MOVES‐Based	Mobile	Source	Emissions	

Modeling	for	the	Atlanta	Nonattainment	

Area	 	
1

Table of Contents

Federal Clean Air Act Legislation and Transportation Conformity ............................................................... 2

Current Attainment Status............................................................................................................................ 4

1997 Eight‐Hour Ozone Standard ............................................................................................................. 4

1997 Annual PM2.5 Standard..................................................................................................................... 4

Modeling Assumptions .................................................................................................................................6

Emissions Modeling Assumptions............................................................................................................. 6

Travel Demand Modeling Assumptions.................................................................................................... 6

Travel Model Networks......................................................................................................................... 6

Transit Modeling ...................................................................................................................................8

MOVES Overview........................................................................................................................................10

MOVES Input Development – Travel Demand Post Processing Procedures .............................................. 12

VMT Adjustment Factors ........................................................................................................................ 12

Network Refinements............................................................................................................................. 14

VMT by Hour...........................................................................................................................................15

Roadtype Classification........................................................................................................................... 15

MOVES County Data Manger Input Files.................................................................................................... 17

Age Distribution ......................................................................................................................................17

Average Speed Distribution .................................................................................................................... 17

Fuel..........................................................................................................................................................18

I/M Program............................................................................................................................................18

Meteorology ...........................................................................................................................................19

Ramp Fraction.........................................................................................................................................19

Road Type Distribution ........................................................................................................................... 19

Source Type Population .......................................................................................................................... 19

Vehicle Type VMT ...................................................................................................................................20

Off‐Model Putnam County Mobile Emissions Analysis............................................................................... 22

MOVES Model Output ................................................................................................................................24

Eight‐Hour Ozone Standard Maintenance Plan...................................................................................... 24

MOVES Model Output – Annual PM2.5 Standard Maintenance Plan...................................................... 24
2

Federal Clean Air Act Legislation and Transportation Conformity

The Clean Air Act requires the United States Environmental Protection Agency (USEPA) to set limits on

how much of a particular pollutant can be in the air anywhere in the United States.  National Ambient

Air Quality Standards (NAAQS) are the pollutant limits set by the USEPA; they define the allowable

concentration of pollution in the air for six different pollutants – Carbon Monoxide, Lead, Nitrogen

Dioxide, Particulate Matter, Ozone, and Sulfur Dioxide.  

The Clean Air Act specifies how areas within the country are designated as either “attainment” or

“nonattainment” of an air quality standard, and provides USEPA the authority to define the boundaries

of nonattainment areas.  For areas designated as nonattainment for one or more NAAQS, the Clean Air

Act defines a specific timetable to attain the standard and requires that nonattainment areas

demonstrate reasonable and steady progress in reducing air pollution emissions until such time that an

area can demonstrate attainment. Each state must develop and submit a State Implementation Plan

(SIP) that addresses each pollutant for which it fails to meet the NAAQS.    Individual state air quality

agencies are responsible for defining the overall regional plan to reduce air pollution emissions to levels

that will enable attainment and maintenance of the NAAQS.  This strategy is articulated through the SIP.  

In Georgia, the agency responsible for SIP development is the Georgia Environmental Protection Division

(GA EPD).   

The delineation and implementation of strategies to control emissions from on‐road1mobile sources is a

significant element of the state plan to improve air quality, thereby creating a direct link between

transportation and air quality planning activities within a nonattainment area.  The process of ensuring

that a region’s transportation planning activities contribute to attainment of the NAAQS, or “conform”

to the purposes of the SIP, is referred to as transportation conformity.    In order to receive federal

transportation funds within the nonattainment area, the area must demonstrate through a federally

mandated transportation conformity process that the transportation investments, strategies and

programs, taken as a whole, contribute to the air quality goals defined in the State’s air quality plan.   

To ensure that conformity requirements are met, Section 176(c) of the Clean Air Act authorizes the

USEPA Administrator to “promulgate criteria and procedures for demonstrating and assuring conformity

in the case of transportation plans, programs, and projects.” This is accomplished through the

Transportation Conformity Rule, developed by the USEPA to outline all federal requirements associated

with transportation conformity.    The Transportation Conformity Rule in conjunction with the

Metropolitan Planning Regulations direct transportation plan and program development as well as the

conformity process. The final conformity rule (last updated in March 2010) incorporates revisions

resulting from the passage of the Safe, Accountable, Flexible, Efficient Transportation Equity Act: A

Legacy for Users (SAFETEA–LU); the latest transportation funding legislation which specifies the process

for development of metropolitan transportation plans and programs for urbanized areas.

                                                            

1 On‐road, or highway, sources include vehicles used on roads to transport passengers or freight.
3

Mobile source modeling is required to establish emissions inventories that are used by GA EPD to

demonstrate progress towards, or attainment of, air quality standards.    Emission inventories are

incorporated into these SIP demonstrations for air quality planning purposes.  They are also used in the

transportation conformity process to establish the maximum level of mobile source emissions that an

area can produce and still “conform” to the SIP; these maximum levels are referred to as Motor Vehicle

Emissions Budgets (MVEB).    The modeling process used to develop emissions inventories utilizes the

latest Interagency approved planning assumptions and modeling techniques to prepare an emissions

inventory for all pollutants (or pollutant precursors) for which a region is in nonattainment.

The Atlanta Regional Commission (ARC) is the federally designated Metropolitan Planning Organization

(MPO) for all or portions of 18 counties within the 19‐county Atlanta Urbanized Area.2

  ARC is directly

responsible for developing both a long‐range Regional Transportation Plan (RTP) and a short‐range

Transportation Improvement Program (TIP) that conform to the air quality goals established in the SIP,

according to the guidelines outlined in the Metropolitan Planning Regulations and Transportation

Conformity Rule.

A small portion of the Atlanta Urbanized Area extends into Hall County.    In February 2003, the

Gainesville‐Hall County MPO (GHMPO) was designated for the Gainesville Urbanized Area; the planning

boundary for the GHMPO covers Hall County in its entirety.  Hall County is included both in Atlanta's

ozone and fine particulate nonattainment areas.    The ARC performs the planning and technical work

required by the Transportation Conformity Rule, including, by agreement with the GHMPO, the

emissions modeling for Hall County.    ARC documents the analysis in a combined Conformity

Determination Report (CDR).    The United States Department of Transportation (USDOT) approves or

disapproves the conformity analysis in consultation with the USEPA.    A positive conformity

determination is required in order for the RTP and TIP to advance.   In addition, all of Carroll County,

which is not within an MPO boundary, is included within the Atlanta nonattainment area and included in

the travel and emissions modeling effort.  

                                                            

2 The ARC metropolitan planning area comprises  the City of Atlanta and the counties of Cherokee,

Clayton, Cobb, Coweta, DeKalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Henry, Paulding and

Rockdale, as well as portions of the counties of Barrow, Bartow, Newton, Spalding and Walton.
4

Current Attainment Status

1997 Eight‐Hour Ozone Standard

Effective June 15, 2004, 20 counties (see Figure 1) in the Atlanta area were designated as nonattainment

under the eight‐hour ozone standard with an initial classification of Marginal.   Ozone is not emitted

directly by any source; it is formed when Nitrogen Oxides (NOx) and Volatile Organic Compounds (VOC)

combine in the atmosphere in the presence of sunlight.   Air pollution control strategies are aimed at

controlling NOx and VOC since they are precursors to ozone formation. The eight‐hour ozone

nonattainment area encompasses the previous 13‐county one‐hour ozone maintenance area3 plus

seven additional "ring" counties.4

  

Since designation, the region was reclassified as a moderate ozone nonattainment area in April 2008

with an attainment date of June 15, 2010.  MVEBs were established for the 20‐county region as part of

the Atlanta Early Progress State Implementation Plan for the year 2008.    The GA EPD submitted a

Reasonable Further Progress Plan in 2009, extending the attainment deadline by one year, due to clean

data observations.  In the fall of 2009, GA EPD submitted an Attainment Plan for the 1997 eight‐hour

ozone standard to the USEPA.

1997 Annual PM2.5 Standard

On December 17, 2004, the USEPA also designated 20 whole counties and two partial counties (Heard

and Putnam, see Figure 1) near the metropolitan Atlanta area as nonattainment under the annual fine

particulate matter (PM2.5) standard.  Particulate matter, or PM, is the term for particles found in the air,

including dust, dirt, soot, smoke, and liquid droplets. The primary source of concern in air quality

emissions analyses is direct motor vehicle PM emissions, both from the combustion process and from

tire and brake wear, and a precursor to PM formation in the atmosphere, NOx. Particles less than 2.5

micrometers in diameter are referred to as "fine" particles and are believed to pose the greatest health

risks. The PM2.5 nonattainment area encompasses the previous 13‐county one‐hour ozone maintenance

area plus seven additional “ring” counties: Carroll, Bartow, Hall, Barrow, Walton, Newton, and Spalding

counties; and parts of Heard and Putnam counties.

The PM2.5 NAAQS has two standards associated with it – an annual standard of 15 micrograms per cubic

meter (ug/m3

) averaged over the course of a year, and a daily standard of 35ug/m3 measured over 24

hours.   

Under the PM2.5 standard, there is no classification system to determine stringency of emission control

measures or attainment year.  PM2.5 nonattainment areas must attain as soon as possible, but no later

than April 2010, with an additional five years provided if the state can demonstrate that it is warranted.  

The PM2.5 attainment SIP was submitted to USEPA by GA EPD on July 6, 2010.   The GA EPD plans on

requesting this SIP not be processed as a result of the pending PM2.5 clean data determination and the

                                                            

3 Cherokee, Clayton, Cobb, Coweta, DeKalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Henry, Paulding

and Rockdale Counties 4 Barrow, Bartow, Carroll, Hall, Newton, Spalding and Walton Counties
developm

methodol

ent of a Mai

logy is used to

intenance Pla

o determine

Figure 1 –

an.  Until a fin

conformity o

Atlanta Non

nalized plan w

f the RTP and

nattainment

with MVEB is

d TIP.

t Area Boun

s in place, an

ndaries

interim emis

5

sions
6

Modeling Assumptions

Emissions Modeling Assumptions

Section 93.105(c)(1)(i) of the Transportation Conformity Rule requires that Interagency partners be

provided the opportunity for evaluating and choosing a model and associated methods and assumptions

to be used in the regional emissions analysis needed to demonstrate conformity.

The ARC has consulted with the Interagency group as to the required version of the USEPA’s mobile

source emissions model.  This is documented along with the other planning assumptions and modeling

inputs in Exhibits 1A and 1B.  These documents were submitted to the Interagency consultation group in

accordance with Section 93.105(c)(1)(i) of the Transportation Conformity Rule.  The documents include

assumptions for both the eight‐hour ozone and the PM2.5 emissions analyses.  Interagency approval of

these assumptions was granted on August 26, 2011.

Travel Demand Modeling Assumptions

The regional emissions analysis utilized to develop Maintenance Plan MVEBs for both the eight‐hour

ozone standard and the annual PM2.5 standard relies on a methodology which utilizes ARC’s 20‐county

regional travel demand model.    A brief outline of the model structure follows.    More specific

information is available on the ARC’s website.5

Travel Model Networks

Updated travel model networks were created for each required emissions inventory year (2008 and

2024) to reflect projects in the currently approved Regional Transportation Plan, PLAN 2040.  This plan

received a positive conformity determination from USDOT, with USEPA concurrence, on September 6,

2011.  These projects have been identified by policy makers as the highest priority for transportation

investments in the Atlanta region.

ARC’s travel demand model was most recently calibrated to the year 2000, with some 2005 interim

validations and benchmarking thereafter.  Demographic data was developed for use in PLAN 2040 and is

outlined in Exhibit 1C.

Within the ARC travel demand model and emissions modeling process, free flow speeds are adjusted to

reflect the increase in delay and travel time on a roadway segment as traffic volumes build and

congestion levels increase.    Table 1 illustrates the speeds by facility and area type used in the travel

demand model.

                                                            

5 http://www.atlantaregional.com/transportation/travel‐demand‐model
7

Table 1 – Speeds by Facility and Area Type in the ARC Travel Demand Model

Facility Type

Urban

Very

High

Density

Urban

High

Density

Urban

Medium

Density

Urban

Low

Density

Suburban Exurban Rural Metered

Ramps

0 Zone Centroid

Connectors 7 11 11 11 11 14 14

1

Interstate /

Freeway  Free

Flow

55 58 58 61 61 63 65   

2 Parkway 50 50 55 55 57 60 60

3 HOV Buffer

Separated 55 58 58 61 61 63 65   

4 HOV Barrier

Separated 55 58 58 61 61 63 65

5

High Speed

Ramp / CD

Road

50 50 55 55 57 60 60 15

6 Medium Speed

Ramp 50 50 50 50 50 50 50 10

7 Low Speed

Ramp 40 40 40 40 40 40 40 10

8 Loop Ramp 30 30 30 30 30 30 30 10

9 Off Ramp w/

Intersection 25 25 25 25 25 25 25   

10 On Ramp w/

Intersection 40 40 40 40 40 40 40 5

11 Expressway 40 42 45 48 52 55 60   

12

Principal

Arterial ‐ Class

I

26 30 33 36 42 46 55

13

Principal

Arterial ‐ Class

II

24 27 30 34 40 44 48   

14 Minor Arterial

‐ Class I 22 25 28 31 38 42 45

15 Minor Arterial

‐ Class II 20 23 26 29 34 38 42   

16 HOV ‐ Arterial

(all classes) 20 27 30 33 36 39 42

17 Major

Collector 18 22 25 28 31 34 38   

18 Minor

Collector 15 18 21 24 27 30 35
8

Facility Type

Urban

Very

High

Density

Urban

High

Density

Urban

Medium

Density

Urban

Low

Density

Suburban Exurban Rural Metered

Ramps

19

Planned

Ramps w/

Intersections

30 30 30 30 30 30 30 5

20

Planned

Directional

Ramps

45 45 45 45 45 45 45 10

Transit Modeling

The transit portion of ARC’s travel demand model was calibrated to 2000 transit ridership estimates,

provided by regional transit operators.  Results from the 2001‐2002 Transit On‐Board Survey, as well as

preliminary adjustments from the 2009 Transit On‐Board Survey, are reflected in the travel demand

model’s transit parameters.    Current and projected transit routes are updated regularly to reflect

operational plans for the transit providers.

ARC’s travel demand model uses a mode choice model to determine the quantity of people that will

utilize transit services, versus those that will drive to their destinations.    Individual modal trips are

estimated from the person trip movements developed in the trip distribution model.    This model is

composed of three nested logit models:  

 Home based work trips, which include home based university trips

 Home based other trips, which include home based other, home based shopping and home

based grade school

 Non‐home based trips

From there, the final mode choice model is organized in terms of seven characteristics:

1) Mathematical structure

2) Trip purpose and choice sets

3) Limitations on choice sets

4) Analysis of transit access

5) Treatment of HOV lanes

6) Stratification by income groups

7) Analysis of alternative transit paths

Zero‐Car	Household	Distribution	

The auto ownership model was updated and validated using census data in 2008.    New income

coefficients were asserted using observed 2000 auto ownership shares as the basis.  CTPP TAZ level data

were processed to generate the expected auto‐ownership levels for each respective income group.  

Densities were found to still play a role in the decision to own an automobile.  As a result, the census
9

calibrations were modified to include a coefficient for zone density, providing a more accurate

prediction of auto‐ownership in the regional model.    

Survey	Expansion	

ARC conducted a regional transit on‐board survey in 2009‐2010 to get a better understanding of transit

travel behavior.  While the full expansion of the survey was not available in time for this model version

update, the survey was used to make important updates to the mode choice model.  A list of areas that

were modified follows:

 New transit coefficients were generated by trip purpose, mode of access and socioeconomic

class

 Use of kiss‐and‐ride facilities was adjusted

 Walking travel distance to transit was increased

 A pedestrian environment factor was introduced to adjust for easier walking conditions in more

urban areas of the region

 The transfer penalty assignment was modified

Fare	Changes	

As a part of the transportation conformity analysis performed for PLAN 2040, assumptions about transit

fares for the existing and planned regional transit system were made and coded in the regional travel

demand model.  Transit fares are used as supplied by the local transit operators and remain constant

over time, throughout the life of the plan, across all network years.  The fares reflect current operating

plans, as provided to ARC by the various transit operators throughout the region.    The transit fare

structure used to develop the plan makes use of a fare matrix on a zone‐to‐zone level with a universal

fare structure (flat fare) for all bus and rail lines.  

With the addition of new transit operators providing regional transit services, transfer fare agreements

between different interconnecting systems and the need to plan for future transit modes, more specific

transit coding was needed to accurately reflect the transit levels of service.    The current ARC coding

approach enables most of the fares to be coded universally for each mode, and all providers are allowed

to have different fares.  In addition, a protocol was established in the model stream to allow transit fare

to be coded by transit link.    The current fare values in the model are weighted according to the

percentage of riders using a discounted fare pass, and changes to these assumptions can be

incorporated directly into the model. The ARC model currently assumes that peak and off‐peak fares are

equivalent.

   
10

MOVES Overview

The Motor Vehicle Emissions Simulator (MOVES) is EPA’s latest available, state‐of‐the‐art tool for

estimating mobile source emissions from highway vehicles.    MOVES replaces the MOBILE6 emissions

model for use in State Implementation Plans (SIPs) and transportation conformity analyses.  It must be

used for new SIP development and for all conformity determinations after a three year conformity grace

period ending on March 2, 2013.6

    In preparation for the transition to MOVES, the ARC and GA EPD

jointly developed MOVES‐based methodologies to estimate emissions inventories for the Atlanta region.   

The MOVES modeling platform is substantially different than MOBILE6 due to the availability of a

graphical user interface (GUI) to set the general parameters   for running MOVES and a County Data

Manager to assist the user in managing data inputs and data format.  In addition, MOVES provides two

modes to estimate emissions – emissions rate mode and emissions inventory mode.  Inventory mode

was chosen over emission rate mode after extensive testing of both approaches.  The following section

provides detail on MOVES general parameters and data inputs, as applied in the PM2.5 and Ozone

Maintenance SIPs using MOVES in inventory mode.   

The MOVES GUI is used to set the general parameters of a particular MOVES run, while the County Data

Manager is used to tailor the MOVES inputs using local data.    Table 2 shows the selections applied

through the MOVES GUI to set the general parameters for each of the four types of MOVES runs needed

to estimate emissions for the Atlanta PM2.5 and Ozone nonattainment areas.  It should be noted that

for PM2.5 runs the month July is chosen as a “dummy month,” but the fuel and meteorology inputs

provided through the County Data Manager represent the entire year by providing average annual data.   

Fulton County is chosen to represent the 13 I/M program counties included in the previous one‐hour

ozone nonattainment area and Bartow County is chosen to represent the 7 additional ring counties that

were added with the transition to the eight‐hour ozone standard and PM2.5 standard.  This distinction

was needed to reflect different types of emission controls in place in the two geographies.  Note that

additional inputs imported through the County Data Manager represent the entire 13 or 7 county areas,

respectively.

                                                            

6 Based on the EPA’s Direct Final Rule from October 13, 2011 to extend the MOVES grace period for

regional conformity analysis for one year.
11

Table 2 – MOVES General Parameters

MOVES

Screen Input Item 13‐CountyOzone

13‐County

PM

7‐County

Ozone

7‐County  

PM

Description Description User Choice

Scale Domain/Scale County

Calculation Type Inventory

Time Spans

Time Agg. Level Hour Hour Hour Hour

Year Varies Varies Varies Varies

Months July July July July

Days Weekday Weekday Weekday Weekday

Hours Select All Select All Select All Select All

Geographic

Bounds Geographic Bounds Fulton Fulton Bartow Bartow

Vehicles Vehicles All Gas & Diesel Combinations + CNG Transit Buses

Road Type Road Type Select All

Pollutants/

Processes Pollutants/Processes VOC, NOx, andsupporting

PM2.5 with all

sub‐species,

NOx

VOC, NOx, and

supporting

PM2.5 with all

sub‐species,

NOx

General

Output

Database Name 13‐County

Ozone [Year]

13‐County PM

[Year]

7‐County

Ozone [Year]

7‐County PM

[Year]

Units Select "Grams", "Joules", and "Miles"

Activity No Selections Required

Output

Emissions

Detail

On Road Select "Source Use Type"
12

MOVES Input Development – Travel Demand Post Processing Procedures

The Atlanta regional travel demand model produces estimates of travel and vehicle hours traveled (VHT)

and for each link in the highway network for four separate time of day periods.    The links from the

highway assignment contain a variety of attributes such as the number of lanes, distance, speed,

capacities and daily volumes.  In order to account for travel conditions throughout the day, vehicle miles

traveled (VMT) estimates, times and speeds by hour were produced.  Other refinements to the network

link data discussed below were performed to produce the files needed for MOVES.  The highway and

transit assignments were used in addition to Highway Performance Monitoring System (HPMS) counts,

Georgia Department of Transportation (GDOT) vehicle classification counts7 and MOVES defaults to

develop input files for MOVES using Cube Voyager scripts.  

VMT Adjustment Factors		

Traffic volumes produced by the travel model are adjusted within the emissions modeling process by

applying a VMT adjustment factor, which is a combination of HPMS adjustment factors, used to

reconcile travel model VMT to HPMS VMT estimates,8 and to reflect seasonal adjustment.    For the

purpose of ozone precursor emissions modeling,9 seasonal adjustment factors are used to convert the

average annual daily traffic produced by the travel model to average summer‐time daily traffic.  For the

purpose of PM2.5 emissions modeling, no seasonal adjustment is necessary since the HPMS data in the

GDOT 445 report reflects annual average travel conditions and a direct adjustment factor between the

model data and the HPMS data can be developed.

EPA requires10 that reasonable methods be used to estimate VMT on off‐network (off‐model) roadways

within the urban transportation planning area. Off‐model VMT is travel that is accounted for within

HPMS estimates, but not accounted for within the coded transportation network; it typically reflects

travel on the local road system. EPA also recommends11 for areas with travel demand models in place,

that HPMS adjustments be made based on comparison of base year VMT from the transportation model

to base year HPMS VMT estimates. The ARC calculates HPMS adjustment factors by comparing HPMS

VMT to travel model VMT by HPMS functional classes for the 2000 calibration year. In the past, the

adjustment factors were developed for the 12 functional classes which stratifies the facilities by urban

versus rural designation.  To be consistent with the new USDOT policy which eliminated the urban/rural

stratification in the functional classification designations beginning with 2009 data reported in 2010,12

the aggregate functional classification level was used.  The resulting factors are then applied to travel

                                                            

7 See Exhibit 2

8 40 CFR Sections 93.122(a)(7) and 93.122(b)(3)

9 Section 3.4.2.6, Procedures for Emission Inventory Preparation, Volume IV: Mobile Sources, EPA420‐R‐

92‐009, USEPA Office of Air and Radiation, Office of Mobile Sources, 1992.

10 40 CFR Section 93.122(a)(7) 11 40 CFR Section 93.122(b)(3)   12 Guidance for the Functional Classification of Highways (updated), Federal Highway Administration,

October 14, 2008
13

model VMT estimates for future analysis years. The following equation was used to calculate the HPMS

adjustment factors:  

HPMS Adjustment Factori = 2000 HPMS VMTi/ 2000 MODEL VMTi

Where i = HPMS functional class

To determine the 2000 HPMS VMT, average daily VMT for the year 2000 were summarized by the

aggregate HPMS functional classes for the 13 and 7‐county areas separately. County‐level HPMS data by

functional class was taken from the GDOT Office of Transportation Data 445 Report.  GDOT’s 445 Report

provides information on mileage and VMT by route type and road system and contains county‐specific

State Route, County Road and City Street mileage and VMT broken down by functional classification.

VMT by county and functional class were aggregated to total VMT by HPMS functional class. 2000 Travel

Demand Model VMT at the HPMS functional class level was derived from the recalibrated 2000 travel

model network. HPMS adjustment factors for the 13‐  and 7‐county areas are listed below which are

used for PM2.5 emission modeling.  

Table 3 – 13‐County PM2.5 HPMS Adjustment Factors

Functional Class Name Functional Class No. HPMS Data Model Data VMT HPMS Adjustment

Interstates/Frwy 1,11,12 47,171,325 46,049,179 1.02

Arterials 2,6,14,16 39,900,297 40,382,825 0.99

Collectors 7,8,17 12,242,686 11,240,938 1.09

Local 9,19 18,734,189 21,040,927 0.89

Total 118,048,497 118,713,869 0.99

Table 4 – 7‐County PM2.5 HPMS Adjustment Factors

Functional Class Name Functional Class No. HPMS Data Model Data VMT HPMS Adjustment

Interstates/Frwy 1,11,12 4,482,987 5,247,292 0.85

Arterials 2,6,14,16 7,776,636 8,016,746 0.97

Collectors 7,8,17 3,517,297 1,955,582 1.80

Local 9,19 3,133,469 2,868,633 1.09

Total 18,910,389 18,088,253 1.05

Summer (seasonal) adjustment factors are used to convert from average annual daily VMT to average

summer‐season daily VMT for the purposes of ozone precursor emissions modeling.13 Seasonal

adjustment factors reflect the latest factors provided by the GDOT Office of Transportation Data on

August 9, 2006.  Summer‐adjustment factors for the 13‐ and 7‐county geographies are listed below.

                                                            

13 Procedures for Emission Inventory Preparation, Volume IV: Mobile Sources, Section 3.4.2.6, EPA420‐R‐

92‐009, USEPA Office of Air and Radiation, Office of Mobile Sources, 1992.
14

Table 5 – Summer Adjustment Factors

Functional Class Name Functional Class No. 13 Counties 7 Counties

Interstates/Freeways 1,11,12 1.02 1.04

Arterials 2,6,14,16 1.00 1.02

Collectors 7,8,17 0.99 1.01

Local 9,19 0.98 1.01

Total 1.00 1.02

HPMS adjustment factors were multiplied by the seasonal adjustment factors for the HPMS functional

classification categories to produce a set of VMT adjustment factors by HPMS functional classification for

13‐county and 7‐county portions of the 20‐county eight‐hour ozone nonattainment area, separately. The

final VMT adjustment factors listed below are used for ozone precursor modeling.

Table 6 – VMT Adjustment Factors for Ozone

Functional Class Name Functional Class No. 13 Counties 7 Counties

Interstates/Frwy 1,11,12 1.05 0.89

Arterials 2,6,14,16 0.98 0.99

Collectors 7,8,17 1.07 1.81

Local 9,19 0.87 1.10

Total 1.00 1.06

Network Refinements

The following refinements were performed on the final highway assignment:

    

 Transit volumes from the daily transit assignment reflecting bus service were added to the

highway network

 Links with missing or out of range HPMS code were assigned a code based on the link facility

and area type

 Centroid connector speeds were set based on area type to represent speeds on local roads

o Urban Very High Density = 15

o Urban High Density = 18

o Urban Medium Density = 21

o Urban Low Density = 24

o Suburban = 27

o Exurban  = 30

o Rural = 35
15

VMT by Hour

MOVES requires the stratification of the VMT, VHT and speeds by hour to provide more accurate

information for use in estimating emissions.    The regional travel demand model produces VMT

estimates and speeds by the four time‐of‐day periods listed below:   

 AM Period 6:00 am – 10:00 am 4 hours

 Midday Period 10:00 am – 3:00 pm 5 hours

 PM Period 3:00 pm – 7:00 pm 4 hours

 Night Period 7:00 pm – 6:00 am 11 hours

To allocate the VMT by time period from the assignment, the MOVES national factors that stratify VMT

by hour and source type were used.  First, the hourly shares of the VMT based on the MOVES factors

were normalized within the four time periods.  Next, the hourly share of each associated time period

was calculated and applied to each link to determine the hourly volumes.    The sum of the hourly

volumes by time of day matched the time of day volumes from the highway assignments.   The hourly

volumes were then processed through the volume/delay curves based on the time of day to estimate

hourly speeds and times.

Roadtype Classification

The network link data was also classified by MOVES roadtype based on functional classification.    The

mapping of Federal Highway Administration (FHWA) highway functional system classifications to the

appropriate MOVES roadtypes used for this modeling is listed in Table 7.  Interstate and freeway ramps

are functionally classified as local facilities in Georgia.    Since these facilities operate with restricted

access, the facility type definition variable (a unique variable in the highway network that defines the

highway facilities based on their operation) was used to classify ramps as either rural or urban restricted

facilities.  Off‐network activity is calculated within the MOVES process based on the source type vehicle

population and is not an input from the travel demand model data.  
16

Table 7 – Listing of FHWA Highway Functional Classifications Mapped to MOVES Road Types

FHWA Highway Functional System MOVES Road Type MOVES Value

Rural interstate Rural restricted access 2

Rural other principal arterial Rural restricted access 2

Rural minor arterial Rural unrestricted access 3

Rural major collector Rural unrestricted access 3

Rural minor collector Rural unrestricted access 3

Rural local Rural unrestricted access 3

Urban interstate Urban restricted access 4

Urban other freeways Urban restricted access 4

Urban other principal arterial Urban unrestricted access 5

Urban minor arterial Urban unrestricted access 5

Urban collector Urban unrestricted access 5

Urban local Urban unrestricted access 5
17

MOVES County Data Manger Input Files

The MOVES County Data Manager serves as the user interface to input locally derived data for an

emissions analysis.   Local data are derived using a variety of modeled and available sources.  Table 8

outlines the range of local data incorporated into the MOVES model.  An explanation of how these data

are developed follows.  In addition, Exhibit 3 provides a sample set of MOVES inputs used by ARC to

develop the Maintenance Plan mobile source inventory.

Table 8 – County Data Manager Worksheets

County Data Manager Input Worksheet Name

Age Distribution sourceTypeAgeDistribution

Average Speed Distribution avgSpeedDistribution

Fuel FuelSupply

FuelFormulation

I/M Programs IMCoverage

Meteorology DayMonthHour

Ramp Fraction roadType

Road Type Distribution roadTypeDistribution

Source Type Population sourceTypeYear

Vehicle Type VMT

HPMSVTypeYear

monthVMTFraction

dayVMTFraction

hourVMTFraction

Age Distribution

Latest available age distribution data for the Atlanta region was converted from a MOBILE6 to a MOVES

format using an EPA converter.14    MOBILE6 age distributions are shown over 25 years, but MOVES

requires age distributions over 30 years.  The EPA converter spreadsheet makes assumptions about how

vehicles that are 25‐30 years old are distributed over the oldest 5 years.  MOBILE6 distributions were

derived from 2002 R.L. Polk & Co. registration data for the 13 and 7 county areas separately for all

vehicle types, except for HDV8B where MOBILE6 defaults were used.

Average Speed Distribution

To prepare this input the weekday link hourly vehicle hours travelled (VHT) is summarized by road type

and speed bin.  The MOVES defaults for the 13 source types by year are used to allocate to vehicle type.  

The fraction of time in each speed bin for each hour based on vehicle type, road type, and average

speed is calculated where the fractions sum to one for each combination of vehicle type and road type

by hour.

                                                            

14 RegistrationDistributionConverter_Veh16 (XLS) available at

http://www.epa.gov/otaq/models/moves/tools.htm
18

Fuel

MOVES defaults for fuel characteristics in Fulton County (13‐county) and Bartow County (7‐county)

were reviewed and determined to accurately reflect the local fuel in use, which has the following

characteristics:  

 Fuel ‐ Phase 2 Low Sulfur, Low RVP Georgia Gasoline15

 100% market share of 10% ethanol‐blend gasoline (E10) assumed

 Volatility waiver for E10 allows 1.0 psi RVP increase

The following provides more details on the MOVES default values used:

 Ozone ‐ MOVES defaults are used for a July weekday for Fulton County and Bartow County

 PM2.5 – MOVES defaults are used for the 12 months of the year for Fulton County and Bartow

County.  The 12 months of fuel data are annualized by setting the single month market share

equal to the fraction of time that fuel is used throughout the year (number of months in use

divided by 12).

I/M Program

The 13‐county area has an inspection/maintenance program that is modeled in MOVES, but the 7‐

county area does not.  MOVES defaults for Fulton County were inspected and modified to provide the

correct model years covered and testing methods used as summarized in the I/M program

characteristics below:

 Stage II Refueling Vapor Recovery

o Started in 1992

o Three phase in years

o 81% efficiency

 Exhaust and Evaporative (OBD and gas cap pressure test) for 1996 and newer vehicles

o Annual inspection required

o Computerized test and repair OBD – Exhaust

o Computerized test and repair OBD & GC ‐ Evaporative

o Applies to all LDG vehicle types

o Three year grace period

o 3% waiver rate for all vehicles – Exhaust test

o 0% waiver rate for all vehicles – Evaporative test

o 97% compliance

 Exhaust and Evaporative test for 1975 – 1995 vehicles

o Annual inspection required

o Computerized test and repair ASM 2525/5015 Phase‐in – Exhaust

o Computerized test and repair GC – Evaporative

                                                            

15 In 2002, Georgia's two‐phase gasoline sulfur control program limited average sulfur in gasoline sold in

the 13‐county Atlanta area and in 12 surrounding counties to 150 parts per million (ppm).  In addition,

there was a seasonal (June 1 to September 15) 7.0 pounds per square inch (psi) Reid vapor pressure cap

on gasoline sold in this Phase 1 area.  In 2003, Phase 2 of Georgia's gasoline rule reduced average sulfur

to 30 ppm year‐round and added 20 additional counties to the sulfur and RVP control program. 
19

o Applies to all LDG vehicle types

o 3% waiver rate for all vehicles – Exhaust

o 0% waiver rate for all vehicles – Evaporative

o 97% compliance

o 25 year and older model years are exempt

Exhibit 4 documents the calculations of the emissions reductions credit loss from the senior I/M

exemption.

Meteorology

Meteorological data on hourly temperatures and relative humidity were obtained from the National

Mobile Inventory Model (NMIM) County Database (version NCD20090531) for the year 2008.  

Temperature and humidity values were extracted for all 20 counties and averaged together to produce

one set of values for the entire 20‐county area.  The following provides more details on the differences

between meteorology data used for ozone and PM2.5 analyses:

 Ozone – Meteorological data from July 2008 were used to represent the ozone season

 PM2.5 – Meteorological data from all 12 months of the year in 2008 were extracted and

averaged together to represent an average annual 2008 meteorological condition.

Ramp Fraction

The weekday link VMT is summarized for interstate, freeway and ramp facilities by urban versus rural

area type classifications.  The percent of ramp VMT of the total interstate, freeway and ramp VMT was

calculated by area type.

Road Type Distribution

The weekday link hourly VMT is summarized by roadtype. The MOVES defaults for the 13 source types

by year are used to allocate to vehicle type.    The fraction of VMT by road type and vehicle type is

calculated, where the fractions sum to one for each vehicle type.

Source Type Population

Source Type Population (the number of each of 13 vehicle types) is an input that was not required with

MOBILE6.   Registration data, which were used to produce age distributions, are used to produce this

input for most vehicle types.  However, for long‐haul combination trucks (source type 62) a VMT‐based

method is used since these types of trucks from around the country move through the region and are

usually not registered here.

Source type population for source types 11‐61 are derived from registration data and human population

estimates and forecasts.  The following data sources are used:  

 2002 R.L. Polk & Co. registration data each of the 20 counties

 Georgia registration data (2003 and 2007)16

 2002 and 2007 Census human population estimates

                                                            

16 Obtained from www.georgiastats.uga.edu
20

 2007‐2040 ARC human population forecasts

After this data was accumulated, the following method is used to project future source type population:

1. Grow 2002 Polk registration data to 2007 using different growth factors that depend on vehicle

type as shown in Table 9.

2. Convert the Polk registration data to MOVES vehicle types using a modified EPA converter

spreadsheet17

3. Grow the 2007 source type population by county to the appropriate future year(s) using 2007‐

2040 ARC human population forecasts by county

4. Summarize the source type population by 13 and 7‐county areas separately

Table 9 – 2002‐2007 Growth Factors used

Vehicle types Growth factor

HDBS Georgia registration data (2003 and 2007), Buses

HDBT Georgia registration data (2003 and 2007), Buses

MC Georgia registration data (2003 and 2007), Motorcycles

All Others Population 2002 and 2007

Vehicle population for source type 62 (long‐haul trucks) was recalculated using corresponding VMT and

national default ratios of VMT and vehicle population in order to account for activity from trucks not

registered but run locally.

Vehicle Type VMT

Vehicle Type VMT is broken into four separate MOVES worksheets (HPMSVTypeYear,

monthVMTFraction, dayVMTFraction and hourVMTFraction).    These four variables define travel

characteristics in the area of study and are calculated separately or derived from MOVES defaults.

HPMSVTypeYear

The weekday VMT is summarized by MOVES roadtype and then weighted by the vehicle classification

counts18 for the 13 or 7‐county area by the 6 HPMS vehicle types.  The fractions for vehicle type 20 and

30 are then re‐distributed based on the MOVES source vehicle defaults for the year.  This is because the

vehicle classification counts are collected using counters which count vehicles by the number of axles

and as a result, the counts do not accurately reflect the difference between passenger cars and SUVs.  

The daily VMT is annualized using the EPA AADVMT Calculator Excel workbook.

                                                            

17 A converter was developed by EPD based on the EPA RegistrationDistributionConverter_Veh16 (XLS)

available at http://www.epa.gov/otaq/models/moves/tools.htm

18The summary of the vehicle classification counts is in Exhibit 3
21

monthVMTFraction and dayVMTFraction

MOVES national defaults were used for these two inputs because reliable local data was not available.  

The regional travel demand model is developed for an average weekday.    The vehicle classification

counts used for some analyses were not collected to be statistically reliable by day of week or monthly

basis.

hourVMTFraction

The weekday link hourly VMT is summarized by roadtype and hour. The MOVES defaults for the 13

source types by year are used to allocate to vehicle type.  The fraction of VMT by road type and vehicle

type is calculated where the fractions sum to one for each vehicle type by roadtype. This variable must

sum to 1 for each source type‐road type‐type of day combination.
22

Off‐Model Putnam County Mobile Emissions Analysis

The Atlanta PM2.5 Nonattainment Area includes small parts of two counties, Heard and Putnam, which

fall outside of the core 20 whole counties which make up the eight‐hour ozone and PM2.5 nonattainment

areas.  A travel model is not in place for these counties.  According to the Transportation Conformity

Rule 93.122(a)(7), reasonable methods shall be used to estimate nonattainment or maintenance area

VMT on off‐network roadways within the urban transportation planning area, and on roadways outside

the urban transportation planning area.  Therefore, a revised off‐travel model technique was developed

to estimate average annual daily VMT for use in the MOVES model in the partial county areas.

For Heard County the roads identified are private roads that service Georgia Power’s Plant Wansley.  

These roads do not experience through‐traffic and, therefore, do not need to be included in the regional

emission analysis.  As such, this methodology only applies to Putnam County.

Like the 7 and 13‐county portions, a MOVES run was prepared for Putnam County using the inputs

described in Table 10.  Travel characteristics in Putnam County were considered to be similar to the 7‐

county outer‐portion of the Atlanta Nonattainment Area.  These characteristics were mixed with data

from GDOT’s 445 VMT reports and state data to generate the necessary inputs to produce a MOVES run

for the entirety of Putnam County.

Table 10 – Putnam County MOVES County Data Manager Inputs19

MOVES Input Data Source

Age Distribution Derived from the 139 county average of R.L. Polk Data

Source Type

Population

Grown from the 2002 R.L. Polk data based on human population estimates from

the Georgia Office of Planning and Budget

Fuel Annualized MOVES Defaults for Putnam County

Meteorology    Annualized 20‐county meteorology for 2008

Vehicle Type

VMT

 HPMSvTypeYr – derived from the GDOT 445 workbooks with MOVES

default source type fraction break outs and converted using the EPA

provided AADVMT calculator

 Month and Daily Fractions – MOVES defaults

 Hourly Fractions – Taken from 7‐county portion of travel model post‐

processing

Road Type

Distribution Taken from the 7‐county portion of the travel model post‐processing

Average Speed

Distribution Taken from the 7‐county portion of the travel model post‐processing

Ramp Fraction    Taken from the 7‐county portion of the travel model post‐processing

                                                            

19 More detail on the development of MOVES Inputs is available in the chapter regarding the MOVES

County Data Manager Input Files
After tota

match the

imported

Putnam C

boundary

account fo

al emissions f

e percent of h

into GIS and

County’s pop

y.    Therefore

or the ratio o

for Putnam C

human popul

d an analysis

ulation (Figu

e, total Putna

of population

Figure 2

County were

ation in the P

s was perfor

re 2).    3,484

am County M

inside the No

– Putnam C

calculated u

PM2.5 Nonatta

rmed to dete

4 of Putnam

MOVES emis

onattainment

County Nona

using MOVES,

ainment Area

ermine the N

County’s 21

ssion’s result

t Area to the t

attainment A

, the value w

a.  2010 Censu

Nonattainmen

1,218 citizens

ts are multip

total county’s

Area

was scaled ba

us TIGER files

nt Area’s sha

s reside insid

plied by 16.4

s population.

23

ack to

s were

are of

de the

4% to
24

MOVES Model Output		

The following sections contain the data output from running the MOVES model with the travel data and

methodologies outlined in this document.  In addition, Exhibit 5 discusses work the ARC underwent to

determine required safety margins.

Eight‐Hour Ozone Standard Maintenance Plan

Table 11 documents the results of the emissions analysis for the eight‐hour ozone standard for the years

2008 and 2024.    This table accounts for both running and nonrunning emissions estimated by the

MOVES model.  MOVES output in grams per day is converted to tons per day by dividing by the grams to

tons conversion factor 907,184.74.  Final emissions account for the senior I/M exemption.

Table 11 – Daily Ozone Precursor Emissions

Pollutant 2008 Emissions (tons/day) 2024 Emissions (tons/day)

NOx 364.02 99.43

VOC 165.53 62.56

MOVES Model Output – Annual PM2.5 Standard Maintenance Plan

Table 12 documents the results of the emissions analysis for the annual PM2.5 standard for the years

2008 and 2024.    This table accounts for both running and nonrunning emissions estimated by the

MOVES model.  MOVES output in grams per day is converted to tons per day by dividing by the grams to

tons conversion factor 907,184.74.    The result is then annualized by multiplying by the number of

weekday equivalent days in a year (341.9809), which accounts for the MOVES urban weekend

adjustment factor:

Weekday Equivalent = 365 x (5 weekdays/7days) + 365 x (2 weekends/7days) x 0.77927

Where 0.77927 is the MOVES Default Urban Weekend Adjustment Factor

Final values account for the weekday factorization, the partial Putnam County emissions and the senior

I/M exemption.  Outputs of PM2.5 emissions include the sum of total PM2.5 exhaust, brake wear and tire

wear.

Table 12 –PM2.5 Precursor Emissions

Pollutant 2008 Emissions (tons/day) 2024 Emissions (tons/day)

NOx 128,954.56 35,271.63

PM2.5 4,661.88 1,642.17

SO2 725.14 469.08