EPA Optimization Model for Reducing 

Emissions of Greenhouse Gases from 

Automobiles (OMEGA) 

Core Model Version 1.4.1 Documentation
 
EPA-420-R-12-024 

August 2012

Assessment and Standards Division 

Office of Transportation and Air Quality 

U.S. Environmental Protection Agency

EPA Optimization Model for Reducing 

Emissions of Greenhouse Gases from 

Automobiles (OMEGA) 

Core Model Version 1.4.1 Documentation
Table of Contents
 

I Background......................................................................................................................................... 3
 

II Model Overview ................................................................................................................................. 3
 

III Input Files ........................................................................................................................................... 7
 

A The Market File: Vehicle Fleet Characterization......................................................................... 7
 

B The Technology File: Technology Package Characterization................................................... 11
 

C The Fuels File: Physical Properties and Prices of Fuel and Energy Sources............................. 13
 

D The Scenario File: Definition of Regulatory Scenarios and Other Economic Parameters ........ 14
 

D.i Universal Target......................................................................................................................... 15
 

D.ii Piece-wise Linear....................................................................................................................... 16
 

D.iii Logistic Curve Target ......................................................................................................... 17
 

E The Reference File: Vehicle Survival Rates and Miles Driven................................................. 20
 

F Non-editable Input Data............................................................................................................. 20
 

G Input Files Currently Distributed with Model ........................................................................... 21
 

IV Model Operation ............................................................................................................................... 22
 

A Calculating Technology Effective Basis (TEBs) and Cost Effective Basis (CEBs) ................. 22
 

B Calculating Other Effectiveness Basis (OEBs).......................................................................... 24
 

C Platform Aggregation................................................................................................................. 24
 

D Technology Application............................................................................................................. 25
 

D.i Determination of Manufacturer-Specific CO2 Emission Standards .......................................... 25
 

D.ii Converting Lifetime Refrigerant Emissions to CO2-Equivalent emissions per Mile ................ 26
 

D.iii Application of Technology - Methodology ........................................................................ 27
 

D.iv Technology Application Ranking Factors .......................................................................... 32
 

D.v Applying Technology - Calculations......................................................................................... 38
 

V Output Files....................................................................................................................................... 40
 

A Summary of Outputs.................................................................................................................. 40
 

A.i Log of Technology Application Steps – Text Format ............................................................... 41
 

A.ii Summary of Cost and Emissions – Excel Format ..................................................................... 45
 

A.iii Summary of Technology Pack Distribution – Text format ................................................ 45
 

A.iv VH1 / Final summary of Vehicle Attributes– Excel Format .............................................. 45
 

A.v VH2 / Stepwise listing of Vehicle Attributes—Excel Format................................................... 45
 

VI Running the Model ........................................................................................................................... 46
 

2
 
I Background 

On-road vehicles are the predominant source of greenhouse gas (GHG) emissions from 

the transportation sector. Of all on-road vehicles, light-duty vehicles and light-duty trucks 

(hereafter referred to as cars and trucks) produce the majority of the GHG emissions. There are 

many methods for reducing GHG emissions from cars and trucks due to the myriad technology 

options available to improve the efficiency of vehicles. A detailed analysis of the costs and 

benefits of various GHG emissions reduction requires an application that accounts for all the 

potential technologies. Therefore, EPA’s Office of Transportation and Air Quality (OTAQ) has 

developed the Optimization Model for reducing Emissions of Greenhouse gases from 

Automobiles (hereafter referred to as the “OMEGA” model) to help facilitate the analysis of the 

costs and benefits of reducing GHG emissions from cars and trucks. 

This documentation accompanies the fifth public release of the OMEGA model. 

Versions 1.0.0 and 1.0.2 were respectively released with the noticed of proposed rulemaking and 

final rule regarding “Model Year 2012-2016 Light-Duty Vehicle Greenhouse Gas Emissions 

Standards and Corporate Average Fuel Economy Standards.” Versions 1.3.0, 1.4.0, and this 

version were respectively released with the first notice of intent, the proposed rulemaking, and 

the final rule regarding the “2017 and Later Model Year Light-Duty Vehicle Greenhouse Gas 

Emissions and CAFE Standards.” These model releases, as well as their related inputs and 

documentation are available at the OMEGA page on the EPA website.1 

The model is written in the C# programming language. Inputs to and outputs from the model are 

provided using spreadsheet and text files. The spreadsheet output files also facilitate additional 

manipulation of the results. The model source code is available in the relevant rulemaking dockets.2 

EPA has established a webpage for the OMEGA model on the EPA agency website 

(http://www.epa.gov/otaq/climate/models.htm). The OMEGA version 1.4.1 release includes a 

set of sample input files; those used to support EPA’s final rulemaking on cars and light trucks 

for model years 2017+ are also available on the website. Input files from earlier versions of 

OMEGA are not compatible with this release. Periodic updates of both the model and this 

documentation will be available to be downloaded. Those interested in using the model are 

encouraged to periodically check this website for these updates. 

II Model Overview 

Broadly speaking, the OMEGA model evaluates the relative cost and effectiveness of 

available technologies and applies them to a defined vehicle fleet in order to meet a specified 

GHG emission target. Once the target has been met, OMEGA reports out the cost and societal 

benefits of doing so. This document focuses on the core model, which is the component which 

calculates cost of compliance. OMEGA models two GHGs; carbon dioxide (CO2) from fuel use 

and refrigerant emissions from the air conditioning (A/C) system. 

OMEGA is primarily an accounting model. It is not a vehicle simulation model, where basic 

information about a vehicle, such as its mass, aerodynamic drag, an engine map, etc. are used to 

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

2 EPA-HQ-OAR-2004-0075 and EPA-HQ-OAR-2010-0799 

3
 
predict fuel consumption or CO2 emissions over a defined driving cycle.3 Such simulations may 

be used to inform the OMEGA inputs, but are not performed by OMEGA itself. 

While OMEGA incorporates functions which generally minimize the cost of meeting a 

specified CO2 target, it is not an economic simulation model which adjusts vehicle sales in 

response to the cost of the technology added to each vehicle. While OMEGA allows vehicle 

sales to change over time, the vehicle sales in OMEGA 1.4.1 do not dynamically respond to the 

addition of technology.4 That being said, EPA has begun development of an economic 

simulation or consumer choice component to OMEGA. The model documentation and peer 

review documents are provided on the EPA website.5 

OMEGA can be used to model either a single vehicle model or any number of vehicle 

models. Vehicles can be those of specific manufacturers or generic fleet-average vehicles. 

Because OMEGA is an accounting model, the vehicles can be described using only a relatively 

few number of terms. The most important of these terms are the vehicle’s baseline emission 

level, the level of CO2 reducing technology already present, and the vehicle’s “type,” which 

indicates the technology available for addition to that vehicle. Information determining the 

applicable CO2 emission target for the vehicle must also be provided. This may simply be 

vehicle class (car or truck) or it may also include other vehicle attributes, such as footprint.6 

Since there are a large number of technologies which reduce CO2 emissions and a wide 

array of different vehicle systems to which they apply, the manufacturers’ design and production 

processes play a major role in determining the technology cost associated with lowering fleetwide CO2 emissions. Vehicle manufacturers typically develop several unique models based on a 

limited number of shared vehicle platforms, allowing for efficient use of design and 

manufacturing resources. The platform typically consists of common vehicle architecture and 

structural components. Given the very large investment put into designing and producing each 

vehicle model, manufacturers typically plan on a major redesign for the models approximately 

every 5 years. At the redesign stage, the manufacturer will upgrade or add all of the technology 

and make all of the other changes needed in order that the vehicle model will meet the 

manufacturer’s plans for the next several years. This includes meeting all of the emissions and 

other requirements that would apply during the years before the next major redesign of the 

vehicle. 

This redesign often involves a package of changes, designed to work together to meet the various 

requirements and plans for the model for several model years after the redesign. This often involves 

significant engineering, development, manufacturing, and marketing resources to create a new product 

with multiple new features. In order to leverage this significant upfront investment, manufacturers plan 

vehicle redesigns with several model years’ of production in mind. Vehicle models are not completely 

static between redesigns as limited changes are often incorporated for each model year. This interim 

process is called a refresh of the vehicle and generally does not allow for major technology changes 

although more minor ones can be done (e.g., aerodynamic improvements, valve timing improvements). 

3 EPA has released other models that perform full vehicle simulations. See the ALPHA
 

(http://www.epa.gov/otaq/climate/alpha.htm) and GEM models (http://www.epa.gov/oms/climate/gem.htm).
 4 OMEGA may be expanded in the future to incorporate such market responses, however, such responses may currently be
 

addressed “outside of the model” through sequential model runs with market adjustments made between runs.

5 http://www.epa.gov/otaq/climate/publications.htm
 6 A vehicle’s footprint is the product of its track width and wheelbase, usually specified in terms of square feet.
 

4
 
More major technology upgrades that affect multiple systems of the vehicle thus occur at the vehicle 

redesign stage and not in the time period between redesigns. 

There are a wide variety of emissions control technologies which involve several different 

vehicle systems. Many can involve major changes to the vehicle, such as changes to the engine block 

and heads, or redesign of the transmission and its packaging in the vehicle. This calls for tying the 

incorporation of the emissions control technology into the periodic redesign process. This approach 

reflects manufacturer capability to develop appropriate packages of technology upgrades that combine 

technologies in ways that work together and fit with the overall goals of the redesign. It also reflects the 

reality that manufacturers fit the process of upgrading emissions control technology into its multi-year 

planning process, and it avoids the large increase in resources and costs that would occur if technology 

had to be added outside of the redesign process. 

Within OMEGA, GHG emission control technology can be applied individually or in 

groups, often called technology “packages.” The user specifies the cost and effectiveness of 

each technology or package for a specific “vehicle type,” such as midsize cars with V6 engines 

or minivans. The user can limit the application of a specific technology to a specified percentage 

of each vehicle’s sales (i.e., a “cap”). The effectiveness, cost, application limits of each 

technology package can also vary over time.7 A list of technologies or packages is provided for 

each vehicle type, providing the connection to the specific vehicles being modeled. 

OMEGA is designed to apply technology in a manner similar to the way that a vehicle 

manufacturer might make such decisions. In general, the model considers three factors which EPA 

believes are important to the manufacturer: 1) the cost of the technology at the consumer level, 2) the 

value which the consumer is likely to place on improved fuel economy and 3) the degree to which the 

technology moves the manufacturer towards its CO2 emission target. 

Technology can be added to individual vehicles using one of three distinct ranking 

approaches. Within a vehicle type, the order of technology packages is set by the user. The 

model then applies technology to the vehicle with the lowest Technology Application Ranking 

Factor (hereafter referred to as the TARF). OMEGA offers several different options for 

calculating TARF values. One TARF equation considers only the cost of the technology and the 

value of any reduced fuel consumption considered by the vehicle purchaser. The other two 

TARF equations consider these two factors in addition to the mass of GHG emissions reduced 

over the life of the vehicle. Fuel prices by calendar year, vehicle survival rates and annual 

vehicle miles travelled (VMT) with age are provided by the user to facilitate these calculations. 

For each manufacturer, OMEGA applies technology to vehicles until the sales-weighted 

GHG emission average complies with the specified GHG emission standard or until all the 

available technologies have been applied. The GHG emission standard can be a flat standard 

applicable to all vehicles within a vehicle class (e.g., cars, trucks or both cars and trucks). 

Alternatively the GHG standard can also be in the form of a linear or constrained logistic 

function, which sets each vehicle’s target as a function of vehicle footprint (vehicle track width 

times wheelbase). When the linear form of footprint-based standard is used, the “line” can be 

7 “Learning” is the process whereby the cost of manufacturing a certain item tends to decrease with increased production 

volumes or over time due to experience. While OMEGA does not explicitly incorporate “learning” into the technology cost 

estimation procedure, the user can currently simulate learning by inputting lower technology costs in each subsequent 

redesign cycle based on anticipated production volumes or simply with time. 

5
 
converted to a flat standard for footprints either above or below specified levels. This is referred 

to as a piece-wise linear standard. 

The GHG emission target can vary over time, but not on an individual model year basis. 

One of the fundamental features of the OMEGA model is that it applies technology to a 

manufacturer’s fleet over a specified vehicle redesign cycle. OMEGA assumes that a 

manufacturer has the capability to redesign any or all of its vehicles within this redesign cycle. 

OMEGA does not attempt to determine exactly which vehicles will be redesigned by each 

manufacturer in any given model year. Instead, it focuses on a GHG emission goal several 

model years in the future, reflecting the manufacturers’ capability to plan several model years in 

advance when determining the technical designs of their vehicles. Any need to further restrict 

the application of technology can be effected through the caps on the application of technology 

to each vehicle type mentioned above. 

GHG emission standards are specified in terms of CO2 equivalent emissions. These CO2 

equivalent emissions can be based on any test procedure. The only requirement is that the base 

CO2 emissions specified for each vehicle and the effectiveness of the specified technologies be 

based on the same test cycle(s). For example, these emissions can simply be those from the 

tailpipe as measured over the current two-cycle GHG standard test procedure or they can also 

include tailpipe CO2 emissions from air conditioner use, as well as refrigerant emissions from the 

air conditioning system. In the case of the latter, the descriptions of vehicle emissions and 

technologies must include baseline refrigerant emissions and the effectiveness of each 

technology in reducing these emissions. GHG emissions could also be based on the 5-cycle 

formulae now used to calculate most vehicles’ fuel economy labels. The user simply needs to 

take care to specify CO2 and refrigerant emission and technology effectiveness estimates which 

are based on emissions over all five emission tests and as combined according to the five-cycle 

formulae. OMEGA bases all of its calculations on a single estimate of test cycle emissions. 

Compliance cannot be specified for two distinct test cycles, for example, city and highway test 

emissions. Only combined city alone, highway alone or city-highway emissions can be modeled. 

Once technology has been added so that every manufacturer meets the specified targets 

(or exhausts all of the available technologies), the model produces a variety of output files. 

Outputs include specific information about the technology added to each vehicle and the 

resulting costs and emissions. Average costs and emissions per vehicle by manufacturer and 

industry-wide are also determined for each vehicle class. 

The remainder of this document is divided into four sections. The first section describes 

the information which can be input to the model. The second section describes the application of 

technology in order to comply with the specified standards, what we define as the “core model.” 

The third section describes the various output files produced by the model. The fourth section 

describes the steps necessary to operate the OMEGA model. 

6
 
III Input Files 

OMEGA is designed to be flexible in a number of ways. Very few numeric values are 

hard-coded in the model, and consequently, the model relies heavily on its input files. The 

model utilizes five input files: Market, Technology, Fuels, Scenario, and Reference. All of the 

input files are Microsoft Excel 2003 spreadsheets and should not be converted into other formats. 

The headings of the various types of input data are contained in Row 1 of each worksheet. It 

should be noted that these headings cannot be modified by the user. Each input file also contains 

two common types of worksheets. One is named “Validation List” and lists the types of value 

allowed in each column along with an allowed range of valid values. This worksheet is typically 

hidden and can be viewed using the Format/Sheet/Unhide command. The user can change the 

range of valid values as desired. The user should not change the type of data shown as OMEGA 

is designed to look for certain types of information in each column and changing the values 

entered in an input file does not affect this expectation. 

The second common worksheet is named “Errors.” This worksheet contains a button 

labeled “Validate Data” which can be selected. When “clicked” this button triggers a macro 

which determines if all values in the current workbook fit the expected type of data and fall 

within the allowed range of values. Cells that do not fit the criteria are listed and the problem 

described. This function can be very useful when developing new input files by reducing the 

number of aborted model runs. While useful, please note that the error validation routines are 

outdated and may falsely indicate errors, or may not indicate all errors.8 

It is important to note that OMEGA expects all the cells below the last row of required 

data to be blank and, more specifically, to have never been written into. If these cells are used 

for temporary calculations, the user should go further below to a row which has never been 

written into and copy the entire row of blank cells into the row which have been used 

temporarily. The error identification process will then recognize these cells as actually being 

blank. 

A The Market File: Vehicle Fleet Characterization 

The market input file contains much of the required information which describes the vehicles being 

modeled. This file consists of three worksheets in addition to the Validation List and Errors worksheets: 

Vehicle, Manufacturer, and Vehicle Type. The “Manufacturer” and “Vehicle Type” tabs are lists of 

valid values for columns C and E in the Vehicle worksheet. The “Vehicle” worksheet, which is the 

substance of the market file, is discussed below. 

8 Generally, OMEGA is moving towards a dynamic where more error reporting is provided by the model itself, rather than 

these validation routines. The trace log, located in the same file directory as the model executable, provides useful 

diagnostics on the model run. 

7
 
Table 1 shows the various types of data included in the “Vehicle” worksheet. 

Table 1 - Input Data in Market Data Worksheet of the Market File* 

Column Name 

A Platform Index # 

B Vehicle Index # 

C Manufacturer 

D Model 

E Vehicle Type # 

F EPA Vehicle Class 

G Classic Vehicle Class 

H Baseline Sales 

I-P Annual Sales by Cycle 

Q Combined FE (mpg) 

R Tailpipe CO2 (g/mi) 

S Footprint (ft2) 

T Curb Weight (lb) 

U No. of Cylinders 

Column Name 

V Displacement (L) 

W Horsepower 

X Max Seating 

Y Transmission Type 

Z Drive 

AA Structure 

AB Towing Capacity 

AC Primary Fuel Type 

AD Combined EC (kWh/mi) 

AE Refrigerant Type 

AF Refrigerant Lifetime Leakage (g) 

AG-CD TEB Tech Package 1-50 

CE-EB CEB Tech Package 1-50 

EC-FZ OEB Tech Package 1-50 

* Columns highlighted in gray are not currently used by OMEGA 

Column A contains a positive numerical identifier matching each vehicle with a specific 

platform type. Each platform represents a unique combination of vehicle characteristics. During 

input data pre-processing OMEGA automatically creates a version of the market.xls data set 

aggregated by manufacturer and unique platform. This process is described further in later 

sections. 

Column B contains a unique, positive numerical identifier for each vehicle being 

modeled. The indices do not need to be in numerical order, just unique and positive. Column C 

contains the name of each manufacturer. There are no requirements with respect to the names, 

except that the user needs to take care that vehicles intended to be produced by the same 

manufacturer are given exactly the same name. Slight differences in spelling or spacing will 

cause the model to treat them as separate manufacturers. A list of manufacturers has been 

provided in the validation routine to help avoid this issue. Column D contains an alpha-numeric 

name for each vehicle. These names do not need to be unique, simply to be as descriptive as the 

user desires. 

Column E contains the vehicle type number. This value provides the connection 

between the vehicles listed in the market data worksheet and the available technologies listed in 

the Technology file. 

Column F contains the vehicle class designator. Currently OMEGA can model up to two 

vehicle classes: cars indicated with “C” and trucks indicated with “T.” This code provides the 

8
 
connection between the vehicles listed in the market data worksheet and the standards listed in 

the Scenario file. If only one standard applicable to both cars and trucks is being modeled, 

vehicles can be labeled as either cars or trucks or both. If both vehicle labels are used, 

compliance will still be based on the combination of both vehicle classes, but emissions will be 

tracked separately in the model’s outputs. This latter situation is advantageous if cars and trucks 

are to have distinct scrappage rates and annual travel estimates. 

Column G contains the car/truck classification of vehicles under the pre-MY 2011 CAFE 

definition. This column is not currently used by the OMEGA model 

Column H contains baseline sales. The baseline is the model year prior to the first year 

of the first redesign cycle being modeled. Baseline sales are not used in the core model to add 

technology to facilitate compliance; instead they are used in order to linearly interpolate annual 

vehicle sales during the interim years between the baseline year and the year of the end of the 

first redesign cycle. Sales must be positive and may be fractional. 

Columns I through P contain sales for the last year of each of up to eight redesign cycles. 

Sales must be positive and may be fractional. The basic assumption made by the model related 

to the length of the redesign cycle is quite simple: that every vehicle sold by the manufacturer is 

capable of being redesigned within a redesign. 

Sales must be entered for each vehicle, even if the value of sales is zero. Values need 

only be entered for redesign cycles actually being modeled. Thus, if only one redesign cycle is 

being modeled, then sales need only be entered in Column I. Columns J through P can be blank 

in this case. Sales can change in any manner between redesign cycles. 

Column Q contains each vehicle’s baseline fuel economy value in miles per gallon 

(mpg). It is not currently used by the model. 

Column R contains each vehicle’s baseline CO2 emissions in grams per mile (g/mi) over 

whichever test cycle or cycles comprise the basis for compliance with the standards described in 

the Scenario file. This value should not include the CO2 equivalent emissions related to 

refrigerant leakage emissions. Those emissions are described in later columns. The CO2 

emissions of Column R could include the CO2 equivalent emissions of GHGs like methane and 

nitrous oxide, as long as the effectiveness of the technologies described in the Technology file 

and the standards listed in the Scenario file consider these emissions in a consistent manner. 

Column S contains each vehicle’s footprint value in square feet. This value is used to 

determine each vehicle’s CO2 emission target when the standard is either a constrained logistic 

curve or linear function. 

Columns T through AA describe several vehicle attributes which are not currently used 

by the model. These are included to facilitate future versions of the model which may base 

compliance or evaluate model output using one or more of these attributes. Column AB contains 

the vehicle towing capacity in pounds. 

Column AC contains a designator for each vehicle’s primary fuel type. Any fuel type is 

allowed in the model, so long as its details appear in the Fuels input file. Plug in hybrid vehicles 

would be designated by their liquid fuel type, depending on which liquid fuel they used. The 

model will consider the electricity used by plug in vehicles based on the value of electricity 

consumption per mile described in Column AD, which is described below. Electric vehicles 

9
 
must be designated with the fuel “EL.” Fuel names are case sensitive, and each vehicle fuel 

must appear, in exactly the same format, in the fuels file. 

Column AD contains the vehicle’s baseline electricity consumption in units of kilowatthour per mile (kw-hr/mi). This value is used in calculating the fuel savings component of the 

TARF equation, in which a comparison must be made between vehicles and technologies which 

may consume different types of energy sources, such as liquid gasoline or diesel, or electricity. 

Since consumers tend to make decisions on which vehicle to purchase based on how much the 

vehicle costs them to drive it, this column helps the model account for the any energy in the 

baseline vehicles which is supplied by the electrical grid. This term only applies to plug in 

hybrids and battery based electric vehicles. In the Fuels input file, OMEGA allows the user to 

input a value for the GHG emissions associated with generating a kw-hr of electricity when 

determining compliance with the GHG standards. Should a non-zero value be entered, the level 

of electricity usage per mile also affects the vehicle’s baseline CO2 emission level when the 

model is run. 

Column AE designates the type of refrigerant used by the vehicle. This designator must 

match one of the types of refrigerant listed on the Refrigerant worksheet of the Reference file 

described further below. The primary purpose of this designation is to specify the Global 

Warming Potential (GWP) of the refrigerant so that mass emissions of refrigerant leakage can be 

converted to their CO2 equivalent emissions. Editable refrigerant data is in the Reference file, so 

that the user can edit or add additional refrigerant names and GWPs. 

Column AF of the market file designates the lifetime leakage of the refrigerant, which the 

model uses to calculate the leakage rate in CO2 equivalents. EPA chose to input the lifetime 

leakage instead of the leakage rate because the lifetime leakage is easier to quantify. The yearly 

distribution of leakage is hard-coded, and OMEGA uses it to convert the refrigerant leakage to 

grams of CO2 equivalents per mile. 

Columns AG through CD are used to track technology that may be present in the baseline 

or reference case. This data is necessary to prevent the model from double counting technology 

costs and GHG improvements. Columns AG through CD represent the fraction of the 

technology package effectiveness for the different vehicles that is present in the reference case; 

for example, a value of 35% for technology package 1 means that 35% of the effectiveness of 

technology package 1 on that vehicle type is already present in the baseline vehicle. Similarly, 

columns CE through EB represent the fraction of the technology packages’ cost that is reflected 

in the baseline. Likewise, a value of 75% in any of these columns means that 75% of the 

technology package’s cost on the particular vehicle has been included in the reference case. A 

method for calculating these values is described in Appendix A. 

Columns CE through FZ contain Other Effectiveness Basis (OEB) gram-per-mile credits 

that may be associated with each technology package. Typically these are negative numbers. 

While each technology package may have an associated gram-per-mile credit (specified in the 

Technology.xls input data set) those are only applied when calculating the TARF CO2 value. 

When calculating total vehicle CO2 for compliance purposes, the OEB values from columns CEFZ are used instead. As documented in a later section, the use of OEBs provides vehicle level 

accounting for credits. 

10
 
B The Technology File: Technology Package Characterization 

The technology input file defines the technology packages (up to 50) which the model 

can add to the vehicle fleet. For each vehicle type, the user must add a separate row for each 

technology package in the order of how OMEGA should add them to that specific vehicle type. 

This approach puts considerable onus on the user to develop a reasonable sequence of 

technologies. However, the model also produces output information which can help the user 

determine if a particular technology package might be “out of order”. The package approach 

also simplifies the model’s calculations and enables synergistic effects among technology 

packages to be included to the fullest degree possible. 

There are four tabs which contain technology packages, each tab keyed to a 

particular redesign cycle. Similar to the Market file, the Technology file contains an additional 

tab entitled “errors”, which is used for validation purposes. Table 2, below describes the data in 

the each redesign cycle tab. 

Table 2 - Input Data in Each Worksheet of the Technology File 

Column(s) Contents 

A Vehicle type number 

B Technology package number 

C Technology package name 

D Abbreviation 

E Market penetration caps 

F Incremental tailpipe CO2 emission control effectiveness 

G Incremental Cost 

H Primary fuel of the new technology package 

I The fuel to which the technology package applies 

J Electrical Conversion % 

K Gram/mile CO2 credit 

L Refrigerant emission control effectiveness 

M Refrigerant type (NC = no change from previous step) 

The data in this file can be categorized in four ways: 1) Information which describes the 

individual packages, such as name and vehicle type; 2) Parameters the model uses to calculate 

CO2 improvement, such as effectiveness and market penetration cap (the latter being the cap of 

sales for each vehicle model of a vehicle type that can receive a technology package); 3) 

technology costs 4) Properties of the technology package, such as refrigerant type, fuel type, 

electricity usage, credit value, and applicable fuel. 

Each tab in the Technology input file contains a user-defined list of technology packages 

for all of the different vehicle types. This list is organized in ascending order by the vehicle type 

to which it applied (Column A), and then by ascending technology package (Column B). The 

user need not use the full 20 lines for each vehicle type, but can stop after the last technology 

package has been listed. There cannot be any blank lines between technology packages or 

vehicle types. The user must record the technology packages within each vehicle type from top 

to bottom in the order of how the model should add them to the particular vehicle. In typical 

OMEGA usage, each package is replaced by the subsequent technology package, so it is critical 

that packages improve in aggregate CO2 reduction. The user records a description of the 

11
 
technology package in Column C, and an abbreviation, if desired, in Column D. The 

abbreviation of the last technology package added is displayed in the output files. 

Column E contains the maximum market penetration caps for the technology packages. 

When technology is sufficiently new, or the lead-time available prior to the end of the redesign 

cycle is such that it is not reasonable to project that it could be applied to all vehicle models that 

are of the same specific vehicle type (i.e,; all minivans), the user can limit its application to 

minivans through the use of a market cap of less than 100%. If subsequent technology packages 

can be applied to the vehicle, the user should consider whether in reality the new technology 

would likely be applied to those vehicles which received the previous technology or those which 

did not, and design the technology file accordingly. The effectiveness of adding the subsequent 

technology will depend on which vehicles are receiving it. 

Column F contains the Average Incremental Effectiveness (AIE) of the technology 

package over the previous package (or over the baseline in the case of technology package 1). 

For example, a value of 7.0% in the AIE column would denote a 7.0% tailpipe CO2 improvement 

beyond any CO2 improvements already realized. (“Tailpipe CO2” refers to the CO2 emitted over 

the test cycle assumed to be used to determine compliance- which relates it to vehicle 

efficiency.) This value of 7% would include any synergistic effects that components of the 

technology package may have with technologies that are remaining on the vehicle type. 

Column G contains the incremental technology package cost, which represents the cost 

beyond the cost of other technology packages that the model may have added in a previous step. 

In the specific case of technology package 1 on each vehicle type, this will be the package cost 

over the baseline, since no other technology has been added prior to technology package 1. 

Column H and I respectively contain the fuel used by the vehicle after addition of the 

technology package, and the fuel of the vehicles to which the technology package applies. These 

fuel abbreviations must also appear in the Fuels input file, and are case specific. 

Column J contains the electrical conversion percentage. Each technology package potentially 

has an “electricity conversion percentage,” which refers to the increase in the grid-supplied electrical 

energy consumed by the electric drivetrain relative to reduction in the consumption of energy from 

liquid fuel. More specifically, the electricity conversion percentage is the ratio of the increase in gridsupplied electrical energy used by the vehicle (in BTU per mile) divided by the reduction in liquid fuel 

use (also in BTU per mile), multiplied by 100%. Electricity is a highly refined form of energy which 

can be used quite efficiently to create kinetic energy. Thus, electric motors are much more efficient than 

liquid fuel engines. Consequently, the electric consumption percentages input in the Technology File 

for plug-in hybrid vehicles and battery electric vehicles are generally well below 100%. It may be 

possible that this percentage could exceed 100% under certain circumstances, for example when one 

type of plug-in vehicle is being converted into another plug-in vehicle and electricity consumption per 

mile is increasing due to larger and heavier batteries, etc. 

Column K contains a gram per mile credit that is applied to this technology step when 

calculating the TARF CO2 values. As described above, the OEB, rather than this credit value, is 

used in calculating the compliance CO2 for a vehicle using this technology package. However, 

this value is used in computing the TARF. 

Column L contains the refrigerant effectiveness and is based on the fraction reduction in 

direct refrigerant leakage emissions and is separate from tailpipe CO2. Based on a change in 

12
 
refrigerant included as part of a technology package, noted in Column V, the model will convert 

the refrigerant emissions to grams per mile of CO2 equivalent emissions, and add the resultant to 

the tailpipe CO2 emissions for the vehicle compliance calculation. A value of “NC” in column 

M denotes that there is “No Change” in refrigerant from the previous step, or in the case of 

technology package 1, no change from the baseline refrigerant. 

C The Fuels File: Physical Properties and Prices of Fuel and Energy Sources 

The Fuels input file contains data relevant to liquid fuel and electricity, including energy, 

mass, and carbon density, and annual price forecasts for up to 20 years. Similar to the other 

input files, the fuels input file is comprised of two worksheets: A worksheet containing data used 

by the model and an additional worksheet designed to ensure that the data is within allowable 

ranges. There is a third hidden worksheet which contains the range of allowable values. Table 3 

describes the layout and content of the “fuel” tab in the fuels input file. 

Table 3 - Input Data in Fuel Worksheet of the Fuels File 

Column(s) Contents 

A Fuel Type 

B Energy Density 

C* Mass Density* 

D Carbon Density 

E CAFE Equivalency Factor 

F - Y Fuel Price ($/gal) 

*The columns highlighted in gray are not used 

by the model’s calculations. 

Column A describes the fuel type. This value can be any descriptor desired, but EPA 

typically specifies gasoline as “G”, diesel fuel as “D,” etcetera. The one exception is that 

electricity must be designated as “EL”, in order for the model to connect inputs like the 

electricity conversion factor with this fuel. Please note that the fuel names in this file must 

match the fuels in the technology and market files at a case specific level. 

Column B contains the energy density of the energy source. For the liquid fuels, this 

factor has the units of BTU per gallon. Electricity has the units of BTU per kilowatt-hour, which 

is essentially a fixed conversion factor. This factor is used when a technology package increases 

the ability of the vehicle to operate on grid-supplied electricity. It is used in conjunction with the 

electrical conversion factors listed in the technology file. 

Column C contains the mass density of the liquid fuels in terms of grams per gallon, and 

is not used in the model. 

Column D describes the carbon density of the energy source, and is used in the 

calculation of the fuel savings component of the TARF9 as well as in the compliance 

calculations. Carbon density is specified in units of grams of carbon per gram per the unit of fuel 

9 TARF formulas are discussed on page 26. 

13
 
which is associated with the fuel price. For liquid fuels, this is grams of carbon per gallon and 

for electricity this is grams of carbon per kWh. If a user wishes to incorporate the upstream 

emissions of the carbon content of CO2 emissions in the TARF and compliance calculations, 

they could enter a positive value in this cell. Please note that these emission values are in terms 

of grams of carbon, not grams carbon dioxide. 

Column E contains the CAFE equivalency factor used in the calculation of manufacturer fines. 

If there is a fine, and if the manufacturer fails to meet the target, then the TARF rankings would change. 

However, because the OMEGA model does not allows the manufacturer to choose to pay fines, this 

input should typically be set to 1.10 

Columns F through Y contain the fuel price either in US Dollars per gallon or US Dollars per 

kWh for liquid fuel and electricity, respectively, for 20 calendar years. Fuel prices are to be input in 

ascending order by year and are used when calculating the fuel savings over the payback period in the 

TARF. The first calendar year listed should be that of the baseline year plus one. 

D The Scenario File: Definition of Regulatory Scenarios and Other Economic Parameters 

The Scenario input file contains data specifying the number and types of model runs. 

The Scenarios tab acts as a directory for different model runs, where the user can create an entry 

for any number of runs that the model can perform in succession. In the Scenarios tab, the user 

must specify the base year, type of compliance target (CO2 or MPG), type of compliance 

function, the number of redesign cycles, and the names of the other input files that describe the 

vehicle fleet, technology packages, and fuel properties. At present, the model is limited to a CO2 

equivalent standard. The elements in the “Scenarios” tab described above are summarized in the 

following table: 

10 In other words, the OMEGA model’s technology application algorithm only ceases to apply technology when a 

manufacturer comes into compliance, or when all technology options have been exhausted. There is no option to pay fines 

rather than comply through technology. 

14
 
Table 4 - Input Data in Scenarios Worksheet of the Scenario File 

Column(s) Contents 

A Scenario ID number 

B Scenario name 

C Baseline year 

D Target Type 

E TARF Option 

F GHG Target Function Type 

G Fleet type (single or combined) 

H Number of redesign cycles 

I Fleet trading limit 

J Market input file indicator 

K Technology input file indicator 

L Fuels input file indicator 

M Reference input file indicator 

*The columns highlighted in gray are not used by the model’s calculations. 

Column A in the Scenarios tab indicates the ID number of the model run. From a single 

scenario file, the model can run as many different scenarios as the user desires. In Column B, 

the user can give each scenario a name, which the model will use in naming the output directory 

and files for each scenario. Column C denotes the baseline year for each scenario. This is the 

year prior to the first year of the first redesign cycle. Column D indicates the type of standard or 

target (CO2 or MPG) the model will use for compliance, and is not currently active in the model. 

Column E is where the user designates which of the three TARF equations the model 

should use. The model uses the TARF equations to determine the order of technology package 

application on the different vehicle models. There are three TARF equations which are 

summarized below and are described in detail on page 32. 

1.	 Effective Cost = [Technology package cost minus fuel savings over the payback 

period]. 

2.	 Cost Effectiveness-Society = [Effective Cost] divided by discounted lifetime CO2 

emissions. 

3.	 Cost Effectiveness -Manufacturer = [Effective Cost] Divided by lifetime CO2 

emissions. 

Column F indicates the user’s preference for type of function for the industry-wide GHG 

level. There are four options for compliance targets: 1 = universal; 2 = piecewise linear; 3 = 

constrained logistic. 

D.i Universal Target 

The universal target option is a numeric designation which the manufacturers’ average 

fleet CO2 cannot exceed. For a universal standard (which could apply to cars, trucks or cars and 

trucks combined), only the value listed in the first of each set of the four coefficients is used 

(Labeled “A” in the header row of the Target worksheet). 

15
 
D.ii Piece-wise Linear 

The attribute-based linear target function is described by up to four coefficients and has 

the following piecewise linear mathematical form: 

A; FP  FP  min 

 B  A 

y  [ ]* (FP  FP min )  A; FP min  FP  FP max FP  FP  max min Where B; FP  FP  max A: Minimum level of CO2 target 

B: Maximum level of CO2 target 

FPmin: Footprint value where CO2 target 

reaches minimum value (i.e., 

intersection of lower asymptote with 

slope) 

FPmax: Footprint value where CO2 target 

reaches maximum value (i.e., 

intersection of upper asymptote with 

slope) 

FP: Vehicle footprint (square feet) 

When inputting a piece-wise linear target into the Target worksheet, FPmin and FPmax should be 

respectively entered in the C and D coefficient columns. 

Example of Footprint-Based CO2 Piecewise Linear Target Function 

CO2 (g/mi) 

Footprint (ft2) 

16
 
D.iii Logistic Curve Target 

The footprint-based logistic curve (shown below) is described by four coefficients and has the 

mathematical form described below. 

FP C    D 

T  A  B  A e  FP C    1  e D  

Example of Footprint-Based CO2 Logistic Target Function 

Where A, B, and FP have the same definitions 

as above 

C: Footprint value at equation inflexion point 

(i.e., midpoint) 

D: The term which controls the rate at which 

the CO2 target moves from the minimum to 

maximum values. High values of D cause the 

curve to move slowly (in terms of footprint) 

from the minimum to maximum target (i.e., a 

sort of “inverse slope”) 

FP: Vehicle footprint 

CO2 (g/mi) 

Footprint (ft2) 

17
 
Column G of the Scenarios tab in the Scenario input file is entitled “fleet type.” There 

are two acceptable values for cells in this column: 1 = 1 fleet and 2 = 2 fleets. If 1 is chosen, the 

standard defined in the “Standards” tab will be taken from the “Car” standard section and applied 

to all of the vehicles listed in the market file, whereas if 2 is chosen, the standards will be defined 

by both the “Car” and “Truck” standard sections and applied to cars and trucks separately. 

Column H contains the number of redesign cycles the model considers in a given run. 

There can be as few as one redesign cycle and as many as eight. The model allows any length to 

be assumed for a redesign cycle, as long as the redesign cycle length is the same for all vehicles. 

The inputs should be designed appropriately to reflect the user’s assumptions. 

Column I contains the limit (in units of g/mi CO2) imposed on the trading of compliance 

credits between cars and trucks. 

Columns J-M indicate which files the model will access for the different runs. Column J 

contains the name of the market input file; column K contains the name of the technology input 

file; column L contains the name of the fuels input file; column M contains the name of the 

References file. All files must be in the same directory as the scenario file. 

The Scenario input file also contains the economic parameters that the model uses to 

calculate the TARF equations. Such economic data is contained in the “Economics” tab and is 

organized as illustrated in the following table: 

Table 5 - Input Data Contained in the Economics Worksheet of the Scenario File 

Column(s) Contents 

A Scenario ID number 

B Discount rate 

C Payback period 

D CAFE fine 

E Gap 

F Threshold cost 

G CO2 value increase rate 

H EPA Lifetime VMT – Car 

I EPA Lifetime VMT - Truck 

Column A contains the ID number for the model run, and it must be identical to that in 

Column A of the Scenarios tab. 

Column B contains the discount rate for future dollar values. The model uses the 

discount rate in the TARF calculations when calculating the fuel savings over the payback 

period. 

Column C designates the payback period over which consumers are believed to consider 

fuel savings when purchasing a vehicle. 

Column D indicates the value of a fine for non-compliance. EPA typically records $0 

into this column. Changes to this value will affect the TARF, but not allow fine payment. 

18 
Column E contains the gap, which is the percentage difference between on-road fuel 

economy and test cycle fuel economy. This value is important because compliance is based on 

test cycle CO2, whereas the true impact on climate is based on the on-road CO2 and consumer 

fuel savings are based on on-road fuel economy. The model uses this difference to convert test 

cycle CO2 emissions to on-road fuel economy and calculate fuel savings in the core model’s 

TARF equations, as described further on page 32 below. 

Column F contains the value for the “threshold cost”. This value determines whether the model 

will accept some degree of over-compliance when it determines the degree of technology addition 

needed for a manufacturer to meet a standard, or if it will reduce the addition of technology so that a 

manufacturer just barely complies. Specifically, if the per vehicle cost of the last technology added by 

the model in order to reach compliance exceeds the threshold value, the model reduces the percentage of 

that vehicle’s sales which receives that technology to just the degree needed to enable compliance. If 

the per vehicle cost of the last technology added by the model in order to enable compliance is below the 

threshold value, the model leaves the percentage of vehicle sales receiving that technology at the 

technology penetration cap for that technology.11 

Column G represents the rate of increase in the real value of CO2 emission reductions over time. 

This value is included since some studies have predicted that the real value of CO2 emission reductions 

will increase over time as the impact of global climate change increase. The units of this term are 

percent per annum. This value is used in the Cost Effectiveness-Society TARF described below. 

Columns H and I contain the statutory lifetime miles driven by cars and trucks. These values are 

used to calculate the credit trading ratio between cars and trucks. Because real VMT tends to grow over 

time, but the VMT used in the credit trading equation is determined by regulation, this value can differ 

from the VMT in the reference file (described below). For example, the lifetime VMTs per vehicle for 

cars and trucks provided in EPA’s current GHG regulations are 195,264 and 225,865, respectively.12 

The Target tab of the Scenario file contains the parameters describing the GHG compliance targets 

required by the universal, piece-wise linear and constrained logistic functions described above. The first 

40 columns describe the car standards for up to eight redesign cycles, if “2” fleets are selected in column 

G of the Scenarios worksheet. If “1” fleet is selected, then the standards described in Columns A 

through AO apply to both cars and trucks. Similarly, the next 40 columns (AP through CC) describe the 

truck standards for up to eight redesign cycles if “1” fleet is selected. This second set of values is not 

used if “1” fleet is selected. This is described in Table 6. 

11 This flexibility was included in the model to reflect the different ways in which manufacturers apply various technologies. 

For example, when adding basic engine technology such as variable valve timing, the manufacturer would generally convert 

the entire production volume of a specific engine to this technology. The production of two otherwise identical engines, one 

with the technology and one without, would likely not be maintained. However, with more extreme technologies, such as 

dieselization or hybridization, the manufacturer often maintains two versions of the vehicle, one with and one without these 

technologies. By setting the threshold in between the costs of these two examples, the model will reflect these two 

approaches to technology application on the part of a manufacturer.

12 However, while the user may choose to model different statutory and accumulated VMT, differences in this values can 

yield to counter-intuitive TARF values. 

19 
Table 6 - Input Data Contained in the Target Worksheet of the Scenario File 

Column(s) Contents Vehicle Class 

B – F Coefficients describing the CO2 Standard for Design Cycle 1 

Car If “2” fleets 

selected 

Car and Truck if “1” 

fleet selected 

G – K Coefficients describing the CO2 Standard for Design Cycle 2 

L – P Coefficients describing the CO2 Standard for Design Cycle 3 

Q – U Coefficients describing the CO2 Standard for Design Cycle 4 

V-Z Coefficients describing the CO2 Standard for Design Cycle 5 

AA – AE Coefficients describing the CO2 Standard for Design Cycle 6 

AF – AJ Coefficients describing the CO2 Standard for Design Cycle 7 

AK – AO Coefficients describing the CO2 Standard for Design Cycle 8 

AP – AT Coefficients describing the CO2 Standard for Design Cycle 1 

Truck If “2” fleets 

selected 

Not used if “1” fleet 

selected 

AU – AY Coefficients describing the CO2 Standard for Design Cycle 2 

AZ – BD Coefficients describing the CO2 Standard for Design Cycle 3 

BE – BI Coefficients describing the CO2 Standard for Design Cycle 4 

BJ – BN Coefficients describing the CO2 Standard for Design Cycle 5 

BO – BS Coefficients describing the CO2 Standard for Design Cycle 6 

BT – BX Coefficients describing the CO2 Standard for Design Cycle 7 

BY – CC Coefficients describing the CO2 Standard for Design Cycle 8 

As indicated, each CO2 standard is described by up to five coefficients. For a universal standard, 

only the value listed in the first of each set of four columns is used (Labeled “A” in the header row of 

the Target worksheet). The first four columns are required to describe either the segmented linear or 

constrained logistic functions described above. 

E The Reference File: Vehicle Survival Rates and Miles Driven 

The Reference file contains car and truck annual miles driven and survival rates by year. These 

estimates are used in the cost effective TARF (1) and the cost effectiveness-society TARF (2) 

calculations when determining fuel savings over the payback period and in the cost effectivenessmanufacturer TARF (3) when determining the lifetime CO2 reduction. TARF 3 uses the statutory VMT 

values in the scenario file. 

The vehicle survival and VMT estimates are inputted in the tab entitled Vehicle Age. Column A 

in this tab contains the vehicle age in years. Columns B and C contain the percentage of cars and trucks 

still projected to be on the road of the specified ages, respectively. Columns D and E contain the 

average miles driven annually (per vehicle) for cars and trucks, respectively, for vehicles of the specified 

ages. 

The Refrigerant tab contains data which is only used if refrigerant emissions are included in the 

market file. A dynamic list of acceptable refrigerants can be created, and accompanied with their 

respective global warming potential. Column A is the refrigerant name, while column B is the GWP. 

F Non-editable Input Data 

The only values “hard-coded” into the model which are potentially used in the 

application of technology to vehicles are the distribution of leakage rate by vehicle age. 

The following table describes the refrigerant leakage rates which are currently hard-coded. 

20 
Table 7 – Refrigerant leakage rates 

Refrigerant Leakage Fractions 

Year % of Total Lifetime 

Leakage g/year 

Year % of Total Lifetime 

Leakage g/year 

1 1.1% 19 3.3% 

2 1.5% 20 2.7% 

3 2.0% 21 2.3% 

4 2.4% 22 1.8% 

5 2.9% 23 1.4% 

6 3.3% 24 1.1% 

7 3.6% 25 0.9% 

8 4.4% 26 0.7% 

9 5.5% 27 0.0% 

10 6.9% 28 0.0% 

11 8.5% 29 0.0% 

12 8.1% 30 0.0% 

13 7.5% 31 0.0% 

14 7.0% 32 0.0% 

15 6.5% 33 0.0% 

16 6.0% 34 0.0% 

17 4.8% 35 0.0% 

18 3.9% 36 0.0% 

EPA intends to make this data editable in a future version. 

G Input Files Currently Distributed with Model 

The sample files bundled with the installation file contain example or “dummy” data and 

are only indicative of realistic values. The input files from recent rulemaking analyses are 

available on the EPA OMEGA webpage. 

21 
IV Model Operation 

A Calculating Technology Effective Basis (TEBs) and Cost Effective Basis (CEBs) 

The market data input file utilized by OMEGA, which characterizes the vehicle fleet, is designed 

to account for the fact that the vehicles which comprise the baseline fleet may already be equipped with 

one or more of the technologies available in general to reduce CO2 emissions. As described previously, 

OMEGA is typically used with technologies in packages, as opposed to one at a time. However, actual 

vehicles are equipped with a wide range of technology combinations, many of which cut across the 

packages. Thus, EPA developed a method to account for the presence of the combinations of applied 

technologies in terms of their proportion of the technology packages. This analysis can be broken down 

into four steps 

The first step in the process is to break down the available GHG control technologies into five 

groups: 1) engine-related, 2) transmission-related, 3) hybridization, 4) weight reduction and 5) other. 

Within each group we gave each individual technology a ranking which generally followed the degree 

of complexity, cost and effectiveness of the technologies within each group. More specifically, the 

ranking is based on the premise that a technology on a baseline vehicle with a lower ranking would be 

replaced by one with a higher ranking which was contained in one of the technology packages which we 

included in our OMEGA modeling. The corollary of this premise is that a technology on a baseline 

vehicle with a higher ranking would not be replaced by one with an equal or lower ranking which was 

contained in one of the technology packages which we chose to include in our OMEGA modeling. 

In the second step of the process, we use these rankings to estimate the complete list of 

technologies which would be present on each baseline vehicle after the application of each technology 

package. We then use the EPA lumped parameter model to estimate the total percentage CO2 emission 

reduction associated with the technology present on the baseline vehicle (termed package 0), as well as 

the total percentage reduction after application of each package, including any baseline technology still 

expected to remain present after the application of each package. Similarly, we use a cost estimation 

tool to estimate the cost of the CO2 reducing technology present on the baseline vehicle and after the 

addition of each package. 

The third step in this process is to convert these total levels of emission control effectiveness and 

cost to TEB and CEB13 values which can be used when the OMEGA model applies technology packages 

on an incremental basis. This is done by comparing each technology package’s incremental 

effectiveness and incremental cost on each specific vehicle to those of the package when applied to a 

vehicle with no baseline technology. The value of each vehicle’s TEB for each applicable technology 

package is determined as follows: 

13 As described earlier, the degree to which a technology package’s incremental effectiveness is reduced by technology 

already present on the baseline vehicle is termed the technology effectiveness basis, or TEB, in the OMEGA model. The 

degree to which a technology package’s incremental cost is reduced by technology already present on the baseline vehicle is 

termed the cost effectiveness basis, or CEB, in the OMEGA model. 

22 
 TotalEffect   1TotalEffect  v,i1 p,i 1  

     1TotalEffect 1TotalEffect  v,i   p,i1  TEB i   1TotalEffect  p,i 1    1TotalEffect  p,i1 

Where 

TotalEffectv,i = Total effectiveness of all of the technologies present on the baseline vehicle after 

application of technology package i 

TotalEffectv,i-1 = Total effectiveness of all of the technologies present on the baseline vehicle after 

application of technology package i-1 

TotalEffectp,i = Total effectiveness of all of the technologies included in technology package i 

TotalEffectp,i-1 = Total effectiveness of all of the technologies included in technology package i-1 

i = the technology package being evaluated 

i-1 = the previous technology package 

Equation A-1 – TEB calculation 

The value of each vehicle’s CEB for each applicable technology package is determined as 

follows: 

CEBi = 1 – (TotalCostv,i – TotalCostv,i-1) / (TotalCostp,i – TotalCostp,i-1) 

Where 

TotalCostv,i = total cost of all of the technology present on the vehicle after addition
 

of package i to baseline vehicle v
 

TotalCostv,i-1 = total cost of all of the technology present on the vehicle after addition
 

of package i-1 to baseline vehicle v
 

TotalCostp,i = total cost of all of the technology included in package i
 

TotalCostp,i-1 = total cost of all of the technology included in package i-1
 

i = the technology package being evaluated
 

i-1 = the previous technology package
 

Equation A-2 – CEB calculation 

The fourth step is to combine the TEB and CEB values for each individual vehicle 

models to match the vehicles being included in the Market file. The CEB for each vehicle group 

is simply the sales-weighted average of the CEB values for each individual vehicle model, since 

the cost of each package is the same for each vehicle in a vehicle type. (Only vehicles of the 

same vehicle type should be combined.) The TEB for each vehicle group is determined in a 

slightly more complex fashion. The individual TEB values are weighted by both sales and base 

CO2 emission level. This appropriately weights vehicle models with either higher sales or CO2 

emissions within a vehicle type. Once again, this process prevents the model from adding 

technology which is already present on vehicles, and thus ensures that the model does not double 

count technology effectiveness and cost associated with complying with the reference standards 

or the CO2 control scenarios. 

23 
B Calculating Other Effectiveness Basis (OEBs) 

As noted above, the market data input file utilized by OMEGA is also designed to account for 

the fact vehicles may not have the exact equipment in the package after the package is applied. This is 

particularly relevant in the context of a regulatory incentive for specific technologies. As an example, if 

incentives are provided for start-stop systems, the model needs to know whether that vehicle contains a 

start-system in order to provide the credit. If a vehicle platform already contains start-stop before any 

packages are applied, the model needs to account for the baseline credit impacts of the technology. As it 

varies at the vehicle, rather than vehicle type, level, this accounting needs to occur at the level of the 

market file rather than the technology file. 

However, it is important that the technology packages are ranked in the same order for all 

vehicles in a vehicle type. Therefore, the TARF is calculated with the credit value in the technology 

file, but the compliance CO2 value is calculated using the vehicle specific value. 

C Platform Aggregation 

The market file includes a vehicle Platform Index (see the description of the new market.xls file 

layout in section 2A.) Vehicles with the same Platform Index share a common Vehicle Type and engine 

configuration. While every entry in the market.xls file has a unique Vehicle Index, several vehicles may 

share the same Platform Index. Vehicles in a single platform should share vehicle class and vehicle 

type. 

In some analytical situations it is useful to have a market file with a single record for every unique 

manufacturer / platform combination.14 This requires combining individual vehicles with matching 

manufacturer / platforms into single representative records. Since OMEGA already loads all of the 

information necessary to perform this calculation, EPA has chosen to include creation of a manufacturer 

/ platform version of the market file as a standard feature in the model. 

After loading the market file, OMEGA performs the necessary calculations and creates a Platform 

Aggregation version of the market file, and then uses this new market file in the subsequent OMEGA 

run. The new output data set is tab-delimited with a layout matching the market.xls file (the output 

filename is X-Market-Platform_Mfr.log, as shown in Table 8.) 

Records in the manufacturer / platform file are created by calculating weighted average values for 

the vehicle records with matching manufacturer and platform codes. 

The following data elements in the market file are calculated as a sales weighted average using the 

Annual Sales in Cycle 1: 

 CO2 (grams per mile) 

 Footprint (ft2 ) 

 Curb Weight (pounds) 

 Displacement (Liters) 

 Horsepower 

 Max Seating 

 Towing Capacity (pounds) 

14 This is how EPA has typically run the model, although this calculation is typically done in a spreadsheet, rather than 

through using this model feature. 

24 
 Combined EC (kWh/mi) 

 Refrigerant Lifetime Leakage (grams) 

 CEB_Tech_1-CEB_Tech_50 

 Combined Miles per Gallon (harmonically averaged) 

The following data elements in the market file are calculated as a sales-CO2 weighted average 

using CO2 * Annual Sales in Cycle 1: 

 TEB_Tech_1-TEB_Tech_50; 

 OEB_Tech_1-OEB_Tech_50;15 

Vehicle sales (baseline and annual sales) are the sum of sales in the individual vehicle records. 

All other data elements are set equal to the values found in the first vehicle in the manufacturer / 

platform set. 

D Technology Application 

The technology application portion of the model can be described in several steps. The first step 

determines the effective CO2 emission standard for each manufacturer and vehicle class. The second 

step converts the baseline lifetime refrigerant emissions specified for each vehicle into its g/mi CO2 

equivalent and adds this to the baseline tailpipe CO2 emissions for each vehicle. The third step applies 

technology until this standard is met or all available technology has been applied. These steps are 

described below. 

D.i Determination of Manufacturer-Specific CO2 Emission Standards 

As described above, three types of standards can be evaluated by OMEGA: universal or 

flat, piecewise linear, and constrained logistic. Determining each manufacturer’s effective 

standard under a flat standard is simple; it equals the flat standard. The other two types of 

standards require sales-weighting the CO2 target applicable to each specific vehicle model 

produced by that manufacturer. Under these standards, the model calculates each vehicle’s CO2 

target by plugging the vehicle’s footprint into the formula describing the standard. Each of the 

vehicle-specific targets are then multiplied by the vehicle’s sales in that redesign cycle and the 

statutory lifetime VMT for that vehicle class and summed across all vehicles. The sum is then 

divided by the sum of the product of vehicle sales by that manufacturer in that redesign cycle and 

the lifetime VMT for each vehicle. The result is a sales and lifetime VMT weighted corporate 

average CO2 target for each manufacturer’s relevant set of vehicles (i.e., cars, trucks, or cars and 

trucks combined). 

If one fleet is specified, then the model only performs this calculation once and includes 

both cars and trucks in the calculation. If separate standards are specified for cars and trucks, 

then the model performs this task twice for each manufacturer for each redesign cycle being 

modeled: once for cars and once for trucks. If the same standard is specified for both cars and 

trucks and two compliance fleets are specified in the Scenario file, then two separate calculations 

are still performed. The result is still two distinct CO2 emission targets, one for cars and one for 

trucks. 

15 This weighting will be changed to sales-weighted only in future model versions, which is consistent with the methodology 

used in the MY 2017 and later light duty greenhouse gas rulemaking. 

25 
If a trading limit of “0” is specified, then this stage of the model operation is complete. If 

a non-zero trading limit is specified, an additional step is required to ensure that this trading limit 

is not exceeded, as described in the section below on credit trading algorithms. Conceptually, we 

assume that a manufacturer would prefer to evaluate the application of technology to both its 

cars and trucks at the same time in order to optimize compliance (via the TARF) over the widest 

set of vehicles. At the same time, the manufacturer is assumed to want to avoid generating 

credits from one of its two vehicle class fleets which cannot be used by the other fleet due to the 

limit on trading, since it would incur cost with no benefit. 

D.ii Converting Lifetime Refrigerant Emissions to CO2-Equivalent emissions per Mile 

Refrigerant leakage emissions are input to the model in terms of lifetime emissions, 

where refrigerant leakage increases with wear and tear of the A/C system. Leakage emissions 

also occur during accidents, repairs and vehicle scrappage. Refrigerant emissions per year 

increase significantly with age. Since annual mileage decreases with age in general, refrigerant 

emissions per mile increase even more significantly with age than emissions per year. In 

contrast, CO2 tailpipe emissions are input in terms of g/mi and are generally assumed to be 

constant with age. Thus, some processing is needed to ensure that the leakage rates for the two 

types of emissions are comparable. 

OMEGA converts lifetime refrigerant emissions to their equivalent value in terms of CO2 

emissions per mile (RCO2) considering the change in societal value of CO2 emissions over time. 

The goal is to estimate a level of CO2 emissions per mile, which, if constant over the vehicle’s 

life, like tailpipe CO2 emissions are generally assumed to be, would produce the same societal 

value of CO2 emissions as the distribution of refrigerant emissions over the life of the vehicle. 

This equality is shown in the following equation: 

Equation 3 – Conversion of refrigerant emissions to equivalent lifetime emissions 

Value of Equivalent Lifetime CO2 Tailpipe Emissions = 

Value of Lifetime Refrigerant Emissions 

L L 

RCO 2*[VMT i *ValueofCO 2i]  GWP * [RefLeakagei *ValueofCO 2i] 

i1 i1 

Where: 

VMTi = the annual miles travelled for the relevant class of vehicle at age i, (i.g., VMTi =
 

Survival Fraction for a vehicle of age i times the annual vehicle miles driven for a vehicle
 

of age i as input in the Reference file),
 

L = the lifetime of the vehicle.
 

ValueofCO2i = the societal value of CO2 emissions in the calendar year when the vehicle
 

is at age i,
 

RefLeakagei = the annual rate of refrigerant emissions when the vehicle is at age i, and
 

GWP is the global warming potential of the refrigerant relative to CO2.
 

The value of CO2 in a particular year can be described as its base value divided by one 

plus the applicable discount rate raised to the power of the age of the vehicle. In this case, the 

applicable discount rate is the societal discount rate less the rate of increase in the real value of 

CO2 emissions. Since the normal discounting equation assumes that the relevant activity (e.g., 

26 
payment) occurs at the end of the year and emissions occur throughout the year, we multiply by 

one plus half of the applicable annual discount rate. The resulting equation is described as 

follows: 

DR  IR L 1 

RCO 2(g / mi ) * [VMT i * BaseValueofCO 2 *  2 ]  i1 1  DR  IR 

i 

DR  IR 

L 1

 2 GWP * [RefLeakag ei 

*BaseValueo fCO2* 

i ] 

i1 1 DR  IR 

This equation can be rearranged to solve for the level of CO2 equivalent emissions per mile as 

shown in the next equation. (Note that the societal value of CO2 in the base year falls out of the 

equation.) 

 DR  IR  36 1 

2 

LeakRate i  i 



  GWP i1  1  DR  IR     RCO 2(g / mi )   DR  IR  36 1 



 i 

2 i 



VMT   i1  1  DR  IR    

There are other approaches to converting lifetime refrigerant emissions to their g/mi 

equivalent level. Future versions of OMEGA may provide the user with several approaches 

from which to select. One approach would be to simply allow the user to specify a baseline 

value for g/mi CO2 equivalent refrigerant emissions in the Market file. This way, the user could 

use whatever approach was deemed appropriate to estimate this value. Another approach would 

be the same as the above, except to base the equivalency on physical emissions and remove the 

factors involving discounting. Therefore, if the user desires to perform this equivalency using 

physical emissions, they should set the rate of increase in the societal value of CO2 emission 

reductions to equal the overall societal discount rate being specified. This will cause all of the 

discount factors in the above equation to be equal to 1.0. Then, if the user desires to use a 

different rate of increase in the societal value CO2 emission reductions in the estimation of 

benefits, they can change this value in the benefits calculation spreadsheet. 

D.iii Application of Technology - Methodology 

The portion of the model which applies technology can most easily be described as the multiple 

application of three logical steps. The first step is to determine the vehicle in the “best” position to 

receive the next technological improvement to enable the manufacturer to meet the specified CO2 

27 
emission standard. The second step is to apply this technology, reduce the vehicle’s emissions 

accordingly and add the cost of this technology to the manufacturer’s total cost for this redesign cycle. 

The third step is to assess the compliance situation and act accordingly. If the standard applies to cars 

only, trucks only, cars and trucks combined with a single standard, or cars and trucks combined with two 

distinct standards and a zero trading limit (i.e., no trading), the model will: 

	 Recalculate the manufacturer’s sales and VMT-weighted emissions and compare this new
 

corporate average emission level to the manufacturer’s standard
 

o	 If the manufacturer is now below the standard, determine if the cost of the last technology 

is above or below the threshold cost specified 

 if the cost is below the threshold, the evaluation of this manufacturer is over and 

the model moves onto the next manufacturer; 

 If the cost is above the threshold, the percentage of sales which receive the 

technology is decreased until the standard is just met; the evaluation of this 

manufacturer is over and the model moves onto the next manufacturer. 

	 If the manufacturer is still above the standard, the model goes back to steps 1 and 2 above and 

applies another technology package to further reduce emissions. If no more technology packages 

are available, the model moves onto the next manufacturer. 

If a non-zero trading limit is specified, the model will follow largely the same procedure, but 

additionally will consider the credit trading algorithms. 

Once all manufacturers are in compliance or have exhausted the technology available for their 

vehicles, the model moves to the next redesign cycle and repeats the above sequence of steps. The 

evaluation of the second and any subsequent redesign cycles starts from scratch in that every vehicle 

begins with only those technologies present in the Market file. In other words, the model does not start 

with the technology added in previous redesign cycles. The assumption behind this aspect of the model 

is that manufacturers have the flexibility to reevaluate technology each time a vehicle is being 

redesigned. This could involve the evaluation of a technology which was not available in the prior 

redesign cycle or a technology which had a maximum penetration cap of less than 100%. Of course, 

starting the analysis over each redesign cycle could lead to situations where a manufacturer is projected 

to utilize several very different technologies for most of their vehicles in each of several redesign cycles. 

The user would have to evaluate the reasons for such an outcome and determine if the inputs were 

reasonable or required modification. 

The application of technology, described conceptually above, is described in more detail below. 

In the following formulae, the subscripts (t-1) and (t) indicate vehicle conditions before and after 

applying technology package “t”, respectively. 

D.iii.a Use of Technology phase in “Caps” 

OMEGA 1.4.0 tracks CO2 emissions by fuel and at each package application step within each vehicle. 

Conceptually, a vehicle platform is composed of vehicles, each with its own fuel, CO2 emission rate and 

energy consumption rate. When a technology is fully available (when its cap is 100%), it can be applied 

to all vehicles within a platform. However, when the cap is less than 100%, OMEGA applies the 

technology to only a portion of the vehicle platform. An example follows (Figure IV-1). 

28 
igure

fies the ability to apply technology packages which have caps of less

ng the cap limited packages as separate segments within a platform, we

nt technologies to the subset of veh

hicle platform level is consistent with our platform based approach, in

es would not necessarily replace all instances of other technologies

r a hybrid package, which is often offered in parallel to a conventional

s credit trading between a manufacturer’s car and truck fleets,

e a full range of credit trading scenarios. This trading is

I of the scenarios tab of the Scenario input sheet. Entering a

edit trading and requires manufacturers to comply with the

ir cars and its trucks separately. If the user wants to allow

ished by inputting a large non

allows the model to apply tech

ndard described above. We say “effectively”, because the

the trading limit is not triggered and this cannot be definitively

ature simpl ch have caps of less

than 100%. By effectively treat s within a platform, we

simplify the addition of subse th this technology and

Applying the caps at the form based approach, in

that many cap limited technolog other technologies

platform. As an example, consi rallel to a conventional

Clean Air Act all and truck fleets,

utili rading is

controlled in OMEGA in colum t. Entering a

zero into this column prevents c y with the

levant emission standards for t nts to allow

unlimited trading, this is accom olumn I (e.g.,

). This effectivel h cars and

trucks and meet the combined st cause the

model still checks to ensure that be definitively

ature simplifies the ability to apply technology packages w

than 100%. By effectively treating the cap limited packages as separate segme

icle sales w

Applying the caps at the vehicle platform level is consistent with our pla

that many cap limited technologies would not necessarily replace all instances

platform. As an example, consider a hybrid package, which is often offered in

Clean Air Act allows credit trading between a manufacturer’s car

utilize a full range of credit trading scenarios. This

controlled in OMEGA in column I of the scenarios tab of the Scenario input she

zero into this column prevents credit trading and requires manufacturers to com

levant emission standards for their cars and its trucks separately. If the user w

zero number in

nology across

trucks and meet the combined standard described above. We say “effectively”,

model still checks to ensure that the trading limit is not triggered and this ca

Figure IV-1 – Application of packages 

This model feature simplifies the ability to apply technology packages which have caps of less 

than 100%. By effectively treating the cap limited packages as separate segments within a platform, we 

simplify the addition of subsequent technologies to the subset of vehicle sales with this technology and 

those without it. 

Applying the caps at the vehicle platform level is consistent with our platform based approach, in 

that many cap limited technologies would not necessarily replace all instances of other technologies on a 

platform. As an example, consider a hybrid package, which is often offered in parallel to a conventional 

engine package. 

D.iii.b Credit Trading 

As the Clean Air Act allows credit trading between a manufacturer’s car and truck fleets, 

OMEGA allows the user to utilize a full range of credit trading scenarios. This trading is 

controlled in OMEGA in column I of the scenarios tab of the Scenario input sheet. Entering a 

zero into this column prevents credit trading and requires manufacturers to comply with the 

relevant emission standards for their cars and its trucks separately. If the user wants to allow 

unlimited trading, this is accomplished by inputting a large non-zero number in Column I (e.g., 

1000 g/mi CO2). This effectively allows the model to apply technology across both cars and 

trucks and meet the combined standard described above. We say “effectively”, because the 

model still checks to ensure that the trading limit is not triggered and this cannot be definitively 

29 
determined until compliance is achieved at the end of the evaluation of this manufacturer.16 

Thus, in addition to requiring compliance with the fleetwide average CO2 target, the model must 

also ensure that each fleet complies with its applicable target plus the trading allowance. 

Should a non-zero number be entered in column I, OMEGA determines the overall sales- and 

VMT-weighted emissions target for the manufacturer with cars and trucks combined:17 

+௦஼௔௥ܶ ܸܯ ݕݎ݋ݐ݈ܽݑ ܴ݁݃ ݔ௦ ௖௔௥݀ܽ݀݊ܽݎ ݐܵݔ௦ ௖௔௥ܵܽݏ݈݁

݈݁ݏܵܽ ௧௥௨௖௞௦ݔܵݐ ݎ݀ܽ݀݊ܽ ௧௥௨௖௞௦ݔ ܴ݁݃ ݑ݈ܽݕݎ݋ݐ ܯܸ ܶ௧௥௨௖௞௦

= ௥௙ ௠ݐ ݃ܽܶݎ݁ +௦ ஼௔௥ܸܯܶ ݕݎ݋ݐ݈ܽݑ ܴ݁݃ ݔ௦ ௖௔௥ܵܽݏ݈݁

݈݁ݏܵܽ ௧௥௨௖௞௦ݔ ܴ݁݃ ݑ݈ܽݕݎ݋ݐ ܶܯܸ ௧௥௨௖௞௦

The model also determines the starting point for each manufacturer using the same basic equation 

+௦ ஼௔௥ܸܯܶ ݕݎ݋ݐ݈ܽݑ ܴ݁݃ ݔ௦ ௖௔௥݊݋݅ݏݏ݅ݏ ݁݉ ܤ݁ܽݏ ݔ௦ ௖௔௥ܵܽݏ݈݁

+௦ ஼௔௥ܸܯܶ ݕݎ݋ݐ݈ܽݑ ܴ݁݃ ݔ௦ ௖௔௥ܵܽݏ݈݁ = ௥௙ ௠ ݊݋݅ݏݏ݅ݏ ݁݉ ܤ݁ܽݏ ௦௖௞௨௥௧ܶ ܸܯ ݕݎ݋ݐ݈ܽݑ ܴ݁݃ ݔ௦௖௞௨௥௧ ݊݋݅ݏݏ݅ݏ ݁݉ ܤ݁ܽݏ ݔ௦௖௞௨௥௧ ܵܽݏ݈݁

݈݁ݏܵܽ ௧௥௨௖௞௦ݔ ܴ݁݃ ݑ݈ܽݕݎ݋ݐ ܶܯܸ ௧௥௨௖௞௦

Credits are generated when a manufacturer’s fleet of either cars or trucks overcomplies with the 

applicable standard. The amount of credits generated equals the difference between the sales weighted 

average emission level for that vehicle class and the applicable standard multiplied by the lifetime VMT 

per vehicle for that vehicle class. For either vehicle class, in aggregate, the generated credits are 

calculated by the equation below.

݁݀ݐܽݎ݁

= 

ܩ݁݊ ݏݐ ܥ݁݀ݎ݅

( ݀ܽ݀݊ܽݎ ݐݏ݊݋݅ݏݏ݅ ݁݉ ܥܱݔܶ ܸܯ ݕݎ݋ݐ݈ܽݑ ܴ݁݃ ݔ ܵܽݏ݈݁ )

ሻ ܽݎ݁݃݁ ݒ݊ܽ݋݅ݏݏ݅ ݁݉ ܥܱݔ ܸܯܶ ݕݎ݋ݐ݈ܽݑ ܴ݁݃ ݔ ܵܽݏ݈݁ ሺ െ

ʹ

ʹ
 

Where 

Sales = Sales volume of each car or truck in that redesign cycle, 

Regulatory VMT = Lifetime VMT per vehicle according to regulation (from the reference file). 

CO2 emission standard = The target set in the scenario file 

CO2 emission average = The achieved CO2 level for the vehicles after the application of technology 

Credit use is determined by the same formula, except for the substitution of the vehicles 

from the other vehicle class, as shown below.

݀ܽ݀݊ܽݎ ݐݏ݊݋݅ݏݏ݅ ݁݉ ʹ ܥܱݔܶ ܸܯ ݕݎ݋ݐ݈ܽݑ ܴ݁݃ ݔ ܵܽݏ݈݁ ൌ ݁݀ݏݑݏݐ ܥ݁݀ݎ݅

ʹ

( )

ሻ ܽݎ݁݃݁ ݒ݊ܽ݋݅ݏݏ݅ ݁݉ ܥܱݔ ܸܯܶ ݕݎ݋ݐ݈ܽݑ ܴ݁݃ ݔ ܵܽݏ݈݁ ሺ െ

Where 

Sales = Sales volume of each car or truck in that redesign cycle, 

Regulatory VMT = Lifetime VMT per vehicle according to regulation (from the reference file). 

16 If the trading limit is greater than the emission standard, trading is effectively unlimited.
 17 VMT weighting allows the user to account for the difference in miles driven between difference classes of vehicles and
 

provides for environmentally neutral credit trading:
 

30 
CO2 emission standard = The target set in the scenario file 

CO2 emission average = The achieved CO2 level for the vehicles after the application of technology 

OMEGA utilizes a simple set of algorithms to determine the correct distribution of 

technology between car and truck fleets. OMEGA calculates the level of sales and VMT 

weighted emissions of either car and truck emissions which will generate the maximum 

allowable use of credits by the other vehicle class (the “lower limit”). It then tracks sales and 

VMT weighted car, truck and combined emissions when adding technology. When the sales and 

VMT weighted average emissions for either cars or trucks reaches this lower limit, no additional 

technology is applied to that vehicle class. Technology is only applied to the other vehicle class, 

as this latter class still exceeds the level of its standard plus the allowable trading level. 

For example, assume a trading limit of 10 g/mi CO2 is input and the applicable car and 

truck standards for a manufacturer are 220 and 300 g/mi CO2, respectively. The model 

calculates the combined sales and VMT weighted CO2 emission target using the above equation 

for FleetwideCO2Target, which can be simplified as follows: 

2 

Sales v  LifeVMT v  Target v  vc 1 Fleetwide CO 2Target  2 

Sales v  LifeVMT v 

vc 1 

Where vc represents the two vehicle classes, cars and trucks. 

Once the Fleetwide CO2 Target is known (assumed to be 260 g/mi in this example), this 

same equation can be used to determine the level of average car emissions which achieves 

compliance when the level of average truck emissions exceeds its target by 10 g/mi CO2 (310 

g/mi in this example). For this example, assume this level is 198 g/mi CO2. Any level of 

average car emissions between 198 and 220 g/mi produces credits for trading which can be 

effectively utilized towards compliance by trucks. Likewise, the minimum level of average truck 

emissions which produces useful credits for use towards compliance by cars is determined which 

achieves compliance when the level of average car emissions exceed its target by 10 g/mi CO2 

(230 g/mi in this example). Again, for this example, assume this level is 290 g/mi CO2. 

The model then proceeds to add technologies to cars and trucks (described in greater 

detail below) until one of three criteria is met: 

1) combined car and truck emissions reach 260 g/mi CO2,
 

2) car emissions reach 198 g/mi CO2, or
 

3) truck emissions reach 290 g/mi CO2.
 

If combined car and truck emissions reach 260 g/mi CO2 before the other two criteria are 

met, the evaluation of this manufacturer is complete. The manufacturer complies with the sales 

and VMT weighted standard applicable to cars and trucks combined and any level of trading 

implied is less than the maximum allowed. If criterion 2 is reached first, the model continues to 

evaluate and apply technology, but only to trucks. In this case, the model continues to 

effectively add technology to trucks only until criterion 1 is met (unless insufficient technology 

exists to enable overall compliance). Likewise, if criterion 3 is reached first, the model continues 

to evaluate and apply technology to cars. 

31 
Fleetwide total tailpipe and refrigerant CO2 equivalent emissions are determined in an 

analogous fashion. Compliance is achieved when fleetwide total CO2 is equal to or less than the 

fleetwide CO2 Target. 

D.iv Technology Application Ranking Factors 

The Technology Application Ranking Factor (TARF) is used to rank the application of 

available technology packages across various vehicles. As described above, the user can choose 

between three different TARF equations for ranking technology application: 1) Effective Cost, 2) 

Cost Effectiveness–Society, and 3) Cost Effectiveness–Manufacturer. The first and third TARF 

equations take the view of the manufacturer in determining the application of technology. This 

can be deemed appropriate since the manufacturer controls the decision making process. Since 

the manufacturer must satisfy its customers and regulatory mandates, a manufacturer’s decision 

making processes will reflect these needs, as well. More explicitly, the technology cost is 

assumed to be the full cost of that technology at the consumer level, including research and 

development costs, amortization of capital investment, etc. This cost is generally the same cost 

as EPA estimates in its regulatory support analyses when estimating the cost of new standards.18 

This cost is not necessarily the increment in price that the manufacturer would charge for that 

technology, since price is a function of many factors which can change fairly quickly depending 

on market conditions. The fuel savings of interest are those assumed by a manufacturer to be 

valued by the customer, so they are based on fuel prices including taxes and reflect the 

timeframe which a customer might consider when purchasing a vehicle. The residual value of 

the added technology is not currently reflected in either TARF, but could be added in the future. 

While the first and third TARFS take the veiew of the manufacturer, the second TARF 

takes the view of society in deciding which technologies should be added first. This distinction 

will be described further below. In all three cases, the vehicle with the TARF with the most 

negative value is applied first. 

D.iv.a Effective Cost TARF (TARF No. 1) 

The Effective Cost TARF (EffCost) is defined as the cost of the technology (TechCost) 

less the discounted fuel savings over a specified payback period of vehicle use. The Effective 

Cost TARF was included in the OMEGA model, since it is the equivalent of the technology 

ranking process used in NHTSA’s CAFE compliance Model. It allows a user to match this 

aspect of the Volpe Model when modeling equivalent standards using both models, if this is 

desired. Quantitatively, it is defined as follows: 

1 EffCost  TechCost  FS  CAFEFine 

(1 GAP ) 

TechCost is the cost of technology t per vehicle, as input in the Technology file. Fuel 

consumption per mile (over the compliance test cycle used to determine compliance with the 

input CO2 emission standards) before (FCt-1) and after technology addition (FCt) is calculated as 

follows: 

18 See Section III.H of the Draft Regulatory Impact Analysis to the recent EPA NPRM for the control of GHG emissions 

from cars and light trucks for a discussion of technology costs at the manufacturer and consumer levels. 

32 
CO2t1 FC t1  44 gCO 2 CD t1     12 gC 

CO2TARF ,t FC t  44 gCO 2 CD t     12 gC 

Where:
 

CDt-1 and CDt = the carbon density of the liquid fuel (in terms of grams carbon per gallon) before
 

and after technology application. 

CO2t-1 = the level of tailpipe emissions prior to the application of the technology being evaluated 

(i.e., after the application of technology t-1), and 

CO2TARF,t = the level of tailpipe emissions after application of technology t, without considering 

any cap on the level of the penetration of technology t. 

44g CO2/12 g C = the mass ratio of CO2 to C, used in converting the carbon density of a fuel to 

an emitted mass of carbon dioxide. 

CO2t-1 is the actual level of CO2 emissions from the particular vehicle which would occur 

after the application of all the technologies prior to technology t, considering both the fact that: 

1) some or all of these technology packages may already be present on this vehicle (i.e., the 

TEBs), and 2) there may be caps on the application of one or more of these technology packages 

which are less than 100%. This level is the appropriate “baseline” CO2 level from which to 

evaluate technology t since all previous technologies must be added to the vehicle before 

technology t can be added. 

Please note, that the TARF equations are defined on a per vehicle basis. Consequently, 

OMEGA does not factor in the potential cap on the level of the penetration of technology t into 

the TARF calculation.19 Because the calculation of CO2TARF,t does not consider the impact of 

any cap on technology penetration, this level of CO2 emissions will differ from the CO2 emission 

level of the vehicle should this technology be selected for addition. The equation for the latter 

CO2 emission level is described further below. In order to be consistent with the calculation of 

CO2TARF,t, the technology cost (TechCost) is also determined without consideration of the 

presence of the technology on the vehicle (via the value of CEB) and without consideration of 

the cap on the penetration of the technology. Thus, TechCost is simply the incremental cost of 

the technology listed in the Technology file. 

With these premises, the formulae describing tailpipe CO2 emissions and refrigerant 

emissions after the application of this technology package are as follows: 

19 Amortized capital costs tend to be higher for technologies which are applicable to lower production volumes. However, 

the capital investment of many technologies can be spread across more than one vehicle model. Thus, incorporating the 

capital investment associated with technology into the TARF would not be a simple matter. If explicit consideration of 

capital costs is added to the model’s operation in the future, both the cap on application of a particular technology and the 

sales volume of the vehicle model will likely be relevant and included in the revised TARF. The net result is that the cost of 

each technology should represent that for the timeframe and expected production volume for each redesign cycle. 

33 
CO TARF ,  CO  1 AIE t  2 t 2t1 

Please note that the TEB term is not included when calculating TARFS. This is to 

maintain consistency with the ranking process, which also does not include TEBS. 

GWP t RCO 2  RCO 1 AIE t  TARF ,t 2t1 GWP t1 

The ratio of GWPs reflects the fact that the technology might change the refrigerant used and 

affect the conversion of refrigerant mass emissions to CO2 equivalent emissions. 

Fuel savings without consideration of the gap between on-road and certification fuel 

economy (FS) is calculated as follows. Vehicles can have up to two separate energy sources, a 

liquid fuel (subscript “1” in the equation) and electricity (subscript “2” in the equation ), as 

would be the case with plug in hybrids.20 

௒ା௉௉

௡ݐ ܥ݈݁݁ܿݏ݋ ൅ ௡ݐ ܥ݈݁ݏ݋ ݑ݂ሺ ሻെ௢ݐ ܥ݈݁݁ܿݏ݋ ൅ ௢ݐ ܥ݈݁ݏ݋ ݑ݂ሾሺ ෍ ൌ ܨܵ

௜ୀ௒

Y = cycle no * 5 

PP = payback period [yrs] 

fuelCosto = fuel cost with original technology 

elecCosto = electricity cost with original technology 

fuelCostn = fuel cost with new technology 

elecCostn = electricity cost with new technology 

Where energy costs are: 

൰൨ ܴ௬

2

ܦ൤ ͳ൅ ൬

× ௬ ܸܯܶ ൈ ௢ ܨܥ ൈ ௢ ܨܲ ൦ ෍ ൌ௢ ݐ ܥ݈݁ݏ݋ ݑ݂

௒ା௉௉ ൪ ͳ൅ ܴܦ ௬ ௜ୀ௒

௒ା௉௉ ൰൨ ܴ௬

2

ܦ൤ ͳ൅ ൬

ݏ݋݈݁݁ܿܥ ݐ ௢ൌ ෍ ൦ ܲܧ ௢ ൈ ܧܥ ௢ ൈ ܶܯܸ ௬ × ൪ ͳ൅ ܴܦ ௬ ௜ୀ௒

)]
 

[ ×5 (ͳ െ ݕܿ) ൅ ݕ]

[ ×5 (ͳ െ ݕܿ) ൅ ݕ]

20 For purposes of calculating TARFS, the CO2 credit values from the technology files are treated as both generating CO2 

reductions and fuel savings. This equivalency is required for two reasons. First, from the manufacturer’s perspective, the 

CO2 credit does provide real CO2 benefit towards their CO2 compliance goals. However, as will be seen in the next section, 

providing CO2 benefit without increasing fuel savings in the TARF can provide perverse results, where the denominator is 

increased, but the numerator of the TARF stays constant. Having the credit generate “fuel savings” in the TARF, is a workaround for this issue. 

34 
5 × ൅ ݕ

൰൨ ܴ௬

2

ܦ൤ ͳ ൅ ൬

݂ݑ ݏ݋݈݁ܥ ݐ௧ ൌ ෍ ൦ ܲܨ ௡ ൈ ܨܥ ௧ ൈ ܶܯܸ ௬ × ൪ ͳ൅ ܴܦ ௬

௒ା௉௉

൰൨ ܴ௬

2

ܦ൤ ͳ ൅ ൬

ܿݕ െ ͳ) ൈ ܧܥ ௡ ൈ ܶܯܸ ௬ × ൪ ͳ൅ ܴܦ ௬

FP = fuel (liquid) price [$/gal]
 

FC = fuel (liquid) consumption [gpm]
 

EP = electricity price [$/kWh]
 

EC = electricity consumption [kWh/mi]
 

VMTy = vehicle miles of travel in year y
 

DRy = discount rate for year y
 

t, n = current technology
 

o = original technology from tech-apply step (or baseline) 

i = year index 

Annual fuel prices for both fuels (liquid & electricity) are used 

CAFEFine is the fine a manufacturer pays for failing to meet the CAFE target. The equation for this is: 

1 1 

௢ ܥܣܨܧܨܥ െ ௧ ܥܣܨܧܨܥ

− ܥܣܨܧܨܥ௔ ௩௚ ൈ ቈ ܵܨ௟௖௦

௜ୀ௒

௒ା௉௉

௡ ܧܲ ൦ ෍ ൌ ௧ݐ ܥ݈݁݁ܿݏ݋ ]

௜ୀ௒

[ ( ܿݕ െ ͳ) ] 

 [5 × ) ൅ ݕ

݁݅݊ܥܣܨܧܨ ൌ ܨܧܧ ൈ ቉ ܥܣܨܧܨܥ௔ ௩௚ െ ܵܨ௟௖௦ × (

1
 

)

Where: 

FEE = CAFEFee [$/mpg] 

SFcls = Sales fraction of vehicle in its class, for a given Manufacturer 

CAFEFCo = FCo x CAFE_LFeqv 

(CAFE Weighted Fuel Consumption for baseline technology [gpm]) 

CAFEFCt = FCt x CAFE_LFeqv + ECt x CAFE_ELeqv 

(CAFE Weighted Fuel Consumption for current technology [gpm]) 

CAFEFCavg = Co2target x (12/44) / CDgas 

(Manufacturer’s CAFE Fuel Consumption at the beginning of redesign cycle [gpm]) 

Co2target = manufacturer’s CO2 target [g/mi]
 

CDgas = carbon density of gasoline [g/gal]
 

CAFE_LFeqv = CAFE equivalence factor for liquid fuel [gal/gal]
 

CAFE_ELeqv = CAFE equivalence factor for electricity [gal/kWh]
 

FC = fuel (liquid) consumption [gpm]
 

t = current technology
 

o = original technology from tech-apply step (or baseline) 

A positive value for this TARF indicates that the consumer might view the vehicle less 

desirably with the technology than without. A negative value for this TARF indicates that the 

35 
consumer might view the vehicle more desirably with the technology than without.21 This TARF 

assumes that manufacturers will incrementally add technologies which increase this desirability 

to the maximum extent possible. 

D.iv.b Cost Effectiveness-Society TARF (TARF No. 2) 

The Cost Effectiveness-Society TARF (CostEffSoc) is identical to the Cost Effectiveness–Manufacturer 

TARF (TARF 3) with one exception. The Cost Effectiveness-Society TARF divides the Effective Cost 

TARF by the discounted lifetime CO2 emission reduction instead of the lifetime CO2 emission 

reduction. The discount rate used would be for the value of CO2 emission reductions over time. The 

rationale for discounting is simply that society is presumed to value CO2 reductions in this way. Also, 

in this case, we would recommend that the user increase the payback period for fuel savings to cover the 

life of the vehicle instead of the much shorter period of time often assumed to be considered by 

consumers when purchasing a vehicle. Society values fuel savings over the life of the vehicle and not 

just for the first few years of use. The user could also estimate technology costs from a societal point of 

view if this produced different cost estimates than those used above. The Cost Effectiveness- Society 

TARF can be described mathematically as follows: 

݃݅݊ ݒܵܽଶ ܥܱ ൈݐ ܧ݂݂ܥݏ݋ ൌ ܧܱ݂݂ܵܥ ݐ ܥݏ݋ ሻ ܩܽ݌ ሺͳെ

Where EffCost is defined using the equation in TARF1 

Where CO2Saving is:

ܸ݉ܯܶ ݑݏ ൈ ଶ ݀ܥܱ  ൌ ݃݅݊ ݒܵܽଶ ܥܱ

dCO2	 = delta CO2 as calculated in TARF3 

sumVMT	 = discounted present value of lifetime VMT using the VMT schedules from the reference input 

file 

ቁ ܫܴ ͳ൅ ቀ ܴܦ ௬ − ܶܯܸ ݕ ൈ 2 

ͳ൅ ൫ ܴܦ ௬ െ ܫܴ൯

Where sumVMT: ௡

ා ൌ ܸ݉ܯܶ ݑݏ

௬ୀ଴

VMTy = VMT in year y 

n = vehicle lifetime 

DRy = discount rate [%] for year y 

IR = CO2 value increase rate [%] 

Cost Effectiveness-Manufacturer TARF (TARF No. 3) 

The Cost Effectiveness-Manufacturer TARF represents the degree to which consumer desirability 

might change with the technology on a per ton of CO2 controlled basis. The Effective Cost TARF 

21 Of course, the calculated TARF values are dependent upon the assumed views of consumer valuation of fuel savings, the 

payback period assumed, the discounting over that payback period, and other factors. 

36 

D.iv.c 
ignores the degree to which the technology moves the manufacturer closer to compliance. Thus, a fairly 

expensive technology which produces a large fuel savings might have a fairly large negative Effective 

Cost TARF. The sequence of several less expensive technologies with smaller fuel savings might all 

have less negative Effective Cost TARFs and so would not be chosen over the more expensive 

technology. However, in total, the sequence of smaller steps might achieve the same overall emission 

reduction as the more expensive technology at a lower cost. The Cost Effectiveness–Manufacturer 

TARF would divide these less expensive technologies by smaller CO2 emission reductions, thereby 

imrpoving their TARF values relative to the more expensive technology. This would allow the model to 

choose the sequence of less expensive technologies over the single expensive technology if their 

increase in effective cost per ton of CO2 reduced was higher. 

The Cost Effectiveness-Manufacturer TARF (CostEffManuf) incorporates all of the terms included 

in the effective cost TARF, but also accounts for the degree that the technology brings the manufacturer 

closer to its CO2 standard. It can be described simply as the Effective Cost TARF divided by the mass 

of the CO2 equivalent emission reduction over the life of the vehicle due to addition of the technology. 

The Cost Effectiveness-Manufacturer TARF can be described mathematically as follows: 

݃݅݊ ݒܵܽଶ ܥܱȀݐ ܧ݂݂ܥݏ݋ ൌ ݂ݑ ݊ܽ ܧ݂݂ܯ ݐ ܥݏ݋

Where EffCost is defined using the equation in TARF1 

Where CO2Saving is:

݂݅ܮܸ݁ܯܶ  ൈ ଶ ݀ܥܱ ൌ ݃݅݊ ݒܵܽଶ ܥܱ

lifeVMT = lifetime VMT for a vehicle 

Where dCO2 is: 

ଶ ݀ܥܱ )൫ ൌ ଶ ݌ܥܱ ݐ െ݋ଶ ݌ܥܱ ݐ (݊

tpCO2 = tailpipe CO2 

rfCO2 = refrigerant CO2 

grCO2 = grid CO2 

crCO2 = CO2 credit 

݊) ܱݎܥ݂ ଶ݋െ ܱݎܥ݂ ଶ ( + ݊) ܱܥݎ݃ ଶ݋െ ܱܥݎ݃ ଶ + ( ൅ ሺ ܱܿܥݎ ଶ݋െ ܱܿܥݎ ଶ݊ሻ൯

o = original technology from tech-apply step (or baseline) 

n = new Technology 

(

= original technology from tech-apply step (or baseline) 

= average incremental effectiveness of the new technology 

( ܣܧܫ ͳെ ൈ݋ଶ ݌ܥܱ ݐ ൌ ݊ଶ ݌ܥܱ ݐ

Where tpCO2n is: 

tpCO2o 

AIE
 

37 
ܲ ܩܹ ൈ ݂݁ݎ݅݃ݎܧ݂݂ ൈ݋ଶ ݂ݎܥܱ ൌ ݊ଶ ݂ݎܥܱ

Where rfCO2n is:

rfCO2o = original refrigerant from tech-apply step (or baseline) 

refrigEff = refrigerant effectiveness 

GWP = global warming potentials (varies by refrigerant) 

Where grCO2n is:

ܥݎ ൈ ܥܦ ൈ ݄ܹ݇ܯ݅ ൌ ݊ଶ ݃ܥݎܱ

kWhMi = kilo-watt hours per mile of travel 

CD = carbon density (gC/kWh) 

Cr = CO2/C ratio for electricity = 44.0 / 12.0 

D.v Applying Technology - Calculations 

As described above, for any individual vehicle, technologies are applied in the order in which they 

are listed in the Technology file for the relevant vehicle type. Thus, at the beginning of the evaluation 

for a manufacturer, the only technology which is available to each vehicle is technology package 1 for 

its vehicle type. Thus, the OMEGA model compares the TARF equations for applying technology 

package 1 to all of the vehicles in that manufacturer’s fleet and chooses the vehicle with the most 

negative TARF. The model then applies technology package 1 to that vehicle and reduces its GHG 

emission level. The formulae for calculating the new tailpipe and refrigerant CO2 emission levels after 

application of the technology are shown below: 

CO  CO 2 t 1  1  CAP  AIE 

2 t 1  AIE TEB 

RCO  1 CAP  AIE  GWP 2 t 1 t RCO 2 t  

1 AIE TEB GWP t 1 

Here, both the presence of the technology in the baseline configuration of this vehicle and the 

cap on technology application are considered. The terms shown in the denominators of both equations 

are included due to the definition of the incremental effectiveness of technology. When calculating the 

effectiveness of a technology, the user should assume that the vehicle to which this technology is being 

applied has all of the previous technology packages applied, but none of the additional technologies 

included in the technology of interest. Thus, the incremental effectiveness of hybridization over an 

advanced gasoline engine and transmission package might be 10%. If a specific vehicle or more likely 

group of vehicles already reflected half of this 10% hybrid benefit, it would not be correct to simply 

reduce the effectiveness of the hybrid package to half of the 10% (i.e., 5%) and multiply base emissions 

by 0.95. It is more accurate to remove the effect of the partial hybridization by dividing by 100% minus 

38 
5% (i.e., 0.95) and then multiplying by 100% minus 10% (i.e., 0.9). The net effect in this case is to 

multiply base emissions by 0.9474, which produces a slightly greater emission reduction than 

multiplying by 0.95. For modest technologies, the difference is small. However, for technologies which 

might reduce emissions by 30% or more, the difference in methodology becomes more significant. See 

the section discussing calculation of TEB values. 

The model also adds the cost to the manufacturer’s running total cost and recalculates the 

manufacturer’s corporate average emission level. The formulae used to perform these two calculations 

are as follows: 

Equation 4 – calculation of compliance CO2 value 

ܱܧܤ ൅ ଶ ܥܱ ݐ ݂ܴ݅݃݁ݎܽݎ݊݁ ൅ ଶ ܥܱ ܩ݅݀ݎ ൅ ଶ ܥܱ ݄݁ܿܶ݌ܿ݇ܽ ൌ ଶ ܥܱ

Equation 5 – Total Cost Calculations 

TotalCost t  TotalCost t  1  TechCost  (1CEB )  Sales v 

Equation 6 – Fleet Average CO2 calculations 

V 

Sales  LifeVMT TCO  v v 2 t 

v1 FleetTCO  2 step V

Sales v  LifeVMT v 

v1 

Where:
 

v = a vehicle produced by the manufacturer,
 

V = the total number of vehicles (cars, trucks, or both) produced by that manufacturer,
 

TCO2t= the emissions of the vehicle after application of the technology
 

LifeVMTv = the lifetime VMT of the class of vehicle to which vehicle v belongs. Lifetime VMT is statutory
 

VMT as given in the scenario file.
 

As mentioned above, compliance with the CO2 standards is performed on a sales and VMT 

weighted basis, for ease in trading between cars and trucks under the provisions of the proposed CO2 

standards. 

At this point, the model checks to see if the manufacturer is in compliance with its CO2 emission 

standard. If so, it stops and moves on to the next manufacturer. If not, the model then evaluates the 

TARF for the next technology package for the vehicle which just received the last technology package. 

The model calculates the TARF for this package and compares it to the TARF equations for the 

technology packages 1 for all of the other vehicles. This sequence of adding one technology package to 

one vehicle, reevaluating compliance, and so on, continues until either the manufacturer complies or 

until all the available technologies have been applied. When either of these two endpoints is reached, 

the model moves to evaluating the next manufacturer or the next redesign cycle. 

39 
The model keeps track of a number of intermediate values throughout the process of adding 

technology. These include the order of technology application, the TARF equations for each 

combination of vehicle and technology, the cumulative cost per vehicle, etc. for use in producing the 

various output files. 

V Output Files 

A Summary of Outputs 

The model places each scenario output in a separate subfolder. The name of each of these files 

includes the name of the scenario listed in Column B of the Scenarios tab of the Scenario file. Each of 

these output files and their purpose are summarized in the table below. The main output files are also 

discussed in greater detail later in this section. 

40 
Table 8 – Summary of Model Outputs 

File* Summary Description 

Main Output Files 

X.log Step by step details of the model operation including tech 

pack application, cost, CO2, and electricity. 

X.xls Summary file that includes manufacturer specific details on 

tech pack application, cost, CO2 and electricity. 

X-Techpacksales.log Details on the sales of vehicles by tech pack at the 

completion of the scenario. Useful in tracking technology 

application. 

X-vh1.xls Summary of final cost, emissions, and electricity 

consumption by vehicle 

X-vh2.xls Step by step details of cost by technology pack application, 

summarized by vehicle. 

Diagnostic Output Files 

X-CycleResults.log Repeats data that is contained in X.xls. 

X-DetailedCycleResults.xls Summarized Manufacturer-Fleet results by Fuel type for 

every cycle. 

X-Market-Platform_Mfr.log Data for a Manufacturer/Platform version of the Market.xls 

file 

X-TARF.log Summarizes the TARF of every technology package vehicle 

combination. 

X-TechPackSFx.xls Final Sales Fraction for each Tech Pack on every vehicle 

X-VehicleFuelBreakDown.xls Reports fuel-level summaries for every vehicle. 

X-VehSteps.xls Lists the sales fraction and CO2 emissions for each fuel type 

without all of the extra detail in CO2.log 

Scenario Comparison Table 

SummaryOutputResults.xls Summary table comparing manufacturer-level results across 

all scenarios in the scenario.xls file. 

*X is substituted here for scenario name. 

A.i Log of Technology Application Steps – Text Format 

This file depicts the process of technology application to each manufacturer’s fleet and shows the 

progress being made towards compliance with the specified standards. Please note that the log has 

several different formats which depend upon the user options selected. 

The beginning of the file lists basic information about the model user, the version of OMEGA 

being used and the input files. It then presents the technology application information by redesign cycle 

41 
and within each redesign cycle by manufacturer and within each manufacturer by vehicle class (i.e., cars 

first and then trucks). If a combined car-truck standard is being evaluated, then only one set of 

technology application steps is presented which combines both types of vehicles. At the beginning of 

each redesign cycle, the file describes the standard or standards being evaluated. For universal 

standards, this means the standard itself. For footprint-based standards, the four coefficients described 

in the input file are listed. The file then begins a sequence of sections which apply to a single 

manufacturer and single vehicle class, as shown below. 

The first line lists the manufacturer, its starting CO2 emission level, its CO2 target or standard for 

this scenario and the vehicle class (C for car or combine, and T for Truck). The starting CO2 emission 

level is simply the base CO2 emission level of each vehicle weighted by vehicle sales in this redesign 

cycle. The CO2 standard is either the universal standard listed in the Scenario file, or the foot-print 

based CO2 standard applied to that manufacturer’s vehicles. 

The following lines list the step-by-step application of technology packages. Going through the 

columns, step is simply a numerical counter following by a hyphen. Index identifies the vehicle 

receiving the technology or package and refers to the vehicle number in the Market file. Type shows the 

vehicle type for this vehicle. The first column labeled CO2 pipe shows the tailpipe CO2 emissions prior 

to the application of technology. For the application of technology package 1, this value is the base CO2 

emission level shown in the Market file. For subsequent packages, it is the CO2 emission level resulting 

from the application of the previous technology package. The first column labeled CO2tot stands for 

total CO2 equivalent emissions and is analogous to CO2pipe. CO2tot equals CO2pipe plus refrigerant 

emissions in terms of equivalent CO2 emissions. Again, this is either the base refrigerant emission level 

or the refrigerant emission level after application of the previous technology package. TP is the 

technology package added in this step. TARF is the value of the TARF for this package applied to this 

vehicle. 

The second column labeled CO2pipe shows the tailpipe CO2 emissions after the application of 

the technology package. This value considers the efficiency of the technology package, the cap on the 

percentage of sales which can receive the package, as well as the percentage of that package already 

present on the vehicle (i.e., the TEB). The second column labeled CO2tot shows this value plus the level 

of refrigerant emissions existing after any control which have been applied to these. 

CO2avg represents the corporate average CO2 emission level for this manufacturer and vehicle 

class combination. It will generally decrease after each step of technology application and show 

progress towards the manufacturer’s standard. Occasionally, this value will remain constant. This could 

be due to round off. Or, the vehicle receiving the technology may have already been completely 

equipped with that technology. In this case, the model simply holds both emissions and costs constant 

when it applies the technology. 

kWhavg represents the avg kwh/mile of electricity consumed by the fleet. This includes both the 

baseline electricity and the additional electricity consumed by plug-in vehicles. To be clear, this is the 

average electricity consumed over all miles, not simply the electrically powered miles. 

TotCost represents the cumulative cost in dollars per model year of the technology added up to 

that point. The increment in this value from step to step is the product of three terms: 1) the cost of the 

technology package being added, 2) the sales of the vehicle in this redesign cycle, and 3) the cap minus 

the percentage of that package already present in terms of cost (i.e., CEB) or zero, whichever is higher. 

42 
The very last step of technology addition for each manufacturer and vehicle class combination 

may be shown twice, with “OC” following the second listing. In this case, this step does not represent 

the addition of technology, but a backwards interpolation between the previous two steps of technology 

addition which eliminates the over-compliance which usually results from adding discrete technologies 

to specific vehicles. The presence of this interpolation step depends on the value of the threshold cost 

input specified in the Scenario file and the cost of the last technology package, as discussed above under 

Input files. 

This file can be very useful both for diagnostic and analytical purposes. The presence of the 

TARF values in the file can be useful in identifying technology packages which have relative poor cost 

effectiveness followed by packages with better cost effectiveness. In general, the list of TARF values 

should start out negative and become more positive with continued technology application. The only 

exception to this should be when the same vehicle receives technology in sequential steps. In this case, 

the TARF may become more negative in a successive step, since the OMEGA model could not consider 

the more cost effective technology until it applied the previous technology to that vehicle. When the 

user observes a series of technologies being applied to the same vehicle in successive modeling steps, 

this indicates that separating these technology packages provides little practical purpose in the model 

run. Worse, the relatively poor cost effectiveness of the first of the series of technology packages may 

be causing the model to add technology to other vehicles which have worse cost effectiveness than the 

combination of packages for the vehicle in question. This sequence of technology package additions to 

the same vehicle could also be an indication that the order of technologies might not be appropriate (or 

there might be an error in one of the technology input values). 

From an economic perspective, this file presents the increase in cumulative cost for each 

manufacturer as its average CO2 level is reduced. If a sufficiently stringent CO2 standard (e.g., 50 g/mi) 

is input to the model, manufacturers will not comply with the specified standard. However, the model 

will apply all of the technology available to each vehicle. Thus, the file represents a complete 

relationship between cost and emissions for each manufacturer. By reading the information contained in 

this file into a spreadsheet or other program capable of analysis, the user can quickly determine the cost 

for a wide range of CO2 standards without rerunning OMEGA each time. Since the social costs and 

benefits of CO2 standards tend to be relatively linear with CO2 level, it is possible to represent these 

costs and benefits with simple linear equations. The user can then easily combine the relationship 

between manufacturer’s emission levels and technology costs with social costs and benefits at an 

industry-wide level. It would then be possible to solve for the industry-wide emission levels which 

maximized net societal benefits, produced zero net societal benefit or met some other economic criteria. 

Example: 

The following table depicts a portion of the log file from an OMEGA model run. 

43 
CYCLE 1 Target Coeffs: (A=204.0, B=275.0, C=41.0, D=56.0) , (A=246.0, B=347.0, C=41.0, D=66.0) 

Industry Baseline CO2avg = 287.35, Target CO2avg = 223.31, Fleet Type = 'C' 

Step Index Type CO2pipe CO2tot TP TARF CO2pipe CO2tot CO2avg kwhavg TotCost 

1­ 19 6 405.13 405.13 1 -0.1266 375.33 375.33 286.92 0.0000 33,256,539 

2­ 14 6 403.17 403.17 1 -0.1264 372.63 372.63 286.61 0.0000 57,241,908 

3­ 29 13 446.63 446.63 1 -0.1261 412.62 412.62 286.61 0.0000 57,306,310 

4­ 13 10 392.46 392.46 1 -0.1255 362.57 362.57 286.44 0.0000 70,885,077 

5­ 18 10 389.46 389.46 1 -0.1253 359.8 359.8 286.28 0.0000 83,589,991 

0.0000 

33­ 28 2 232.56 232.56 1 -0.1106 217.03 217.03 267.17 0.0000 2,117,945,615 

34­ 14 6 372.63 372.63 2 -0.0904 357.54 357.54 267.01 0.0000 2,158,753,183 

35­ 14 6 357.54 357.54 3 -0.0973 305.57 305.57 266.49 0.0000 2,238,406,536 

36­ 19 6 375.33 375.33 2 -0.0901 355.62 355.62 266.21 0.0000 2,297,680,885 

0.0000 

54­ 7 5 325.61 325.61 2 -0.0615 300.75 300.75 244.96 0.0000 6,904,283,762 

55­ 7 5 300.75 300.75 3 -0.0779 250.06 250.06 243.95 0.0000 7,106,439,868 

0.0000 

92­ 25 4 250.33 250.33 2 -0.0457 212.85 212.85 225.84 0.0000 11,043,478,070 

93­ 28 2 217.03 217.03 2 -0.0426 203.45 203.45 221.06 0.0000 12,799,723,914 

93-OC 28 2 217.03 217.03 2 -0.0426 216.53 216.53 223.31 0.0000 11,973,039,155 

The first five technologies added to cars in this model run were all the first technology listed for 

each vehicle type (TP = 1). The same is true for steps 6-32 (not shown). Step 33 also adds the first 

technology available to vehicle 28. Step 34 adds the second technology available to vehicle 14, while 

step 35 adds the third technology available to this vehicle. This sequence demonstrates how the model 

evaluates the next available technology for each vehicle when deciding where to add technology next. 

In this case, technology number 3 for vehicle 14 was preferred over any of the second technologies for 

all the other vehicles. Examination of the TARF values explains why this was the case. 

The TARF for the technology number 2 for vehicle 14 was-0.0904, while that for technology 3 

was -0.0973. Thus, if -0.0904 was the lowest TARF for step 34, an even lower TARF would have to be 

the lowest TARF in step 35. When it is observed that the model adds two technologies in a row to the 

same vehicle, the user should question whether the first technology should be modified or the two 

technologies should be combined. The reason for this is that, unless step 34 is the very last technology 

added to enable compliance, the model will never simply add technology 2 to vehicle 14. Vehicle 14 

will always receive either technology 1 or 3. The primary concern is that a relatively high TARF value 

for technology package 2 could inappropriately inhibit the application of the combination of technology 

packages 2 and 3 to this vehicle relative to the application of technologies to other vehicles. 

In this case, the TARFs for technologies 2 and 3 are quite close. Thus, combining them into one 

technology package would not produce substantively different results. The same sequence occurs with 

44 
vehicle 7 later in the run (steps 54 and 55 in the above table). In this latter case, the difference between 

the TARFs is much greater. Combining the two steps may have resulted in the earlier application of the 

two technologies than applying them separately. 

The final three lines of the above table illustrate the interpolation that occurs in the compliance 

determination if the cost of the last technology added exceeds the “threshold” input in the Scenario file. 

After step 93, the manufacturer’s corporate average CO2 level was 221.06 g/mi, while the standard was 

223.31 g/mi. The model adjusted the manufacturer’s corporate average CO2 level to 223.31 g/mi by 

only applying technology 2 to a portion of the sales of vehicle 28. This reduced the overall cost of 

compliance from $12.8 billion to $12.0 billion. Mathematically, this is equivalent to interpolating 

between the average emissions (CO2avg) and cumulative costs of steps 92 and 93. 

A.ii Summary of Cost and Emissions – Excel Format 

This file presents a summary of vehicle and manufacturer costs and emission levels resulting 

from a model run. The file contains summary information about the run, the model user, the version of 

OMEGA being used and the values input on the first tab of the Scenario file. The file then lists five 

types of information by manufacturer and vehicle class: 1) vehicle sales, 2) total costs, 3) cost per 

vehicle, 4) electricity consumption, and 5) emission level per vehicle. 

The file continues by presenting the cost of the technology added to each vehicle and the last 

technology package added to each vehicle. The last section of the file presents the series of technologies 

added to each vehicle. For each technology, the file shows the step (for each manufacturer-vehicle class 

combination) in which the technology was added, the vehicle’s emission levels before and after this 

technology and the incremental total cost of adding this technology. 

A.iii Summary of Technology Pack Distribution – Text format 

This file lists the final distribution of technology packs applied to each vehicle, and takes the 

form of a matrix of vehicles and technology packages, with the sales presented within the matrix. This 

is useful information when calculating technology penetrations. As an example, if 40% of vehicle 7 

sales receive technology package 6, then 40% of vehicle 7 sales have the technologies in package 6.22 

A.iv VH1 / Final summary of Vehicle Attributes– Excel Format 

The “VH1” file lists each vehicle, the final technology package applied to that vehicle, the final 

cost, and various attributes about the vehicle. Most of these attributes are carried through from the 

market data file, however some such as the CO2 emission rate and electricity consumption are modified 

by the model. In many senses, this file is a lower level corollary of the Excel summary file described in 

IV.B, and is useful for determining the average cost increase for a class of vehicles. 

A.vVH2 / Stepwise listing of Vehicle Attributes—Excel Format 

The VH2 file provides the cost and CO2 emissions of each vehicle after each technology package 

is applied. Similar to the VH1 file, it is organized by vehicle. 

22 In rulemaking analyses, EPA typically uses a more detailed methodology to calculate technology penetrations. This 

method is documented in Appendix F of the Interim Join Technical Assessment Report. 

45 
VI Running the Model 

Installing the model should add an “OMEGA” icon to the user’s desktop. OMEGA is started by 

double clicking on this icon. A graphic user interface (GUI) should appear in a few seconds. The 

current GUI is simple and relies on the fact that all of the information needed to run the model is 

contained in the input files. 

Once the GUI appears, the first step is for the user to select the desired scenario file. Click on 

“File” in the menu bar and choose “Open” from the drop down menu. A window will open which 

displays the files contained in the model’s input directory. Double click on the desired Scenario file and 

the model will load the data contained in this file and that in the Market, Technology, Fuel and 

Reference files specified in the Scenario file. The GUI will update and display portions of the Scenario, 

Market and Technology input files. The GUI allows the user to partially navigate through these three 

files in order to confirm that the correct input files were specified in the Scenario file. When everything 

is loaded, the car icon will turn green. 

By default, OMEGA saves output files in the Output subdirectory where the executable is 

installed. However, the user can specify an alternative output directory by selecting File/Output Files 

To... From there, browse to, and select, the desired output directory. As a reminder, the selected output 

directory name will display in the GUI. 

In addition to the standard results, the model can generate a number of outputs which the user 

may select prior to running the model. Click on Log to see a drop-down list of selectable outputs. The 

contents of these outputs are described in Section 4. The user selections are “sticky”, and will remain 

selected (or not) between OMEGA runs. 

The user can now run the cases included in the Scenario file by clicking on the green car button. 

As the model is running, the lower left hand corner of the GUI will indicate progress 

(e.g., processing Scenario 1 of 5, processing Scenario 2 of 5, etc.). If the Scenario file only 

specifies one case to be run, when the model is done with this case, the log (text) file showing 

the sequence of technology addition by manufacturer and by redesign cycle appears. This file, as 

all of the output files, is automatically named with the case name from the Scenario file, with the 

file type “log” added. If more than one case is run, the indicator in the lower left hand corner 

will simply say “Done” and no log files are displayed. 

46