Overview of EPA's MOtor Vehicle
Emission Simulator (MOVES5)
&EPA
United States
Environmental Protection
Agency
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Overview of EPA's MOtor Vehicle
Emission Simulator (MOVES5)
This technical report does not necessarily represent final EPA decisions
or positions. It is intended to present technical analysis of issues using
data that are currently available. The purpose in the release of such
reports is to facilitate the exchange of technical information and to
inform the public of technical developments.
Assessment and Standards Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
NOTICE
United States
Environmental Protection
Agency
EPA-420-R-24-011
November 2024
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Table of Contents
1. Introduction 4
1.1 MOVES Scope 4
1.2 MOVES Versions 8
1.3 MOVES Uses 10
2. Updates for MOVES5 11
2.1 New Regulations
2.2 New Features
2.3 Updates to Emission Rates
2.4 Updates to Fuel Characteristics, Vehicle Populations and Activity
2.5 Updates to User Interface and User Inputs 14
3. MOVES Onroad Algorithms 18
3.1 Running Exhaust and Energy 18
3.2 Start Exhaust 19
3.3 Hotelling Emissions (Extended Idle Exhaust and Auxiliary Power Exhaust) 19
3.4 Crankcase (Running, Start & Extended Idle) 20
3.5 Brake Wear 20
3.6 Tire Wear 20
3.7 Evaporative Permeation 21
3.8 Evaporative Fuel Vapor Venting 21
3.9 Evaporative Fuel Leaks (Liquid Leaks) 21
3.10 Refueling Displacement Vapor and Spillage Loss 22
3.11 Preaggregation 22
4. MOVES Nonroad Algorithms 23
4.1 Running Exhaust 23
4.2 Crankcase Exhaust 23
4.3 Refueling Displacement Vapor and Spillage Loss 24
4.4 Fuel Vapor Venting (Diurnal, Hot Soak and Running Loss) 24
4.5 Permeation: Tank, Hose, Neck, Supply/Return and Vent Hose 24
5. MOVES Software Structure 26
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5.1 MOVES Software Components 27
5.2 MOVES Databases 29
6. MOVES5.0 Results 30
6.1 Onroad 30
6.2 Nonroad 48
7. MOVES Testing and Evaluation 51
7.1 Peer Review 51
7.2 MOVES Review Work Group 51
7.3 Internal Testing 52
7.4 Beta Testing and Shared Release Candidate 52
7.5 Accessibility Testing 52
7.6 MOVES Sensitivity Analysis 52
7.7 Evaluation by Industry-Funded Research Group 52
7.8 Comparisons to Independent Data 53
8. Considerations When Using MOVES 59
9. MOVES5 Documentation 62
10. Acronyms 69
11. References 71
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1. Introduction
EPA's MOtor Vehicle Emission Simulator (MOVES) is a state-of-the-science emissions modeling system
that estimates air pollution emissions for criteria air pollutants, greenhouse gases and air toxics. MOVES
covers onroad vehicles such as cars, trucks, and buses, and nonroad equipment such as bulldozers and
lawnmowers. MOVES does not cover aircraft, locomotives, or commercial marine vessels. MOVES
accounts for the phase-in of federal emissions standards, vehicle and equipment activity, fuels,
temperatures, humidity, and emission control activities such as inspection and maintenance (l/M)
programs.
MOVES models calendar year 1990 and 1999 through 2060. Emissions from onroad and nonroad
sources can be modeled at the national or county scale using either model defaults or user-supplied
inputs. Emissions from onroad sources can also be modeled at a more detailed "project" scale if the user
supplies detailed inputs describing project parameters. The onroad module uses operating mode-
specific emission rates to create a consistent approach across all three scales.
MOVES is a bottom-up emissions model that is designed to estimate emissions from separate physical
emission processes depending on the source. MOVES models "fleet average" emissions, rather than
emissions from individual vehicles or equipment types. And MOVES adjusts emission rates to represent
real-world conditions.
This document provides a high-level overview of MOVES5, the latest official public version of the MOVES
model. The model and supporting materials are available for free download on the EPA MOVES website,
https://www.epa.gov/moves.
1.1 MOVES Scope
The functional scope of MOVES5 is detailed in Table 1-1 below.
Table 1-1 MOVES Scope
Onroad
Nonroad
Geographic
Scope
U.S. including Puerto Rico and U.S.
Virgin Islands with option to aggregate
to county, state or nation3
Same
Scale
Default (national), county or project
National allocated to state and county
Mode
Inventory (grams) or Rates (grams per
activity)
Inventory (although rates can be
generated with integrated post-processing
scripts)
aNote, California uses the California Air Resources Board EMFAC and nonroad models for regulatory purposes.
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Onroad
Nonroad
Time Span
MOVES estimates hourly emissions for
weekdays and weekends by month
and year for calendar years 1990 and
1999 through 2060, with options to
run at more aggregate levels - day,
month or year.
MOVES estimates daily emissions for
weekdays and weekends by month and
year for calendar years 1990 and 1999
through 2060.
Vehicles and
Equipment
MOVES covers all highway vehicles,
divided into 13 source use types
(source types): motorcycles,
passenger cars, passenger trucks, light
commercial trucks, other buses,
transit buses, school buses, refuse
trucks, single-unit short-haul trucks,
single-unit long-haul trucks,
motorhomes, short-haul combination
trucks and long-haul combination
trucks.
MOVES covers nonroad equipment in 12
broad economic sectors: construction,
agriculture, industrial, lawn & garden
(commercial and residential), commercial,
logging, railroad support (excluding
locomotives), recreational vehicles,
recreational marine (pleasure craft;
excluding commercial marine vessels),
airport service (excluding aircraft), oil
field, and underground mining.
Regulatory
Classes
MOVES covers all onroad regulatory
classes (groups of vehicles with similar
emission standards) ranging from
motorcycles to heavy heavy-duty
vehicles.
Most nonroad equipment is classified by
horsepower bin and engine type-
compression ignition (CI), 2-stroke spark
ignition (SI) and 4-stroke SI. Small SI
equipment is further classified by engine
use (handheld and non-handheld) and
engine displacement.
Fuels
MOVES models emissions from
onroad vehicles using gasoline,b
diesel, compressed natural gas (CNG),
electricity0 and ethanol (E85). Fuels
are further characterized by fuel
subtype and fuel formulation.1,2
MOVES models emissions from nonroad
equipment using gasoline,d nonroad
diesel, marine diesel, CNG, and liquid
propane gas (LPG). MOVES does not
model nonroad equipment powered by
electricity. Fuels are further characterized
by fuel subtype and fuel formulation.3
Road Type
MOVES models onroad vehicles on
rural and urban restricted access and
unrestricted access roads. MOVES also
models vehicle emissions associated
with non-driving operation as "off-
network."
MOVES assigns nonroad emissions to the
"nonroad"road type.
b Including ethanol/gasoline blends of up to 15% ethanol.
c Electric vehicles modelled in MOVES include those powered by batteries and by fuel cells.
d Including ethanol/gasoline blends of up to 10% ethanol.
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Onroad
Nonroad
Pollutants and
Energy
Outputs6
MOVES models a long list of criteria
pollutants and their precursor
emissions/ air toxics,4 greenhouse
gases, and energy use for onroad
vehicles. These include total
hydrocarbons (THC), volatile organic
compounds (VOC), carbon monoxide
(CO), nitrogen oxides (N0X),
particulate matter8 (PM25& PM10),
elemental carbon (EC)h, carbon
dioxide (C02), methane (CH4), nitrous
oxide (N20), sulfur dioxide (S02),
ammonia, benzene, ethanol, 1,3
butadiene, formaldehyde,
acetaldehyde, acrolein, polycyclic
aromatic hydrocarbons, metals,
dioxins, and furans. Organic gas
emissions can be output in various
aggregations (e.g., total organic gases
and volatile organic compounds), but
"chemical mechanism species" must
be generated in post-processing.
MOVES models many criteria pollutants
and precursors, air toxics and greenhouse
gases, as well as energy use for nonroad
equipment. These include fuel
consumption, THC, VOC, CO, NOx, PM2.5,
PM10, C02, CH4, S02, ammonia, benzene,
ethanol, 1,3 butadiene, formaldehyde,
acetaldehyde, acrolein, polycyclic
aromatic hydrocarbons, metals, dioxins.
and furans. Organic gas emissions can be
output in various aggregations (e.g., total
organic gases and volatile organic
compounds), but "chemical mechanism
species" and PM species such as
elemental carbon from nonroad
equipment must be generated in post-
processing. Note, MOVES does not model
N20 for nonroad equipment.
Emission
Processes
MOVES calculates emissions for
running, start, extended idle (e.g.,
heavy-duty truck hotelling), brake
wear, tire wear, evaporative
permeation, evaporative fuel vapor
venting, evaporative fuel leaks,
crankcase venting, and refueling vapor
and spillage.1
MOVES calculates emissions from running
exhaust, crankcase venting, refueling
vapor and spillage, evaporative tank
permeation, evaporative hose
permeation, and fuel vapor venting from
diurnal, hot soak and running activity.
e A full list of MOVES pollutants is available in the MOVES "Cheat Sheets" found at
https://github.com/USEPA/EPA MOVES Model/blob/master/docs
f The Clean Air Act identifies six criteria pollutants: ground-level ozone, particulate matter, carbon monoxide, lead,
sulfur dioxide, and nitrogen dioxide.
g PM2.5 refers to fine inhalable particles, with diameters that are generally 2.5 micrometers and smaller. PMi0
describes inhalable particles, with diameters that are generally 10 micrometers and smaller.
h While not exactly equivalent, elemental carbon is often used as a surrogate for black carbon in GHG estimates.
' MOVES does not include the capability to estimate emissions of re-entrained road dust. To estimate emissions
from re-entrained road dust, practitioners should continue to use the latest approved methodologies.
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Onroad
Nonroad
Activity
Outputs
MOVES can output distance travelled,
source hours, source hours operating,
source hours parked, vehicle
population, starts, extended idle
hours, hotelling diesel auxiliary hours,
hotelling battery or plug-in hours, and
hours spent hotelling with all engines
off.
MOVES can output equipment source
hours, equipment population, average
horsepower, and load factors.
MOVES is intended to model the impact of regulatory standards on fleet-wide emissions. MOVES5
incorporates the regulations listed in Table 1-2 as well as many earlier regulations as explained in the
MOVES technical reports.
Table 1-2 Recent Mobile Source Regulations Covered by MOVES
National Onroad Rules:
All onroad control programs
finalized as of the date of
the MOVES5.0.0 release,
including most recently:
Multi-Pollutant Emissions Standards for Model Years 2027 and Later
Light-Duty and Medium-Duty Vehicles (LMDV), March 2024
Greenhouse Gas Emissions Standards for Heavy-Duty Vehicles -
Phase 3 (HDP3), March 2024
Control of Air Pollution from New Motor Vehicles: Heavy-Duty Engine
and Vehicle Standards, January 2023
Revised 2023 and Later Model Year Light-Duty Vehicle Greenhouse
Gas Emissions Standards, December 2021
Safer Affordable Fuel Efficient (SAFE) Vehicles Rule: March 2020
Greenhouse Gas Emissions and Fuel Efficiency Standards for Medium-
and Heavy-Duty Engines and Vehicles—Phase 2: October, 2016
Tier-3 Vehicle Emissions and Fuel Standards Program: March, 2014
2017 and Later Model Year Light-Duty Vehicle Greenhouse Gas
Emissions and Corporate Average Fuel Economy Standards: October,
2012
Greenhouse Gas Emissions Standards and Fuel Efficiency Standards
for Medium- and Heavy-Duty Engines and Vehicles: September, 2011
Regulation of Fuels and Fuel Additives: Modifications to Renewable
Fuel Standard Program (RFS2): December, 2010
National Nonroad Rules:
All nonroad control
programs finalized as of the
date of the MOVES4.0.0
release, including most
recently:
Emissions Standards for New Nonroad Spark-Ignition Engines,
Equipment, and Vessels: October, 2008
Growth and control from Locomotives and Marine Compression-
Ignition Engines Less than 30 Liters per Cylinder: March, 2008
Clean Air Nonroad Diesel Final Rule - Tier 4: May, 2004
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Ozone Transport
California Advanced Clean Trucks Rulej
Commission (OTC)
California Advanced Clean Car 1 Low Emissions Vehicle (LEV) Program
"National Low Emissions
OTC NLEV Program
Vehicle" (NLEV) Program
California Advanced Clean Car 1 Zero Emission Vehicle (ZEV) Program
and California Regulations
Adopted Under Clean Air
Act Section 177
These programs are not
incorporated in MOVES
defaults, but may be
modelled by running MOVES
input tools
State and Local Programs:1"
Inspection and maintenance programs
Fuel programs (also affect gasoline nonroad equipment)
Stage II refueling control programs
1.2 MOVES Versions
EPA's official public versions of MOVES are characterized as "major" releases when they include
substantial changes to onroad criteria pollutant emissions. "Minor" releases include no substantial
changes to onroad criteria emissions - for example, they may include updates to the user interface,
changes to toxic or GHG emissions, or updates to nonroad emission rates.
EPA may also develop internal versions of the model for regulatory and analytic support. These versions
typically lack some features required for a public release, but they are made available in relevant
rulemaking dockets and their updates are generally incorporated into the next official public version.
Table 1-3 summarizes the public release history of MOVES.1
As of this writing, EPA provides support for MOVES versions 3.1 and later. The current list of supported
MOVES versions is available at https://github.com/USEPA/EPA MOVES Model?tab=security-ov-file. We
will provide security updates for these versions as needed.
J As explained in the Vehicle Population and Activity report, the ACT rule was also considered when estimating
national default EV fractions for HD vehicles.
k As explained in the Technical Guidance, states and local areas should check and update default values for all local
programs.
1 MOVES was preceded by EPA's MOBILE and NONROAD series of models. Beginning in 1978, MOBILE estimated
onroad emissions in gram per mile. Beginning in 1998, NONROAD estimated emissions for nonroad sources.
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Table 1-3: MOVES Version History
Public Releases
Release Date
Key Features
MOVES2010
2010
• Onroad only
• Designed to model at project, county, and national scales
MOVES2010a
2010
• Modeled 2012+LD GHG rule
MOVES2010b
2012
• Performance improvements
• Improved vapor venting calculations
MOVES2014
2014
• Modeled Tier 3 and 2017+LD GHG rules
• Updated gasoline fuel effects
• Improved evaporative emissions and air toxics
• Updated onroad activity, vehicle populations and fuels
• Incorporated NONROAD model
MOVES2014a
2015
• Added nonroad VOC and toxics
• Updated default nonroad fuels
• Added new options for user vehicle miles travelled (VMT) input
MOVES2014b
2018
• Improved emission estimates for nonroad mobile sources
• Updated outputs used in air quality modeling
M0VES3
2020
• Updated onroad exhaust emission rates, including HD GHG
Phase 2 and Safer Affordable Fuel Efficiency (SAFE) rules
• Updated onroad activity, vehicle populations and fuels
• Added gliders and off-network idle
• Revised inputs for hotelling and starts
MOVES3.0.1-
MOVES3.0.4
2021-2022
• Updated as detailed in the MOVES3 Update Log.
M0VES3.1
2022
• Added an l/M benefit for Class 2b and 3 gasoline trucks with a
gross vehicle weight rating between 8,500 and 14,000 pounds.
M0VES4
2023
• Accounted for heavy-duty low NOx rule for model years 2027
and later and the light-duty greenhouse gas rule for model years
2023 and later
• Improved the modeling of light-duty electric vehicles and added
heavy-duty battery-electric and fuel-cell vehicles, and CNG long-
haul combination trucks
• Updated vehicle populations, fuel supply, travel activity, and
emission rates
MOVES4.0.1
2024
• Improved interface and repaired minor errors as detailed in the
MOVES4 Update Log
M0VES5m
2024
• Updates as explained in Section 2
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1.3 MOVES Uses
MOVES is used by the U.S. EPA to estimate emission impacts of mobile source regulations and policies,
to generate inputs for other EPA tools, and to generate mobile sector information for national
inventories of air pollutants such as the National Emissions Inventory and AirToxScreen.
U.S. state and local agencies outside of California use MOVES to develop emission inventories for a
variety of regulatory purposes, including the development of state implementation plans (SIPs),
transportation conformity determinations, general conformity determinations, and analyses required
under the National Environmental Policy Act (NEPA), among others.5 EPA provides training6 and
technical guidance on using MOVES for SIP and conformity modeling,7 PM hot-spot analyses,8 and CO
hot-spot analyses,9 including information on how to choose appropriate model inputs. MOVES is also
used for state and local greenhouse gas emission planning.10
Others, including academics and interest groups, may also use MOVES to model the effects of policy
choices and various mobile source scenarios.
When determining if MOVES is appropriate for a given use, modelers should be aware of both EPA
guidance5,710 and the limitations discussed in Section 8 below. Also see "Is MOVES the best tool for my
work?" for suggestions of other resources that may be appropriate when estimating U.S. mobile source
emissions for non-regulatory purposes.11
m If additional updates are made to MOVES, they will be documented in an update log available as a link from the
MOVES page, https://www.epa.gov/moves/latest-version-motor-vehicle-emission-simulator-moves.
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2. Updates for M0VES5
Updates to MOVES5 are detailed in the MOVES5 technical reports for onroad. The most important
changes between MOVES4 and MOVES5 are summarized here. The only change made for nonroad was a
change to fuel properties.1
2.1 New Regulations
MOVES5 accounts for EPA's Light- and Medium-Duty Multi-Pollutant Rule12 (LMDV) with higher
projected electric vehicle (EV) fractions and more stringent standards for carbon dioxide (C02),
particulate matter (PM), non-methane organic gases (NMOG) and oxides of nitrogen (NOx).
MOVES5 also accounts for EPA's Greenhouse Gas Emissions Standards for Heavy-Duty Vehicles—Phase
3ri] (HDP3) with higher projected fractions for zero emission vehicles and updated energy consumption
estimates for heavy-duty vehicles (both ICE and ZEV).13
2.2 New Features
We have expanded detailed calculations for a given analysis year to vehicles up to 40 years old, instead
of 30. MOVES4 and earlier MOVES versions account for only 31 model years in any individual calendar
year analysis (vehicle ages 0 through 30+). Vehicles older than 30 years are assigned characteristics of
age 30 vehicles in these models.
MOVES5 has been updated to account for 41 model years (vehicle ages 0 through 40+). Adding model
years better quantifies emissions from vehicles in the 31-40 age range and allows better modeling of
vehicles without onboard diagnostic systems (OBD) and pre-OBD inspection and maintenance programs.
Vehicles older than 40 years are modelled as 40-year-old vehicles, but the number of vehicles in this
group, and their VMT, is much smaller. Because this change may lead to longer run-times, we provide
improved guidance on constructing faster MOVES runs.7
2.3 Updates to Emission Rates
MOVES5 incorporates new data on brake wear from light- and heavy-duty vehicles14 and new data on
ammonia emissions from CNG vehicles.15
MOVES5 also updates future-year base emission rates16 and fleet-averaging adjustments17 for light- and
medium-duty internal combustion engine C02, PM, hydrocarbons, and NOx associated with the more
stringent standards under the LMDV.
For a more complete list, see Table 2-1.
2.4 Updates to Fuel Characteristics, Vehicle Populations and Activity
The gasoline fuel supply has been updated using data from an expanded nationwide retail survey
program that was implemented following the 2020 Fuels Regulatory Streamlining rule. This program
collects approximately 5,000 retail samples throughout the year distributed across the states
proportional to their share of national gasoline sales, and within each state accounting for population
density and transportation corridors. Starting with calendar year 2021, all the regional gasoline fuel
properties have been redeveloped in MOVES5 based on this retail survey data, which has the benefit of
more accurately representing fuel properties at the point of use. These new data indicate that sulfur
levels are generally higher than in MOVES4, summer RVP values are generally lower, and winter RVP
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values are generally higher. M0VES5 also accounts for recent changes to Reformulated Gasoline
programs in Colorado and Maine, increased default E85 usage, updated default biodiesel blend levels,
and reduced sulfur levels for marine diesel fuel.1 MOVES5 does not change our modeling of how
different fuel parameters affect emissions.2
Updates to national VMT and vehicle population inputs were based on newer historical data from the
Federal Highway Administration (FHWA) and updated forecasts from the Department of Energy.
Updates to national default source type, fuel type, regulatory class, and age distributions were based on
newer vehicle registration data, as well as the EV sales forecasts mentioned in Section 2.2.18
For a more complete list, see Table 2-1.
Table 2-1: Algorithm and Data Updates for MOV ESS and Emission implications
Area
Description of Change and Emission Implications
Energy Consumption
Rates
Updated LD and HD energy consumption rates based on recent data and new
C02 emission standards.1315 Account for fleet average emissions standards.17
These changes lead to significant declines in future year C02.
Electric Vehicle
Fractions
Updated LD and HD ZEV fractions based on recent data and projections that
account for new EPA emission standards.18 These lead to substantial
reductions in exhaust and evaporative pollution after about 2040
Brake Wear PM Rates
• Updated LD and HD brake wear emission rates for MY 2011 and later
based on new test data. In general, the new PM2.5 brake wear rates
are lower for light- and medium-duty vehicles, light-heavy-duty
vehicles, and urban buses, but they are higher for other heavy-vehicle
classes, most notably for heavy-heavy-duty vehicles.
• Account for regenerative braking in electric vehicles.
• Account for light-duty vehicle mass by fuel type.
• Particle size data allowed us to update the brake wear PM10/PM2.5
ratios in MOVES. The new data imply lower PM10 emission rates for
all vehicle classes.1414
Exhaust PM Rates
Updated LD exhaust PM rates that account for new PM standards. The lower
PM rates for gasoline vehicles phase-in beginning in MY 2027.16
Exhaust HC and NOx
Rates
Updated start and running rates and adjustments for LD and 2b3 vehicles to
account for new emission standards16 and new fleet averaging provisions.17
The lower rates phase-in beginning in MY 2027.
Start HC, CO, and
NOx Rates
Updated rates for LD start emissions to account for new emission
standards.16 The lower rates phase-in beginning in MY 2027.
Exhaust Ammonia
Rates
Updated ammonia emission rates for all CNG vehicles based on new data.15
The new rates are lower for MY 2009-and-earlier and higher for MY 2010-
and-later.
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Area
Description of Change and Emission Implications
Age Coverage
Extended MOVES onroad algorithm to allow detailed accounting for ages 0-
40 vehicles, as compared to ages 0-30 in previous version. The improved
modeling of older vehicles leads to increased emissions for most pollutants
through about 2040.
Fuel Characteristics
Updated default fuel characteristics. New surveys of retail gasoline indicate
that sulfur levels are generally higher than predicted in MOVES4,
summer RVP values are generally lower, and winter RVP values are
generally higher. Gasoline properties were updated to account for
changes to Reformulated Gasoline programs in Maine and Colorado.
The national average biodiesel blend level was updated from 3.6 to 3.5
percent. Marine diesel sulfur levels were updated.1
Default Vehicle
Populations and
Activity
Updated historical and forecast default VMT; vehicle populations;
vehicle mix by source type, regulatory class, and fuel type; and age
distributions.18 This change generally increases emissions. No diesel
passenger cars after MY 2019.
Inspection
Maintenance
Program Coverage
Updated descriptions of county-specific l/M programs based on new
information received from states.17
Refueling HC
Emissions
Updated to reflect end of Stage II refueling control programs in some states.22
C02 Equivalent
Emissions
Updated Global Warming Potential (GWP) values used to convert N20 and
CH4to C02 equivalent.13 Additionally, MOVES now requires C02, CH4, and N20
to be included in a run when C02 equivalent is requested.
Exhaust HC, NOx, and
C02.
Improved modeling of medium-duty truck fleet averaging provisions for
vehicles subject to the Tier 3 and HD GHG Phase 2 rules.17
LD HQ CO, NOx and
PM
Updated modeling of LEV III for Section 177 states.
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Area
Description of Change and Emission Implications
Other Minor Fixes
We repaired problems including:
• an error in extended idle PM rates for gliders
• missing PM emissions for CNG long-haul combination trucks
• an issue when aggregating over daylD when using the summary
reporter
• a problem when importing user-supplied start activity for only one
day type
• an issue with reporting the correct units when using the
EmissionRates.sql post-processing script
• an error in summary reporter when selecting certain pollutants
• a problem with starts when pre-aggregating emissions at default scale
• missing pollutants when running Project Scale with a linkID 0
• an error in EV energy rate adjustments for temperature and air
conditioning at project scale
2.5 Updates to User Interface and User Inputs
The MOVES5 interface is very similar to MOVES4. Users will see minor changes to the screens of the
graphical user interface (GUI), but Run Specifications (RunSpecs) created with MOVES4 should work with
MOVES5."
Updates to MOVES databases and calculations mean that user input databases created for previous
versions of MOVES will not work directly with MOVES5. Specifically, all user input tables that include
vehicle age or cover all model years have changed because MOVES5 covers ages 0-40 and model years
1950-2060. For input databases that still contain the latest data, MOVES5 includes conversion tools and
detailed instructions to update MOVES3 and MOVES4 input databases to work with MOVES5.
In addition, we have improved the AVFTTool to make it easier to develop user input fuel type
distributions (including electric vehicle fractions). We also provide updated versions of the following
external tools:
• Age Distribution Projection Tool
• AADVMT Converter Tool
Additional information on changing to MOVES5 from older versions is included in the MOVES5 Technical
Guidance7 and the MOVES5 code documentation at https://github.com/USEPA/EPA MOVES Model.
" The only exception to this is if a MOVES4 RunSpec includes C02 equivalent and one or two (but not all) of C02,
CH4, or N20. Since MOVES5 requires all three to be selected to run C02 equivalent, opening such a RunSpec in the
MOVES GUI will show a red X on the Pollutants and Processes panel. This issue can be resolved by clicking the
"Select Prerequisites" button and saving the RunSpec.
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Inputs for nonroad runs have not changed. Nonroad RunSpecs developed for MOVES4 should generally
work with MOVES5.
The most important interface and user input changes are summarized in Table 2-2.
Table 2-2: Changes in MOVES interface from MOVES4 to MOVES5
Description
Notes
RunSpec Selections
Onroad Vehicles Panel
Source type IDs are now included in the source type description.
Road Type Panel
The Road Type Panel now appears after the Pollutants and
Processes Panel.
• In Default Scale and County Scale, the selections on this
panel will be made for you automatically based on your
selections on the Pollutants and Processes Panel.
• In Project Scale, all on-network road types will be
automatically selected for you if you select a running process.
However, not all road types are necessary in Project Scale,
and you may delete unnecessary types if applicable.
User Tools
AVFT Tool
• Replaced the "fill with Os" gap-filling option with
"automatic". This option fills missing values with Os if
possible. However, if a model year is entirely missing from
the input data, this method fills with default values instead.
• Added the "use defaults, preserve inputs" gap-filling option,
which could be useful if you have inputs for only one fuel
type, for example.
• Gap-filling is run back to model year 1950, allowing easier
use of the outputs with multiple analysis years.
• Improved error checking and handling.
Age Distribution Projection
Tool
• Added an option to automatically insert default age
distributions for long-haul source types.
• Requires input age distributions to cover ages 0-40.
User input DB Converters
Conversion scripts for databases created with MOVES3 and
MOVES4.
User Input Tables
HotellingActivityDistribution
If this optional table is included in a user input database, it must
cover all model years 1950-2060, whereas previous versions only
covered 1960-2060. The database conversion tools can update
the data in this table from MOVES3 or MOVES4 databases for use
with MOVES5.
HotellingAgeFraction
If this optional table is included in a user input database, it must
cover all ages 0-40, whereas previous versions only covered 0-30.
The database conversion tools cannot update the data in this
table from older databases for use with MOVES5.
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Description
Notes
IdleModelYearGrouping
If this optional table is included in a user input database, it must
cover all model years 1950-2060. The database conversion tools
can update the data in this table from MOVES3 or MOVES4
databases for use with MOVES5.
SourceTypeAgeDistribution
This required table in County Scale and Project Scale input
databases must cover all ages 0-40. The database conversion
tools can update the data in this table from MOVES3 or MOVES4
databases for use with MOVES5.
Starts
StartsAgeAdjustment
StartsOpModeDistribution
If these optional tables are included in a user input database, it
must cover all ages 0-40. The database conversion tools cannot
update the data in this table from older databases for use with
MOVES5.
TotalldleFraction
If this optional table is included in a user input database, it must
cover all model years 1950-2060. The database conversion tools
can update the data in this table from MOVES3 or MOVES4
databases for use with MOVES5.
Output Changes
Output Databases
MOVES includes no diesel passenger cars after MY 2019, so these
rows no longer appear in correlated MOVES output.
Changes in GUl
AVFT Tool
• Source types can be included/excluded from the AVFT Tool
output by checking a box.
• Clicking "Create Template" for the Known Fractions input file
now provides a dialog for you to select the source type / fuel
type combinations for which you have known fractions.
Data Manager
• Improved the description of the user option for automatically
assigning worksheets to MOVES input tables
• Added the "Export Defaults" button to the Hotelling tab for
Project Scale
Miscellaneous
• GUI windows now include the MOVES version in their titles
• Improved description of the sources covered by the Nonroad
model
Software Changes
Version updates
MOVES5 is distributed with updated versions of MariaDB, Go,
Java, and Ant.
Command Line Changes
AVFT Tool
The AVFT Tool is now available for use on the command line using
the ant avftTool command.
Default Database Schema
Added new tables
• FleetAvgGroup: describes the fleetAvgGroupID field
• FleetAvgAdjustment: adjusts ICE emission rates based on EV
sales where fleet averaging is allowed
Removed tables
• EVPoplceAdjustLD: this table has been replaced by the new
FleetAvgAdjustment table.
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Description
Notes
Changed schema for existing
tables
• All tables now use UTF-8 encoding, which supports
international use of MOVES as well as changes in Java
libraries used by MOVES.
• RegulatoryClass: added the column fleetAvgGrouplD.
• TemperatureAdjustment: added the column regClasslD.
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3. MOVES On road Algorithms
The way MOVES calculates emissions varies depending on the processes and pollutants being modeled,
and the vehicle or equipment type. This section provides a brief general overview of the algorithms used
to model emissions from cars, trucks and other onroad sources. The MOVES onroad technical reports,
available at https://www.epa.gov/moves/moves-onroad-technical-reports. provide detailed information
on algorithms and default inputs for all onroad source types and pollutant process combinations.
For all onroad processes, the emissions of detailed organic gas and PM species are calculated by
applying appropriate speciation factors.19
For electric vehicles, the only relevant processes in MOVES are brake wear and tire wear, as well as
running and hotelling (for energy consumption).
3.1 Running Exhaust and Energy
Running emissions are the archetypal mobile source emissions—exhaust emissions from a running
vehicle. "Running emissions" also covers energy consumption while running. For internal-combustion
engines, running operation is defined as operation of internal-combustion engines after the engine and
emission control systems have stabilized at operating temperature, i.e., "hot-stabilized" operation.16
The general flow of information to calculate running emissions for onroad sources is summarized in
Figure 3-1, below. The model uses vehicle population information to sort the vehicle population into
source bins defined by vehicle source type, fuel type (gas, diesel, etc.), regulatory class, model year and
age. Regulatory classes define vehicles with similar emission standards, such as heavy heavy-duty
regulatory classes, which may occur in vehicles classified in several different source types, such as long-
haul combination, short-haul single-unit and refuse trucks.18
For each source bin, the model uses vehicle characteristics and activity data (vehicle miles traveled
(VMT), speed, idle fractions and driving cycles) to estimate the source hours in each running operating
mode. The running operating modes are defined by the vehicle's instantaneous vehicle speed,
acceleration and estimated vehicle power.1516 20
Each source bin and operating mode is associated with an emission rate, and these are multiplied by
source hours, adjusted as needed, and summed to estimate the total running emissions. Depending on
the pollutant and vehicle characteristics, MOVES may adjust the running emissions to account for local
fuel parameters,2 heating and air conditioning effects, ambient temperature, humidity, electrical
charging losses, fleet averaging, LD inspection and maintenance programs17 and fuel economy
adjustments.13
18
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Figure 3-1: Calculating Running Emissions for Onroad Vehicles
3.2 Start Exhaust
Onroad "start" emissions are the instantaneous exhaust emissions occur at the engine start (e.g., due to
the fuel rich conditions in the cylinder to initiate combustion) as well as the additional running exhaust
emissions that occur because the engine and emission control systems have not yet stabilized at the
running operating temperature. Operationally, start emissions are defined as the difference in emissions
between an exhaust emissions test with an ambient temperature start and the same test with the
engine and emission control systems already at operating temperature. As such, the units for start
emission rates are instantaneous grams/start.
The model uses vehicle population information to sort the vehicle population into source bins defined
by vehicle source type, fuel type (gas, diesel, etc.), regulatory class, model year and age. The model uses
default data from instrumented vehicles (or user-provided values) to estimate the number of starts for
each source bin and to allocate them among eight operating mode bins defined by the amount of time
parked ("soak time") prior to the start. Thus, the model accounts for different amounts of cooling of the
engine and emission control systems. Each source bin and operating mode has an associated g/start
emission rate. Start emissions are also adjusted to account for fuel characteristics, LD inspection and
maintenance programs, fleet averaging, and ambient temperatures.1516
3.3 Hotelling Emissions (Extended Idle Exhaust and Auxiliary Power Exhaust)
MOVES defines "hotelling" as any long period of time (e.g., > 1 hour) that drivers spend in their long-
haul combination truck vehicles (source type 62) during mandated rest times. Hotelling is differentiated
from off-network idling because the exhaust temperatures and engine load may differ, causing different
emissions.
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The default MOVES hotelling hours are computed as a fixed ratio to the miles these trucks travel on
restricted access roads.18
The hotelling algorithm applies only to long-haul combination trucks. Hotelling activity is allocated
among four operating modes: engine idle ("extended idle"), diesel auxiliary power unit (APU) use,
"Shore Power/' i.e., plugged-in, and "Battery or All Engines and Accessories Off." This allocation varies
by model year and fuel type.18 MOVES computes emissions for extended idle and APU use based on the
hours and source-bin specific emission rates. Hotelling NOx emissions are adjusted for ambient
humidity. In MOVES output, extended idle, APU, and shore power are assigned separate emission
processes.15
3.4 Crankcase (Running, Start & Extended Idle)
Crankcase emissions include combustion products that pass by the piston rings of a compression ignition
engine as well as oil droplets from the engine components and engine crankcase that are vented to the
atmosphere.21
In MOVES, onroad crankcase emissions are computed as a ratio to the exhaust emissions, with separate
values for running, start and hotelling (extended idle mode only). The crankcase ratio varies by
pollutant, sourcetype, regulatory class, fuel type, model year and exhaust process.15
3.5 Brake Wear
Brake pads lose material during braking. A portion of this lost material becomes airborne particulate
matter. This "brake wear" differs from exhaust PM in its size and chemical composition.
MOVES estimates brake wear from onroad vehicles using weighted average g/hour rates. The emission
rates vary by vehicle regulatory class and fuel type.0 They were developed using emissions test data that
included brake pad composition, number and type of brakes, and braking intensity. The rates account
for average vehicle weight and for regenerative braking by electric vehicles.14
Braking activity is modeled as a portion of running activity. In MOVES, the running operating modes for
braking, idling and coasting (opModes IDs 0, 1, 11, 21, 33) are all modeled as including some amount of
braking. The operating mode "brakewear; stopped" (opMode 501) can be used at the project scale to
model emissions of an idling vehicle with no braking.14
3.6 Tire Wear
Contact between tires and the road surface causes tires to wear, and a portion of this material becomes
airborne. This "tire wear" differs from exhaust PM in its size and chemical composition.
MOVES tire wear rates in g/hr are based on analysis of LD tire wear rates as a function of vehicle speed,
extrapolated to other vehicles based on the number and size of tires. The analysis also considers the
° For heavy-duty vehicles, all fuel types within a regulatory class are modeled with the same mass. For example,
we assume that the electric HD fleet has the same vehicle characteristics (weight, wheel configuration, number of
axles, etc.) as its non-EV counterpart, because we lacked data on the weight of HD EVs and assume that heavy-
duty truck weights depend less on powertrain weight and more on payload and GVWR.
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fraction of tire wear that becomes airborne. The tire wear operating mode bins differ from those used
for running emissions and brake wear because they account only for speed and not for acceleration.14
3.7 Evaporative Permeation
Permeation is the migration of hydrocarbons through materials in the fuel system. Permeation
emissions are strongly influenced by the materials used for fuel tank walls, hoses, and seals, and by the
temperature, vapor pressure and ethanol content of the fuel.
In MOVES, permeation is estimated only for vehicles using gasoline-based fuels (including E-85).
Permeation is estimated for every hour of the day, regardless of activity. Permeation rates in g/hour
vary by model year to account for the phase-in of tighter standards. Permeation emissions are adjusted
to account for gasoline fuel properties and ambient temperatures.22
3.8 Evaporative Fuel Vapor Venting
When gasoline fuel tank temperatures rise due to vehicle operation or increased ambient temperatures,
hydrocarbon vapors are generated within the fuel tank. The escape of these vapors is called Tank Vapor
Venting (TVV) or Evaporative Fuel Vapor Venting. This vapor venting may be eliminated with a fully
sealed metal fuel tank. More commonly, venting is reduced by using an activated charcoal canister to
adsorb the vapors as they are generated; vapors from the canister are later consumed during vehicle
operation. However, to prevent pressure build-up, canisters are open to the atmosphere, and after
several days without operating, fuel vapors can diffuse through the charcoal or pass freely through a
completely saturated canister. Tampering, mal-maintenance, vapor leaks and system failure can also
result in excess vapor venting.
MOVES calculates vapor venting only for vehicles using gasoline-based fuels (including E-85). The tank
vapor generated depends on the rise in fuel tank temperature, fuel vapor pressure, ethanol content and
altitude. Fuel tank temperature changes are modeled as a function of 24-hour temperature patterns and
default vehicle activity, with different vapor generation rates for vehicles that are operating, "hot
soaking" (parked, but still warm) and "cold soaking" (parked at ambient temperature). MOVES
evaporative emission calculations have not been updated for off-network idle and thus model this idle
time as hours parked. Vapor venting is modeled as a function of vapor generated, days cold soaking,
model-year specific vehicle fuel system characteristics, and age and model year related vapor leak rates.
Inspection and maintenance (l/M) programs can also impact leak prevalence rates.22
3.9 Evaporative Fuel Leaks (Liquid Leaks)
Liquid leaks are fuels escaping the gasoline fuel system in a non-vapor form. In MOVES, they are referred
to as evaporative fuel leaks because they subsequently evaporate into the atmosphere after escaping
the vehicle. These leaks may occur due to failures with fuel system materials, or due to tampering or
mal-maintenance. Liquid spillage during refueling is modeled separately as part of the refueling process.
In MOVES, fuel leak frequency is estimated as a function of vehicle age and vehicle emission standards.
Fuel leak size (g/hour) is a function of age and vehicle operating mode (cold soaking, hot soaking or
operating).22
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3.10 Refueling Displacement Vapor and Spillage Loss
Refueling emissions are the displaced fuel vapors when liquid fuel is added to the vehicle tank. Refueling
spillage is the vapor emissions from any liquid fuel that is spilled during refueling and subsequently
evaporates. Diesel vehicles are assumed to have negligible vapor displacement, but MOVES does
compute emissions for onroad diesel fuel spillage.
Refueling vapor and spillage emissions are estimated from the total volume of fuel dispensed (gallons).
This volume is based on previously calculated fuel consumption. In addition, refueling emissions are a
function of gasoline vapor pressure, ambient temperatures, the presence of an on-board refueling vapor
recovery system (ORVR) on the vehicles, and the use of Stage II vapor recovery controls at the refueling
pump. The effectiveness of ORVR systems decline with age.22
3.11 Preaggregation
MOVES is designed to calculate emissions for each selected county and hour, and then to aggregate
emissions to the level of output detail selected in the RunSpec. However, modelers may sometimes
choose to simplify MOVES calculations by preaggregating MOVES inputs to cover larger geographic or
temporal scales. For example, modelers may run MOVES for the nation as a whole or for an entire year.
When a user selects preaggregation, average values for MOVES inputs are calculated as activity-
weighted distributions or averages. For geographical preaggregation, the StartAllocFactor column in the
Zone table is used as a weighting factor. StartAllocFactor contains the ratio of each county's VMT to the
total national VMT, based on data from the NEI. Temporal preaggregation from Hour to Day is based
upon the values in the HourVMTFraction table; the weighting used for the Month aggregation is based
upon the values in the DayVMTFraction table; and the activity weighting used for the Year aggregation is
based upon the values in the MonthVMTFraction table.
Runs with geographic or temporal preaggregation lack important detail and tend to underestimate
emissions; they do not meet the regulatory requirements for SIPs and conformity determinations.7
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4. MOVES Nonroad Algorithms
This section provides a brief general overview of the algorithms used to model emissions from nonroad
equipment types. These calculations vary depending on the processes and pollutants being modeled and
the equipment type. They also depend on whether the equipment uses a spark-ignition (SI) or
compression-ignition (CI) engine, and the engine horsepower (hp) size class. The MOVES nonroad
technical reports at https://www.epa.gov/moves/nonroad-technical-reports provide detailed
information on algorithms and inputs for the nonroad calculations.
The MOVES nonroad module estimates emissions as the product of an adjusted emission factor
multiplied by rated power, load factor, engine population and activity. Starting with base-year
equipment populations by technology type and model year, the model uses growth factors to estimate
the population in the analysis year. Estimates of median life at full load, load factors, activity and age
distributions are then combined to generate estimates of nonroad emissions by equipment type, fuel
type and age. Equipment populations are also allocated to county and season; national equipment
populations are allocated to the county level using surrogate data.
The nonroad module has importers for user information on meteorology and fuels, and a "generic"
importer that can be used to enter data on retrofit programs. We recommend accounting for custom
population and activity using post-processing scripts as explained in the MOVES training and technical
guidance.
For all nonroad processes, toxics are estimated in the nonroad portion of the model, but detailed TOG
speciation and speciation of PM2.5 must be post-processed.23
4.1 Running Exhaust
For nonroad, "running exhaust" emissions include exhaust emissions both at start and during running
operation.
The MOVES nonroad module calculates an emission factor for THC, CO, N0X, PM and brake-specific fuel
consumption (BSFC)P as the product of a steady-state emission factor for new ("zero-hour") engines, a
transient adjustment factor if needed to represent typical operation, and a deterioration factor to
account for wear and aging. Gasoline THC, CO and N0X emissions are adjusted to account for gasoline
oxygenate content. S02 emissions from all nonroad equipment is a function of BSFC and fuel sulfur level.
Diesel PM emissions are adjusted to account for diesel fuel sulfur levels.24 Temperature effects are
applied to THC, CO and N0X exhaust emissions from 4-stroke SI engines.25
4.2 Crankcase Exhaust
Crankcase emissions are those emissions that escape from the combustion chamber past the piston
rings into the crankcase and out to the atmosphere. The MOVES nonroad module models THC crankcase
p When BSFC is selected as a "pollutant" in the MOVES RunSpec, MOVES will output fuel consumption. Although it
is labeled "brake-specific fuel consumption," the output is total mass of fuel. The units depend on the units
selected on the "General Output" panel.
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emissions for four-stroke spark-ignition engines that have open crankcases26 and for all compression-
ignition engines prior to implementation of the Tier 4 NR diesel standard.27
4.3 Refueling Displacement Vapor and Spillage Loss
Refueling emissions are the displaced fuel vapors when liquid fuel is added to the equipment fuel tank.
Refueling spillage is the vapor emissions from any liquid fuel that is spilled during refueling and
subsequently evaporates.28
For both spillage and vapor displacement, the MOVES nonroad module initially calculates an THC
emission factor in terms of grams of emissions per gallon of gasoline fuel consumed. Fuel consumption
is then used to calculate total emissions. The g/gal emission factor varies as a function of fuel tank
volume, gasoline RVP, ambient and dispensed fuel temperatures, and whether the equipment is more
likely fueled using a portable container or at the pump, and the use of Stage II vapor recovery controls at
the refueling pump.
No refueling emissions are reported for diesel, CNG or LPG nonroad equipment.
4.4 Fuel Vapor Venting (Diurnal, Hot Soak and Running Loss)
Fuel vapor venting emissions for nonroad equipment are analogous to the evaporative vapor venting
emissions for onroad vehicles. Diurnal emissions are vapors generated due to temperature changes
throughout the day; running emissions are generated by heating caused by engine operation, and hot
soak emissions are generated from residual heat from the equipment just after the engine is shut off.
In general, diurnal emissions are calculated based on equipment standards, percent tank fill, percent
headspace, tank size, vapor pressure of the fuel, and the minimum and maximum ambient temperature.
Diurnal emissions for recreational marine emissions are calculated slightly differently. Running loss
emissions are calculated as a function of operating time and are not affected by ambient temperatures.
Hot soak emissions are a function of default equipment starts/hour and gram/start rates.
No fuel vapor venting emissions are reported for diesel, CNG or LPG nonroad equipment.29
4.5 Permeation: Tank, Hose, Neck, Supply/Return and Vent Hose
Permeation is the migration of hydrocarbons through materials in the fuel system. Permeation
emissions are strongly influenced by the materials used for fuel tank walls, hoses, and seals—and are
also affected by the temperature, vapor pressure and ethanol content of the fuel.
The MOVES nonroad module calculates various types of permeation. No permeation is calculated for
spark-ignition engines larger than 25 hp because they usually have impermeable metal fuel tanks and
lines.
Fuel tank permeation is calculated as the product of the inside area of the fuel tank, a tank permeation
emission factor that varies with equipment emission standard and a temperature adjustment. The
permeation is also adjusted to account for the market share of ethanol blend gasolines.
Fuel hose permeation is calculated as the product of the surface area of non-metal hoses, a hose
permeation emission factor that varies with equipment size category and emission standard, and a
temperature adjustment. For recreational marine equipment, separate fuel hose emissions are
calculated for the supply/return, fill neck, and vent lines.
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No permeation emissions are reported for diesel, CNG or LPG nonroad equipment.29
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5. M OVES Softwa re Structu re
MOVES is written in Java (compiled with Microsoft's build of OpenJDK), MariaDB, and the Go
programming language. The MOVES Nonroad module is written in Fortran. The principal user inputs,
outputs and most of the model's internal working storage are held in MariaDB databases. The model
includes a default database with emission rates, adjustment factors, and relevant information for all U.S.
counties. The default database supports model runs for calendar years 1990 and 1999-2060.
The MOVES architecture was originally designed to model only onroad vehicles. In 2014, the existing
NONROAD2008 model was integrated into MOVES as the "MOVES nonroad module". The nonroad
module uses the same interface as the rest of MOVES, but the calculations are handled by a separate
Fortran program.
MOVES uses a main-process/worker-process program architecture that enables multiple computers to
work together on a single model run. However, a single computer can be used to execute MOVES runs
by running both the main and worker components on the same computer.
The following diagram illustrates the overall flow of processing in MOVES highlighting the division of
work between the MOVES Main and Worker programs.
In general, modelers use the GUI to create a RunSpec that specifies the scope and options for a given
run. It can be started via the GUI or the command line. Based on the contents of the RunSpec, MOVES
Main selects relevant data from the Default Database and any user-provided input databases (e.g.,
county and project databases) and performs any internal pre-processes needed to generate an
Execution Database with all the data needed for the run. Then MOVES Main runs the calculators for the
run. MOVES Main creates bundles of work (TODO files) to be performed by MOVES Workers. After the
Workers finish processing the bundles, they send them back to MOVES Main as DONE files. Finally,
MOVES Main retrieves the DONE files and completes any final aggregation before saving the results in
the MOVES Output Database indicated in the RunSpec.
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Figure 5-1- Diagram of MOVES information flow
5,1 MOVES Software Components
Looking at this architecture in greater detail, the MOVES software application consists of several
components, introduced briefly in this chapter. More information is available in the documentation at
the MOVES GitHub site, https://github.com/USEPA/EPA MOVES Model/tree/master/docs.
RunSpec
Users create a RunSpec file to define the place and time period of the analysis as well as the vehicle
types, road types, fuel types, emission processes, and pollutants that will be included in the analysis. The
RunSpec also specifies the input and output databases that will be used for the run. The RunSpec is a
text file in XML format that can be edited and executed directly, or that can be accessed, changed, and
run through the MOVES GUI. For more information, see the MOVES training.
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MOVES Graphical User Interface (GUI)
The MOVES GUI is a Java program that may be used to create, save, load, and modify a RunSpec, and to
initiate and monitor the status of a model run. The MOVES GUI also includes data managers that assist
users in building the input databases required for county and project scale runs and includes error-
checking code to ensure that the RunSpec and inputs are consistent with MOVES algorithms and
capabilities.
MOVES Main Program
When the run is started, MOVES Main uses information in the RunSpec, the default database, and the
user input domain database to generate the execution database specific to the MOVES run. This is done
using "Generator" modules. The Main program then bundles data and calculation instructions into ToDo
files to be processed by MOVES Workers. The MOVES Main also compiles the results returned from the
MOVES Workers via Done files into the MOVES output database and performs final aggregation steps.
During the MOVES run, both the ToDo and Done files are stored in the SharedWork directory which
must be accessible to both the Main and Worker programs.
Note that only one executing MOVES Main program can be used during a MOVES run. That is, a single
computer can run only one RunSpec at a time.
MOVES Worker Program
The MOVES Worker program processes the ToDo files created by the MOVES Main program and returns
the results as Done files. This processing is done by various "Calculator" modules.
At least one executing copy of this program is needed to complete a MOVES run. Running multiple
MOVES Worker programs during a MOVES run enables ToDo files to be processed in parallel. While this
capability may reduce the duration of a MOVES run, the improvement in performance strongly depends
on the contents of the RunSpec and the computing environment. The MOVES Worker program may be
executed on the same computer as the MOVES Main program, or on other computer(s) having access to
the SharedWork file directory.q
MOVES Nonroad Module
The code used to model nonroad emissions in MOVES predates the MOVES model. Beginning with
MOVES2014, the standalone NONROAD model was incorporated into MOVES such that the NONROAD
Fortran program is called by the MOVES Worker program. MOVES supplies the Fortran program with the
appropriate flat file inputs based on values from the MOVES default database and any optional user
input databases. Note that nonroad and onroad share the same default meteorology and fuel inputs.
After the MOVES Worker executes the NONROAD Fortran program, it post-processes the Fortran output
flat files and saves the results in the MOVES output database.
q See additional information on configuring MOVES for faster runs at
https://github.com/USEPA/EPA MOVES Model/blob/master/docs/TipsForFasterMOVESRuns.pdf
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Later minor releases of MOVES2014 improved nonroad population growth estimates and diesel
emission factors, in addition to new features including Go-based calculators that compute nonroad fuel
subtype splits, some nonroad THC species, and nonroad air toxics.
5.2 MOVES Databases
The MOVES model stores and accesses data for its calculations in a series of MariaDB databases. This
section introduces the different types of MOVES databases, and how they are used by the program. A
detailed description of each MOVES input and output table is available at MOVES Database Tables.
Default Database
The default database is included in the MOVES Installation Package and is required for MOVES to run.
This database contains the required emission factors, adjustment factors, fuel data, and default vehicle
population and activity data for all U.S. counties to support model runs for calendar years 1990 and
1999-2060.
User Input Databases
User databases may contain any of the tables that are in the default input database and are used to add
or replace records as input by the user; EPA's MOVES Technical Guidance7 describes which data inputs
must be updated by the user for SIP and conformity purposes. These databases typically contain region-
specific fuels, vehicle populations, age distributions, activity, and where applicable, l/M program
characteristics. These databases are optional for a default run, but user input is required for runs at the
County or Project Scale. The MOVES GUI includes a County Data Manager and a Project Data Manager
that assist the user in creating an input database that contains all the necessary data for a MOVES run.
The MOVESExecution Database
The MOVESExecution database is created by the MOVES Main program. It is used for temporary working
storage during the MOVES run. Users do not interact with this database.
MOVES Output Databases
These databases are the final outputs of MOVES runs. The output database name is specified by the user
in the RunSpec. Output for Emission Inventory mode runs is contained in the movesOutput table.
Emission Rates mode produces output in multiple tables.
The output databases also include tables that describe each run in the output, activity data, translation
tables for the codes used in the output, information on errors during the run, and other tables used for
diagnostics and troubleshooting.
MOVESWorker Database
This temporary database is used as working storage by the MOVES Worker Program. When running with
multiple MOVES Workers, each Worker program creates its own MOVESWorker database. The user does
not interact directly with this database.
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6. MOVES5.0 Results
Vehicle and equipment emissions vary by location and time. This section shows MOVES5 results for the
United States as a whole, based on national defaults. For brevity, the graphs here show only a few of the
pollutants calculated by MOVES and are aggregated by fuel type and calendar year.
However, for the most accurate results for a given time and location, it is important to run MOVES for
the specific case using accurate local inputs. In contrast, the national results shared in this document are
calculated based on average inputs that do not fully capture the variation in emissions from time to time
and place to place. For selected pollutants, we also show onroad results for two sample urban counties
as modeled at County Scale with county-specific inputs. While the two counties shown here differ in
their traffic mix, fuels, and meteorology, they are not intended to represent the full range of local
trends. To understand mobile source emissions in a particular county, one must model that county.
These caveats are also true for the average emission rates EPA provides to the Bureau of Transportation
Statistics (https://www.bts.gov/content/estimated-national-average-vehicle-emissions-rates-vehicle-
vehicle-type-using-gasoline-and).
Additional emission summaries for selected past years are available from the National Emissions
Inventory (https://www.epa.gov/air-emissions-inventories/national-emissions-inventory-nei). The NEI
emissions are calculated with county-level inputs; NEI mobile source inventories prior to the 2023 NEI
were generated with previous versions of MOVES and thus lack M0VES5 updates.
6.1 Onroad
The following plots summarize key results for onroad vehicles from running M0VES5 at the national,
annual level using default inputs as compared to runs using the previous model, MOVES4.0.1.30 Because
results for specific times and locations will vary, for some pollutants, we also show results for two
sample urban counties with county-specific fleet, fuel, and meteorological conditions.
Compared to M0VES4, M0VES5 generally predicts higher national emissions for years prior to about
2040. This reflects the change to better account for older vehicles as well as other changes detailed in
Section 2. The exception is C02, which is generally lower in M0VES5 starting in the early 2020s.
Figure 6-1 shows a shift in M0VES5 defaults to more E-85, CNG and EV VMT and a decrease in VMT from
gasoline and diesel vehicles. There is a slight decrease in total vehicle miles travelled starting in 2022.
30
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VMT
Version
MOVES4.0.1
-- MOVES5
Fuel Type
— Gas
— Diesel
— CNG
E-85
EV
2010 2020 2030 2040 2050 2060
Calendar Year
Black line shows total VMT
Figure 6-1—National onroad vehicle miles travelled (VMT) by fuel type in MOVES5 as compared to MOVES4.0.1. Note the y-axis
is in log space. The black lines are totals across all fuel types.
For county level runs, modelers must enter county-specific VMT and fuel mix. Figure 6-2 illustrates VMT
for two example counties. In these county runs, total VMT and most other inputs are the same for the
MOVES4 and MOVES5 runs. However, the MOVES5 inputs include EV fractions consistent with the new
EPA GHG rules and the 41-year age distributions. For both MOVES4 and MOVES5, County A includes
future year electric vehicle population fractions that are proportional to the county's historic share of
national EVs. In contrast, County B includes future year electric vehicle population fractions that reflect
adoption of California's Advanced Clean Car I (2012) and Advanced Clean Trucks (2020) rules requiring
electric vehicle sales for light- and heavy-duty vehicles. In both counties, the expected effect of the new
EPA GHG rules is visible in the MOVES5 EV VMT starting in the early 2030s. The VMT values shown here
are used as inputs in the sample county illustrations below.
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County Scale Input VMT by Fuel Type
County A
Fuel Type
County Scale Input VMT by Fuel Type
County B
Fuel Type
Figure 6-2—Sample county-specific onroad vehicle miles travelled (VMT) in MOVES4.0.1 and MOVES5. Percentage values
indicate change compared to calendar year 2021. The values shown here are used in the sample county illustrations below.
Greenhouse Gases
While total VMT is quite similar in both models, for exhaust C02 (Figure 6-3), M0VES5 projects
substantially greater decreases over time than M0VES4. This reflects the shift to more EVs as well as
more efficient vehicles with internal combustion engines.
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Atmospheric C02
CO
=j
Version
MOVES4.0.1
MOVES5
Calendar Year
Figure 6-3—Notional onrood corbon dioxide in MOVES5 as compared to MOVES4.0.1. Note the y-axis is in log space.
Similar C02 reductions are seen at the county level (Figure 6-4). As noted above, County A is modeled
with EPA rules only. County B is modeled with California's Advanced Clean Car I (2012) and Advanced
Clean Trucks (2020) rules requiring electric vehicle sales for light- and heavy-duty vehicles.
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C02 by Fuel Type
County A
12,500,000-
10,000,000-
H
(/)
5,000,000 -
Fuel Type
C02 by Fuel Type
County B
w 3,000,000"
U)
D
1,000,000"
Fuel Type
Figure 6-4—Sample county-specific onroad carbon dioxide in MOVES4.0.1 and MOVES5. Percentage values indicate change
compared to calendar year 2021.
As shown in Figure 6-5, both models predict a pre-2020 decline in methane emissions from onroad
vehicles, followed by an increase in later years; however, MOVES5 emissions are higher than MOVES4 in
all years. In later years, this reflects the shift in MOVES defaults to include more activity from CNG
vehicles, which have high methane emissions.
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Methane (CH4)
° 1 e+04-
c/j
=j
2030 2040
Calendar Year
Version
— MOVES4.0.1
MOVES5
Fuel Type
— Gas
— Diesel
— CNG
E-85
2050 2060
Black line shows total inventory
Figure 6-5—National onroad methane in MOVES5 as compared to MOVES4.0.1. Note the y-axis is in log space. The black lines
are totals across all fuel types.
MOVES inputs for nitrous oxide emission rates have not changed since MOVES4, but, as shown in Figure
6-6, MOVES5 N20 emission results track changes in the vehicle fuel mix. At the national scale, MOVES5
net N20 is higher before 2020 and lower afterwards.
N20
co
zj
2030 2040
Calendar Year
Version
— MOVES4.0.1
MOVES5
Fuel Type
— Gas
— Diesel
— CNG
— E-85
EV
2050 2060
Black line shows total inventory
Figure 6-6—National onroad N2Oin MOVES5 as compared to MOVES4.0.1. Note the y-axis is in log space. The black lines are
totals across all fuel types.
The net C02 equivalent emissions are shown in Figure 6-7. These are based on the emissions of C02, CH4
and N20 as weighted by their global warming potentials (GWPs). The GWPs were updated for
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MOVES5.13 In total, the MOVES5 projects lower C02 equivalent emissions with decreases in C02 and N20
outweighing the increase in CH4.
C02 Equivalent
(O
z>
Version
— MOVES4.0.1
MOVES5
Fuel Type
— Gas
— Diesel
— CNG
E-85
EV
2030 2040
Calendar Year
2050 2060
Black line shows total inventory
Figure 6-7—National onroad C02 equivalent in MOVES5 as compared to MOVES4.0.1. Note the y-axis is in log space. The black
lines are totals across all fuel types.
Criteria Pollutants and Precursors
Oxides of Nitrogen
Figure 6-8 shows national NOx emissions decline through about 2040 with the phase-in of light-duty and
heavy-duty rules already accounted for in MOVES4. MOVES5 shows additional declines in later years
due to tighter emission standards under the LMDV and a higher fraction of EVs under both the LMDV
and HDP3 rules. At the national scale, NOx emissions in MOVES5 are higher than MOVES4 until about
2040. This is due to more detailed accounting of vehicles age 30-40 and changes in the fleet mix.
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2010 2020 2030 2040 2050 2060
Calendar Year
Black line shows total inventory
Figure 6-8— National onroad NOx in MOVES5 as compared to MOVES4.0.1. Note the y-axis is in log space. The black lines are
totals across all fuel types.
Figure 6-9 illustrates NOx for two example counties with the VMT shown in Figure 6-2. As noted above,
County A includes future year electric vehicle population fractions that are proportional to the county's
historic share of national EVs. In contrast, County B includes future year electric vehicle population
fractions that reflect adoption of California's Advanced Clean Car (2012) and Advanced Clean Trucks
(2020) rules requiring electric vehicle sales for light- and heavy-duty vehicles.
As in the national runs, MOVES5 NOx is higher than MOVES4 until about 2040 due to changes in fleet
mix and the modeling of older vehicles. After about 2040, MOVES5 NOx is lower due to more stringent
LD standards and a greater fraction of EVs. Note that until about 2040, the percent reduction in
emissions from 2021 is similar in the two versions.
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NOx by Fuel Type
County A
NOx by Fuel Type
County B
2021
4,000-
U)
-53.5%
-54.8%
m
u
70.0%
-79.0% -79.6%
¦81-6% -84.3%
Fuel Type
| Gas
| Diesel
I CNG
I E-85
EV
Figure 6-9—Onroad NOx from two sample urban counties in MOVES5 as compared to MOVES4.0.1. Percentage values indicate
change compared to 2021.
Particulate Matter
MOVES PM emissions include exhaust PM, tire wear and brake wear. Figure 6-10 shows national PM2.5
inventory declining with the phase-in of light-duty and heavy-duty PM regulations already in place.
MOVES5 shows additional declines in later years due to tighter emission standards under the LMDV and
a higher fraction of EVs under both the LMDV and HDP3 rules. At the national scale, PM emissions in
MOVES5 are higher than MOVES4 until about 2040. The higher emissions are due to data on brake wear
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that shows higher brake wear emissions from HD vehicles, plus changes due to detailed accounting of
vehicles age 30-40 and changes in the fleet mix. In MOVES5, brake wear emission rates for electric
vehicles are lower than for internal combustion engine vehicles after accounting for both increased
vehicle mass and regenerative braking.
Total PM2.5
Version
— MOVES4.0.1
— MOVES5
Fuel Type
— Gas
— Diesel
— CNG
— E-85
EV
2010 2020 2030 2040 2050 2060
Calendar Year
Black line shows total inventory
Figure 6-10—National PM2.5 in MOVES5 as compared to MOVES4.0.1. Note the y-axis is in log space. The yellow line graphs
brake and tire wear emissions from EVs. The black lines are totals across all fuel types..
Figure 6-11 depicts total PM2.5 emissions by fuel type in two sample counties. The gasoline and diesel
emissions include exhaust, brake, and tire wear. The EV emissions are from brake and tire wear only.
The trends resemble the trends for national PM2.5- Note that until about 2035, the percent reduction in
emissions from 2021 is similar in the two versions.
1e+01
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Total PM2.5 by Fuel Type
County A
-48.0%
-46.5% -55.i
-46.4%
¦
-60.0%
¦
Fuel Type
| Gas
| Diesel
| CNG
E-85
EV
Total PM2.5 by Fuel Type
County B
-53.4% -60.7%
-53.5%
"¦3" ->
CO <
LU U
Fuel Type
| Gas
| Diesel
| CNG
| E-85
EV
Figure 6-11—Onroad PM2.sby fuel type from two sample urban counties in MOVESb as compared to MOVES4.0.1. Percentage
values indicate change compared to 2021.
Figure 6-12 shows the same county results distinguished by grouped emission processes (e.g., with
crankcase emissions summed with corresponding exhaust emissions). These graphs clearly illustrate the
reductions in start and running PM emissions, and the enduring contribution of brake and tire wear.
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Total PM2.5 by Process
County A
Process
| Running
| Starts
| Brakewear
j Tirewear
Hotelling
Total PM2.5 by Process
County B
Process
| Running
| Starts
| Brakewear
Tirewear
Hotelling
Figure 6-12—Onroad PM2.5by grouped emission process from two sample urban counties in MOVES5 as compared to
MOVES4.0.1. Percentage values indicate change compared to 2021.
MOVES5 updates the factors used to compute PMi0 brake wear from PM2.s brake wear.14 Because brake
wear dominates PMio emissions, this change results in a notably different trend for PMio as compared to
PM2.5. MOVES5 estimates much less PMio. Figure 6-13 illustrates the PMio trend for County A. Trends
are similar in other counties and at the national scale.
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Total PM10 by Process
County A
cD
=)
Figure 6-13—Onroad PM10by grouped emission process from o sample urban county in MOVES5 as compared to MOVES4.0.1.
Percentage values indicate change compared to 2021.
Volatile Organic Compounds
As shown in Figure 6-14, onroad VOC emissions are dominated by emissions from gasoline vehicles,
which decline with the phase-in of Tier 3 standards, the increased fraction of electric vehicles, and
tighter standards under the LMDV rule. Like other pollutants, VOC emissions in MOVES5 are higher than
MOVES4 until about 2040 due to more detailed accounting of vehicles age 30-40 and changes in the
fleet mix.
42
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voc
2010 2020 2030 2040 2050 2060
Calendar Year
Black line shows total inventory
Figure 6-14—National onroad VOC by fuel type in MOVES5 as compared to MOVES4.0.1. Note the y-axis is in log space. The
black lines are totals across all fuel types.
The graphs for sample urban counties shown in Figure 6-15 illustrate the decrease in VOC over time, as
well as higher MOVES5 emissions pre-2040. In both versions of MOVES, onroad VOC is dominated by
emissions from refueling and other evaporative emissions.
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VOC by Process
County A
4,000-
(/) 3,000-
c
o
I-
(/)
—' o nnn-
VOC by Process
County B
2,000-
Figure 6-15—Sample county onroad VOC by grouped emission process in MOVES5 os compared to MOVES4.0.1. Percentage
values indicate change compared to 2021.
Carbon Monoxide
Like VOC, onroad CO emissions (Figure 6-16) are heavily dominated by emissions from gasoline vehicles.
The CO emissions decline over time with the phase-in of Tier 3 standards, improved technology and EVs.
Carbon monoxide emissions in MOVES5 are higher than MOVES4 until about 2040 due to more detailed
accounting of vehicles age 30-40 and changes in the fleet mix.
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CO
(/)
=j
2030 2040
Calendar Year
2050 2060
Black line shows total inventory
Figure 6-16—National onroad VOC by fuel type in MOVES5 as compared to MOVES4.0.1. Note the y-axis is in log space. The
black lines are totals across all fuel types.
Figure 6-17 illustrates these trends in two sample urban counties.
45
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CO by Fuel Type
County A
60,000-
Cf)
ZD
Fuel
Type
¦
Gas
Diesel
¦
CNG
¦
E-85
EV
CO by Fuel Type
County B
30,000-
(/)
D
10,000-
Fuel
Type
¦
Gas
Diesel
¦
CNG
¦
E-85
EV
Figure 6-17—Onrood CO by emission process for two sample counties in MOVES5 os compared to MOVES4.0.1. Percentage
values indicate change compared to 2021.
Ammonia
Ammonia (NH3) emissions in MOVES5 are similar to MOVES4, except for an update to the NH3 rates
from CNG vehicles. Net emissions in the two MOVES versions are similar in early years, but lower in
MOVES5 after about 2030 due to the phase-in of more EVs.
46
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NH3
1e+02-
Calendar Year
Black line shows total inventory
V)
c
o
I- 1 e+04-
(/)
Z>
Version
— MOVES4.0.1
— MOVES5
Fuel Type
— Gas
— Diesel
— CNG
— E-85
Figure 6-18—National onroad NH3 by fuel type in MOVES5 as compared to MOVES4.0.1. Note the y-axis is in log space. The
black lines are totals across all fuel types.
Sulfur Dioxide
As illustrated in Figure 6-19, S02 emissions are dominated by emissions from gasoline vehicles. From
2021 to about 2040, MOVES5 estimates higher S02 emissions as compared to MOVES4, primarily due to
updated information on gasoline sulfur content. After about 2040, S02 emissions are lower in MOVES5
due to the shift to EVs and more efficient vehicles.
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S02
CO
Z>
^ ^
¦** - - -
2030 2040
Calendar Year
Version
— MOVES4.0.1
— MOVES5
Fuel Type
— Gas
— Diesel
— CNG
— E-85
2050 2060
Black line shows total inventory
Figure 6-19—National onroad S02 by fuel type in MOVES5 as compared to MOVES4.0.1. Note the y-axis is in log space. The black
lines are totals across all fuel types.
6.2 Nonroad
The only nonroad inputs that were changed for MOVE5 were the sulfur levels for nonroad gasoline and
marine diesel fuels, resulting in a net increase in S02 emissions from nonroad vehicles as shown in Figure
6-20.
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Figure 6-20 Nonroad S02.in M0VES5 as compared to MOVES4.0.1. Note the y-axis is in log space. The black lines are totals
across all fuel types.
Emissions of other nonroad pollutants are the same in MOVES5 as in MOVES4. Figure 6-21 summarizes
annual nonroad emissions for key pollutants from running MOVES5 at the national level using default
inputs. Because nonroad activity varies substantially with season and geography, results for specific
times and locations will differ from these national results. As noted previously, MOVES does not cover
aircraft, locomotives, and commercial marine vessels.
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I Gasoline fl Nonroad Diesel I . CNG LPG Marine Diesel
Atmospheric C02
Methane (CH4)
3e+08•
2e+08"
1e+08"
0e+00-
^1000000
c
o
5e+05
0e+00
2017
2035
2050
2017
2035
2050
Figure 6-21 MOVES5 Nonroad emissions by calendar year
50
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7. MOVES Testing and Evaluation
To ensure that the MOVES model contains the state-of-the-science when estimating emissions from
mobile sources and that it is usable by a variety of modelers, MOVES is subject to review and evaluation
in several different ways. Because the MOVES model is developed incrementally, reviews and
evaluations of earlier versions of MOVES are often relevant even for later versions.
7.1 Peer Review
Since MOVES2014b, we have conducted five rounds of peer review for the updates to MOVES data and
algorithms, following EPA's peer review policies and procedures.31 Reviewer comments and EPA's
responses are documented in EPA's Science Inventory, online at https://cfpub.epa.gov/si/index.cfm with
the Record IDs listed below.
• In 2017, we conducted peer review of updates to onroad vehicle population and activity, heavy-
duty exhaust emission rates, fuel supply defaults, speciation and toxic emissions from on-road
vehicles, and particulate matter emissions from light-duty gasoline vehicles. (Record IDs 328810
and 328830)
• In 2019, we conducted a peer review of additional updates to the modeling of heavy-duty
vehicles, including updates to heavy-duty exhaust emission rates, incorporation of glider trucks
to MOVES, and updated start, hotelling and idling activity data from instrumented vehicle
studies. (Record IDs 347135 and 347136)
• In 2020, we conducted peer review of updates to the light-duty exhaust emission rates, updates
to heavy-duty crankcase emission rates, and updated fuel supply and fuel wizard factors.
(Record ID 347138)
• In 2022 and 2023, we conducted peer review of updates to the modeling of electric vehicles and
updates to refueling and ammonia emissions. (Record IDs 356887 and 356914)
• In 2024, we conducted peer review of updates to the MOVES fuel supply, updates to brake wear
emissions, and updates to ammonia emission rates from CNG vehicles. (Record IDs 361938,
361941, and 361938)
Peer review documents for previous versions of MOVES are also available at the Science Inventory page.
7.2 MOVES Review Work Group
To provide expert feedback and advice on development of the first three versions of MOVES, the Mobile
Sources Technical Review Subcommittee (MSTRS) chartered a series of MOVES Review Work Groups
focused on sharing technical expertise. Members of the work group represented a variety of
stakeholders, including vehicle and engine manufacturers, fuel producers, state and local emission
modelers, academic researchers, environmental advocates, and affected federal agencies. The first work
group was chartered in April 2007 and met through April 2010 to provide feedback on MOVES initial
development, culminating with the release of MOVES2010 in December 2009. A second work group met
from July 2012 through July 2013 during the development of MOVES2014, released in October 2014. A
third work group met from September 2016 through September 2021 to provide feedback on the
development of MOVES3, released in November 2020.32
Each work group was charged with reviewing information about MOVES development and providing
recommendations to the MSTRS. In turn, the MSTRS evaluated the work group recommendations and
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decided how these issues should be reported to the Clean Air Act Advisory Committee (CAAAC), which,
under the Federal Advisory Committee Act (FACA), may formally give EPA collective advice. Notes and
presentations from the MOVES3 workgroup meetings are available at
https://www.epa.gov/moves/moves-model-review-work-group.
7.3 Internal Testing
The MOVES development team performs rigorous testing throughout the model development life cycle.
This includes unit testing to ensure that every change to MOVES affects emissions and activity as
expected, and systematic integrated testing to ensure changes do not have unintended side effects. We
also test to ensure that Rates Mode and Inventory Mode generate the consistent outputs if used with
same inputs.
7.4 Beta Testing and Shared Release Candidate
Prior to public release, draft versions of MOVES are tested by a small group of experienced MOVES users
outside of EPA. This beta testing has helped to identify errors and to improve the MOVES interface and
documentation.
Immediately prior to the official release, we also posted a draft, release candidate version to the MOVES
GitHub site (https://github.com/USEPA/EPA MOVES Model/releases/tag/MOVES5-RC2). This posting
allowed additional user testing of a near-final version of the model and allows modelers to become
familiar with functional changes prior to the official public release.
7.5 Accessibility Testing
The M0VES3 graphical user interface was reviewed for accessibility under the Web Content Accessibility
Guidelines 2.0 and the Revised Section 508 standards published January 18. 2017 and corrected January
22. 2018. The MOVES interface partially supports Section 508 accessibility requirements.33 Interface
changes for MOVES4 and MOVES5 were minimal and the MOVES3 assessment is still applicable. We plan
to improve MOVES accessibility in future versions.
7.6 MOVES Sensitivity Analysis
A number of studies have been conducted to identify the input factors that are most important in
influencing MOVES results.34,35,36,37 In general, model year-and thus calendar year and age distribution-
is important because it captures the decline in emissions as emission standards become more stringent
over time. Other factors such as vehicle speed and driving pattern, fuel parameters, humidity and
ambient temperature may also be important for specific vehicle categories, emission processes, and
pollutants. However, changes to MOVES emission factors, emission adjustments, and the relative
activity and vehicle population across MOVES versions can affect the model's sensitivity greatly. This
means that one should not assume that sensitivity determinations developed for one version of MOVES
are accurate for other versions.
7.7 Evaluation by Industry-Funded Research Group
The MOVES2014 model was reviewed by the Coordinating Research Council, a non-profit corporation
supported by the energy and mobility industries. The review (CRC project E-101) included three distinct
task elements: (1) a critical evaluation of modeling methods, (2) inventory analyses applied to three
locations, and (3) a validation of the fuel methodology using independent data sources.38 The report
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provided detailed recommendations in 10 areas. EPA used these recommendations to help prioritize
efforts for MOVES3 and published a detailed response.39
An additional review (CRC project E-116) investigated MOVES2014 evaporative inputs.40 While the
feedback was valuable, most of the issues pointed out in this CRC report were expected to have very
little impact on the magnitude of the evaporative emissions computed by MOVES.
7.8 Comparisons to Independent Data
Evaluating the performance of the MOVES model in comparison to other measures is useful for
assessing the model's performance in accurately estimating current emission inventories and
forecasting emission trends. It also helps to identify areas in need of improvement, and guide future
work and research. However, it is not appropriate to evaluate MOVES by comparing against
measurements based only on a few vehicles, or without sufficiently customizing MOVES inputs to
account for the measurement conditions (e.g., fleet composition, vehicle activity, meteorology).
In our efforts to evaluate MOVES, we have prioritized comparisons for the major sources of emissions
(e.g., onroad light-duty gasoline, heavy-duty diesel) and areas where significant independent data is
available. In assessing our results, we consider systematic bias observed across multiple data sources as
indicative of model underperformance. On the other hand, if the model predictions are generally within
the variability of independent measurements, it gives confidence that the model is predicting real-world
emissions reasonably well.
Evaluating vehicle emissions is complex. Lyu and coauthors summarized potential evaluation methods in
a 2021 review study and concluded that "selecting different measurements will significantly impact the
assessment of the vehicle emission results and the applicable scope of the measurements. Considering
the different influencing factors of the operating vehicle emissions will have an impact on the model
application of the vehicle emission evaluation."41 In addition, some aspects of emissions, such as start
and evaporative emissions, are particularly challenging to measure in the real world, and, thus, to
evaluate.
Evaluating MOVES emission rates may include comparisons to data from sources such as dynamometer
tests, remote sensing devices (RSD) and portable emission monitoring systems (PEMS). To capture rare
(but influential) high emitters, it is important that the data samples are large and diverse. Likewise, we
prefer comparison data that represent known operating conditions (e.g., a pre-conditioned IM240 drive
cycle). Such comparisons are particularly valuable because the emission rates from the study can be
compared with MOVES emission rates using the same activity and fleet variables such as vehicle mix,
vehicle age, and vehicle operating mode. For example, a broad-based study was used to evaluate
MOVES2014b and subsequently to update high-power emission rates in MOVES3.42
Another study compared light-duty gasoline vehicle emissions measured with remote sensing to
emission rates from MOVES3. The study was intended to evaluate a new RSD methodology rather than
to judge the accuracy of MOVES. The authors noted differences in the time scale of measured emissions
and the resulting complication in determining emissions by VSP bin. However, they found that their
measured emission rates were in the same range as MOVES3 input rates for C02, CO, and NO.
Hydrocarbon emission rates were high compared to MOVES values. They suspected an error or noise in
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their THC measurements. The relative effects of vehicle age were similar between the observed values
and those incorporated into MOVES3.43
For heavy-duty vehicles, Allen et al. used RSD to measure heavy-duty truck emissions in Utah and
compared measured NOx emissions to MOVES4 emission rates. Unlike MOVES predictions, they found
that winter NOx emissions were twice as high as summer emissions. They also saw much more emission
deterioration with age than MOVES predicts.44
Other studies compare "localized composite" emissions, using composite emission measurements from
many vehicles by tunnel45 or roadside emission monitors46 where vehicle emissions are predominant
and vehicle activity and fleet mix can be accounted for to some degree. A strength of tunnel and
roadside measurements is that they can capture the large sample sizes of vehicles operating in real-
world conditions needed to measure 'fleet-average' emission rates. However, such comparisons may
not include all pollutants, and they only assess the operating conditions represented at the specific
location. And, as Simon, et al. demonstrated, the inferred emissions depend on the observation method
and the distance from the roadway.47 The heavy-duty exhaust technical report includes comparisons of
MOVES heavy-duty emission rates to tunnel and roadside measurements and examples of using such
data to update ammonia and N20 emissions.15 A near-road study that suggests increases in heavy-duty
diesel emissions with decreasing ambient temperature48 is discussed in more detail in the MOVES
adjustment report.17
While tunnel studies and remote sensing can measure real-world emissions from many vehicles in a few
locations, portable emission monitors can measure emissions from a smaller number of vehicles
throughout a real-world driving route. Frey and coauthors instrumented light-duty gasoline vehicles
driven on prescribed routes and compared their emissions to MOVES model projections, concluding that
the MOVES operating mode approach has good accuracy and moderate-to-high precision, explaining a
wide range of variability in emission rates,49 and that MOVES is highly accurate in locating measured
emission "hotspots," that is, segments of a driving route with emissions in the 80th and 90th
percentiles.50 Similarly for HD diesel vehicles, Farzaneh etal. compared draft MOVES3 NOx emission
factors to emissions measured using PEMS on three trucks of model year 2005, 2009 and 2014 with
different load weights and sizes. However, they comment, "The current MOVES opMode equations do
not appear to capture the impact of weight on the emission rates of HDDVs." In addition, while the
emision rates in their comparison are not corrected for fuels or ambient conditions, the pattern of
relative emissions by operating mode can be compared with MOVES base rates. The results for the MY
2005 truck and the MY 2009 tested with a normal load show a much flatter curve than predicted by
MOVES based on heavy-duty in-use testing data. The results for the MY 2014 truck tested with a normal
load show a curve with much higher emissions for the lower-speed coasting bins (11 & 21) than
predicted by MOVES based on heavy-duty in-use testing data.51)
At a more general level, some MOVES evaluations compare regional air quality model results from
models such as the Community Multiscale Air Quality Modeling System (CMAQ) with air quality monitor
and deposition data and satellite data. These "top-down studies" are useful to assess the overall
emissions contribution from all relevant emission sources to air quality measurements. Discrepancies
between air quality modeling predictions and measurements can point to deficiencies in the emissions
inventory but may be confounded with deficiencies in the air quality model (e.g., modeling transport,
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boundary layer, deposition, transformation, and other physical and chemical processes). In addition,
top-down studies on their own cannot identify the individual sources in the emissions inventory that are
responsible for the modeling discrepancy.52,53 Newer studies54 have focused on efforts to minimize
influence of parameters other than emissions, providing valuable insights into differences between
MOVES and other methods to estimate onroad inventories; however the use of MOVES in air quality
model studies necessarily involves using support tools that facilitate the use of local activity inputs as
well as gridding of emissions spatially and temporally, which can add uncertainty to the identification of
specific sources contributing to discrepancies.
Like air quality studies, "macro-scale" fuel consumption studies are also useful, comparing "bottom-up"
fuel consumption as estimated by MOVES to "top-down" fuel tax data. These studies can help assess
MOVES large-scale vehicle activity estimates and fuel economy values.
o
Regional Onroad
Emissions
m m
VMT, population,
activity estimates
Localized Composite
Emissions
operating mode & fleet
mix estimates
AIR QUALITY MONITOR
DATA
0
CMAQ
Other Sector Emissions
TUNNEL, ROADSIDE
MONITOR DATA
Emission
Rates
DYNO, RSD, PEMS DATA
Figure 7-1-MOVES evaluation opportunities at rising levels of generalization and uncertainty.
Fuel Consumption Comparisons
Beginning with MOVES3, we have conducted a detailed comparison of the gasoline and diesel fuel
consumption estimated by MOVES and estimated by FHWA based on fuel tax data. For our MOVES5
analysis, we used MOVES5 release candidate 2 (MOVES5RC2), a near-final version of that captures all
the major activity and energy consumption updates to the model.
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As show in Figure 7-2 and Figure 7-3, MOVES5 and MOVES4 both overestimate gasoline and diesel
consumption when compared to FHWA estimates. The comparisons should note a number of caveats,
such as uncertainties in the MOVES activity inputs, potential inaccuracies in the state-provided fuel tax
data, and difficulties in matching the vehicle categories covered by the two estimates-including
accounting for public vehicles excluded from the FHWA analysis and uncertainties in the methodology
used by FHWA to allocate between highway and off-road fuel use.
Also, note that certain inputs to MOVES do not capture changes over time, such as relative mileage
accumulation rates and fuel energy consumption. Given the important use of MOVES in forecasting
future emissions, we have chosen updates for these values such that MOVES better represents current
and future conditions rather than past. This may partially explain the better agreement seen in Figure
7-2 for years after 2020, and in Figure 7-3 for years after 2018.
160-
l
1
1
1
1
1
J1
J1
J1
J1
J1
_n
J1
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
Calendar Year
¦ FHWA
[] MOVES4
I MOVES5RC2
Figure 7-2—National gasoline consumption (in billion gallons) by calendar year estimated by MOVES4, a near-final version of
MOVES5, and FHWA.
56
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60
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
Calendar Year
Figure 7-3—National diesel consumption (in billion gallons) by calendar year estimated by MOVES4, a near-final version of
MOVES5, and FHWA.
NOx Evaluation Work
Several studies using emissions generated with versions of MOVES2014 have shown differences
between air quality model estimates and monitored values for nitrogen oxides. Researchers suggested
that air quality models appear to overestimate NOx ambient values due to an overestimate in NOx
emissions55,56,57 particularly from LD gasoline vehicles.58
In response, as part of MOVES3 development efforts, we evaluated the MOVES2014 light-duty emission
rates against in-use measurements and, based on the comparisons,4242, we updated the emission rates in
MOVES3, generally decreasing light-duty NOx emissions.
We also formed a cross-EPA workgroup to coordinate efforts to evaluate NOx emissions and modeling.
This effort concluded that:
Model over-predictions were likely due to multiple compounding factors that each contributed to a
portion of the bias. Based on our review of the evidence, the most important contributing factor to
the summer NOx bias was:
• Planetary boundary layer (PBL) and vertical mixing algorithms in the Community Multiscale Air
Quality (CMAQ) model (version 5.0.2 and earlier) led to too little vertical mixing at certain times
and in some locations. These algorithms have been improved in CMAQv5.1 and later versions of
CMAQ. These changes substantially reduced the NOx bias, as well as the NOx diurnal bias
pattern in simulations run with more recent CMAQ versions.
We also demonstrated that there is important uncertainty in the model bias caused by NOxand NOy
measurement uncertainty, as well as chemical mechanism used. Caution should be taken in using
modeled NOx bias to constrain NOx emissions or processes incorporated into air quality modeling.
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Through this effort, we identified aspects of the mobile source N0X emissions that were
overestimated in the evaluated air quality platforms, but based on our analysis so far, mobile source
N0X only had a modest impact on the magnitude and pattern of the bias in modeled N0X
concen trations.59
The workgroup is no longer formally active, but EPA offices continue to work together to understand
and improve our emission and air quality models.
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8. Considerations When Using MOVES
The task of keeping MOVES current with manufacturers' ever-changing vehicle and equipment products,
activity data that reflect how these vehicles and equipment are used, and the evolving scientific
understanding of emissions can be daunting. We must prioritize our efforts on updates that will affect
emissions results the most, are of the most value for our users, and have the largest impact on the
overall accuracy of the model.
So, while the functional scope of MOVES is large, the model is not designed to answer every possible
question about mobile source emissions. While there are areas of the model that rely on assumptions or
limited data, in many cases, these areas either have a small contribution to the total emissions inventory
or represent cases where no data was available (e.g., emission deterioration of MY 2027+ heavy-duty
diesel emissions).
When deciding whether to use MOVES for a given purpose, it is important to note the following features
of the MOVES design:
• MOVES algorithms calculate emissions based on physical and chemical principles, statistical
relationships, and use of good engineering judgement. We develop MOVES algorithms based on the
best available knowledge at the time, and emission relationships inferred from present emission
databases. MOVES algorithms have and will continue to be updated in future MOVES versions as our
knowledge of technologies and emission processes is updated.
• MOVES is designed to model fleet-average emissions rather than the emissions of any specific
vehicle or piece of equipment.
• MOVES models the emissions from vehicles and equipment designed to meet emission standards in
the United States. There are considerable challenges to adapting the MOVES framework to other
nations, primarily related to the need for specific information about the emission performance and
activity of vehicles.60 6 1 62 63 64
• While MOVES models onroad and nonroad emissions in California, the MOVES defaults do not
capture all the details of California emission standards and control programs. Instead, California uses
California-specific models for modeling mobile sources.65
• MOVES allows users to "pre-aggregate" location and time-specific input data when modeling
emissions at the national and state level and overtime periods longer than one hour. Pre-
aggregating inputs to these larger scales is faster but reduces the model accuracy and precision
compared to modeling at a more detailed level and aggregating the results at the end.
• MOVES defaults generally characterize fleet characteristics and activity at the national level. To
accurately model emissions in a specific location, accurate local inputs must be used. For example,
MOVES national default information on vehicle fleet mix, including the fraction of electric vehicles,
does not capture the substantial variation by location.
• MOVES allows user input of many parameters, and therefore, the quality of model output will
depend on the quality of these inputs, as well as the appropriateness of the model defaults relied
on. When inputs are generated by other models, it is important to understand the limitations of
those models as well.66
• MOVES does not separately model hybrids or plug-in hybrids with a conventional gas or diesel
engine. Onroad hybrid vehicles meet the same emissions standards as conventional gasoline or
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diesel vehicles and are incorporated into the fleet average criteria pollutant, energy, and C02
emissions for each model year in MOVES.
• MOVES uses the same estimates of vehicle activity regardless of fuel type, i.e., activity for vehicles
fueled by electricity and compressed natural gas are the same for vehicles fueled by gasoline and
diesel.
• MOVES includes default tampering and mal-maintenance rates that are used to derive heavy-duty
diesel emission rates, which cannot be updated by users. These rates were last updated for
MOVES2014 with many of the data and assumptions from studies conducted between 1988 and
2007.15 MOVES does not explicitly account for tampering and mal-maintenance of light-duty onroad
vehicles or nonroad equipment.
• MOVES is not designed to model the impact of grade at national or county levels. MOVES does allow
grade to be included at the project scale. The project scale allows modeling of a wide variety of
onroad drive cycles and grades; users should assess whether the modeled drive cycle is realistic at a
given grade for the project-scale analysis.
In addition, it is useful to understand the sources and process used to update the MOVES default data.
MOVES5 and MOVES4 updates were limited in scope as described in Section 2.3 above and in the
MOVES4 Overview Report,67 so most emission rates have not been updated since MOVES3. While the
MOVES3 updates were based on millions of emission test results, coverage varies depending on data
availability. MOVES forecasts emissions up to calendar year 2060; these estimates are necessarily based
on forecasts and extrapolation from data available at the time of analysis, generally 2021 or earlier.
Consistent with MOVES purpose and design, MOVES relies on multiple datasets and analysis methods to
estimate emissions across model years, fuel types, vehicle and engine types, and emission processes.
Thus, fleet-average emission estimates and overall trends are generally more robust than emission rates
from individual vehicle types, model years, fuel types and emission processes that may be based on a
single data set or analysis.
Furthermore, due to MOVES priorities and data availability, some onroad inputs have not been updated
recently or have other notable limitations. For example, due to the small number of light-duty diesel
vehicles in the U.S. fleet, MOVES uses the same exhaust emission rates for light-duty diesel vehicles as
for light-duty gasoline vehicles.16 MOVES motorcycle emissions rates were last analyzed in 2010.68 Light-
duty gasoline running emission rates were updated for MOVES3 based on millions of test results,16 but
differences between "with l/M" and "non l/M" rates for THC, CO and NOx emission rates are based on
previous analysis, and the emissions effects of different l/M program designs were generated using
MOBILE6.1617 Light-duty gasoline start deterioration with age is derived from information on running
emissions.16 Evaporative emissions other than refueling have not been updated since MOVES2014, and
the refueling updates are based on a limited range of ambient temperatures, gasoline RVPs and model
years. Also, while MOVES3 updated the vehicle activity patterns used to estimate start and ONI exhaust
emissions, MOVES evaporative emission calculations rely on older, more limited, trip pattern data.18
MOVES3 emission rate updates included updates to HD diesel running emissions rates based on analysis
of a substantial database of running emissions data from well-maintained heavy-duty diesel trucks,69 but
the values used to estimate heavy-duty emission deterioration with age were last updated for
MOVES2014. We also have fewer data on start and crankcase emissions. Forecasts of HD diesel start
emission rates for MY 2027 and later are based on tests of a single prototype engine. MOVES4 crankcase
60
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changes are due to an updated algorithm but continue to use MOVES3 data. In addition, while we also
updated rates for heavy-duty gasoline and heavy-duty CNG vehicles, data are sparse for these vehicles.
In particular, peer reviewers have suggested that we may be underestimating crankcase emissions from
CNG vehicles.15
MOVES tire wear emission rates are based primarily on a literature review from 2006 and 200714 and do
not account for technology and market changes such as the increasing number of electric vehicles. Fuel
effects and some other MOVES adjustment factors are based on testing of older vehicle technologies.217
Nonroad emissions estimates are generally based on more limited data than onroad emissions for both
emission factors and population and activity. Many of the onroad emissions factors are applied to
nonroad engines due to a lack of nonroad data; therefore, several of the previously mentioned
limitations for onroad also apply to nonroad, with the added uncertainty of applying onroad factors to
nonroad engines. Since many of the source data and algorithms used to model nonroad equipment date
from the first release of EPA's NONROAD model in 1998, some recent industry trends, such as the
increased adoption of electric- or battery-powered equipment (e.g., lawn and garden equipment) and
transition from 2-stroke to 4-stroke engines, are not reflected in the model. We are currently working on
acquiring nonroad emissions and activity data to improve the emissions characterization of the nonroad
sector.
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9. M0VES5 Documentation
There is extensive documentation for MOVES, including guidance documents to help explain regulatory
requirements, user instructions, training materials, and technical reports.
MOVES documentation is available on the web at https://www.epa.gov/moves. In addition, user help is
built into the MOVES GUI. Information on installing and using MOVES is available at
https://www.epa.gov/moves/latest-version-motor-vehicle-emission-simulator-moves.
The MOVES source code is available at https://github.com/USEPA/EPA MOVES Model and
documentation relating to the code and the computer technology aspects of using MOVES are at
https://github.com/USEPA/EPA MOVES Model/tree/master/docs.
To cite MOVES5.0.0 in general:
USEPA (2024) Motor Vehicle Emission Simulator: MOVES5.0.0. Office of Transportation and Air Quality.
US Environmental Protection Agency. Ann Arbor, Ml. November 2024. https://www.epa.gov/moves
Table 9-1 lists the various documentation currently available for M0VES5 and provides information on
accessing each document.
Table 3-1 MOVES Documentation
jGeneral:
EPA Releases M0VES5
Mobile Source Emissions
Model: Questions and
Answers
Highlights the difference between
M0VES5 and earlier versions of
MOVES and explains EPA policy
on using M0VES5 in state
implementation plans and
transportation conformity
analyses
https://www.epa.gov/moves/latest-
version-motor-vehicle-emission-
simulator-moves#background
Frequently Asked
Questions
Answers to frequently asked
questions on MOVES installation,
use, terminology and output
https://www.epa.gov/moves/freque
nt-questions-about-moves-and-
related-models
MOVES Webinars
Webinars describing MOVES
versions and their use
https://www.epa.gov/moves/moves-
training
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Using MOVES for Regulatory and Other Purposes:
Federal Register Notice
I of Availability
Announces the official release of
MOVES5 for use in SIP
development and transportation
conformity purposes in states
other than California.
https://www.epa.gov/state-and- (
local-transportation/policv-and- 1
technical-guidance-state-and-local- 1
transportation#emission 1
MOVES5 Technical
Guidance: Using MOVES
to Prepare Emission
Inventories for State
Implementation Plans
and Transportation
Conformity
Guidance on appropriate input
assumptions and sources of data
for the use of MOVES5 in SIP
submissions and regional
emissions analyses for
transportation conformity
purposes.
https://www.epa.gov/state-and- I
local-transportation/policv-and- I
technical-guidance-state-and-local- (
transportation#emission (
j MOVES5 Policy
Guidance: Use of MOVES
for State Implementation
Plan Development,
Transportation
Conformity, General
Conformity, and Other
Purposes
How and when to use the
MOVES5 for SIP development,
transportation conformity,
general conformity, and other
purposes.
https://www.epa.gov/state-and- !
local-transportation/policv-and- (
technical-guidance-state-and-local- (
transportation#emission 1
J j Additional Guidance
Other guidance covers MOVES at
the Project Scale (used for hot-
spot analyses), using MOVES to
model specific control programs
(e.g., replacing or retrofitting
older diesel vehicles and
equipment with cleaner
technologies), using MOVES to
conduct l/M performance
standard modeling analyses for
l/M SIPs, using MOVES to develop
port-related emissions
inventories, and using MOVES to
estimate GHGs
Until updated, existing guidance is
generally applicable to M0VES5
See https://www.epa.gov/state-and- I
local-transportation I
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Training & Cheat Sheets:
Onroad Cheat Sheet
Summarizes common tables and
https://github.com/USEPA/EPA MO
n/alues used to create onroad
VES Model/blob/master/docs/MOV
MOVES runs and interpret their
ES5CheatsheetOnroad.pdf
outputs.
Also available in the MOVES GUI
Help menu.
Nonroad Cheat Sheet
Summarizes common tables and
https://github.com/USEPA/EPA MO
k/alues used to create nonroad
VES Model/blob/master/docs/MOV
MOVES runs and interpret their
ES5CheatsheetNonroad.pdf
outputs.
Also available in the MOVES GUI
Help menu.
MOVES Hands-on
1
IA detailed hands-on course for
https://www.epa.gov/moves/moves-
Training
state and local agency staff who
training#hands-on-training
¦will use MOVES for developing
emissions inventories for SIP and
conformity analyses. The course
is designed to be self-taught in
periods where no classes are
scheduled, or constraints prevent
attending an in-person course.
Users can work through the
modules and hands-on exercises
at their convenience.
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Project-Level Training for
Quantitative PM Hot-
Spot Analyses
EPA's training course on
implementing EPA's PM Hot-Spot
Guidance is a technical, hands-on
course geared toward state and
local agency staff. The course
focuses on using EPA's emission
model MOVES and EPA's
dispersion model AERMODto
complete quantitative PM hot-
spot analyses. The course can be
self-reviewed when training
sessions are not available.
The course is based on
MOVES2014b and still largely
applicable to MOVES5.
https://www.epa.gov/moves/moves-
training-sessions#hotspot
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Installation and Computer-Related Aspects of Using MOVES
Installation Suite
Executable program to install
MOVES5 and all required
software. Instructions are
embedded in the installer
https://www.epa.gov/moves/latest-
version-motor-vehicle-emission-
simulator-moves#download
MOVES Installation
Troubleshooting
How to resolve common
installation issues
https://github.com/USEPA/EPA MO
VES Model/blob/master/docs/lnstall
ationTroubleshooting.pdf
Quick Start Guide to
Accessing MariaDB Data
Hints on how to access data in
new MariaDB installation
https://github.com/USEPA/EPA MO
VES Model/blob/master/docs/Quick
StartGuideToAccessingMariaDBData.
pdf
MOVES5 Database
Conversion Tool Help
Explains use of tool to convert
MOVES3 and MOVES4 databases
for use with MOVES5
https://github.com/USEPA/EPA MO
VES Model/blob/master/database/C
onversionScripts/lnputDatabaseConv
ersionHelp.pdf
Speciation Profile Scripts
Tool Help
Instructions for how to speciate
MOVES output for air quality
modeling as a post-processing
step
https://github.com/USEPA/EPA MO
VES Model/blob/master/database/P
rofileWeightScripts/profileScriptHelp
.pdf
AVFT Tool Help
Instructions on how to use the
AVFT Tool for building the AVFT
input table
https://github.com/USEPA/
EPA MOVES Model/blob/master/
gov/epa/otaq/moves/master/gui/
avfttool/AVFTToolHelp.pdf
Building LEV and NLEV
Input Databases Help
Instructions on how to use the
LEV/NLEV Tool in the MOVES GUI
https://github.com/USEPA/EPA MO
VES Model/blob/master/database/L
EV NLEVScripts/lnstructionsForLEV
NLEV Tool.pdf
ONI Tool Help
Instructions on how to use the
ONI Tool when running MOVES in
rates mode with default off-
network idling activity
https://github.com/USEPA/EPA MO
VES Model/blob/master/database/
ON ITool/lnstructionsForON ITool.pdf
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Anatomy of a RunSpec
An overview of all of the fields
contained in a MOVES RunSpec
https://github.com/USEPA/EPA MO
VES Model/blob/master/docs/Anato
mvOfARunspec.md
Command Line MOVES
A brief guide on how to run
MOVES and MOVES tools from
the command line
https://github.com/USEPA/EPA MO
VES Model/blob/master/docs/Com
mandLineMOVES.md
Debugging MOVES
Tips for troubleshooting and
debugging unexpected behavior
in MOVES runs
https://github.com/USEPA/EPA MO
VES Model/blob/master/docs/Debu
ggingMOVES.md
MOVES Code: Folder by
Descriptions of the contents
within the folders in the MOVES
source code directory
https://github.com/USEPA/EPA MO
| Folder
VES Model/blob/master/docs/Folde
rBvFolder.md
| MOVES Input/Output
| Database Changes
Description of the schema ) https://github.com/USEPA/
changes to MOVES Countv Scale 1 EPA MOVES Model/blob/master/
and Prnjprt Sralp input rlatahacpcl docs/lnputOutputDBChanges.md
| MOVES Database
| Glossary
Glossary of the column names
used in the MOVES default
database
https://github.com/USEPA/EPA MO
VES Model/blob/master/docs/MOV
ESGIossarv.md
1 MOVES Database Tables
Schema descriptions for each
table in the MOVES default
database
https://github.com/USEPA/EPA MO
VES Model/blob/master/docs/MOV
ESDatabaseTables.md
| Tips for faster MOVES
| runs
Suggestions for how to structure ( https://github.com/USEPA/
MOVES runs to be as efficient as (EPA MOVES Model/blob/master/
pnccihlp I docs/TipsForFasterMOVESRuns.pdf
| MOVES5 Update Log
Chronological listing of updates
to M0VES5
https://www.epa.gov/moves/moves
5-update-log
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MOVES Algorithms and Default Inputs
Onroad Technical
Reports
Nonroad Technical
Reports
1 .ink to MOVES technical reports
lescribing the default inputs and
ilgorithms for the onroad
unctions of MOVES5 and earlier
*/IOVES versions
iink to MOVES technical reports
escribing the default inputs and
Igorithms for the nonroad
jnctions of MOVES5 and earlier
ersions Although the stand-
lone NONROAD model is now
icorporated into MOVES, many
fthe NONROAD technical
eports still apply to the nonroad
iputs and algorithms used in
/IOVES.
https://www.epa.gov/moves/moves-
onroad-technical-reports
https://www.epa.gov/moves/nonroa
d-technical-reports
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10. Acronyms
Acronym Meaning
2b3 Class 2b and 3 Trucks (8,500 lbs < GVWR <= 14,000 lbs)
AERMOD Atmospheric dispersion modeling system
APU Auxiliary power unit
AVFT Alternative vehicle fuels and technologies
BSFC Brake-specific fuel consumption
CH4 Methane
CI Compression ignition
CMAQ Community Multiscale Air Quality Modeling System
CNG Compressed natural gas
CO Carbon monoxide
C02 Carbon dioxide
CRC Coordinating Research Council
EC Elemental carbon
EMFAC California onroad vehicle emission factor model
EPA Environmental Protection Agency
EV Electric vehicle
FHWA Federal Highway Administration
GHG Greenhouse gases
GUI Graphical user interface
GVWR Gross vehicle weight rating
GWP Global warming potential
HD Heavy duty
HD2027 Control of Air Pollution from New Motor Vehicles: Heavy-Duty Engine and
Vehicle Standards
HDGHG2 Greenhouse Gas Emissions and Fuel Efficiency Standards for Medium- and
Heavy-Duty Engines and Vehicles—Phase 2
HDP3 Greenhouse Gas Emissions Standards for Heavy-Duty Vehicles—Phase 3
l/M Inspection and maintenance
LEV Low-emission vehicle
LD Light duty
LHD Light Heavy-Duty
LMDV Light- and Medium-Duty Multi-Pollutant Rule
LPG Liquified petroleum gas
MOVES Motor Vehicle Emission Simulator
MY Model year
NEI National Emissions Inventory
NEPA National Environmental Policy Act
NLEV National low-emissions vehicle
NMHC Non-methane hydrocarbons
NMOG Non-methane organic gases
NonEC PM other than elemental carbon
NonHAPTOG Residual total organic gases
NOx Oxides of nitrogen
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NR
Nonroad
NREL
National Renewable Energy Laboratory
ONI
Off-network idling
ORVR
Onboard refueling vapor recovery system
PEMS
Portable emission measurement systems
PMio
Particulate matter <= 10 pim
PM2.5
Particulate matter <= 2.5 pim
RSD
Remote sensing device
RVP
Reid vapor pressure
SAFE
Safer Affordable Fuel Efficient Vehicles rule
SI
Spark ignition
SIP
State implementation plan
THC
Total hydrocarbons
TOG
Total organic gases
TVV
Tank vapor venting
VMT
Vehicle miles travelled
VPAT
Voluntary Product Accessibility Template
VSP
Vehicle specific power
VOC
Volatile organic compounds
ZEV
Zero emissions vehicle (battery electric and fuel cell vehicles)
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11. References
1 USEPA (2024). Fuel Supply Defaults: Regional Fuels and the Fuel Wizard in MOVES5. EPA-420-R-24-017. Office of
Transportation and Air Quality, Ann Arbor, Ml. November 2024. https://www.epa.gov/moves/moves-onroad-
technical-reports
2 USEPA (2020). Fuel Effects on Exhaust Emissions from Onroad Vehicles in MOVES3. EPA-420-R-20-016. Office of
Transportation and Air Quality. US Environmental Protection Agency. Ann Arbor, Ml. November 2020.
https://www.epa.gov/moves/moves-technical-reports
3 USEPA (2005). Exhaust Emission Effects of Fuel Sulfur and Oxygen on Gasoline Nonroad Engines. NR-003c EPA-
420-R-05-016. Office of Transportation and Air Quality. US Environmental Protection Agency. Ann Arbor, Ml.
December, 2005. https://www.epa.gov/moves/nonroad-technical-reports.
4 USEPA (2020). Air Toxic Emissions from Onroad Vehicles in MOVES3. EPA-420-R-20-022. Office of Transportation
and Air Quality. US Environmental Protection Agency. Ann Arbor, Ml. November 2020.
https://www.epa.gov/moves/moves-technical-reports
5 USEPA (2024). MOVES5 Policy Guidance: Use of MOVES for State Implementation Plan Development,
Transportation Conformity, General Conformity, and Other Purposes. EPA-420-B-24-038. Office of Transportation
and Air Quality. US Environmental Protection Agency. Ann Arbor, Ml. November 2024.
https://www.epa.gov/state-and-local-transportation/policv-and-technical-guidance-state-and-local-transportation
6 https://www.epa.gov/moves/moves-training
7 USEPA (2024). MOVES5 Technical Guidance: Using MOVES to Prepare Emission Inventories for State
Implementation Plans and Transportation Conformity. EPA-420-B-24-043. Office of Transportation and Air Quality.
US Environmental Protection Agency. Ann Arbor, Ml. November 2024. https://www.epa.gov/state-and-local-
transportation/policv-and-technical-guidance-state-and-local-transportation
8 USEPA (2021). PM Hot-Spot Guidance: Transportation Conformity Guidance for Quantitative Hot-spot Analyses in
PM2.5 and PM10 Nonattainment and Maintenance Areas. EPA-420-B-21-037. Office of Transportation and Air
Quality. US Environmental Protection Agency. Ann Arbor, Ml. October 2021. https://www.epa.gov/state-and-local-
transportation/proiect-level-conformitv-and-hot-spot-analvses
9 USEPA (2021). Using MOVES3 in Project-Level Carbon Monoxide Analyses. EPA-420-B-21-047. Office of
Transportation and Air Quality. US Environmental Protection Agency. Ann Arbor, Ml. December 2021.
https://www.epa.gov/state-and-local-transportation/proiect-level-conformitv-and-hot-spot-analvses
10 USEPA (2024) MOVES Greenhouse Gas Guidance: Using MOVES for Estimating State and Local Inventories of
Onroad Greenhouse Gas Emissions and Energy Consumption. EPA-420-B-24-023. Office of Transportation and Air
Quality. US Environmental Protection Agency. Ann Arbor, Ml. June 2024. https://www.epa.gov/state-and-local-
transportation/estimating-greenhouse-gas-emissions
11 USEPA (2023), Is MOVES the best Tool for my work? Frequently Asked Question at
https://www.epa.gov/moves/moves-best-tool-mv-work
12 Multi-Pollutant Emissions Standards for Model Years 2027 and Later Light-Duty and Medium-Duty Vehicles, 89
Fed. Reg. 27842, April 18, 2024.
D1 Greenhouse Gas Emissions Standards for Heavy-Duty Vehicles—Phase 3, 89 Fed. Reg. 29440., April 22, 2024.
13 USEPA (2024). Greenhouse Gas and Energy Consumption Rates for Onroad Vehicles in MOVES5. EPA-420-R-24-
018. Office of Transportation and Air Quality, Ann Arbor, Ml. November 2024.
https://www.epa.gov/moves/moves-onroad-technical-reports
14 USEPA (2024). Brake and Tire Wear Emissions from Onroad Vehicles in MOVES5. EPA-420-R-24-012. Office of
Transportation and Air Quality, Ann Arbor, Ml. November 2024. https://www.epa.gov/moves/moves-onroad-
technical-reports
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15 USEPA (2024). Exhaust Emission Rates for Heavy-Duty Onroad Vehicles in MOVES5. EPA-420-R-24-015. Office of
Transportation and Air Quality, Ann Arbor, Ml. November 2024. https://www.epa.gov/moves/moves-onroad-
technical-reports
16 USEPA (2024). Exhaust Emission Rates for Light-Duty Onroad Vehicles in MOVES5. EPA-420-R-24-016. Office of
Transportation and Air Quality, Ann Arbor, Ml. November 2024. https://www.epa.gov/moves/moves-onroad-
technical-reports
17 USEPA (2024). Emission Adjustments for Onroad Vehicles in MOVES5. EPA-420-R-24-013. Office of
Transportation and Air Quality, Ann Arbor, Ml. November 2024. https://www.epa.gov/moves/moves-onroad-
technical-reports
18 USEPA (2024). Population and Activity of Onroad Vehicles in MOVES5. EPA-420-R-24-019. Office of
Transportation and Air Quality, Ann Arbor, Ml. November 2024. https://www.epa.gov/moves/moves-onroad-
technical-reports
19 USEPA (2023). S peciation of Total Organic Gas and Particulate Matter Emissions from Onroad Vehicles in
MOVES4. EPA-420-R-23-006. Office of Transportation and Air Quality. US Environmental Protection Agency. Ann
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