APPENDIX F

Cecil County MOBILE Source Emissions

Technical Support Document

An Explanation of Methodology

Prepared for:

Maryland Department of the Environment

1800 Washington Boulevard

Baltimore, MD  21230

Prepared by:

Michael Baker, Jr., Inc.

1304 Concourse Drive, Suite 200

Linthicum, MD  21090

March 2007

Cecil County: Mobile Source Emissions

Technical Support Document

March 2007

Table of Contents

  TOC \o "1-4"  Introduction	  PAGEREF _Toc161045226 \h  4 

Highway Vehicle Emissions Inventory	  PAGEREF _Toc161045227 \h  4 

Overview of Methodology	  PAGEREF _Toc161045228 \h  4 

Analysis Process and Tools	  PAGEREF _Toc161045229 \h  6 

MOBILE6.2	  PAGEREF _Toc161045230 \h  6 

PPSUITE	  PAGEREF _Toc161045231 \h  6 

Traffic Data SOURces	  PAGEREF _Toc161045232 \h  8 

Roadway Data	  PAGEREF _Toc161045233 \h  8 

Additions and Adjustments to Roadway Data	  PAGEREF _Toc161045234 \h  9 

Producing Future Year Volumes	  PAGEREF _Toc161045235 \h  11 

MOBILE6.2 Input Data	  PAGEREF _Toc161045236 \h  12 

Overview of Emission Rates	  PAGEREF _Toc161045237 \h  12 

Local Inputs to MOBILE6.2	  PAGEREF _Toc161045238 \h  13 

SPEED/EMISSION ESTIMATION PROCEDURE	  PAGEREF _Toc161045239 \h  17 

Volume/VMT Development	  PAGEREF _Toc161045240 \h  17 

Speed/Delay Determination	  PAGEREF _Toc161045241 \h  21 

HPMS and VMT Adjustments	  PAGEREF _Toc161045242 \h  21 

VMT and Speed Aggregation	  PAGEREF _Toc161045243 \h  22 

MOBILE6.2 Emissions Run	  PAGEREF _Toc161045244 \h  23 

Time of Day and Diurnal Emissions	  PAGEREF _Toc161045245 \h  23 

Process MOBILE6.2 Output	  PAGEREF _Toc161045246 \h  23 

RESOURCES	  PAGEREF _Toc161045247 \h  24 

 

List of Tables

  TOC \h \z \c "Table"    HYPERLINK \l "_Toc161045248"  Table 1	Summary
of Attachments	  PAGEREF _Toc161045248 \h  5  

  HYPERLINK \l "_Toc161045249"  Table 2	Summary of Inventory Analysis
Tools	  PAGEREF _Toc161045249 \h  6  

  HYPERLINK \l "_Toc161045250"  Table 3	Cecil County VMT Growth
Assumptions	  PAGEREF _Toc161045250 \h  11  

  HYPERLINK \l "_Toc161045251"  Table 4	Summary of VEIP Program
Parameters	  PAGEREF _Toc161045251 \h  16  

  HYPERLINK \l "_Toc161045252"  Table 5	Summary of Weather Data	 
PAGEREF _Toc161045252 \h  16  

 

List of Figures

  TOC \h \z \c "Figure"    HYPERLINK \l "_Toc161045253"  Figure 1
Emission Calculation Process for Cecil County	  PAGEREF _Toc161045253 \h
 7  

  HYPERLINK \l "_Toc161045254"  Figure 2	SHA-Based Process
Classification Scheme	  PAGEREF _Toc161045254 \h  8  

  HYPERLINK \l "_Toc161045255"  Figure 3	MOBILE6.2 Vehicle Classes	 
PAGEREF _Toc161045255 \h  10  

  HYPERLINK \l "_Toc161045256"  Figure 4	MOBILE6.2 Inputs	  PAGEREF
_Toc161045256 \h  13  

  HYPERLINK \l "_Toc161045257"  Figure 5	MOBILE6.2 Speed and Emissions
Curves	  PAGEREF _Toc161045257 \h  15  

  HYPERLINK \l "_Toc161045258"  Figure 6	PPSUITE Speed/Emission
Estimation Procedure	  PAGEREF _Toc161045258 \h  18  

  HYPERLINK \l "_Toc161045259"  Figure 7	Sample Summer Seasonal Factor
File	  PAGEREF _Toc161045259 \h  19  

  HYPERLINK \l "_Toc161045260"  Figure 8	Sample Vehicle Mix File	 
PAGEREF _Toc161045260 \h  20  

  HYPERLINK \l "_Toc161045261"  Figure 9	Sample HPMS Adjustment File	 
PAGEREF _Toc161045261 \h  22  

  HYPERLINK \l "_Toc161045262"  Figure 10	VMT Aggregation Scheme	 
PAGEREF _Toc161045262 \h  22  

 

Introduction 

The purpose of this technical document is to explain how Maryland
estimates emissions from highway vehicles for inclusion in its emission
inventories and State Implementation Plans (SIP).

Highway Vehicle Emissions Inventory

The operation of highway vehicles has proven to be a significant
contributor to air pollution, particularly to ground-level ozone, as
they emit both VOCs and NOx during operation. Ground-level ozone is not
created directly rather, it is formed through a chemical reaction
between VOCs and NOx in the presence of sunlight. Given that both VOCs
and NOx are emitted from the operation of highway vehicles, Maryland’s
ozone-related emission inventory efforts have been focused on these
pollutants.

Estimating the emission rate and activity levels of all vehicles on the
road during a typical summer day is a complicated endeavor. If every
vehicle emitted the same amount of pollution all the time, one could
simply multiply those emission standards (emission rate in grams of
pollution per mile) times the number of miles driven (activity level) to
estimate total emissions. But, the fact is that emission rates from all
vehicles vary over the entire range of conditions under which they
operate. These variables include air temperature, speed, traffic
conditions, operating mode (started cold? started warm?) and fuel. The
inventory must also account for non-exhaust or evaporative emissions. In
addition, the fleet is composed of several generations, types of
vehicles and their emission control technologies, each of which performs
differently. This requires that the composition of the fleet (vehicle
ages and types) must also be included in the estimation algorithm. 

In order to estimate both the rate at which emissions are being
generated and to calculate vehicle miles traveled (activity level),
Maryland examines its road network and fleet to estimate vehicle
activity. For ozone-related inventories, this is done for a typical
summer weekday. For CO and PM emission inventories, this may be done for
a typical winter weekday or annual conditions. Not only must this be
done for a baseline year, but it must also be projected into the future.
This process involves a large quantity of data and is extremely complex.


Computer models have been developed to perform these calculations by
simulating the travel of vehicles on the State’s roadway system. These
models then generate emission rates (or emission factors) for different
vehicle types for area-specific conditions and then combine them in
summary form. The “area-specific conditions” include vehicle and
highway data, plus control measure characteristics and future year
projections of all variables.  

Overview of Methodology

EPA guidance documents were used to develop the base and future year
emissions inventories for the Cecil County Nonattainment Area. They
include:

Policy Guidance on the Use of MOBILE6 for SIP Development and
Transportation Conformity, US EPA Office of Air and Radiation, dated
January 18, 2002.

Technical Guidance on the Use of MOBILE6.2 for Emission Inventory
Preparation, US EPA Office of Transportation and Air Quality,
EPA420-R-04-013, dated August 2004.

User’s Guide to MOBILE 6.1 and MOBILE6.2, Mobile Source Emission
Factor Model, EPA Office of Air and Radiation, EPA420-R-03-010, dated
August 2003.

Mobile source emission factors were calculated using EPA’s MOBILE6.2
emission model. The methodologies used to produce the emission results
conform to the recommendations provided in EPA’s Technical Guidance.
Local data has been used for the primary data items that have a
significant impact on emissions. For this submission, local data inputs
to the analysis process reflect the latest planning assumptions based on
2005 data. These include:

VMT and speeds

Vehicle type mixes

Vehicle age distributions/diesel sales fractions

Seasonal adjustments

Hourly distributions 

Temperatures/humidity/barometric pressure 

Inspection/Maintenance parameters 

Fuel program characteristics. 

The analysis methodology is consistent with past statewide inventory
efforts including the 2002 National Emissions Inventory (NEI)
submission. A detailed methodology that addresses the key input data
sources and analysis tools used for the Cecil County Area inventory is
provided in the next chapter. 

To complement this document, attachments have been provided with
additional detail regarding the analysis methodology and the MOBILE6.2
input parameters. These include:

Table   SEQ Table \* ARABIC  1 	Summary of Attachments

Title	Description

MOBILE6.2 Input Parameter Summary	Provides summary of input parameters
related to traffic data sources, fuel, weather, I/M, and other MOBILE6.2
related parameters.

MOBILE6.2 Sample 

Input File	Provides examples of the MOBILE6.2 input files.



Analysis Process and Tools  

The Cecil County inventory analysis utilizes several key
software/programs for producing the county emissions totals. These tools
are outlined in Table 2.

Table   SEQ Table \* ARABIC  2 	Summary of Inventory Analysis Tools

Tool	Purpose

MOBILE6.2	Produces emission factors for each pollutant in Grams/Mile for
VOC and NOx

PPSUITE	Processes the highway data, Calculates hourly congested speeds
for each state roadway segment, Prepares MOBILE6.2 input files,
Processes MOBILE6.2 output files



MOBILE6.2

The heart of the highway vehicle emission calculation procedure is
EPA’s highway vehicle emission factor model, MOBILE. This is a FORTRAN
program that calculates average in-use fleet emission factors for ozone
precursors for each of twenty-eight categories of vehicles under various
conditions affecting in-use emission levels (e.g., ambient temperatures,
average traffic speeds, gasoline volatility) as specified by the model
user. MOBILE produces the “emission rates” referred to in the
previous section. 

The Cecil County inventory reflects the highway mobile source emission
estimations using EPA’s MOBILE6.2 emission model. The latest version
of MOBILE6.2 is a major revision based on new test data and accounts for
changes in vehicle technology and regulations. In addition, the model
includes an improved understanding of in-use emission levels and the
factors that influence them resulting in significantly more detailed
input data. As compared to previous MOBILE versions, MOBILE6.2 has a
significant impact on the emission factors, benefits of available
control strategies, effects of new regulations, and corrections to basic
emission rates. 

PPSUITE

Cecil County also uses a post processor named PPSUITE (formerly named
PPAQ - Post Processor for Air Quality), which consists of a set of
programs that perform the following functions:

Analyzes highway operating conditions

Calculates highway speeds 

Compiles vehicle miles of travel (VMT) and vehicle type mix data

Prepares MOBILE6.2 runs

Calculates emission quantities from output MOBILE6.2 emission rates and
accumulated highway VMT.

PPSUITE has become a widely used and accepted tool for estimating speeds
and processing MOBILE emission rates. It is currently being used in
other states including Maryland, Pennsylvania, New York City, New
Jersey, Louisiana, Virginia, and Indiana. The software is based upon
accepted transportation engineering methodologies. For example, PPSUITE
utilizes speed and delay estimation procedures based on planning methods
provided in the 2000 Highway Capacity Manual, a report prepared by the
Transportation Research Board (TRB) summarizing current knowledge and
analysis techniques for capacity and level-of-service analyses of the
transportation system. 

PPSUITE plays a key role in the development of hourly roadway speed
estimates, which are supplied as input to the MOBILE6.2 model. The
software is also used to prepare the MOBILE6.2 input shell and to
process the MOBILE6.2 outputs. 

These two computer programs interact as shown in Figure 1.

Figure   SEQ Figure \* ARABIC  1 	Emission Calculation Process for Cecil
County

Traffic Data SOURces

This section provides a summary of the key input data and analysis tools
used for producing the Cecil County emissions inventory.  The key
elements to the modeling protocol are described in the sections below. 

Roadway Data

The roadway data input to emissions calculations for the Cecil County
non-attainment area uses information from the 2005 SHA highway database
obtained directly from SHA and is referred to as the “Universal”
highway database and named as “HMIS2005_Max.MDB”.  This data
contains information on all state highways and arterials, most of the
major collectors, and some minor collector and local roadways divided
into links of varying lengths. Each of these link segments contains
descriptive data that is used in the calculation of the congested speeds
input to the MOBILE6.2 emissions model. The PPSUITE post processor
calculates the congested speeds based on the following model network
fields:

Number of Lanes

Distances

Volumes in Average Annual Daily Traffic (AADT)

Facility Type

Area Type (Urban/Rural)

Link free-flow speeds

Zones to relate each link to the county in which it belongs

SHA volumes and distances are used in calculating highway VMT totals for
each county. As discussed in the next section, adjustments are needed to
convert the volumes to an average July weekday. Lane and capacity values
are an important input for determining the congestion and speeds for
individual highway segments. Truck volumes are used in the speed
determination process and are used to split volumes to the individual
vehicle types used by the MOBILE6.2 software.

SHA data classifies its road segments by function, in addition to
whether it is located in an urban or rural area, as indicated below in
Figure 2. The urban/rural (UR) and functional classes (FC) are important
indicators of the type and function of each roadway segment. The
variables provide insights into other characteristics not contained in
the SHA data that are used for speed and emission calculations.  In
addition, VMT and emission quantities are aggregated and reported using
both UR and FC codes.

 

Figure   SEQ Figure \* ARABIC  2 	SHA-Based Process Classification
Scheme

Urban/Rural and Facility Type Codes		

Urban/Rural Code   	1=Urban

			2=Rural

			

Functional Class		Rural Functional Classes Used	Urban Functional Classes
Used

			For Rural Areas			For Urban Areas

			-------------------------------------
------------------------------------------

			1=Rural Freeway			11=Urban Freeway

			2=Rural Other Principal Arterial	12=Urban Expressway		

			6=Rural Minor Arterial		14=Urban Principal Arterial	

			7=Rural Major Collector		16=Urban Minor Arterial

			8=Rural Minor Collector		17=Urban Collector

			9=Rural Local			19=Urban Local

Additions and Adjustments to Roadway Data

Before the SHA data can be used by PPSUITE for speed and emission
calculations, several adjustments and additions must be made to the
roadway data.

HPMS Adjustments: According to EPA guidance, baseline inventory VMT
computed from the 2005 SHA database must be adjusted to be consistent
with Highway Performance Monitoring System (HPMS) VMT totals. Although
it has some limitations, the HPMS system is currently used in all 50
states and is being improved under FHWA direction. 

Adjustment factors are calculated which adjust the 2005 SHA data to be
consistent with the 2005 HPMS data. 2005 HPMS adjustments are calculated
as factors and are carried forward for future year runs. These factors
are developed for each county, urban/rural code and facility group
combination.

                                                                        
                                                                        
                                                                        
                                                                        
                        

Seasonal Adjustments to Volumes: The 2005 SHA database contains volumes
that represent an average of all days in the year including weekends and
holidays. An ozone emission analysis, however, is based on a typical
July weekday. Therefore, those volumes must be seasonally adjusted.
Seasonal factors were developed for each functional class and
urban/rural code using the traffic flow data available by day and month
from ATR Station Reports in the Traffic Trends System Report Module from
the SHA website These factors are applied to the existing SHA AADT
volumes to produce the July volumes.    

Additional Network Information: The PPSUITE software system allows for
many additional variables other than those available in the SHA
database. Using these variables improves the ability of Maryland to
incorporate real roadway conditions into its estimates. The variables
include information regarding signal characteristics and other physical
roadway features that can affect a roadway’s calculated congested
speed. PPSUITE’s ability to estimate congested speeds by road segment
improves Maryland’s emissions inventories because of the overwhelming
role speed plays in emission rates. If specific information regarding
these variables is known or obtained for areas, this information can be
appended to the SHA database. Otherwise, default values are assumed
based on information provided by the PPSUITE input speed / capacity
lookup data, as described below. 

Speed / capacity lookup data provides PPSUITE with initial (free-flow
with no congestion) speeds and capacities for different urban/rural code
and functional class groupings. The initial speeds and capacities are
used by PPSUITE in determining the final congested speed for each
roadway segment. Speeds can also be significantly impacted by traffic
signals and other roadway features. As a result, this data provides
default signal densities (average number of signals per mile for
different functional classes), as well as default values for variables
that determine the decay of speed with varying levels of congestion. As
discussed above, values from the speed/capacity data can be overridden
for specific links by directly coding values to the roadway database
segments. The speed / capacity data was developed from a combination of
sources including the following:

Information contained in the 2000 Highway Capacity Manual

SHA information on speeds and signal densities

Engineering judgment

24-hour Pattern Data: Speeds and emissions vary considerably depending
on the time of day (because of temperature) and traffic volumes, which
may cause congestion. Therefore, it is important to estimate the pattern
by which roadway volume varies by hour of the day. The 24-hour pattern
data provides PPSUITE with information used to split the daily roadway
segment volumes to each of the 24 hours in a day. Pattern data is in the
form of a percentage of the daily volumes for each hour. Distributions
are provided for each county and functional class grouping. This data
was developed from the Traffic Trends System Report Module from the SHA
website. 

Vehicle Type Pattern Data: Vehicle Type Mix is a key input that has
significant impacts on emissions. The vehicle mix data is used in
combination with diesel sales fractions by MOBILE6.2 to develop a
composite emission rate for all 28 output vehicle types. The vehicle
mixes are input to PPSUITE as hourly distributions of vehicles by
vehicle type.  

The Vehicle Mix Pattern was based on Cecil County specific vehicle mixes
from the 2005 SHA TMS database.

Basic emission rates may differ by vehicle type. These types are listed
below in Figure 3.

Figure   SEQ Figure \* ARABIC  3 	MOBILE6.2 Vehicle Classes

MOBILE6.2 Input 		 Composite Vehicle Classes

1.	LDV		- Light-Duty Vehicles (Passenger Cars)

	2.	LDT1 		- Light-Duty Trucks 1 (<6,000 lbs)

	3.	LDT2 		- Light-Duty Trucks 2 (<6,000 lbs, LVW=3,751-5,750)

	4.	LDT3		- Light-Duty Trucks 3 (6,001-8,500 lbs)

	5.	LDT4		- Light-Duty Trucks 4 (6,001-8,500 lbs, LVW>5,751)

	6.	HDV2B	- Class 2b Heavy Duty Vehicles

	7.	HDV3		- Class 3 Heavy Duty Vehicles 

	8.	HDV4		- Class 4 Heavy Duty Vehicles 

9.	HDV5		- Class 5 Heavy Duty Vehicles 

10.	HDV6		- Class 6 Heavy Duty Vehicles 

	11.	HDV7		- Class 7 Heavy Duty Vehicles 

	12.	HDV8A	- Class 8a Heavy Duty Vehicles 

	13.	HDV8B	- Class 8b Heavy Duty Vehicles 

	14.	HDBS		- School Buses

	15.	HDBT		- Transit and Urban Buses

	16.	MC		- Motorcycles

MOBILE summary reports by vehicle type are also useful in knowing what
kinds of vehicles generate emissions. The vehicle type pattern data is
used by PPSUITE to divide the hourly roadway segment volumes to the
sixteen MOBILE6.2 (MOBILE5 had eight) vehicle types. Similar to the
24-hour pattern data, this data contains percentage splits to each
vehicle type for every hour of the day. The vehicle type pattern data
was developed from several sources of information:

Vehicle Mix Patterns for light-duty vehicles, heavy-duty vehicles, buses
and motorcycles based on latest version of SHA’s TMS database.

MOBILE6.2 default vehicle type break downs for the analysis year(s)

The vehicle type pattern data is developed for each county and
functional class combination. Using the percentage volumes for
light-duty vehicles, heavy-duty vehicles, buses and motorcycles by
county, functional class grouping based on latest version of SHA’s TMS
database, the total roadway volume for any segment could be divided to
these four vehicle type categories.  However, these percentages do not
yet enable volumes to be divided to each of the sixteen MOBILE6.2
vehicle types.  As a result, MOBILE6.2 default vehicle type breakdowns
are then used to divide the four categories, calculated above, to each
specific MOBILE6.2 vehicle type.  Note that the defaults used vary by
analysis year; as a result, each forecast year will utilize a unique
vehicle mix distribution.  SHA hourly distributions for trucks and total
traffic are then used to create vehicle type percentage breakdowns for
each hour of the day.

Vehicle Type Capacity Analysis Factors: Vehicle type percentages are
provided to the capacity analysis section of PPSUITE to adjust the
speeds in response to trucks. That is, a given number of larger trucks
take up more roadway space than a given number of cars, and this must be
accounted for in the model. Capacity is adjusted based on the factors
provided in this data. Values are developed from information in the 2000
Highway Capacity Manual and are specific to the various facility types. 

Producing Future Year Volumes   

Traffic growth forecasting plays a pivotal role in estimating future
year emissions for the region.  In the past, separate factors were
derived for each county and highway functional class based on 1990-2002
HPMS VMT data. The factors were then applied to base year traffic
volumes (in this case 2002) on each highway segment in the SHA network
database. This inventory utilizes growth rates based on new 2005 HPMS
VMT data. 

The resulting forecasting system includes the development of VMT
forecasts and growth rates for the total of 12 functional
classifications including urban and rural area types for Cecil County.
The forecasts use statistical relationships based on historic HPMS VMT
trends. The following table summarizes the assumed projected growth of
VMT for future analysis year.

Table   SEQ Table \* ARABIC  3 	Cecil County VMT Growth Assumptions

Analysis

Year	Total Growth 

From 2002	Annualized Growth From Previous Analysis Year

2002	-----	-----

2009	11.87%	1.70%



MOBILE6.2 Input Data

Overview of Emission Rates

Two major types of information are written into the MOBILE6.2 model by
EPA: basic emission rates and travel weighting rates. EPA’s Office of
Mobile Sources obtains this information from a number of sources,
including its new vehicle certification program, in-use vehicle random
sample studies and special studies (including information from some
state I/M programs). For more information on MOBILE, a user’s guide
and various documents (as well as the model itself) are available
through EPA’s website   HYPERLINK "http://www.epa.gov/otaq/mobile.htm"
 www.epa.gov/otaq/mobile.htm .

Basic emission rates are those which are produced under very
standardized conditions. The model then modifies (corrects and/or
weights) these rates based on other model or input parameters. Rates are
incorporated for model year and vehicle type. MOBILE also calculates the
EPA-estimated increase in emissions rates as vehicles accumulate
mileage.

In addition to exhaust emissions, evaporative VOC emission sources from
gasoline-powered vehicles are also included: 

 

Diurnal emissions (evaporated gasoline emissions generated by the rise
in temperature over the course of a day when the vehicle is not being
driven), 

Hot soak emissions (evaporated gasoline emissions occurring after the
end of a vehicle trip, due to the heating of the fuel, fuel lines, fuel
vapors), 

Running loss emissions (evaporated gasoline emissions occurring while a
vehicle is driven, due to the heating of the fuel and fuel lines), 

Resting loss emissions (small but continuous seepage and minor leakage
of gasoline vapor through faulty connections, permeable hoses and other
materials in the fuel system).

Evaporative emissions are very dependent on temperature and fuel
volatility as well as vehicle model year.

Research has found that newer cars tend to be driven more. The model
reflects this in the default mileage accumulation rates used by
MOBILE6.2, which are combined with state-specific vehicle age
distributions from registration data. The model also contains
assumptions about trips per day and miles per day by age of the vehicle.
This is important for exhaust emissions because these emissions are
greater when the vehicle is not warmed up (cold start). Also, this
information helps characterize evaporative emissions.

Local Inputs to MOBILE6.2 

Federal Programs

Federal vehicle emissions control and fuel programs are incorporated
into the MOBILE6.2 software. The programs include:

The Federal Motor Vehicle Control Program (FMVCP) including the National
Low Emission Vehicle Program (NLEV) and federal Tier II / Low Sulfur
Fuel Program;

Emissions standards for medium and heavy duty vehicles in 2002, 2004 and
2007;

Stage II and Onboard Refueling Vapor Recovery (ORVR).

A large number of inputs to MOBILE6.2 are needed to fully account for
the numerous vehicle and environmental parameters that affect emissions
including traffic flow characteristics (as determined from the PPSUITE
software), vehicle descriptions, fuel parameters, inspection/maintenance
program parameters, and environmental variables as shown in Figure 4.
With some input parameters, MOBILE6.2 allows the user to choose default
values, while others require area-specific inputs.

Figure   SEQ Figure \* ARABIC  4 	MOBILE6.2 Inputs

	  Vehicle	   Fuel	  Inspection/	Environmental

	Descriptions	Parameters	 Maintenance	  Parameters

	Vehicle Age	   RVP	  Start Year	   Min, Max

	  Mix		 Model Years	 Temperatures

	Vehicle Type	Reformulated	    Type,	   

	    Mix	   Fuels	 Vehicle Types,	   Humidity

			  Frequency		

	  	 	  Stringency,	

	   Speeds 	 Oxygenated	 Waiver Rate,	 Cloud Cover

	 (PPSUITE)	   Fuels	 Compliance

	    Basic	  Refueling	Anti-Tampering         	Sunrise/Sunset

	Emission Rates	  Controls	 Pressure/Purge		

 			    Tests

	

		    Calculate Emission Factors

			(Grams per Mile) for VOC and NOx	

				

For an emissions inventory, area-specific inputs are used for all of the
items shown in   REF _Ref160945605 \h  Figure 4 , except for the basic
emission rates, which are MOBILE6.2 defaults. In addition, Maryland uses
the MOBILE6.2 default starts-per-day data and soak distributions that
are used to calculate the number of starts in cold and hot start modes.
EPA requires that the number of starts occurring per vehicle be
determined from instrumented vehicle counts. Since such local data is
not available, the MOBILE6.2 national defaults are used for the Maryland
analyses. A vehicle will generate more emissions when it is first
operated (cold start). It generates emissions at a different rate when
it is stopped and then started again within a short period of time (hot
start). Soak distributions are used to determine the time between when
an engine is turned off to the next time it is restarted.

Vehicle Descriptions

Vehicle Age Distributions are input to MOBILE6.2 for Cecil County based
on registered vehicles reflecting July 1 summer conditions. The data is
obtained from the Maryland Motor Vehicle Administration’s vehicle
registration database. These distributions reflect the percentage of
vehicles in the fleet up to 25 years old and are listed by the 16
MOBILE6.2 vehicle types. The Vehicle Type Mix for Cecil County was based
on the latest version of SHA’s TMS database. (See also the discussion
of Vehicle Type Pattern Data in the next section).  Speeds are discussed
extensively in the next section.

Significant changes have occurred in the MOBILE6.2 model as compared to
previous releases. Some of the information previously applied by the
post processor after running MOBILE can now be input directly to the
MOBILE6.2 model run. This includes information on the hourly
distribution of VMT and the hourly speeds that occur during the day.
Another important change in MOBILE6.2 is the influence of facility type
on output emission factors. For example, MOBILE6.2 assumes that an
average speed on a freeway results in a different emission factor than
the same speed on an arterial roadway. Thus MOBILE6.2 is indirectly
accounting for the accelerations and decelerations that typically occur
on such roadways. MOBILE6.2 has four distinct facility types: Freeway,
Arterial, Local, and Ramp. For any emission analysis, the input
functional classes to be analyzed must be mapped to the above facility
types. The following mapping scheme was used for the Maryland runs:

	Maryland Functional Classes	MOBILE6.2 Facility Type

	1,11,12		Freeway

	2,6,7,8,14,16,17		Arterial

	9,19		Local

Since ramps are not directly represented within the SHA highway database
information, it is assumed that 8% of the Freeway VMT is Ramp VMT.  This
is consistent with the recommendations provided in EPA’s Technical
Guidance on the Use of MOBILE6.2 for Emissions Inventory Preparation. 

Emission and Speed Relationships. Of all the user-supplied input
parameters, perhaps the most important is vehicle speed. Emissions of
both VOC and NOx vary significantly with speed, but the relationships
are not linear, as shown in Figure 5. While VOCs generally decrease as
speed increases, NOx decreases only at the low speed range and increases
steeply at higher speeds.

To obtain the best estimate of vehicle speeds, Cecil County uses the
PPSUITE set of programs, whose primary function is to calculate speeds
and to organize and simplify the handling of large amounts of data
needed for calculating speeds and for preparing MOBILE6.2 input files.

Figure   SEQ Figure \* ARABIC  5 	MOBILE6.2 Speed and Emissions Curves

 

Fuel Parameters 

The same vehicle will produce different emissions using a different type
of gasoline. Fuel control strategies can be powerful emission reduction
mechanisms. An important variable in fuels for VOC emissions is its
evaporability, measured by Reid Vapor Pressure. 

MOBILE6.2 allows the user to choose among conventional, federal
reformulated, oxygenated and low Reid Vapor Pressure (RVP) gasoline.
Maryland chooses the MOBILE6.2 inputs appropriate to the year, season,
and control strategy for the area being modeled. Cecil County uses
reformulated gasoline with a RVP of 6.8.

MOBILE6.2 also allows users to calculate refueling emissions, the
emissions created when vehicles are refueled at service stations.
Maryland includes refueling emissions in its area source inventory and
not in its highway vehicle inventory. 

Vehicle Emission Inspection/Maintenance Parameters (VEIP) 

MOBILE6.2 allows users to vary inputs depending on the I/M program in
place for the particular analysis year. The inputs include:

program start year

stringency level 

first and last model years subject to the program

waiver rates

compliance rates

program type (test-only, test-and-repair, etc.) and effectiveness

frequency of inspection (annual, biennial)

vehicle type coverage

test type (idle, loaded, etc.)

pass/fail standards or “cutpoints”

technician training program

The VEIP program parameters used in the current emissions analysis is
summarized in Table 4 below:

Table   SEQ Table \* ARABIC  4 	Summary of VEIP Program Parameters

Model Years	Program Parameters

1996 & newer	OBDII

1977-1983 (Light-Duty)

1977-2050 (Heavy-Duty up to  26k#)	Idle

1984-1995	IM240

1977-1983 	ATP



Some cutpoints (the emissions at which vehicles are failed) are
contained in MOBILE6.2, while others must be put in by the model user. 
Maryland uses the parameters specific for the geographic area and year
for which the modeling is being performed. 

Environmental Parameters

Evaporative emissions are influenced significantly by the temperatures
of the surrounding air. Hourly temperature, absolute humidity and
barometric pressure assumptions have been compiled for Cecil County
based on information from the National Weather Service’s
meteorological stations. 

A summary of the weather data inputs used for the emissions inventory is
shown in Table 5 and also the detailed MOBILE6.2 input file is attached
with the submission.

Table   SEQ Table \* ARABIC  5 	Summary of Weather Data

Weather Data	Data Used

Hourly Temperatures	76.24 78.51 80.13 81.28 81.72 82.23 82.32 81.96
81.49 80.80 80.71 79.56

   77.90 76.39 75.12 74.43 74.08 74.07 73.59 73.44 73.09 72.67 72.54
74.12

Relative Humidity	87.34 81.90 77.17 74.69 74.53 73.67 72.83 73.10 74.00
73.87 74.10 76.87 80.27 84.67 87.63 88.90 90.41 91.00 91.38 92.62 91.73
92.30 92.33 91.77

Barometric Pressure	29.99

Cloud Cover	M6 Default

(0%)

Peak Sun	M6 Default

Sunrise / Sunset	M6 Default

(6 9)



SPEED/EMISSION ESTIMATION PROCEDURE  

The previous sections have summarized the input data used for computing
speeds and emission rates for the Cecil County non-attainment area. This
section explains how PPSUITE and MOBILE6.2 use that input data to
produce emission estimates. Figure 6 on the following page summarizes
PPSUITE’s analysis procedure used for each of the nearly 15,000
roadway links in the region.

Producing an emissions inventory with PPSUITE requires a process of
disaggregation and aggregation. Data is available and used on a very
small scale -- individual ½ mile roadway segments for each of the 24
hours of the day. This data needs to first be aggregated into categories
so that a reasonable number of MOBILE6.2 scenarios can be run, and then
further aggregated and/or re-sorted into summary information that is
useful for emission inventory reporting.

One of the major enhancements of MOBILE6.2 is the increased detail of
traffic that can be input to the emissions model. The PPSUITE post
processor calculates hourly speeds for each roadway segment. Since
previous versions of MOBILE only allowed one average speed as input for
each scenario, the post-processed speeds had to be aggregated and run
through MOBILE with scenarios representing four separate time periods.
MOBILE6.2 allows for direct input of the 24 hourly speeds as well as
options to account for each link’s speed separately. These added
features utilize the full extent of the information output from the
speed processing programs and provide for more accurate emission
estimates of the available traffic data.  

Volume/VMT Development

Before speeds can be calculated and MOBILE6.2 run, volumes acquired from
SHA data must be adjusted and disaggregated. Such adjustments include
factoring to future years, seasonal adjustments, and disaggregating
daily volumes to each hour of the day and to each of the sixteen
MOBILE6.2 vehicle types.

Future Year Volumes: The SHA database contains up-to-date current year
volumes.  However, to produce inventory forecasts, emission budgets, and
conduct conformity analyses, these volumes must be factored to the year
being analyzed.  The historical growth factors have been prepared for
each county and functional class grouping based on 2005 HPMS VMT.  These
growth factors are applied to the base year 2005 SHA volumes to obtain
future year estimates that can be utilized by PPSUITE.

 

Figure   SEQ Figure \* ARABIC  6 	PPSUITE Speed/Emission Estimation
Procedure

Data From PPSUITE Input Files	     PPSUITE Analysis Process	            
  Data from Roadway Source (SHA)

	  The Following is Performed For

	  Each Roadway Segment

		

Percent Pattern Distributions	   Expand to 24 hourly volumes	           
     SHA AWDT Adjusted Volumes

				

	 Adjust Volumes for Peak Spreading

Vehicle Type Patterns	   Disaggregate to Vehicle Type	SHA TMS Auto and
Truck                     Percentages 

	 Calculate Link & Signal Capacities	 Roadway Attributes	

						 (Lanes, FC code, UR code)

Speed/Capacity Lookup Table

	 Calculate Link	   Calculate

	 Midblock Speed	 Approach Delay

	 Calc VMT, Aggregate Link Speed	

						

	      Accumulate VMT, VHT

	  (Aggregate by UR code, FC code,

	        and time periods)

	  The Following is Performed For

		     Each Area, Functional Class 

HPMS VMT Adjustments	  Apply HPMS VMT adjustments

MOBILE Parameters	 Run MOBILE6.2 for Emission Factors

Vehicle Age Distributions

	      

Min/Max/Ambient Temps	     

             Humidity	        Calculate Emissions

	      (VMT x Emission Factor)

Seasonal Adjustments: PPSUITE takes the input daily volumes from SHA
which represent AADT and seasonally adjusts the volumes to an average
weekday in July.  This adjustment utilizes factors developed for each
functional class and urban/rural code.  The above factors are coded into
ASCII files, which are input to PPSUITE in the format shown in Figure 7.
VMT can then be calculated for each link using the adjusted weekday
volumes.

Figure   SEQ Figure \* ARABIC  7 	Sample Summer Seasonal Factor File

                                

       

                       7       1     1.070

                       7       2     1.098

                       7       6     1.098

                       7       7     1.098

                       7       8     1.098

                       7       9     1.098

                       7      11     1.078

                       7      12     1.078

                       7      14     1.092

                       7      16     1.092

                       7      17     1.092

                       7      19     1.092

Disaggregation to 24 Hours: After seasonally adjusting the link volume,
the volume is split to each hour of the day. This allows for more
accurate speed calculations (effects of congested hours) and allows
PPSUITE to prepare the hourly VMT and speeds for input to the MOBILE6.2
model.

After dividing the daily volumes to each hour of the day, PPSUITE
identifies hours that are unreasonably congested. For those hours,
PPSUITE then spreads a portion of the volume to other hours within the
same peak period, thereby approximating the “peak spreading” that
normally occurs in such over-capacity conditions.

  

Disaggregation to Vehicle Type: EPA requires VMT estimates to be
prepared by vehicle type, reflecting specific local characteristics. As
a result, for Cecil County’s emission inventory runs, the hourly
volumes are disaggregated to the sixteen MOBILE6.2 vehicle types based
on SHA class count data and TMS database in combination with MOBILE6.2
defaults. The hourly volumes by four vehicle categories are contained in
the vehicle pattern file which is an ASCII file with free format.  A
sample of the vehicle mix file is provided in Figure 8.

Figure   SEQ Figure \* ARABIC  8 	Sample Vehicle Mix File

   1     2     3     4     5     6     7    8     9     10    11    12  
 13    14    15    16    17    18    19    20    21    22    23    24

7 1 1      0.47   0.47   0.47   0.47   0.47    0.47   0.47  0.47    0.47
   0.47   0.47    0.47    0.47   0.47   0.47    0.47   0.47   0.47   
0.47   0.47   0.47    0.47   0.47   0.47   

7 1 2      72.43  72.43  72.43  72.43  72.43   72.43  72.43 72.43  
72.43   72.43  72.43   72.43   72.43  72.43  72.43   72.43  72.43  72.43
  72.43  72.43  72.43   72.43  72.43  72.43

7 1 3      0.65   0.65   0.65   0.65   0.65    0.65   0.65  0.65    0.65
   0.65   0.65    0.65    0.65   0.65   0.65    0.65   0.65   0.65   
0.65   0.65   0.65    0.65   0.65   0.65 

7 1 4      26.45  26.45  26.45  26.45  26.45   26.45  26.45 26.45  
26.45   26.45  26.45   26.45   26.45  26.45  26.45   26.45  26.45  26.45
  26.45  26.45  26.45   26.45  26.45  26.45

7 2 1      0.54   0.54   0.54   0.54   0.54    0.54   0.54  0.54    0.54
   0.54   0.54    0.54    0.54   0.54   0.54    0.54   0.54   0.54   
0.54   0.54   0.54    0.54   0.54   0.54 

7 2 2      82.66  82.66  82.66  82.66  82.66   82.66  82.66 82.66  
82.66   82.66  82.66   82.66   82.66  82.66  82.66   82.66  82.66  82.66
  82.66  82.66  82.66   82.66  82.66  82.66

7 2 3      0.41   0.41   0.41   0.41   0.41    0.41   0.41  0.41    0.41
   0.41   0.41    0.41    0.41   0.41   0.41    0.41   0.41   0.41   
0.41   0.41   0.41    0.41   0.41   0.41 

7 2 4      16.39  16.39  16.39  16.39  16.39   16.39  16.39 16.39  
16.39   16.39  16.39   16.39   16.39  16.39  16.39   16.39  16.39  16.39
  16.39  16.39  16.39   16.39  16.39  16.39

7 6 1      0.57   0.57   0.57   0.57   0.57    0.57   0.57  0.57    0.57
   0.57   0.57    0.57    0.57   0.57   0.57    0.57   0.57   0.57   
0.57   0.57   0.57    0.57   0.57   0.57 

7 6 2      87.23  87.23  87.23  87.23  87.23   87.23  87.23 87.23  
87.23   87.23  87.23   87.23   87.23  87.23  87.23   87.23  87.23  87.23
  87.23  87.23  87.23   87.23  87.23  87.23

7 6 3      0.29   0.29   0.29   0.29   0.29    0.29   0.29  0.29    0.29
   0.29   0.29    0.29    0.29   0.29   0.29    0.29   0.29   0.29   
0.29   0.29   0.29    0.29   0.29   0.29 

7 6 4      11.91  11.91  11.91  11.91  11.91   11.91  11.91 11.91  
11.91   11.91  11.91   11.91   11.91  11.91  11.91   11.91  11.91  11.91
  11.91  11.91  11.91   11.91  11.91  11.91

7 7 1      0.60   0.60   0.60   0.60   0.60    0.60   0.60  0.60    0.60
   0.60   0.60    0.60    0.60   0.60   0.60    0.60   0.60   0.60   
0.60   0.60   0.60    0.60   0.60   0.60 

7 7 2      91.90  91.90  91.90  91.90  91.90   91.90  91.90 91.90  
91.90   91.90  91.90   91.90   91.90  91.90  91.90   91.90  91.90  91.90
  91.90  91.90  91.90   91.90  91.90  91.90

7 7 3      0.18   0.18   0.18   0.18   0.18    0.18   0.18  0.18    0.18
   0.18   0.18    0.18    0.18   0.18   0.18    0.18   0.18   0.18   
0.18   0.18   0.18    0.18   0.18   0.18 

7 7 4      7.32   7.32   7.32   7.32   7.32    7.32   7.32  7.32    7.32
   7.32   7.32    7.32    7.32   7.32   7.32    7.32   7.32   7.32   
7.32   7.32   7.32    7.32   7.32   7.32 

7 8 1      0.60   0.60   0.60   0.60   0.60    0.60   0.60  0.60    0.60
   0.60   0.60    0.60    0.60   0.60   0.60    0.60   0.60   0.60   
0.60   0.60   0.60    0.60   0.60   0.60 

7 8 2      91.90  91.90  91.90  91.90  91.90   91.90  91.90 91.90  
91.90   91.90  91.90   91.90   91.90  91.90  91.90   91.90  91.90  91.90
  91.90  91.90  91.90   91.90  91.90  91.90

7 8 3      0.18   0.18   0.18   0.18   0.18    0.18   0.18  0.18    0.18
   0.18   0.18    0.18    0.18   0.18   0.18    0.18   0.18   0.18   
0.18   0.18   0.18    0.18   0.18   0.18 

7 8 4      7.32   7.32   7.32   7.32   7.32    7.32   7.32  7.32    7.32
   7.32   7.32    7.32    7.32   7.32   7.32    7.32   7.32   7.32   
7.32   7.32   7.32    7.32   7.32   7.32 

7 9 1      0.60   0.60   0.60   0.60   0.60    0.60   0.60  0.60    0.60
   0.60   0.60    0.60    0.60   0.60   0.60    0.60   0.60   0.60   
0.60   0.60   0.60    0.60   0.60   0.60 

7 9 2      91.90  91.90  91.90  91.90  91.90   91.90  91.90 91.90  
91.90   91.90  91.90   91.90   91.90  91.90  91.90   91.90  91.90  91.90
  91.90  91.90  91.90   91.90  91.90  91.90

7 9 3      0.18   0.18   0.18   0.18   0.18    0.18   0.18  0.18    0.18
   0.18   0.18    0.18    0.18   0.18   0.18    0.18   0.18   0.18   
0.18   0.18   0.18    0.18   0.18   0.18 

7 9 4      7.32   7.32   7.32   7.32   7.32    7.32   7.32  7.32    7.32
   7.32   7.32    7.32    7.32   7.32   7.32    7.32   7.32   7.32   
7.32   7.32   7.32    7.32   7.32   7.32 

7 11 1     0.46   0.46   0.46   0.46   0.46    0.46   0.46  0.46    0.46
   0.46   0.46    0.46    0.46   0.46   0.46    0.46   0.46   0.46   
0.46   0.46   0.46    0.46   0.46   0.46 

7 11 2     70.10  70.10  70.10  70.10  70.10   70.10  70.10 70.10  
70.10   70.10  70.10   70.10   70.10  70.10  70.10   70.10  70.10  70.10
  70.10  70.10  70.10   70.10  70.10  70.10

7 11 3     0.71   0.71   0.71   0.71   0.71    0.71   0.71  0.71    0.71
   0.71   0.71    0.71    0.71   0.71   0.71    0.71   0.71   0.71   
0.71   0.71   0.71    0.71   0.71   0.71 

7 11 4     28.73  28.73  28.73  28.73  28.73   28.73  28.73 28.73  
28.73   28.73  28.73   28.73   28.73  28.73  28.73   28.73  28.73  28.73
  28.73  28.73  28.73   28.73  28.73  28.73

7 12 1     0.61   0.61   0.61   0.61   0.61    0.61   0.61  0.61    0.61
   0.61   0.61    0.61    0.61   0.61   0.61    0.61   0.61   0.61   
0.61   0.61   0.61    0.61   0.61   0.61 

7 12 2     93.37  93.37  93.37  93.37  93.37   93.37  93.37 93.37  
93.37   93.37  93.37   93.37   93.37  93.37  93.37   93.37  93.37  93.37
  93.37  93.37  93.37   93.37  93.37  93.37

7 12 3     0.15   0.15   0.15   0.15   0.15    0.15   0.15  0.15    0.15
   0.15   0.15    0.15    0.15   0.15   0.15    0.15   0.15   0.15   
0.15   0.15   0.15    0.15   0.15   0.15 

7 12 4     5.87   5.87   5.87   5.87   5.87    5.87   5.87  5.87    5.87
   5.87   5.87    5.87    5.87   5.87   5.87    5.87   5.87   5.87   
5.87   5.87   5.87    5.87   5.87   5.87 

7 14 1     0.60   0.60   0.60   0.60   0.60    0.60   0.60  0.60    0.60
   0.60   0.60    0.60    0.60   0.60   0.60    0.60   0.60   0.60   
0.60   0.60   0.60    0.60   0.60   0.60 

7 14 2     92.53  92.53  92.53  92.53  92.53   92.53  92.53 92.53  
92.53   92.53  92.53   92.53   92.53  92.53  92.53   92.53  92.53  92.53
  92.53  92.53  92.53   92.53  92.53  92.53

7 14 3     0.17   0.17   0.17   0.17   0.17    0.17   0.17  0.17    0.17
   0.17   0.17    0.17    0.17   0.17   0.17    0.17   0.17   0.17   
0.17   0.17   0.17    0.17   0.17   0.17 

7 14 4     6.70   6.70   6.70   6.70   6.70    6.70   6.70  6.70    6.70
   6.70   6.70    6.70    6.70   6.70   6.70    6.70   6.70   6.70   
6.70   6.70   6.70    6.70   6.70   6.70 

7 16 1     0.60   0.60   0.60   0.60   0.60    0.60   0.60  0.60    0.60
   0.60   0.60    0.60    0.60   0.60   0.60    0.60   0.60   0.60   
0.60   0.60   0.60    0.60   0.60   0.60 

7 16 2     91.81  91.81  91.81 91.81   91.81   91.81  91.81 91.81  
91.81   91.81  91.81   91.81   91.81  91.81  91.81   91.81  91.81  91.81
  91.81  91.81  91.81   91.81  91.81  91.81

7 16 3     0.18   0.18   0.18  0.18    0.18    0.18   0.18  0.18    0.18
   0.18   0.18    0.18    0.18   0.18   0.18    0.18   0.18   0.18   
0.18   0.18   0.18    0.18   0.18   0.18 

7 16 4     7.41   7.41   7.41  7.41    7.41    7.41   7.41  7.41    7.41
   7.41   7.41    7.41    7.41   7.41   7.41    7.41   7.41   7.41   
7.41   7.41   7.41    7.41   7.41   7.41 

7 17 1     0.61   0.61   0.61  0.61    0.61    0.61   0.61  0.61    0.61
   0.61   0.61    0.61    0.61   0.61   0.61    0.61   0.61   0.61   
0.61   0.61   0.61    0.61   0.61   0.61 

7 17 2     92.78  92.78  92.78 92.78   92.78   92.78  92.78 92.78  
92.78   92.78  92.78   92.78   92.78  92.78  92.78   92.78  92.78  92.78
  92.78  92.78  92.78   92.78  92.78  92.78

7 17 3     0.16   0.16   0.16  0.16    0.16    0.16   0.16  0.16    0.16
   0.16   0.16    0.16    0.16   0.16   0.16    0.16   0.16   0.16   
0.16   0.16   0.16    0.16   0.16   0.16 

7 17 4     6.45   6.45   6.45  6.45    6.45    6.45   6.45  6.45    6.45
   6.45   6.45    6.45    6.45   6.45   6.45    6.45   6.45   6.45   
6.45   6.45   6.45    6.45   6.45   6.45 

7 19 1     0.61   0.61   0.61  0.61    0.61    0.61   0.61  0.61    0.61
   0.61   0.61    0.61    0.61   0.61   0.61    0.61   0.61   0.61   
0.61   0.61   0.61    0.61   0.61   0.61 

7 19 2     92.78  92.78  92.78 92.78   92.78   92.78  92.78 92.78  
92.78   92.78  92.78   92.78   92.78  92.78  92.78   92.78  92.78  92.78
  92.78  92.78  92.78   92.78  92.78  92.78

7 19 3     0.16   0.16   0.16  0.16    0.16    0.16   0.16  0.16    0.16
   0.16   0.16    0.16    0.16   0.16   0.16    0.16   0.16   0.16   
0.16   0.16   0.16    0.16   0.16   0.16 

7 19 4     6.45   6.45   6.45  6.45    6.45    6.45   6.45  6.45    6.45
   6.45   6.45    6.45    6.45   6.45   6.45    6.45   6.45   6.45   
6.45   6.45   6.45    6.45   6.45   6.45

Speed/Delay Determination

EPA recognizes that the estimation of vehicle speeds is a difficult and
complex process. Because VOC and NOx emissions are so sensitive to
speeds, the agency recommends special attention be given to developing
reasonable and consistent speed estimates; it also recommends that VMT
be disaggregated into subsets that have roughly equal speed, with
separate emission factors for each subset. At a minimum, speeds should
be estimated separately by roadway functional class. 

The computational framework used for this analysis meets and exceeds
that recommendation. Speeds are individually calculated for each roadway
segment and hour and include the delays encountered at signals. Rather
than accumulating the roadway segments into area/functional groupings
and calculating an average speed (as done in past), each individual link
hourly speed is represented in the MOBILE6.2 speed VMT file. This
represents a significant enhancement in the MOBILE model since past
versions only allowed input of one average speed for each scenario.
MOBILE6.2 allows the input of a distribution of hourly speeds. For
example, if 5% of a county’s arterial VMT operate at 5 mph during the
AM peak hour and the remaining 95% operate at 55mph, this can be
represented in the MOBILE6.2 speed input file. For the Cecil County
runs, distributions of speeds are input to MOBILE6.2 for separate
scenarios representing county and functional class groupings; VMT is
accumulated by the same groupings for the application of the emission
factors to produce resulting emission totals.

To calculate speeds, PPSUITE first obtains initial capacities (how much
volume the roadway can serve before heavy congestion) and free-flow
speeds (speeds assuming no congestion) from the speed/capacity lookup
data. As described in previous sections, this data contains default
roadway information indexed by the urban/rural code and functional
class. 

The result of this process is an estimated average travel time for each
hour of the day for each highway segment. The average time can be
multiplied by the volume to produce vehicle hours of travel (VHT).

HPMS and VMT Adjustments

Volumes must also be adjusted to account for differences with the HPMS
VMT totals, as described previously. VMT adjustment factors are provided
as input to PPSUITE, and are applied to each of the roadway segment
volumes. These factors were developed from historical growth rates and
2005 HPMS data; however, they are also applied to any future year runs.
The VMT added or subtracted to the SHA database assumes the speeds
calculated using the original volumes for each roadway segment for each
hour of the day. The HPMS factors are coded into ASCII files, which are
input to PPSUITE in the format shown in Figure 9.

Figure   SEQ Figure \* ARABIC  9 	Sample HPMS Adjustment File

                                

       

                       7       1     0.9998

                       7       2     1.0053

                       7       6     1.0013

                       7       7     1.0034

                       7       8     1.0001

                       7       9     5.0800

                       7      11     0.9999

                       7      12     1.0000

                       7      14     1.0004

                       7      16     0.9998

                       7      17     1.0004

                       7      19     2.6714

VMT and Speed Aggregation

As discussed in previous sections, MOBILE6.2’s ability to handle input
distributions of hourly speeds has eliminated the need to aggregate
speed data. For the Cecil County runs, PPSUITE has been set up to
automatically accumulate VMT and VHT by geographic area and highway
functional class. The speed files input to MOBILE6.2 for each scenario
contain the actual distribution of roadway speeds for that aggregation
group. Figure 10 illustrates the scenario aggregation scheme used with
MOBILE6.2.

Figure   SEQ Figure \* ARABIC  10 	VMT Aggregation Scheme

VMT/VHT Aggregation Scheme

County 			1=Cecil County		

											1 entry

			

Urban/Rural Code   	1=Urban

			2=Rural								

			

Functional Class		1=Rural Freeway			11=Urban Freeway

			2=Rural Other Principal Arterial	12=Urban Expressway		12 entries

			6=Rural Minor Arterial		14=Urban Principal Arterial	

			7=Rural Major Collector		16=Urban Minor Arterial

			8=Rural Minor Collector		17=Urban Collector

			9=Rural Local			19=Urban Local

											12 potential

											 combinations

Geographic aggregation is performed by urban and rural areas of each
county. Functional class aggregation is according to 12 functional
classes respecting urban and rural definitions . For an individual
county, this creates a potential for 12 possible combinations, each of
which becomes an input MOBILE6.2 scenario. This allows each MOBILE6.2
scenario to represent the actual VMT mix and speed for that geographic /
highway combination. Altogether then, there are potentially 12
combinations for which speeds and VMT are computed and emissions are
calculated with MOBILE. 	

MOBILE6.2 Emissions Run

After computing speeds and aggregating VMT and VHT, PPSUITE prepares
input files to be run in EPA’s MOBILE6.2 program which is used to
produce VOC and NOx emission factors in grams of pollutant per vehicle
mile. The process uses an unmodified version of the MOBILE program that
was obtained directly from EPA.

 

The MOBILE6.2 input file prepared by PPSUITE contains the following:

MOBILE template containing appropriate parameters and program flags

Temperature data specific to the county and season being run

Vehicle age and diesel sales fraction data for the county being run

Scenario data - contains VMT mix, speed distributions specific to
scenario as produced by PPSUITE	

Time of Day and Diurnal Emissions

Unlike in the past using MOBILE5, VMT and speeds are no longer
aggregated as separate scenarios representing time periods. This was
done in the past to account for the unique speeds encountered during
each time period in the day. Since MOBILE6.2 allows for hourly roadway
speeds to be represented in the speed VMT file, such a process is no
longer needed. MOBILE6.2 will internally account for the emissions
during each hour in the day and make the necessary diurnal calculations.


Process MOBILE6.2 Output

After MOBILE has been run, PPSUITE processes the MOBILE6.2 output files
and compiles the emission factors for each scenario. Using the above
methodology, it allocates daily diurnal emissions to each of the time
periods. Using the MOBILE6.2 emission factors, PPSUITE calculates
emission quantities by multiplying the emission factors by the
aggregated VMT totals. PPSUITE then produces an emissions database
summarizing VMT, VHT, VOC, and NOx emissions. 

RESOURCES

Draft Emissions Inventory Guidance for Implementation of Ozone and
Particulate Matter National Ambient Air Quality Standards (NAAQS) and
Regional Haze Regulations, EPA, June, 2003

Consolidated Emissions Reporting, Federal Register, June 10, 2002

User’s Guide to MOBILE 6.1 and MOBILE6.2, Mobile Source Emission
Factor Model, EPA Office of Air and Radiation, EPA420-R-03-010, dated
August 2003.

Technical Guidance on the Use of MOBILE6.2 for Emission Inventory
Preparation, US EPA Office of Transportation and Air Quality, August
2004.

Policy Guidance on the Use of MOBILE6 for Emission Inventory
Preparation, US EPA Office of Air and Radiation, January 18, 2002.

Modeling Page within EPA’s Office of Mobile Sources Website
(http://www.epa.gov/omswww/models.htm) contains a downloadable model,
MOBILE users guide and other information.  It also contains documents
relating to the next version of MOBILE (MOBILE6.2) expected in 1999.

"AP-42" document, "Compilation of Air Pollutant Emission Factors, Volume
II: Mobile Sources," as updated by Supplement A (January 1991),
available in hard-copy only. This material is also in the process of
being revised and updated. Contact AP-42 Project, Test and Evaluation
Branch, EPA, 2565 Plymouth Road, Ann Arbor, MI 48105.

Highway Vehicle Emission Estimates (June 1992) and Highway Vehicle
Emission Estimates II (May 1995) discusses how EPA obtains data for
MOBILE and some of the shortcomings in earlier models. Similar
discussions of the present version’s shortcomings are discussed in
papers available at the website. 

Traffic Engineering

2000 Highway Capacity Manual, Transportation Research Board, presents
current knowledge and techniques for analyzing the transportation
system.

2005 Traffic Volume Maps By County, Highway Information Services
Division, Maryland State Highway Administration

Truck Volumes Maps By County 2000-2005, Highway Information Services
Division, Maryland State Highway Administration

“Universal” Highway Database “HMIS2005_Max.MDB”, Maryland State
Highway Administration

  

ATR Station Reports, Traffic Trends System Report Module, Maryland State
Highway Administration website

 Some states use MOBILE to estimate refueling emissions (gasoline vapor
emissions generated by the refueling of vehicles, where in the absence
of controls the vapor in the vehicle fuel tank is displaced by the
incoming liquid fuel and released to the atmosphere). Maryland includes
these emissions in the area source inventory.

Maryland considers emissions from refueling operations an area source
category. While MOBILE6.2 is employed to calculate emissions factors for
that source category, refueling emissions are not included in highway
vehicle emissions estimations.

	

 PAGE   25 

 PAGE   2 

	

	

 PAGE   25 

	  PAGE   5 

	

 PAGE   24 

Prepare MOBILE6.2 

Speed VMT File

(Account for each roadway segment’s speed for each hour of the day)

Seasonal Factors

Functional Class

County

(County  Value)

Separate fields with spaces NOT tabs

Facility Type

Vehicle Type

Vehicle Mix Fractions by 24 Hour Time Periods

Separate fields with spaces NOT tabs

Seasonal Factors

Functional Class

(County  Value)

Speed Capacity Lookup

(BPR Formulas)

Vehicle Factor File

(Veh impact on capacity)

Vehicle Mix File

(Volume by vehicle type)

Network Analyzer

(Calculate Speeds)

MOBILE 6.2

Process M6.2 Outputs

Report Generator

Prepare M6.2 Inputs

VMT and Emissions Reports

VEIP Parameters

Vehicle Age Data

Diesel Sales Data

Temperatures

Fuel Parameters

Hourly Pattern File

(Volume by hour of day)

PPSUITE

Driver File

VMT Adjustments

(HPMS & Seasonal)

Other PPSUITE

Input Files

PPSUITE

2005 SHA Universal Highway Database &

HPMS Historical Growth Rates

(Link volume, distance, FF speed, lanes & area type) 

