters, particularly the air toxic pollutants, should 

consult the primary reference documents for the Complex, Predictive and MOBILE6.2 

models. 

10.1 Sulfur Effects in MOVES2010a 

The emission effect of fuel sulfur is shown in Figures 10-1 through 10-3 for the

2001+, 1996 and 1988 model years, respectively. The effects are ‘net fuel effects’ from 

the MOVES model. They were produced by seven separate MOVES runs using a 

constant fuel formulation and varying the fuel sulfur level from 4 ppm sulfur to 500 ppm

sulfur. In each chart, separate curves are shown for THC, CO and NOx. The oldest 

model year represents the fuel effects on Tier0 vehicles, the middle model year group 

represents the Tier1 and LEV standards, and the 2001+ model year represents the newer

vehicles. In all charts the fuel effects are normalized to 90 ppm sulfur for the 1988 and 

1996 model year curve and to 30 ppm sulfur for the 2001+ model year curve. In this 

context, ‘normalization’ means the correction factor is set to one. The other fuel 

parameters were set at Base Fuel levels (6.9 psi RVP, 0% Ethanol volume, 26.1%

aromatic content, 5.6% olefin content, 1.0% benzene content, 218F T50 and 329 F T90. 

Examination of the three figures shows the strongest correlation is for NOx

emissions and for the 2001+ model year group. This result is not unexpected because it

is this group for which a log-log relationship between emissions and fuel sulfur was

found. This relationship is strongly non-linear and produces a relative correction of about

0.15 for an ultra low 2 ppm sulfur fuel and a relative correction of about 3.0 for a 500 

ppm high sulfur fuel (actual in-use fuel sulfur levels are not expected to vary that widely). 

For the HC and CO pollutants, the sensitivity to fuel sulfur is less for the 2001+ MY

model year group than it is for NOx. The other model year groups mostly utilize loglinear relationships between emissions and fuel sulfur. This leads to fuel sulfur emission 

effects which are less sensitive to sulfur than the Tier2 group. 

In the MOVES2010a model, the 2001+ model year group is the latest model year

group, but is based only on data from pre-tier2 (i.e., 2003 and earlier model years)

vehicles. Subsequent versions of MOVES (to be released at a later date) will utilize these 

curves for the 2001 through 2003 model years, but will apply new curves for 2004 and 

later model years based on a new set of vehicle fuel sulfur testing and EPAct testing.

Preliminary results from the analysis of the new data suggests a much stronger 

49 
 

relationship at low sulfur levels between fuel sulfur and HC and NOx emissions than is

used in MOVES2010a. 

No air toxic charts are shown because the air toxic / VOC ratio is not a function of fuel

sulfur level in the Complex model. 

Figure 10-1	 Relative Fuel Sulfur Effect on 2008 Model Year Gasoline Vehicles in 

MOVES 

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

0 100 200 300 400 500 600

Multiplicative Fuel Adjustment 

Fuel Sulfur Content (ppm Sulfur) 

Sulfur Fuel Effect 

2001+ MY - gasoline vehicles 

VOC

CO

NOx

50 
 

Figure 10-2 Relative Fuel Sulfur Effect on 1996 Model Year Gasoline Vehicles in 

MOVES 

Relative Fuel Sulfur Effect on 1996 Model Year Gasoline Vehicles 

(90 ppm Sulfur = 1.0) 

2.5 

2.0 

1.5 

1.0 

0.5 

0.0 

Fuel Adjustment

0 100 200 300 400 500 600
 

Sulfur Level (ppm)
 

THC 

CO 

NOx 

51 
 

Figure 10-3 Relative Fuel Sulfur Effect on 1988 Model Year Gasoline Vehicles in 

MOVES 

Relative Fuel Sulfur Effect on 1988 Model Year Gasoline Vehicles 

(90 ppm Sulfur = 1.0) 

0 100 200 300 400 500 600
 

Sulfur Level (ppm)
 

0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

1.2 

1.4 

Fuel Adjustment

THC 

CO 

NOx 

52 
 

 

 

 

 

 

 

10.2 Fuel Ethanol Adjustment Factors in MOVES2010 

The emission effects of fuel ethanol are shown in Figure 10-4 for model year 

2003. Charts for other model years are not shown, because the results are similar for the 

pre-1994 model years (they differ only slightly for CO) and are identical for the 1995-

through-2002 model years. There are currently no ethanol fuel effects for 2004-and-later

model years in MOVES2010a (only sulfur fuel effects). Other fuel oxygenate types such

as MTBE or ETBE produce the same relative results when the oxygenate volumes are 

identical. The other fuel parameters were set at Base Fuel levels (6.9 psi RVP, 30 ppm

sulfur level, 26.1% aromatic content, 5.6% olefin content, 1.0% benzene content, 218F 

T50 and 329 F T90. 

The effects shown in the chart are ‘net fuel effects’ from the MOVES model. 

They were produced with three separate MOVES runs using a constant fuel formulation 

and varying the fuel ethanol level from 0 percent to 15 percent by volume. In each chart, 

separate curves are shown for THC, CO and NOx. In all curves the fuel effects are 

normalized to 10 percent volume ethanol. In this context, ‘normalization’ means the 

correction factor is set to unity with the ethanol volume is 10 percent. 

Overall, the results are as expected with only small changes in THC emissions,

moderate reductions in CO emissions, and NOx emission increases from the use of 

ethanol. For HC and NOx, there is about a five percent increase from zero ethanol to 10 

percent ethanol. Carbon monoxide emissions show approximately a 15 decrease from

zero ethanol to 10 percent ethanol. This is likely due to the extra oxygen introduced by

ethanol into the combustion and exhaust process that oxidizes the carbon monoxide to 

carbon dioxide. In MOVES2010a, there are no fuel effects on particulate matter (PM) 

emissions. 

Figure 10-4	 Relative Fuel Ethanol Effect on Pre-2004 Model Year Gasoline Vehicles 

in MOVES 

0.8

0.85

0.9

0.95

1

1.05

1.1

1.15

1.2

0 2 4 6 8 10 12 14 16

Multiplicative Fuel Effect (E10 = 1)

Fuel Ethanol Volume (%) 

Ethanol Fuel Effect 

pre-tier2 - gasoline vehicles 

VOC

CO

NOx

Benzene

PM

53 
 

 

 

 

 

 

Figure 10-5 Relative Fuel Ethanol Effect on Pre-2004 Model Year Gasoline Vehicles 

in MOVES 

Ethanol Fuel Effect
 

pre-tier2 - gasoline vehicles
 

Multiplicative Fuel Effect (E10 = 1)

1.8

1.6

1.4

1.2

1

0.8

0.6

0.4

0.2

0

0 5 10 15 20

Ethanol

Acetaldehyde

Figure 10-5 shows the relationship between fuel ethanol and exhaust ethanol and 

acetaldehyde emissions. These are shown on a separate figure because the fuel effects

range from zero to almost a factor of two for these two air toxic pollutants. Both these 

curves show a strong and predictable response to fuel ethanol from 0 to 10 percent

ethanol. 

Figures 10-4 and 10-5 show a maximum value of 15 percent. However, users 

should not attempt to model higher ethanol inputs such as 15 percent ethanol (E15) or 85 

percent ethanol (E85) with MOVES2010a. For ethanol values greater than 10 percent, 

the relationships in MOVES2010a are pure extrapolation. Future versions of MOVES 

will show updated relationships based on recent vehicle testing, rather than mathematical

extrapolations. 

10.3 Benzene Adjustment Factors in MOVES2010a 

The emission effects of fuel benzene are shown in Figure 10-6 for model year 

2003. Charts for other model years are not shown, because the results are similar. Fuel 

benzene levels affect only exhaust and evaporative (not shown) benzene emissions. 

Figure 10-6 shows the relative effect of fuel benzene on benzene exhaust emissions with 

a relative effect of unity assigned to a fuel benzene level of one percent. The effect is 

positive and generally linear over the range of fuel benzene in use. 

Fuel Ethanol Volume (%) 

54 
Figure 10-6 Relative Fuel Benzene Effect on Pre-2004 Model Year Gasoline Vehicles 

in MOVES 

Benzene Fuel Effect
 

pre-tier2 - gasoline vehicles
 

Fuel Effect (Benzene 1.0% = 1.0) 

1.6

1.4

1.2

1

0.8

0.6

0.4

0.2

0

0 0.5 1 1.5 2 2.5 3

Fuel Benzene Content (volume %) 

Benzene

55 
 

 

10.4 Olefin Adjustment Factors in MOVES2010a 

Figure 10-7 shows the relative effect on pre-2004 model year gasoline vehicles to 

fuel olefin levels. The relative effect of unity is assigned to a fuel olefin level of 5.6%

because that is the olefin level of the MOVES2010a reference fuel. Only pollutants VOC 

and 1,3-butadiene are affected by fuel olefin levels. The VOC response is slightly

negative, but the 1,3-butadiene response is positive and quite significant over the range of

olefin levels in use. The other fuel parameters were set at Base Fuel levels (6.9 psi RVP,

30 ppm sulfur level, 0% Ethanol volume, 26.1% aromatic content, 1.0% benzene content, 

218F T50 and 329 F T90. 

Figure 10-7	 Relative Fuel Olefin Effect on Pre-2004 Model Year Gasoline Vehicles in 

MOVES 

Olefin Fuel Effect
 

pre-tier2 - gasoline vehicles
 

Multiplicative Fuel Effect (Olefin

5.6% = 1.0) 

1.4

1.2

1

0.8

0.6

0.4

0.2

0

0 2 4 6

1,3-Butadiene

VOC

8 10 12 14

Fuel Olefin Content (volume %) 

56 
 

 

 

 

10.5 E200 / E300 Adjustment Factors in MOVES2010a 

Figure 10-8 shows the relative effect on pre-2004 model year gasoline vehicles to 

fuel E200 and E300 levels. The relative effect of unity is assigned to a fuel e200 level of

41% and a fuel E300 level of 83% (T50 and T90 are 218F and 329F, respectively)

because those are the levels in the MOVES2010a reference fuel. The parameters E200

and E300 are measures of gasoline volatility, and are shown as a pair in Figure 10-8. In 

this example, both move as a pair either up or down from the 41%/83% reference. Inuse, this relationship between E200 and E300 does not always occur. Also, some of the 

values of E200 and E300 cannot occur in conjunction with the Base Fuel parameters. 

The E200 / E300 domain in Figure 10-8 is the entire range of values in the MOVES fuel

database, and the two points at the end of the curves are extreme values. The other fuel 

parameters were set at Base Fuel levels (6.9 psi RVP, 30 ppm sulfur level, 0% Ethanol

volume, 26.1% aromatic content, 5.6% olefin content and 1.0% benzene content. 

The pollutants VOC and CO are both affected by E200 / E300 and so are most of

the air toxic pollutants. Most of the pollutants increase as E200 / E300 become larger

(i.e., the fuel contains a larger fraction of heavier constituents). The exception is 1,3-

butadiene which shows a negative relationship with E200 / E300. 

Figure 10-8	 Relative Fuel E200 / E300 Effect on Pre-2004 Model Year Gasoline

Vehicles in MOVES 

0.8

0.85

0.9

0.95

1

1.05

1.1

38/78 39.5/81 41/83 50/87 64/92

Fuel Effect (E200:41/E300:83 = 1)

E200 / E300 

E200 / E300 Fuel Effect 

pre-tier2 - gasoline vehicles 

VOC

CO

Benzene

1,3-Butadiene

Formaldehyde

Acetaldehyde

57 
 

 

 

Appendix A Peer Review 

A preliminary draft version of this document was peer reviewed by Professor

Tom Durbin, Ph.D Research Engineer at the University of California, CE-CERT,

Riverside, CA. Many of his comments were addressed in this final version; some 

sections of draft report were removed altogether from the final report. Professor Durbin 

made seventeen distinct comments. These are paraphrased in italics, and addressed 

below. The full text of Professor Durbin’s comments is available in a separate document. 

1.	 The document should have a formal reference section. 

We have added footnotes to the document and plan a references page. Web links are 

inserted throughout the document for important reference documents. 

2.	 Abbreviations should be better defined in the document. 

We agree and have addressed this comment. 

3.	 It would be interesting if the document could tie in the written text with the

Appendices with the code. 

Between the draft that Prof. Durbin reviewed and the release of MOVES2010, much of 

the work that was done outside the model was incorporated in the MOVES code and the

need for the fuel binner was eliminated. For more detail on the MOVES code itself, see 

the MOVES “Software Design Reference Manual” and the “Programmer’s Guide to

MOVES.” 

4.	 Since the values for the fuel formulation table are described in greater detail later

in the document, it might be useful to indicate that these variables will be

discussed in the greater detail in the document. 

Section 9.0 of the document has been added to provide an overview of the fuel

formulation and fuel supply development process. It describes the process of developing

these critical data tables and provides a list of references to the primary documents. 

5.	 There is not a good logical development of the thoughts in Section 2. 

The draft version reviewed by Professor Durbin has been thoroughly revised, and we

hope it contains a clearer description of the Complex model structure. 

6.	 The concept of using the 30 ppm fuel for the 2001 and later model year vehicles

and using the 90 ppm fuel for all 2000 and earlier model years is not very clear. 

Unfortunately, the fuel properties of the vehicle dataset used to develop the basic

emission factors were not measured with any real precision. The value of 30 ppm sulfur

was chosen because is it the standard reference case for most EPA fuel models, and was 

the assumed in-use fuel standard during the latter period of testing Arizona. The value of 

58 
 

 

 

 

 

90 ppm sulfur was a typical value during the beginning of the Arizona test period. The 

value of 90 ppm comes with considerable uncertainty. 

7.	 A slight expansion of the GPA regions would be useful. 

This section has been expanded in the final version. 

8.	 There should be some discussion as to what oxygenate factors are used for

different cases with ethanol, MTBE, and TAME. It might be interesting to include

some statistics in the document about what percent of fuels contained these

various oxygenates. That would provide the reader a good context for the relative

importance of as to how fuel formulations have changed over time. 

We did not provide the statistics, but they could be developed with effort from the

MOVES Fuel Supply and Fuel Formulation tables. In general, the calendar year 2005 

and earlier generally contain modest amounts of MTBE as the primary oxygenate. After 

calendar year 2006, MTBE declines dramatically because of ground water contamination 

concerns and is replaced almost exclusively by Ethanol. TAME and ETBE were never 

major oxygenate sources and rarely achieve more than a five percent market share. In

current years (i.e., 2010+) they are all but gone from the fuel mix. 

9.	 This comment address fuel supplies and the fact that MOVES does not contain 

default fuel supplies past calendar years 2012. 

This topic has been removed in the final draft because it pertains to the detailed fuel

supply data and statistics which are now outside the scope of the document. However, 

the default MOVES only contains fuel supply information through 2012. As this date 

approaches, this limitation will have to be addressed. For current State Implementation 

Plan (SIP) work, users are expected to enter their own fuel supply information for ALL 

years. Once the user supplied data is entered, the model correctly performs all of the fuel

calculations. 

10.	 A mostly editorial comment regarding clarity on E10, E85 and NMIM. 

The topics of E85 and NMIM have been completely removed from the document. 

11.	 A comment regarding at 2022 fuel supply database. 

This topic has been completely removed from the document. 

12.	 An editorial comment on the Predictive model. 

The Predictive model is now built directly into MOVES and is fully documented in 

Section 4.0 

13.	 A comment on High emitters with the question “What information was used to 

come up with the 20% estimate for high emitters”. 

59 
 

 

 

 

 

This assumption has been changed. The new MOVES algorithm now uses the High

emitter fraction from MOBILE6.2 that is a function of age (0 through 30). The 

calculation of High emitters is fully document in the MOBILE6.2 documentation. 

14.	 The assumption that NOx and THC emissions for 1994 and newer vehicles are no 

longer sensitive to the effects of fuel parameters outside of the sulfur is a very

large simplification of the situation. Of the fuel parameters, the addition of

oxygenates / ethanol is one area that would seemingly be fairly critical given that

the levels of ethanol in gasoline will be increasing. He subsequently cites studies 

to boost his argument. 

We agree that the 1994 and later assumption was too much of a simplification and 

changed the assumption to 2004 and later model years. The 2003 and earlier years are

now fully affected by all of the fuel parameters as appropriate for the pollutant. 

15.	 The Fuel Binner code is not in Appendix A. 

MOVES no longer requires fuel binning, so this code is no longer relevant. 

16.	 What is the basis for the EPA belief that Tier2 vehicles are less sensitive to fuel 

properties other than sulfur? 

At the time of this document development, the EPAct vehicle – fuel study had not been 

completed and its results could not be incorporated into the model. Based on very limited 

knowledge of those vehicles, we made the assumption that 2004 and later model years

(i.e., Tier2) vehicles are only sensitive to fuel sulfur in MOVES2010a. 

Since the release of MOVES2010a, the EPAct study and the statistical analysis of the

results have been completed, and these show that Tier2 vehicles are quite sensitive to an 

entire range of fuel properties depending on pollutant. Subsequent versions of MOVES 

will incorporate these new findings. 

17.	 Professor Durbin includes a set of grammatical and editorial comments. 

The document has been restructured and revised to address these comments. 

60